Synergistic Co-processing of Red Mud mining waste and

Synergistic Co-processing of Red Mud mining waste and alkaline Black
Liquor from the Pulp and Paper Industry
by
Christopher Francis George Gissane
A Thesis
presented to
The University of Guelph
In partial fulfillment of requirements
for the degree of
Master of Science
in
Chemistry
Guelph, Ontario, Canada
© Christopher Gissane, April, 2015
ABSTRACT
SYNERGISTIC CO-PROCESSING OF RED MUD MINING WASTE AND ALKALINE
BLACK LIQUOR FROM THE PULP AND PAPER INDUSTRY
Christopher Francis George Gissane
University of Guelph, 2015
Advisor:
Professor Marcel Schlaf
This thesis focused on the explorative study of synergistically co-processing Red Mud and
Black Liquor under varying temperatures, pressures, reaction times, and material ratios. The goal
being to generate a treated Red Mud with a substantially lower pH and increased carbon content
that would be more environmentally tolerable and allow for the consideration of using the treated
material as a viable soil additive and/or allow for the remediation and revegetation of Red Mud
storage sites. Using a factorial design of experiments approach the study identified the most
influential reaction parameters affecting the monitored responses. By applying a central
composite design to those results, the optimum reaction conditions to achieve the desired results
for pH, carbon content and several other characteristics were realized. Additionally, the design
and construction of a unique explosion resistant high pressure hydrogenation laboratory was also
undertaken as part of this thesis.
To my Mom and Dad
iii
ACKNOWLEDGEMENTS
First, I would like to thank my advisor, Dr. Marcel Schlaf. I am very grateful of the
opportunities that you have given me as both a graduate and an undergraduate student. The last
two years have definitely have been a test of patience for the both of us getting the new
laboratory completed but I am grateful you trusted me to take the lead on the project. That
opportunity allowed me to gain experience and learn from mistakes that few in my position ever
get the chance to do. You have taught me to look at the world with a more analytical mindset and
it has been a privilege to work for you and alongside you.
Special thanks to everyone in the electronics and machine shops, especially Ian, Steve,
and Case, for all of their help with the various aspects of the projects.
I am appreciative to the many members of the Schlaf group I have had the pleasure to
know, as well as to my friends throughout the department, for all of their support. I was fortunate
enough to have worked alongside a number of highly talented chemists, all of whom assisted me
to improve my skills every day. I can only hope that my future endeavors bring workplace
dynamics as memorable and rewarding as those I have enjoyed here.
Last, though far from least, I would like to thank my friends and family. I am very
fortunate to have such a select group of people in my life that showed such interest in my work
and helped me in so many ways over the years and to listen to my ranting over all the issues that
kept cropping up.
iv
Table of Contents
1
1.1
INTRODUCTION.............................................................................................................................. 1
Motivation .......................................................................................................................................................1
1.2
Aluminium Industry .......................................................................................................................................2
1.2.1 The Bayer Process ........................................................................................................................................2
1.2.2 Red Mud Waste ............................................................................................................................................4
1.2.2.1
Disposal Techniques and Environmental Issues ..................................................................................4
1.2.2.2
Multi-Functional Catalyst Potential .....................................................................................................6
1.3
Pulp and Paper Industry ................................................................................................................................7
1.3.1 Lingocellulosic Biomass ..............................................................................................................................7
1.3.1.1
Cellulose ..............................................................................................................................................8
1.3.1.2
Hemicellulose ......................................................................................................................................8
1.3.1.3
Lignin ..................................................................................................................................................9
1.3.2 Major Pulping Processes15,16 ...................................................................................................................... 13
1.3.2.1
Kraft Pulping ..................................................................................................................................... 13
1.3.2.2
Sulfite Pulping ................................................................................................................................... 14
1.3.2.3
Soda Pulping ..................................................................................................................................... 15
1.3.3 Black Liquor Waste.................................................................................................................................... 17
1.3.3.1
Composition and Properties .............................................................................................................. 17
1.3.3.2
Disposal Techniques.......................................................................................................................... 19
1.4
Overview of Projects .................................................................................................................................... 21
1.4.1 Project I: Design and Construction of the High Pressure Hydrogenation Lab ........................................... 21
1.4.2 Project II: Neutralization of Red Mud using Strong Black Liquor as a reagent ......................................... 22
2
2.1
RESULTS AND DISCUSSION – PROJECT I .............................................................................. 23
Infrastructure Design Features ................................................................................................................... 23
2.2
High Pressure Reactors ................................................................................................................................ 27
2.2.1 Reactor Installation and Validation ............................................................................................................ 29
2.2.2 Comparison of Temperature and Pressure Response to Theoretical Values using NIST software ............ 30
3
3.1
RESULTS AND DISCUSSION – PROJECT II............................................................................. 34
A Counterintuitive Approach ...................................................................................................................... 35
3.2
24 Factorial Design ........................................................................................................................................ 37
3.2.1 Initial Observations .................................................................................................................................... 41
3.2.1.1
pH of Black Liquor in storage ........................................................................................................... 41
3.2.1.2
Precipitate formation from the aqueous liquid phase ........................................................................ 42
3.2.1.3
pH values ........................................................................................................................................... 45
3.2.1.4
Coloured aqueous phase .................................................................................................................... 46
v
3.2.1.5
Recovered Solid Phase ...................................................................................................................... 48
3.2.2 Significant Factors and Interactions ........................................................................................................... 50
3.2.2.1
pH of Solid Phase .............................................................................................................................. 52
3.2.2.2
pH of Aqueous Phase ........................................................................................................................ 53
3.2.2.3
Mass of Aqueous Phase ..................................................................................................................... 54
3.2.2.4
Carbon Content of Solid Phase .......................................................................................................... 54
3.2.2.5
Water Content of Aqueous Phase ...................................................................................................... 55
3.2.2.6
Magnetic Susceptibility ..................................................................................................................... 55
3.2.2.7
Sodium Concentration in the Solid Phase ......................................................................................... 56
3.2.2.8
Summary ........................................................................................................................................... 57
3.3
Central Composite Design ........................................................................................................................... 58
3.3.1.1
pH of Solid Phase .............................................................................................................................. 60
3.3.1.2
pH of Aqueous Phase ........................................................................................................................ 63
3.3.1.3
Mass of Aqueous Phase ..................................................................................................................... 64
3.3.1.4
Carbon Content of Solid Phase .......................................................................................................... 64
3.3.1.5
Water Content of Aqueous Phase ...................................................................................................... 65
3.3.1.6
Magnetic Susceptibility ..................................................................................................................... 65
3.3.1.7
Sodium Concentration in Red Mud ................................................................................................... 65
3.3.1.8
Statistical relevance of the data ......................................................................................................... 66
3.3.2 Optimum Reaction Conditions ................................................................................................................... 67
3.3.3 Summary .................................................................................................................................................... 69
3.4
Experimental ................................................................................................................................................. 71
3.4.1 Factorial Design Calculations .................................................................................................................... 71
3.4.2 General Procedure for Co-processing Reactions ........................................................................................ 72
3.4.3 Analytical Instrumentation ......................................................................................................................... 73
4
SUMMARY OF RESULTS ............................................................................................................. 75
REFERENCES.......................................................................................................................................... 77
APPENDIX............................................................................................................................................... 79
Appendix A: Select Micro-GC Traces ..................................................................................................................... 80
A1: Micro-GC trace of 1000ppm C1 – C6 alkane standards................................................................................... 81
A2: Micro-GC trace of 1000 ppm C2 – C6 alkene standards.................................................................................. 81
A3: Micro-GC trace of lab atmosphere reference ................................................................................................... 82
A4: Micro-GC trace of DoE reaction, representative over all reactions conducted ................................................ 82
A5: Micro-GC trace of acid digestion white precipitate recovered from aqueous phase post- reaction using 2M
HCl (representative of all applicable reactions) ...................................................................................................... 83
Appendix B: 3D Autogenic Pressure Response as a Function of Time and Temperature for Multi-Reactor
System and REFPROP Water Vapour Pressure Plots ........................................................................................... 84
B1: Bach autogenic pressure response as a function of time and temperature with 50, 100 and 150mL of water .. 85
B2: Escher autogenic pressure response as a function of time and temperature with 50, 100 and 150mL of water
................................................................................................................................................................................. 86
vi
B3: Gödel autogenic pressure response as a function of time and temperature with 50, 100 and 150mL of water 87
B4: Theoretical Pressure-Temperature Response for Water vapour contained in an ideal closed system within the
range of the High Pressure Reactor specifications. ................................................................................................. 88
B5: Theoretical pressure-temperature response for water vapour contained in an ideal closed system near the
limits of the high pressure reactor specifications. ................................................................................................... 89
Appendix C: Spectral data for aqueous phases ...................................................................................................... 90
C1: 1H NMR of red aqueous phase obtained on a 400 MHz spectrometer using D 2O as the solvent. .................... 91
C2: 1H NMR of red aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent and water
suppression NMR program. .................................................................................................................................... 92
C3: 13C NMR of red aqueous phase obtained on a 400 MHz spectrometer using D 2O as the solvent .................... 93
C4: 1H NMR of purple aqueous phase obtained on a 400 MHz spectrometer using D 2O as the solvent ................ 94
C5: 1H NMR of purple aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent and water
suppression. ............................................................................................................................................................. 95
C6: 13C NMR of purple aqueous phase obtained on a 400 MHz spectrometer using D 2O as the solvent ............... 96
Appendix D: Pareto charts, residual plots, main effects plots, interaction plots, and cube plots from DoE
analysis ....................................................................................................................................................................... 97
24 Factorial Design .................................................................................................................................................. 98
D1: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for pH of solid phase before
(Top) and after (Middle) reduction of terms for calculation ............................................................................... 98
D2: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for pH of aqueous phase before
(Top) and after (Middle) reduction of terms for calculation ............................................................................... 99
D3: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for mass of aqueous phase
before (Top) and after (Middle) reduction of terms for calculation .................................................................. 100
D4: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for carbon content of solid
phase before (Top) and after (Middle) reduction of terms for calculation ........................................................ 101
D5: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for water content of aqueous
phase before (Top) and after (Middle) reduction of terms for calculation ........................................................ 102
D6: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for magnetic susceptibility
before (Top) and after (Middle) reduction of terms for calculation .................................................................. 103
D7: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for sodium concentration in the
solid phase before (Top) and after (Middle) reduction of terms for calculation .............................................. 104
Central Composite Design .................................................................................................................................... 105
D8: Residual plot, Contour plots, and response surface plots for pH of solid phase ........................................ 105
D9: Residual plot, Contour plots, and response surface plots for the pH of aqueous phase ............................. 106
D10: Residual plot, Contour plots, and response surface plots for the mass of aqueous phase ........................ 107
D11: Residual plot, Contour plots, and response surface plots for the carbon content of solid phase .............. 108
D12: Residual plot, Contour plots, and response surface plots for the water content of aqueous phase........... 109
D13: Residual plot, Contour plots, and response surface plots for the magnetic susceptibility ........................ 110
D14: Residual plot, Contour plots, and response surface plots for the sodium concentration in the solid phase
.......................................................................................................................................................................... 111
D15: Optimized reaction parameters predicted by Minitab®’s response optimizer ......................................... 112
D16: Overlaid contour plots of response factors highlighting the optimum results while holding reaction time
fixed at 0.5 hrs (Top), 1.75 hrs (Middle), and 3 hrs (Bottom) .......................................................................... 113
Appendix E: SOP for High Pressure Reactors ...................................................................................................... 114
vii
Appendix F: Gas Sensor Alarm Response Procedures and Hydrogenation Lab Information distributed to
EHS, Physical Resources and Campus Police/Fire Dispatch Centre .................................................................. 126
viii
List of Charts
Chart 2-1: High temperature range vs. pressure plots for water validation experiments and NIST
prediction calculations .................................................................................................................. 33
ix
List of Figures
Figure 1-1: Illustration of alumina refining using the Bayer Process 3........................................... 2
Figure 1-2: Representation of cellulose polymer and glucose repeating units ............................... 8
Figure 1-3: Representation of hemicellulose polymer with repeating xylose units and other
possible sugar monomers. ............................................................................................................... 9
Figure 1-4: Representations of Lignin monomers .......................................................................... 9
Figure 1-5: Example of branched lignin structure within lignocellulosic biomass14.................... 10
Figure 1-6: Chemical structures of common turpentine components ........................................... 18
Figure 2-1: Watchtower control screen for multi-reactor system ................................................. 29
Figure 3-1: Pictures of the coloured aqueous phases recovered from various reactions. Examples
of the darken colours (Top), dark red (Top Left), rusty red (Top Middle), dark purple (Top
Right); observed darkening of coloured solution during reaction workup (Bottom), initial colour
(Bottom Left), after five minutes (Bottom Right) ........................................................................ 48
x
List of Schemes
Scheme 1-1: Extraction of aluminium hydroxide compounds by addition of sodium hydroxide .. 3
Scheme 1-2: Precipitation Process .................................................................................................. 3
Scheme 1-3: Calcination Process .................................................................................................... 3
Scheme 1-4: Formation of sulfite pulping liquor 1,18 .................................................................... 14
Scheme 1-5: Proposed α-aryl bond cleavage under alkaline pulping conditions ......................... 16
Scheme 1-6: Examples of reactions within the Recovery Boiler ................................................. 20
Scheme 1-7: Example of the Reconstitution of Pulping Chemicals ............................................. 20
Scheme 3-1: Formation pathway for sodium carbonate in situ. ................................................... 44
Scheme 3-2: Formation of pathway of carbonic acid and sodium bicarbonate in situ. ................ 44
Scheme 3-3: Decomposition pathway of sodium bicarbonate into sodium carbonate when heated.
....................................................................................................................................................... 44
Scheme 3-4: Proposed hydrogen gas reaction with iron species in Red Mud. ............................. 53
xi
List of Tables
Table 1-1: General composition of Red Mud.9 ............................................................................... 7
Table 1-2: Examples of the seven bonding motifs between lignin repeating units.15................... 12
Table 1-3: Sulfite reaction conditions.18 ....................................................................................... 15
Table 2-1: Description of hydrogenation laboratory hazardous environment classification.25,26 . 23
Table 2-2: Gas Sensor Alarm Set points ....................................................................................... 26
Table 3-1: Properties of supplied Red Mud. ................................................................................. 34
Table 3-2: Properties of supplied Black Liquor. ........................................................................... 35
Table 3-3: Main factors chosen for Factorial Design study and selected settings. ....................... 38
Table 3-4: Response Factors chosen for the analysis of reaction products. ................................. 40
Table 3-5: Reaction parameters for Factorial Design. .................................................................. 40
Table 3-6: Peak area comparison of gas samples from the Black Liquor storage bucket and the
laboratory atmosphere. .................................................................................................................. 42
Table 3-7: Peak area comparison of gas samples from acid digestion of solid phase. ................. 43
Table 3-8: Identification of reactions producing a precipitate that could be isolated. .................. 43
Table 3-9: Average pH of solid phase and aqueous phase samples dependant on if the reaction
produced a precipitate. .................................................................................................................. 45
Table 3-10: Mass, water content, and pH of aqueous phases; mass, pH values, carbon content
and magnetic susceptibility of solid phases and degree of reactor coking observed. ................... 49
Table 3-11: Linear regression results and significant effects of regression coefficients from the 24
factorial design in coded units. ..................................................................................................... 51
Table 3-12: Reaction parameters for Central Composite Design. (cf. Table 3-5 for actual values
of +/0/-). ........................................................................................................................................ 58
Table 3-13: Mass, water content, and pH of aqueous phases, pH values, carbon content, and
magnetic susceptibility of solid phases. ........................................................................................ 59
Table 3-14: Experimental model fitted to the responses from the 17 reactions in Table 3-12 with
uncoded factors. ............................................................................................................................ 62
Table 3-15: Analysis of variance for the response factors for the neutralization of Red Mud using
Strong Black Liquor. ..................................................................................................................... 62
Table 3-16: Comparison of optimum reaction conditions between response optimizer function
and overlaid contour plots. ............................................................................................................ 68
xii
Glossary of Abbreviations
AAS
Atomic Absorbance Spectroscopy
AE
Parker Autoclave Engineers
BL
Black Liquor
Coeff.
coefficient
DoE
Design of Experiments
EHS
Environmental Health and Safety
EOS
Equation of State
ESD
Electrostatic Discharge
ft. lbs.
foot-pounds
FPT
Fire Prevention Team
GC
gas chromatography
LDPI
Luminaire Design for Performance and Innovation
M
mole/litre (Molarity)
MFM
Mass flow meter
NIST
National Institute of Standards and Technology
NMR
Nuclear Magnetic Resonance (spectroscopy)
OCC
Original corrugated cardboard
ppm
parts per million
RM
Red Mud
rpm
revolutions per minute
rxn
reaction
SSC
Summerlee Science Complex
T316 SS
type-316 Stainless Steel
T.E.L.
Temperature Electronics Ltd
WGSR
Water-gas shift reaction
wt.
by weight
XRF
X-ray fluorescence
xiii
1
Introduction
1.1 Motivation
Waste management is a crucial operation, especially for large scale industrial operations.
The capital expenditures and possible liabilities associated with waste disposal can quickly
become a financial and environmental burden for companies in a various industries. Two such
industries facing immediate waste issues are the Pulp and Paper Industry which produces a waste
material referred to as Black Liquor on a scale of up to 7 tonnes per tonne of useful pulp and the
Alumina Refining Industry which produces Red Mud as a by-product on a scale of 2 tonnes per
tonne of alumina.1,2 These waste materials are generated on an impressively large scale, but
storage of them is becoming a major problem especially in the case of Red Mud; current
strategies using lagoons and other long term storage methods are quickly becoming unfeasible,
both economically and environmentally. Methods must be developed that utilize the wastes
generated from these streams. This would negate the need for long term storage options and
possibly produce products that are in some way useful to other industries. Such products could
be beneficial as they may add an additional revenue generating stream to outset the processing
costs. If not, the products could be at least more environmentally tolerable and thus be disposed
of without the threat of damaging the environment or causing a legal and financial liability for
the companies and industries as a whole in years to come.
1
1.2 Aluminium Industry
1.2.1 The Bayer Process
Red Mud, the technical name being bauxite residue, is a waste product of the industrial
refining process known as the Bayer Process used to produce pure alumina (Al2O3) from Bauxite
ore. Bauxite is composed of a multitude of metal oxides including a high percentage of
aluminum hydroxide and oxide minerals which is the reason for its use as the raw starting
material in the refining to alumina powder. The Bayer process consists of four main steps:
Digestion, Clarification, Precipitation, and Calcination (Figure 1-1). The bauxite is prepared for
the digestion stage by milling the ore into smaller particles to increase the reaction surface area
before being combined with an aqueous sodium hydroxide solution.
Figure 1-1: Illustration of alumina refining using the Bayer Process 3
Exploiting the amphoteric nature of Al3+ ions, the sodium hydroxide extracts many of the
multiple forms of aluminum hydroxide compounds (Al(OH)3 and AlO(OH)), mostly found in
the forms of Gibbsite, Böhmite, and Diaspore, out of the bauxite as water soluble
tetrahydroxyaluminate(III) ions ([Al(OH)4]-) (Scheme 1-1).
2
Alkaline digestion of Gibbsite
+
−
𝐴𝑙(𝑂𝐻)3(𝑠) + 𝑁𝑎(𝑎𝑞)
+ 𝑂𝐻(𝑎𝑞)
→
𝐻2 𝑂
+
[𝐴𝑙(𝑂𝐻)4 ]−
(𝑎𝑞) + 𝑁𝑎(𝑎𝑞)
Alkaline digestion of Böhmite and Diaspore
+
−
𝐴𝑙𝑂(𝑂𝐻)(𝑠) + 𝑁𝑎(𝑎𝑞)
+ 𝑂𝐻(𝑎𝑞)
+ 𝐻2 𝑂 →
𝐻2 𝑂
+
[𝐴𝑙(𝑂𝐻)4 ]−
(𝑎𝑞) + 𝑁𝑎(𝑎𝑞)
Scheme 1-1: Extraction of aluminium hydroxide compounds by addition of sodium hydroxide
Once the extraction is complete, the aqueous slurry is pumped into raking thickeners
where the suspended non-soluble metal oxides and other impurities are filtered or sedimented
out, gathered and drained off into bauxite residue disposal areas.4 This material is classified as
“Red Mud”, whose characteristic rusty red colour is that of the iron oxide hematite (Fe2O3)
present in up to ~60% w/w. The remaining [Al(OH)4]- ion solution is pumped into the
precipitation tanks where over the course of several days water is drawn off by evaporation,
allowing the Al(OH)3 to crystallize out of solution. The crystallization process can be expedited
by the addition of pure crystalline aluminum oxide seeds which can be recovered once the
precipitation is complete and recycled for future use (Scheme 1-2).
+
[𝐴𝑙(𝑂𝐻)4 ]−
(𝑎𝑞) + 𝑁𝑎(𝑎𝑞) →
−𝐻2 𝑂
+
−
𝐴𝑙(𝑂𝐻)3(𝑠) + 𝑁𝑎(𝑎𝑞)
+ 𝑂𝐻(𝑎𝑞)
Scheme 1-2: Precipitation Process
Once the precipitation has gone to completion, the precipitate is loaded into gas-fired
kilns set to a temperature of >1100 ºC. The crystalline solid is fully dried resulting in a fine
white powder product which is pure aluminum oxide (Al2O3) (Scheme 1-3).5 This powder can
then be further electro-refined into pure aluminum metal ingots.
∆
𝐴𝑙(𝑂𝐻)3(𝑠) → 𝐴𝑙2 𝑂3(𝑠) + 3 𝐻2 𝑂
Scheme 1-3: Calcination Process
3
1.2.2 Red Mud Waste
1.2.2.1 Disposal Techniques and Environmental Issues
Several major issues arise when attempting to dispose of Red Mud. The primary issue is
the quantity of Red Mud produced: in general roughly 2 tons of Red Mud is produced for every
ton of alumina.2 Over the lifetime of the aluminum industry, which began with the display of a
piece of pure aluminum at the World Fair in Paris in 1898 (at the time more valuable than Gold
on w/w basis), this has resulted in an estimated current accumulation of ~3 billion tons of Red
Mud worldwide with an additional ~120 million tons added every year at the current production
rate.6 The secondary issue is the high alkalinity of the Red Mud (typically pH ≥12), which forces
its classification as a hazardous waste and prevents its use, e.g., as an iron ore source or as a soil
or cement additive.
The main concern with Red Mud arises when discussing disposal. With such large
production volumes, the disposal techniques are still fairly basic; three main methods of disposal
exist: direct disposal into the ocean, containment in tailing ponds, and dry-stacking. A series of
reviews by Klauber et. al.7 provide details on most of the advantages and disadvantages of the
methods therefore only a brief overview will be presented. Direct ocean dumping is only used in
areas where enough space for land disposal facilities simply does not exist or is too expensive to
be viable (notably Japan and in the past Greece) and is rarely used today if at all due to
environmental concerns. Certain bauxite sources contain harmful concentrations of transition or
actinide metals such as chromium (Greece) or uranium (Australia), respectively, that can over
time damage to the ecosystem and be detrimental to the long term viability of the local ecology.
Tailing ponds were once the most popular form of disposal but due to the quantity of
current production, the cost of large plots of land used for containment, and the environmental
4
and financial repercussions if containment were to fail this method is quickly becoming a poor
option, both economically and ecologically. The final method is dry-stacking; the method
involves spreading out Red Mud in thin layers and allowing partial evaporation of water to take
place to create a more dense mixture before placing additional layers over top and repeating the
process. At some locations, (AluGreece, Gulf of Corinth) this process is aided by first filterpressing the Red Mud to reduce its water content, while at the same time recovering more NaOH
solution. An issue with this method is that fully dried Red Mud is a very fine powder with a
particle sizes ranging from 160 µm to well below 40 µm.8 If the Red Mud dries, it can easily
become airborne in a breeze which, due to its alkalinity, can be detrimental to a person’s health if
for instance it comes in contact with the mucus membranes of the respiratory system. Therefore,
the challenge becomes maintaining a minimum moisture content threshold in the mixture as not
to allow the powder to fully dry and become airborne.
As stated before, due to the addition of sodium hydroxide in the digestion stage of the
Bayer process Red Mud typically has a pH ≥ 12.7 With such a high pH, many countries classify
Red Mud as hazardous waste which complicates the disposal by making it much more expensive
and difficult. To solve the disposal problem a solution needs to be found through which Red
Mud can be treated effectively and efficiently to lower its pH and generate a substance that is no
longer classified as hazardous and has the possibility for future applications elsewhere. The ideal
situation would be for this treated Red Mud to represent an economic opportunity rather than
liability, i.e., the transformation of a waste with an effectively negative value (due to storage and
stewardship costs) into value-added metallurgical or otherwise usable resource.
5
1.2.2.2 Multi-Functional Catalyst Potential
Red Mud consists of all metal oxides and minerals that were not soluble in the digestion
of bauxite ore due to their formation of insoluble hydroxides, oxides and iso-polybases, notably
[Fe(O)(OH)]n. Although the exact composition of Red Mud will vary wildly throughout all
bauxite deposits worldwide, the general composition of particles expected to be present in the
mixture is fairly consistent.9 This composition is highly complex; however, the compounds can
be grouped by similar elemental content. Grouping the compounds in such a way allows for the
establishment of groupings of known catalytically active compounds to become obvious as
shown in Table 1-1. Iron (III) oxide (Fe2O3) derived suboxides such as magnetite (Fe3O4) and
Wuestite (FeO) are known to be active as hydrogenation catalysts at elevated temperatures (T >
350 °C), while titanium oxide (TiO2) is a viable ketonization catalyst. Iron suboxide catalysts are
also active for the water gas shift reaction and Fischer-Tropsch chemistry.10 Silicon and
aluminum oxides (as SiO2 and Al2O3, respectively) are all known Brønstedt/Lewis acid/base
catalysts often serving as catalyst supports for other metals. Finally, calcium and sodium oxides
(CaO and Na2O respectively) can be viewed as potential modifiers and promoters in an overall
catalytically active matrix.10,11 Intriguing considerations are that the occasional substitution of
Al3+ with Fe3+ in this matrix could generate unique single atom defect sites that may be
catalytically highly active and that the various components of Red Mud could act in a synergistic
manner further enhancing its overall catalytic activity.
Given that Red Mud is composed of such a large percentage of common catalysts allows
for the consideration of using of the waste product as an extremely affordable catalyst; it can
even be considered as a sacrificial catalyst – a deliberate contradiction in terms – given the large
stockpile of Red Mud available globally.
6
Table 1-1: General composition of Red Mud.9
Element
Fe
Al
Si
Ti
Ca
Na
Associated Minerals
Hematite
Goethite
Magnetite
Boehmite
Gibbsite
Diaspore
Sodalite
Cancrinite
Quartz
Rutile
Anatase
Perovskite
Ilmenite
Calcite
Whewellite
Tricalcium aluminate
Sodalite
Cancrinite
Dawsonite
Unit Cell Chemical Formula
α-Fe2O3
α-FeOOH
Fe3O4
γ-AlOOH
γ-Al(OH)3
α-AlOOH
Na6[Al6Si6O24]Cl2
Na6[Al6Si6O24]∙2[CaCO3]∙2H2O
SiO2
TiO2
TiO2
CaTiO3
TiFeO3
CaCO3
CaC2O4∙H2O
Ca3Al2(OH)12
Na6[Al6Si6O24]Cl2
Na6[Al6Si6O24]∙2[CaCO3]∙2H2O
NaAl(OH)2∙CO3
1.3 Pulp and Paper Industry
The Pulp and Paper Industry has existed for centuries. Throughout the years since its
establishment, many different pulping processes have been developed and replaced or further
refined as technology evolved and knowledge of the wood chemistry involved became more
understood. However, the parts that have remained constant have been the feedstocks required.
1.3.1 Lingocellulosic Biomass
The feedstocks utilized for pulp production depend on the pulping method in operation.
Some methods can process multiple sources such as hardwoods, softwoods, and annual plants
without issue while others are only useful for a select source of biomass. Whatever source is
required they are all forms of lignocellulosic biomass. Lignocellulosic biomass is composed of
three different polymers: cellulose, hemicellulose, and lignin; the ratio of the three polymers
7
varying greatly depending on the type of biomass but generally the composition percentages are
38-50% cellulose, 23-32% hemicellulose, and 10-30% lignin.12
1.3.1.1 Cellulose
Cellulose is composed of D-glucose monomers linked together by β-1,4 glycosidic bonds
that form long straight polymer strands. These strands are bound tightly together by
intermolecular hydrogen bonding between the many hydroxyl groups present within glucose
molecules as illustrated in Figure 1-2. The strands are generally between a hundred to ten
thousand units long and as stated above constitute the majority of the plant cell wall structure.12
Figure 1-2: Representation of cellulose polymer and glucose repeating units
1.3.1.2 Hemicellulose
The second most abundant polymer in lignocellulosic biomass, hemicellulose, is more
complex than cellulose as the fibers are branched and are a combination of multiple different
sugar monomers. There is less hydrogen bonding between strands due to the less ordered
structure leading to a decrease in the density of the packed fibers; the fibers are also shorter than
cellulose fibers, approximately only a few thousand units long or less. The fiber backbone is
usually formed by mixed β-1,4 glycoside connected xylose monomers followed by interspersed
and branched mannose, galactose, arabinose, and glucose throughout; the positioning and
8
number of these sugar monomers are dependent on the type of plant.12 Some types of
hemicellulose also contain oxidized forms of the hexose sugars such as glucuronic acid as shown
in Figure 1-3.
Figure 1-3: Representation of hemicellulose polymer with repeating xylose units and other
possible sugar monomers.
1.3.1.3 Lignin
Lignin is the third component of lignocellulosic biomass which is formed from randomly
repeating units of three different types of substituted phenols; trans-p-courmaryl alcohol,
coniferyl alcohol, and sinapyl alcohol as shown in Figure 1-4, i.e., lignin is – strictly speaking –
not a polymer, but better described as a macromolecule.12,13
Figure 1-4: Representations of Lignin monomers
9
These repeating units are bound together using seven types of bonding motifs involving carboncarbon bonds and ether bridges as shown in Table 1-2. The variability of the bonding
arrangements within lignin facilitates the formation of a highly rigid compound that structurally
supports and binds strands of cellulose and hemicellulose fibers together within plants. As Figure
1-5 demonstrates, the three-dimensional bonding of lignin can be complex and difficult to
display in a single plane however it becomes obvious that due to the multitude of varying C-C
and C-O-C cross-linkages lignin is a robust structural system that has evolved to protect the more
easily damaged polymeric structures of plants.
Figure 1-5: Example of branched lignin structure within lignocellulosic biomass14
Breaking lignin down into manageable units and effectively separating it from the more
ordered structures of cellulose and hemicellulose without damaging them presents a major
10
challenge. The required chemical and/or catalytic treatment system would have to possess the
ability to target and cleave a variety of bonding motifs in lignin and hemicellulose without
attacking the bonding of cellulose which needs to be left as intact as possible. Such a system has
yet to be developed and as such, the pulp and paper industry still relies on more brute force and
harsh chemical systems, such as highly acidic or basic conditions, to forcibly breakdown the
cross-linkages of lignin in order to separate the desired cellulose pulp from lignin and
hemicellulose.
11
Table 1-2: Examples of the seven bonding motifs between lignin repeating units.15
Carbon
Bonds
Illustration of Bonding
Motif
Ether Linkages
BetaBeta
Alpha-O-4
Beta-1
Beta-O-4
Beta-5
4-O-5
5-5
12
Illustration of Bonding
Motif
1.3.2 Major Pulping Processes15,16
Originally, the only available method of extracting pulp from wood was exclusively by
mechanical movement of a stone grinding wheel against the pulp feedstock. This method
provided high yields of pulp fibers but lacked the ability to separate the lignin from the cellulose
fibers. This decreased the strength of the final paper product as the lignin interfered with the
formation of hydrogen bond crosslinking between the fibers; the lignin also turned the paper
yellow overtime when exposed to air and light.1 As knowledge and understanding of the
interactions between industrial chemicals and the chemical structure of biomass increased so too
did the dependence on chemical actions to breakdown and separate the cellulose and
hemicellulose from lignin. The entirely mechanical methods were replaced over time by chemimechanical and semi-chemical, and eventually purely chemical processes became the established
methods of pulping. The use of chemical based systems for processing pulp offered increased
fiber strength in the final product as the lignin was successful separated from the cellulose fibers
but at the cost of lower pulp yields. This is because the chemicals that dissolve lignin also
dissolve and/or degrade hemicellulose and cellulose fibers.1 Today, the pulping industry relies
heavily on chemical pulping processes and they account for the majority of the global production
of pulp. The three main techniques are Kraft pulping, Sulfite pulping, and Soda pulping which
constitute 80%, 10%, and 5% of the total pulp production, respectively.17,18
1.3.2.1 Kraft Pulping
The Kraft Process, also referred to as the sulfate process, is by far the most utilized
pulping method due to the efficiency of delignification, stronger fibers and shorter cooking time
than other comparable methods. The method operates using both sodium hydroxide and sodium
sulfide (Na2S) at pH ~13, with reaction temperatures between 160-180 ºC and a steam pressure
13
of 120 psi for approximately 30-180 minutes to dissolve the majority of lignin from the
feedstocks; pulp yields are on the order of ~43% (w/w) for softwoods and ~50% (w/w) for
hardwoods.1,19 The disadvantages associated with the Kraft process are lower yields compared to
mechanical pulping due to chemical degradation of carbohydrates and possibly dangerous
emissions due to the presence of sulphur dioxide in the flue gases from the chemical pulping
digesters.
1.3.2.2 Sulfite Pulping
Another fully chemical pulping process is Sulfite Pulping, which is a collection of several
slightly different methods all requiring the use of sulfurous acid (H2SO3) and the corresponding
alkali salts. The major processes are acidic bisulfite pulping, bisulfite pulping, neutral sulfite
pulping, alkaline sulfite pulping as well as a multistage sulfite pulping process and an
anthraquinone catalyzed process. All the processes require the essential use of sulfur dioxide and
sulfurous acid to be successful in pulping the hardwood and softwood feedstocks. The sulfurous
acid is generated by burning sulfur under controlled contact with oxygen to generate SO2
(instead of the fully oxidized form of SO3 the formation of which requires a V2O5 catalyst),
which is then dissolved in water to form H2SO3. Upon the addition of a hydroxide salt, the acid
reacts to form the corresponding sulfite salt and water as illustrated in Scheme 1-4; the required
reaction conditions are shown in Table 1-3.
𝑆 + 𝑂2 → 𝑆𝑂2
𝑆𝑂2 + 𝐻2 𝑂  𝐻2 𝑆𝑂3
𝐻2 𝑆𝑂3 + 𝑀𝑂𝐻  𝑀𝐻𝑆𝑂3 + 𝐻2 𝑂

𝑀𝐻𝑆𝑂3 + 𝑀𝑂𝐻  𝑀2 𝑆𝑂3 + 𝐻2 𝑂
1
1
𝑊ℎ𝑒𝑟𝑒 𝑀 = 𝑁𝑎, 𝐾, 𝐶𝑎, 𝑁𝐻4 , 𝐶𝑎, 𝑜𝑟 𝑀𝑔
2
2
Scheme 1-4: Formation of sulfite pulping liquor 1,18
14
Table 1-3: Sulfite reaction conditions.18
Process
pH range
Acidic
Bisulfite
1-2
Bisulfite
3-5
Temperature
(ºC)
Time
(min)
Pulp yield
(%)
SO2∙H2O,
H+, HSO3-
125-143
180-420
40-50
H+, HSO3-
150-170
60-180
50-65
Base Cation Active ions
Ca2+, Mg2+,
Na+, NH4+
Mg2+, Na+,
NH4+
Neutral
SO32-,
5-7
Na+, NH4+
160-180
25-180
75-90
Sulfite
HSO3Alkaline
9-13
Na+
SO32-, OH180-300
180-300
45-60
sulfite
Note: The multistage sulfite pulping is a combination of acidic, neutral, and basic pulping
methods and the anthraquinone catalyzed pulping is alkaline pulping with the addition of the
anthraquinone molecule.
A major by-product of sulfite pulping is the generation of lignosulfonates; during the
pulping process the bisulfite ion, HSO32-, and sulfite ion, SO32-, attack and cleave ether bond
linkages within lignin to generate sulfated lignin which is used in the tanning of leather, resins,
dispersants and through alkaline oxidation the production of vanillin.1 A drawback of the Sulfite
process is the possibly dangerous emissions of sulphur dioxide similar to the Kraft process.
1.3.2.3 Soda Pulping
Soda Pulping is the least complicated in terms of chemistry compared to the other two
processes, as the only chemical employed is sodium hydroxide. However soda pulping can only
be utilized on a small percentage of available pulping feedstocks; mainly annual plants such as
agricultural waste material (bagasse, straw), some hardwoods and recyclable paper waste (e.g.
OCC).1,20 Typically, the sodium hydroxide and raw materials are cooked together at temperatures
of 160-170 ºC for several hours generating pulp yields of 40-50%. The reason for the average
yields is the sodium hydroxide can only affect the non-reductive cleavage of the α-aryl ether
bonds within lignin which limits the application of the process towards the pulping of materials
15
high
in
lignin
content.
However,
as
with
the
sulfite
process
the
addition
of
anthraquinone/anthrahydroquinone as a redox catalyst can increase the effectiveness of pulping
by catalyzing the cleavage of β-aryl ether bonds.15
Scheme 1-5: Proposed α-aryl bond cleavage under alkaline pulping conditions
16
1.3.3 Black Liquor Waste
1.3.3.1 Composition and Properties
Black Liquor as mentioned previously is an aqueous mixture of chemicals and organic
matter; of the many organic compounds within the liquor, a few are worth recovering as they
have further industrial applications. Compounds such as Tall oil, Turpentine, and
Lignosulfonates are of keen interest as these compounds have direct applications in downstream
processes within the pulping facility or they can be sold to third parties generating a
supplementary revenue stream.
Tall oil is a mixture of saponified fatty acids, resin acids, and unsaponifiables derived
from softwood feedstocks. This oil can be isolated by skimming of partially concentrated and
acidified Black Liquor and is used in the manufacturing of soaps, rosin size (additive for water
resistant properties in paper), lubricants, and emulsifiers.
The recovery of turpentine is mainly performed by condensation of gas effluent released
during the heating of the digester and throughout the digestion process as the volatile terpene
compounds are released from the wood feedstocks during this process stage.1 The majority of
recovered terpenes are either α-pinene or β-pinene which are bicyclic hydrocarbons with a
similar chemical empirical formula of C10H16; other terpenes recovered are 3-carene (which are
converted into m-cymene) and p-cymene.21 Crude turpentine can be used as a resin cleaning
solvent within the pulping mill and once distilled the recovered turpentine is utilized in the
varnish and paint industry and as a chemical solvent.19
17
Figure 1-6: Chemical structures of common turpentine components
As mentioned in discussion of the sulphite pulping process lignosulfonates are generated
as a component of the black liquor waste stream. The isolation of lignosulfonates has varied over
the years; lignosulfonates with a calcium counter-ion can be isolated by the addition of lime to
the spent liquor, addition of quaternary ammonium salts can also improve the purity of the
isolated lignosulfonates. More modern isolation methods employ ultrafiltration and ion exclusion
systems to purify the isolated lignosulfonates. These systems also have the added benefit of
being able to perform further fractionation of the lignosulfonates by sorting them based upon
molecular weights.19 The uses of lignosulfonates range from the previously mentioned tanning of
leather to a binder in gravel roads and animal food pellets, a component of mineral slurries and
drilling liquids to reduce viscosity and as a component in certain concretes. As an example of
their use in the concrete, the lignosulfonates are absorbed on the mineral surface resulting in the
requirement of less water to provide the fluidity and plasticity for proper handling; the end result
is a concrete with less permeability and higher strength once set.18,19
Vanillin can be produced through the hydrolysis of alkaline sulfite black liquors where
the hydrolysis is carried out with sodium hydroxide at high pressure and temperatures of ~160
ºC. This produces the sodium salt of vanillin which can be extracted using butanol, the remaining
aqueous solution is acidified with sulphur dioxide to remove impurities and upon the addition of
18
sulphuric acid, the vanillin is recovered by distillation and recrystallized from water. The sodium
salt of vanillin can also be precipitated with carbon dioxide and extracted with benzene. In either
case yields are low (<10%) but the introduction of oxygen under pressure can assist in increasing
the yields.22
1.3.3.2 Disposal Techniques
Currently the single major use of black liquor is the generation of electricity. Once the
cooking of biomass and pulping chemicals has completed, the black liquor is now deemed to be
“weak” and is separated from the pulp and sent through a series of evaporator tanks to be
concentrated by removal of water. This step is performed to increase the solids content of the
black liquor thus increasing the caloric energy value when finally burnt. Once the black liquor
reaches a solid content of ~70-80%,23 the evaporation step is considered complete and the
considerably thicker “strong” black liquor is pumped into a recovery boiler where the liquor is
combusted to generate steam for use in on-site power generation facilities. The combustion
process differs based upon the pulping process used to generate the black liquor as the presence
of sulfur in the Kraft and Sulfite processes require different treatment conditions to avoid the
emission of odorous and possibly toxic gases.18 The combustion is controlled through the use of
oxidation and reduction zones such that the majority of gases released are carbon dioxide and
water vapour and the sulphur is converted into sodium sulfide or sodium sulfate.1 Some sulfur
dioxide is also release but the majority of sulfur compounds remain in the ashes.
19
Oxidation Zone
1
𝐶𝑂 + 𝑂2 → 𝐶𝑂2
2
1
𝐻2 + 𝑂2 → 𝐻2 𝑂
2
Between the two zones
Reduction Zone
2𝑁𝑎𝑂𝐻 + 𝐶𝑂2 → 𝑁𝑎2 𝐶𝑂3 + 𝐻2 𝑂
𝑂𝑟𝑔𝑎𝑛𝑖𝑐𝑠 → 𝐶 + 𝐶𝑂 + 𝐻2
𝑂𝑟𝑔𝑎𝑛𝑖𝑐𝑠 → 𝐶 + 𝐶𝑂 + 𝐻2
2𝐶 + 𝑂2 → 2𝐶𝑂
𝑁𝑎2 𝑆𝑂4 + 4𝐶 → 𝑁𝑎2 𝑆 + 4𝐶𝑂
𝑁𝑎2 𝑆 + 2𝑂2 → 𝑁𝑎2 𝑆𝑂4
𝐶 + 𝐻2 𝑂 → 𝐶𝑂 + 𝐻2
3
𝐻2 𝑆 + 𝑂2 → 𝑆𝑂2 + 𝐻2 𝑂
2
Scheme 1-6: Examples of reactions within the Recovery Boiler
The ashes that remain after combustion are mainly the sulfide and carbonate forms of the pulping
chemicals. These remnants are mixed with water to reconstitute as much of the pulping chemicals as
possible. However, this mixture which is referred to as green liquor (colour due to the presence of iron
sulfides) is not alkaline enough to be used directly as pulping chemicals. It is therefore mixed together with
fresh chemicals in causticizing tanks to increase the strength of the pulping chemicals. This mixture referred
to as white liquor can be used to digest biomass and produce more pulp. 18,23
𝑁𝑎2 𝐶𝑂3 + 𝐶𝑎𝑂 + 𝐻2 𝑂 → 2𝑁𝑎𝑂𝐻 + 𝐶𝑎𝐶𝑂3
∆
𝐶𝑎𝐶𝑂3 → 𝐶𝑂2 + 𝐶𝑎𝑂
Scheme 1-7: Example of the Reconstitution of Pulping Chemicals
20
1.4 Overview of Projects
1.4.1 Project I: Design and Construction of the High Pressure Hydrogenation Lab
The first project consisted of participating in the design and assisting in supervising the
construction and commissioning of a new high pressure hydrogenation laboratory. This involved
periodic inspections of the construction area and communicating with the university’s project
manager and the contractors about design and infrastructure issues that developed. This also
required the creation, review, and dissemination of safety and daily maintenance protocols and
signage for the lab that met university policy and government mandates and had to be approved
by the University of Guelph’s Dept. of Environmental Health and Safety (EHS). The creation of
Emergency Response Procedures was also required so that first responders have procedures to
follow in case of an emergency in the lab. These procedures were developed in consultation with
the University of Guelph’s Fire Prevention Team (FPT) and EHS; the documents are updated
and forwarded to the FPT, EHS, and the Campus Police Dispatch call centre on a semesterly
basis so that the last contact information and procedures are available if needed.
Once the laboratory was commissioned, the installation and validation of three custombuilt high pressure reactors, a high pressure liquid injection system, and a computer control
system were conducted before the commencement of any research studies.
21
1.4.2 Project II: Neutralization of Red Mud using Strong Black Liquor as a reagent
The second project consisted of preforming a Design of Experiments (DoE) study on the
feasibility of neutralizing Red Mud (RM) waste from the aluminium industry using strong Black
Liquor (BL) waste from the pulp and paper industry as a reagent. Both materials possess a high
alkalinity (pH 10-11) so the idea of co-processing the material together at elevated temperatures
and pressures to effect a reduction in the pH of any resulting product may seem counter intuitive.
However, based upon a previously successful project that involved the co-processing of RM with
crude glycerol waste (pH ~11) from bio-diesel production generated at the University of Guelph
Ridgetown campus,24 there was a strong possibility for the proposed project to be successful as
well, i.e., lead to a substantial decrease of pH in the product phases. The study initially required
the use of a Factorial Design to identify which process parameters (temperature, material ratios,
reaction time, and initial pressure, etc.) were the most important to effect the desired outcome
based upon closely monitored analytical responses. Once the influential parameters were known,
the study could progress to the optimisation stage.
Using a second experimental design method known as the Central Composite Design
additional supplementary experiments were conducted to allow for the construction of
mathematical models which were to be fitted to the analytical responses being monitored. The
models would then be able to predict the most suitable process parameters that would result in a
chosen set of response values.
22
2
Results and Discussion – Project I
The initial project undertaken during this thesis was the design and construction of a
unique high pressure facility for the explicit use of exploring high pressure chemistry beyond the
limits of current laboratory equipment available at the University of Guelph. The laboratory was
designed in such a way as to minimize the risk of sparks, explosions, fire, gas leaks and damage
to both university infrastructure and personnel. Due to the risk of a highly flammable and
explosive hydrogen atmosphere developing within the room under abnormal operating
conditions, the laboratory was assigned a hazard working environment classification described
below by fire and electrical inspectors.
Table 2-1: Description of hydrogenation laboratory hazardous environment classification.25,26
Classification
Class 1, Division 2, Group B
What does it mean?
Class 1
A location made hazardous by the presence of flammable gases or vapors
that may be present in the air in quantities sufficient to produce an
explosive or ignitable mixture
Division 2
A location where a classified hazard does not normally exist but is possible
to appear under abnormal conditions
Group B
Hydrogen, fuel and combustible process gases containing more than 30%
hydrogen by volume or gases of equivalent hazard such as butadiene,
ethylene, oxide, propylene oxide and acrolein.
2.1 Infrastructure Design Features
The laboratory itself is located in a restricted area on the fifth floor of the Science
Complex (renamed the SSC in the summer of 2014). This room is technically situated on the
outside of the complex’s outer structural wall with a reinforced ceiling and sidewalls. The room
23
features a Explovent® explosion and pressure relief wall system made up of ten insulted
aluminium panels that are designed to swing out from the building in the event of an explosion
within the room. The pressure required to unlatch the panels is approximately 20–30 lbs/sq.ft
(0.14–0.21psi). The design of the panels is such that the pressure wave generated from an
explosion is directed outward through the panels into a safety zone preventing any critical
structural damage to the building.
The electrical system installed in the laboratory compliments the Explovent® wall
system by eliminating the risk of ignition sources being generated at all junction points. Using
Killark® plugs and receptacles, LDPI 380 Series explosion proof fluorescent light fixtures, and a
T.E.L. flameproof airflow sensor almost all electrical connections within the laboratory are
considered gas tight and safe from causing an explosion. The plugs, receptacles, and light
fixtures use specially designed threaded fittings combined with an epoxy to seal the electrical
connections from a potentially hazardous atmosphere. The T.E.L. flameproof alarms and
controls on the fume hoods are designed to be intrinsically safe meaning the electronics are
designed without components that store energy (coils, capacitors, etc.) limiting the energy
available for ignition. In addition, the casing is designed to contain any small explosion or flame
that occurs on the control board, keeping it separate from the potentially hazardous atmosphere
outside the case. The remaining electronics in the laboratory (computer, sentinel control towers,
and TCD-Micro-GC) are not rated to be spark proof as the cost to do so would be prohibitively
high, but all operate on low-voltages only pass their encapsulated power supplies.
The flooring system installed in the lab functions in conjunction with the electrical
system to ensure no sparks can be accidentally generated from the laboratory’s infrastructure.
This is accomplished by utilized a Sikafloor® ESD flooring system which is a multi-layered
24
epoxy coating that is applied directly to the concrete floor; consisting of a concrete primer, ESD
primer, and a chemical resistant ESD coating. The system functions as a static dissipative unit
that is tied into the grounding cables on the laboratory and the Science Complex preventing any
static charge buildup or any sparks being generated from an object being dropped. All major
fixtures in the laboratory such as the fume hoods, workbench and electrical outlet mounting
plate, reactor support tables, sink and storage cabinet, explosion-proof telephone, compressed
gas cylinder support rack, blast resistant doors, and ramp are also tied into the approx. ¼” thick
copper grounding cable that is mounted throughout the perimeter of the room.
The laboratory is also outfitted with six different gas sensors designed to detect the
following gas molecules: hydrogen, methane, hydrogen sulphide, carbon monoxide, carbon
dioxide, and oxygen. The sensors are directly wired to the Physical Resources Control Centre
and the Campus Police/Fire Dispatch Centre, in case of an alarm conditions the control centres
are automatically notified of a potential such that immediate action may be taken if necessary.
The gas sensors have multiple stages of alarm conditions which are triggered progressively based
upon gas concentration reading within the laboratory as shown in Table 2-2. The sensors are also
linked to strobe lights situated outside the laboratory entrances that trigger when the sensor
readings enter a programmed alarm state.
25
Table 2-2: Gas Sensor Alarm Set points
Gas Sensor
Alarm A
Alarm B
Alarm C
Carbon Dioxide1
1400 ppm
N/A
N/A
Carbon Monoxide
25 ppm
50 ppm
225 ppm
Hydrogen2
25% LEL
50% LEL
90% LEL
Hydrogen Sulphide
10 ppm
15 ppm
20 ppm
Methane
25% LEL
50% LEL
90% LEL
Oxygen
19.5% vol.
22% vol.
22.5% vol.
3
1.
2.
3.
Default set points are 0.4% vol. and 0.8% vol.
Lower Explosion Limit (LEL) for Hydrogen is 4%
Lower Explosion Limit (LEL) for Methane is 5%
There is also a strobe light inside the lab that is linked to an airflow sensor situated inside
the exhaust duct that triggers if the flowrate drops below a set minimum threshold to indicate a
lack of sufficient airflow. The strobe should only trigger under a power loss situation as the dual
fan setup on the roof of the Science Complex dedicated solely for the laboratory operate in series
such that if one fan fails, the second unit should step in to compensate. The units rotate
operational duties on a weekly basis for even wear and tear. Each fan unit is capable of fully
recycling the air inside the laboratory every 2 – 5 minutes resulting in approximately 12-30
exchanges per hour minimizing the amount of hazardous gas that could potentially accumulate
inside the room.
All of these preventative measures built into the infrastructure design ensure that the
environment within the laboratory is as safe as possible for the researchers operating inside or in
the immediate area around the lab and for the structural integrity of the building in the event of a
reactor malfunction.
26
2.2 High Pressure Reactors
The multi-reactor system that was custom built by Parker Autoclave Engineers (AE) for
the hydrogenation lab was designed to fulfill two main tasks. The first task was to increase the
operational temperature and pressure ranges for the homogeneous catalysis research division of
the Schlaf Group while removing the issues of background catalytic activity of the original T316
SS reactors.27 The second task was to give the Red Mud/Bio-oil division the ability to inject biooil or other liquid substrates into a hot reactor at process conditions.
To accomplish these tasks the reactor bodies and all wetted surfaces exposed to process
conditions were constructed using Hastelloy C 276 and non-wetted surfaces were constructed out
of T316 SS. The reactor bodies were designed to be capable of an operational pressure of 5000
psi at a temperature of 500 °C. The standard reactor vessels have a total volume of 300 mL each
but the reactors also have conversion kits that includes a smaller 100 mL body and all additional
pieces required to allow the system to function at the reduced volume. The smaller bodies are
rated to the same pressure of 5000 psi as the larger 300 mL bodies but the temperature rating is
much lower at only 343 °C.
All three reactors have the capability of actively feeding and measuring hydrogen at
temperature and pressure using mass flow meters (MFM); however, the limits of these MFMs
differ between the reactors. Two of the reactors possess MFMs capable of feeding in hydrogen
up to a process pressure of 1500 psi while the third reactor has a hydrogen feed specification of
4500 psi, which intrinsically results in lower accuracy for the higher pressures (p = ± 2 %).
Each reactor is capable of injecting liquid substrates by utilizing a high pressure pump identical
to those found in HPLC systems. The pump has a variable flow rate of 0.01 – 5 ml/min and is
27
rated for a maximum pressure of 6000 psi but is limited to 4700 psi by a pressure relief valve in
order not to exceed the maximum pressure of the reactor itself.
All reactors are equipped with ½ hp electric motors coupled to the impeller shaft by a
drive belt and a proprietary Magnedrive® which utilizes stator magnets externally and rotor
magnets internally to generate the rotational motion required for stirring through the sealed
reaction vessel; the system is designed for a maximum stir rate of ~3000 rpm.
A unique feature fitted to all three reactors is a pressure reducing apparatus that enables
the user to obtain samples of a reaction at specific intervals or at the user’s request directly from
a hot pressurized reactor. Using a compressed air powered solenoid, a small amount of reaction
sample (usually ~ 1–4 mL) is allowed to enter the sample loop at process pressure, where the
reducing apparatus relieves the pressure so that the sample is not ejected at an extreme velocity;
the sample is then collected from the loop using low-pressure compressed air.
All three reactors are controlled individually by control towers referred to as Sentinels;
the sentinels are also networked through a computer running a purpose built software package
called Watchtower®. Through Watchtower, each reactor and all associated functions such as
pressure and mass flow, temperature, mixer speed, sampling, and alarm/problem notification can
be viewed and controlled either from within the laboratory or through a secured remote
connection as seen in Figure 2-1.
28
Figure 2-1: Watchtower control screen for multi-reactor system
2.2.1 Reactor Installation and Validation
As a requirement for the validation of the reactors upon installation in the hydrogenation
lab, each reactor was tested to the maximum design specifications of 500 °C and 5000 psi.
Utilizing three different volumes of water (50 mL, 100 mL, and 150 mL), the temperature and
pressure responses over time were monitored until either one of the maximum conditions was
met. Water was the logical choice as a test platform as many of the projects within the research
group utilize water as the major solvent in reactor experiments or is a major component in the
substrates.
29
2.2.2 Comparison of Temperature and Pressure Response to Theoretical Values using
NIST software
Once the reactors were fully functioning, the validation process was completed and the
data sets gathered from the experiments were plotted using an open source 3D-scatterplot
macro28 for Microsoft Excel®; the charts can be found in Appendix B starting on page 84. Each
chart consists of three individual plots (temperature vs. pressure, temperature vs. time, and time
vs. pressure) from which the data points are combined by the macro to create a single data point
in three dimensional space. These charts were intended to be used as a reference for expected
heating times and pressures of each reactor, especially if a reaction is intended to approach the
supercritical region for water, when conducting experiments.
Part of the purpose of the data was to test how the reactor behaved under operation and if
there were any differences between them. Since each machine was custom built there are in fact
small differences that make each unique and this was seen in slightly different rates of heat
transfer, however nothing that would grossly affect performance was observed. The other part of
the reasoning for data collect was to test how the systems would behave under supercritical water
conditions. Using a software package called REFPROP® provided by NIST, the behaviour of
water in an ideal closed system was calculated using the virial equation of state (EOS) and
plotted showing the changes in pressure based of temperature of the system and density of the
water vapour.
𝑍=
𝑝𝑉𝑚
𝑅𝑇
=1+
𝐵
𝑉𝑚
+
𝐶
2
𝑉𝑚
+⋯
[1]
The virial EOS describes the state of a gas as shown in equation [1] where B,C,…are the
second, third,…virial coefficients, Vm is the molar volume, and Z is the compressibility factor.
30
The full chart with water vapour densities of 0.1-1.0 g/cm3 is shown in Appendix B on pages 88
and 89. In Chart 2-1 a selection of densities as well the reactor data have been plotted together to
form a comparison between the theoretical predictions and the real-world performance of solvent
behaviour.
The reactor data used was taken from the reactor originally intended for use with BL/RM
project and as can be seen in the chart, the real-world performance is fairly comparable to the
predictions. Initially the reaction data is slightly offset from the predicted saturation line because
of the extra tubing connecting the reaction vessel to all the added features installed on the
reactor. This tubing which is partially open to the reaction vessel creates areas where process
fluids can condense and collect as portions of these tubes have loops or low point at equal height
or lower than the reaction taking place. These are design flaws that were missed and they will
affect any mass balance calculation in future studies particularly for the homogenous catalysis
division. They affected the testing of the systems by changing the liquid-vapour equilibrium of
the system which created this offset. The impact is particularly visible in the test using 50 mL of
water; the pressure profile is identical to the predictions at a density of 0.1 g/cm3 but at a
temperature 25 °C higher. At larger volumes the amount of lost material has much less impact on
the system resulting in pressure measurements much closer to the theoretical values as seen with
the 100 mL and 150 mL test volumes following the density paths of 0.2 g/cm3 and 0.4 g/cm3,
respectively.
A couple interesting observations were noted during the testing using 150 mL of water.
Once the system reached the critical point of water at 374 °C and 3200 psi, the pressure built up
extremely fast; in less than five minutes, the system was cresting 4500 psi at 400 °C; even
adjusting the mixer speed by 10 rpm increased the pressure of the system by over 50 psi. These
31
observation during testing really highlighted how dangerous working with supercritical water or
any supercritical fluid could be and how much respect these types of systems must be given.
32
5000
4000
Pressure (psig)
3000
Critical Point
Saturation Line
Density 0.1 g/cm^3
2000
Density 0.2 g/cm^3
Density 0.3 g/cm^3
Density 0.4 g/cm^3
50 mL water
100 mL water
150 mL water
1000
275
325
375
425
475
Temperature (°C)
Chart 2-1: High temperature range vs. pressure plots for water validation experiments and NIST prediction calculations
33
525
3
Results and Discussion – Project II
With the one year time delay due to the issues in testing and validation of the new
reactors described in Project I, the black liquor/Red Mud project was conducted in the Parr
Instruments reactor that all previous Red Mud projects utilized. In the past, the reactor was
modified to enable real-time acquisition of both temperature and pressure data and remote
viewing. The achievable temperature and pressure specifications of the Parr reactor (400 °C and
5000 psi) are comparable to the Autoclave reactors which therefore did not limit the range of
possible reaction parameters.
The Red Mud samples used in this study were supplied by Rio Tinto Alcan’s Jonquiére,
Quebec operation. The Red Mud samples were dried in a laboratory oven at 110 °C (±1 °C) and
sieved before use; the Red Mud contains ∼30% iron oxide (as Fe2O3) as previously reported by
Karimi et al.29-32 by XRF, recent testing by AAS found the iron content to be 26.5%. Additional
information about the Red Mud used is shown in Table 3-1.
Table 3-1: Properties of supplied Red Mud.
Properties of Red Mud
pH
Carbon Content (% w/w dry)
Hydrogen Content (%w/w dry)
Iron Content (% w/w)
Sodium Content (% w/w)
Water Content (% w/w)
Magnetic Susceptibility
(m3Kg-1)
11.14
0.6
1.2
26.4
3.9
~1.60
XLF (x10-6) XHF (x10-6)
0.07
0.06
34
Trace Metal Analysis
Vanadium (ug/g)
727
Chromium (ug/g)
811
Manganese (ug/g)
76.7
Cobalt (ug/g)
11.4
Nickel (ug/g)
24.2
Copper (ug/g)
21.7
Arsenic (ug/g)
22.4
The Black Liquor was supplied by Cascades Inc. from the Norampac-Trenton facility
which utilizes the soda pulping process to digest OCC and wood fibres. Two samples of Black
Liquor were acquired: one sample was taken from the evaporators during the evaporation
process and is referred to as strong black liquor as described in Section 1.3.3.2. The second
sample was taken from one of the storage ponds on site and was denoted as pond liquor. This
liquor has been reported to be significantly more dilute and less alkaline (pH  7.5) than the
strong liquor due to exposure to rain and atmospheric CO2, respectively. However, due to time
constraints only the strong black liquor was tested, which due to the time-scale of the study was
realized to have an alkalinity comparable to the pH of the pond liquor (vide infra). Data provided
by Cascades and supplemented by further testing is tabulated in Table 3-2.
Table 3-2: Properties of supplied Black Liquor.
Properties of Black Liquor
Strong Liquor
pH
9.63*
7.58**
Nitrogen Content (% w/w dry)
0.3**
Carbon Content (% w/w dry)
37.4**
Hydrogen Content (%w/w dry)
8.0**
Oxygen Content (% w/w dry)
42.0**
Sodium Content (% w/w)
7.3*
Ash content (% w/w)
2.8*
Moisture Content (% w/w)
52.6*
Solids Content (g/L)
290*
 *Data values supplied by Cascades Inc.
 **As measured before commencement of study
3.1 A Counterintuitive Approach
Attempting to neutralize the pH of two materials which, by virtue of their associated
chemical processes, are both inherently alkaline in nature may seem to be an illogical approach.
However, this tactic has worked in the past on a previous Schlaf Group project co-processing
35
crude glycerol from bio-diesel production and red mud.24 Using crude glycerol which contained
28% wt. glycerol, 26% wt. methanol, 30% wt. free fatty acids and possessed a pH ~10 and Red
Mud from the same batch as described in Table 3-1, co-processing reactions were carried out by
varying the composition, temperature, and pressure of the system. The results of the study found
that the pH of the red mud and the aqueous phase recovered post-reaction were both substantially
lower (7.5-9 and 8-9, respectively) than the starting materials. It was postulated that the decrease
in pH was attributed to the production of large amounts of CO2 from the biomass and methanol
through decarboxylation of the fatty acids or by reforming of the methanol via CH3OH(l) + H2O
→ CO2(g) + 3 H2(g) followed by WGSR. The CO2 would then react by forming insoluble
carbonates in the metal oxide matrix of red mud via CO2(g) + OH-(aq) → CO32-(s) + H+(aq) to
produce the required acidity needed to reduce the pH of the system.24 Therefore based upon
relatively remarkable success of that project, it was thought that by using the strong black liquor
as the biomass source may result in a similar outcome.
A DoE approach was used to evaluate the effectiveness of neutralizing Red Mud using
the strong black liquor as a reagent. The DoE approach uses a rigorous mathematical analysis to
evaluate the effectiveness of chosen experimental parameters. The notable benefits of using a
DoE are that it is less time consuming, less resource intensive, and results in a smaller amount of
data to sort through and categorize than when compared to the usual method of changing a single
parameter at a time. More importantly, the DoE allows for the detection of potentially non-linear
interactions between process parameters. Within the umbrella term of DoE, there are several
different approaches that can be chosen to conduct and analysis experimental data. The two
approaches being utilized for this project are the Factorial Design and the Central Composite
Design.
36
3.2 24 Factorial Design
The most basic Factorial Design approach is referred to as a two-level factorial design
where each selected factor is assigned a high value and a low value. Performing a full two-level
factorial design specifies all combinations of the high and low values as experimental conditions
thus providing 2n experiments to conduct (where n is the number of factors).33 The data obtained
from this type of treatment are the influences each of the individual factors has upon the system,
referred to as main effects, and the influences that multiple factors interacting with one another
have on the system, referred to as interaction effects. This makes it possible to evaluate the
impact a particular factor or set of interacting factors has upon the system and decide if their
influence is significant enough to warrant further investigation to obtain an optimum value for
operating conditions.
This two-level method is advantageous if the number of factors under examination is less
than or equal to four, the reason being that as the number of factors (n) increases the number of
mandatory experiments increases exponentially by the aforementioned 2n. As described by
Soravia and Orth,33 if n = 5 there are 5 main effects, 10 two-factor interactions, and another 16
interactions of higher order. That much data to interpret takes a lot of time and leads to
redundancies in the information, as higher order interactions usually do not influence the system
with any magnitude.
The chosen main factors for the Factorial Design study are shown in Table 3-3 with the
selected high, low, and intermediate parameter values. The response factors that were decided
upon are indicated in Table 3-4. These particular response factors were selected as they yield the
37
most important information required to make decisions about practicality, feasibility, and
scalability.
Table 3-3: Main factors chosen for Factorial Design study and selected settings.
Low
Setting (–)
Temperature (°C)
300
Reaction Time (minutes)
30
Black Liquor/ Red Mud
4:1
Ratio (w/w in grams)
Hydrogen Pressure (psi)
0
Main Factors
Intermediate
Setting (0)
332.5
105
High
Setting (+)
365
180
8:1
12:1
250
500
The pH value of the recovered solid phase is important to know, as it would be the
deciding factor in determining if the material would still be classified as hazardous waste, if it
was not significantly lower than the original RM. The reasoning is analogous when discussing
the pH of the recovered aqueous phase; since this phase will be a waste stream generated from
the co-processing of the RM and BL, the pH of the liquid would help determine if further
downstream processing may be needed to ensure the waste is environmentally tolerable. The
mass of the aqueous phase that is produced is also important to know, as the intent would be to
minimize the amount of waste that is generated while still accomplishing the goal of producing a
material that has a near neutral pH. The water content of the aqueous phase may seem as a nonobvious parameter to monitor, however, since the feedstocks for the study are waste streams
themselves they contain a complex mixture of metal oxides, dissolved salts, and organic matter.
These compounds could be potentially harmful depending upon their respective concentrations
in the aqueous waste therefore to ensure the waste conforms to environmental regulations with
minimal additional processing a high water content would be most desirable. The carbon content
of the solid is essential to monitor as the porous structure of RM allows for the deposition of
38
large amounts of carbon into the matrix of the material. The deposition of carbon coupled with
the large percentage of iron present permits for the potential for the recovered solid to be utilized
as a soil additive or at low loadings even as a fertilizer provided the pH is within the tolerable
range for plants. The magnetic susceptibility of the solid phase is an interesting response to
monitor as it relates directly to the species of iron (sub-)oxides in the RM. The higher the
magnetic susceptibility the higher the content of magnetite (Fe3O4) and possibly maghemite
(Fe2O3) are present in the sample. A magnetic sample allows for the potential to separate out the
solid phase and/or the iron species by exposing the reaction mixture to a magnetic field. The
feasibility of such action has been previously studied using different forms of magnetic
separation in another RM treatment project that attempted to selectively separate magnetic iron
oxides only with lackluster results. The conclusion was that the iron species are finely distributed
throughout the RM making separation difficult however the potential is still there,34,35 and also
leave the possibility to quantitatively separate the treated Red Mud from the liquid product phase
using magnets rather than a potentially more costly and time-consuming filtration or
sedimentation method. The final response chosen for monitoring was the concentration of
sodium in the recovered solid phase. Since Red Mud and Black Liquor both contain large
amounts of sodium, tracking how much sodium is deposited into the solid phase would be a
valuable piece of information. It could contribute meaningful data towards determining if the
recovered solid would be a viable soil additive and if its use would have to be restricted to plants
that can tolerate high levels of sodium. Also with more sodium contained in the solid phase, less
would be present in the aqueous phase which would make disposal of the liquid waste easier.
39
Table 3-5 outlines the experimental setup using -, 0, and + signs to denote the low,
intermediate, and high settings respectively. The intermediate settings serve as the reaction
control centre points to establish any non-linear responses (curvature) and interactions in
addition to providing insight to the repeatability of response factor results.
Table 3-4: Response Factors chosen for the analysis of reaction products.
pH of Solid
Phase
Mass Magnetic
Susceptibility
Response Factors
pH of Aqueous
Mass of Aqueous
Phase
Phase
Carbon Content of Solid
Water Content of
Aqueous Phase
Sodium Concentration in
Solid Phase
Table 3-5: Reaction parameters for Factorial Design.
Reaction Temperature BL/RM Ratio
Reaction Time
X1
X2
X3
1
2
+
3
+
4
+
+
5
+
6
+
+
7
+
+
8
+
+
+
9
10
+
11
+
12
+
+
13
+
14
+
+
15
+
+
16
+
+
+
17
0
0
0
18
0
0
0
19
0
0
0
Note: Each reaction listed was carried out using 10 g Red Mud.
40
H2 Pressure
X4
+
+
+
+
+
+
+
+
0
0
0
3.2.1 Initial Observations
3.2.1.1 pH of Black Liquor in storage
Due to the delays mentioned previously, the commencement of experiments was delayed
by approx. 8 months. As a result, when the time came to begin reactions with the BL the pH of
the material was far different from what was originally reported as described in Table 3-2 and is
in fact very close to that of the pond liquor mentioned earlier, which does therefore not negate
the overall validity of our approach and study. The pH had dropped by two orders of magnitude
while stored in a sealed bucket; the hypothesis behind the decrease in pH is believed to be from
the presence of dissolved CO2 from the atmosphere forming carbonic acid in solution.
For each reaction, the bucket was shaken beforehand, then opened and stirred for 20
seconds to ensure the solution was as homogenous as possible. Upon opening, the bucket there
was a small release of pressure and if stirring was paused between removing samples,
effervescence could be seen at the surface of the BL. To test for the presence of evolving CO2
from solution the bucket was shaken as in normal procedure, a gas sample was then taken
immediately upon opening the storage bucket and injected into a micro-GC qualitatively
calibrated for CO2 and various alkanes and alkenes. A sample was also taken from the laboratory
as a comparison to test if there were significantly higher levels of CO2 present in the
solution/bucket. While the GC was not calibrated to yield absolute concentrations of gases
present in the samples, the peak area results are comparative relative to each other.
41
Table 3-6: Peak area comparison of gas samples from the Black Liquor storage bucket and the
laboratory atmosphere.
Atmospheric
Gases
Oxygen
Nitrogen
Carbon Dioxide
Water Vapour
Laboratory Air
Black Liquor Storage Bucket
(arbitrary units)
(arbitrary units)
350.9
1337.4
2.3
30.3
330.2
1348.2
26.4
23.0
As shown in Table 3-6 there was significantly more CO2 present in the bucket (~10x)
which supports the idea that there exists dissolved or chemically absorbed CO2 within the BL
that over time could react with the large portion of water present in the material to form carbonic
acid. The carbonic acid would then neutralize the remaining sodium hydroxide left over from the
pulping process.
3.2.1.2 Precipitate formation from the aqueous liquid phase
Some reactions produced a white porous solid as a precipitate from the aqueous phase; of
those reactions, some required the recovered aqueous phase to be stored in a refrigerator
overnight (4 °C) before precipitation occurred whereas others contained the white solid already
present upon opening of the reactor. The white solid was believed to be some form of carbonate,
most likely sodium carbonate (Na2CO3) or possibly sodium bicarbonate (NaHCO3). A small
amount of 2.0 M hydrochloric acid was added to 0.1g of the white solid in a vial and quickly
covered with a septum. Gas evolution was immediately evident by the formation of bubbles and
a slight amount of pressure. A gas sample from the headspace of the vial was taken and
analyzed, see
Table 3-7; the sample was then compared against a gas sample of the ambient air in the
laboratory to identify if significant amounts of CO2 were produced.
42
Table 3-7: Peak area comparison of gas samples from acid digestion of solid phase.
Sample #
Lab Air
1
2
3
4
Oxygen
336.2
282.2
214.2
95.0
24.1
Atmospheric Gases
Nitrogen
Carbon Dioxide
1260.0
1.8
1062.3
891.9
806.5
1494.5
356.7
2455.6
83.7
1787.9
H2O Vapor
18.7
30.9
36.8
40.4
20.2
Only about a third of the reactions produced a recoverable precipitate sample from the
aqueous liquid phase; the remaining reactions did not produce any material or it was not
recoverable as the precipitate was mixed in with the rest of the solid phase product as highlighted
in Table 3-8. The additional reactions required for the central composite design study have also
been included for relevance. The inconsistency with carbonate precipitation would also mean an
additional treatment process may be required to remove excessive amounts of sodium from the
effluent if these reactions were performed on a larger scale, increasing the complexity and
associated costs or such a project. However, the fact that a precipitate forms is a very interesting
observation that requires discussion.
Table 3-8: Identification of reactions producing a precipitate that could be isolated.
Reaction
1
2
3
4
5
6
7
9
10
11
Factorial Design
Amount of
Amount of
Reactio
Amount of
Reaction
Precipitate (g)
Precipitate (g)
n
Precipitate (g)
8
15
0.4322
9
16
10
17
In solid phase
2.8768
11
18
In solid phase
0.9955
12
In solid phase
19
In solid phase
0.8468
13
2.2487
14
Additional experiments from Central Composite Design
2.7452
12
In solid phase
15
In solid phase
In solid phase
13
6.7086
16
In solid phase
In solid phase
14
In solid phase
17
In solid phase
43
Sodium carbonate (Na2CO3) has a very high temperature stability of up to 851 °C; thus
once formed, it cannot decompose back into CO2 under the process conditions used in the study.
Therefore, the formation of Na2CO3 in situ effectively creates a thermodynamic sodium and
carbon dioxide sink that can be isolated in relatively high purity considering the highly complex
and dirty nature of the starting materials.
CO2(g) → CO2(aq)
CO2(aq) + H2O → H2CO3 (aq)
H2CO3 (aq) + OH-(aq) → HCO3-(aq) + H2O
HCO3-(aq) + OH-(aq) → CO32- (aq) + H2O
2Na+(aq) + CO32- (aq) ⇌ Na2CO3(s)
Scheme 3-1: Formation pathway for sodium carbonate in situ.
NaHCO3 is much less likely to be present as it decomposes slowly into Na2CO3, water, and CO2
at 50 °C and the decomposition is much more rapid at the process conditions utilized in the
study.
CO2(g) → CO2(aq)
CO2(aq) + H2O(l) ⇌ H2CO3(aq)
H2CO3(aq) + OH-(aq) ⇌ HCO3-(aq) + H2O(l)
HCO3-(aq) + Na+(aq) ⇌ NaHCO3(s)
Scheme 3-2: Formation of pathway of carbonic acid and sodium bicarbonate in situ.
2NaHCO3(s) → Na2CO3(s) + H2O(l) + CO2(g)
Scheme 3-3: Decomposition pathway of sodium bicarbonate into sodium carbonate when
heated.
44
There appears to be some correlation between reactions that produced a precipitate,
recoverable or not, and reactions that did not produce a precipitate. As shown in Table 3-9 there
is a slight difference of ~0.2 – 0.3 units between the pH values of reactions that produced a
precipitate and those that did not. The small increase can be attributed to the fact that sodium
carbonate is a weak base and thus its presence in a sample would cause an increase in the pH
reading.
Table 3-9: Average pH of solid phase and aqueous phase samples dependant on if the reaction
produced a precipitate.
Solid phase
Aqueous Phase
Precipitate
produced
9.33
8.34
Precipitate
not produced
9.14
8.07
3.2.1.3 pH values
The pH values of both recovered aqueous and solid phases were important parameters to
monitor as both starting material were originally highly alkaline and the main goal of the project
was to synergistically co-process those materials aiming to generate reaction products with a
reduced pH by comparison. Considering an industrial scale, any waste products formed would
have to be further treated if the alkalinity was too high in order to avoid any environmental
disposal issues which may affect economic efficiency and feasibility. Table 3-10 shows the
amount of aqueous phase generated for each reaction and the accompanying pH readings for the
liquids and solids recovered after each reaction. While the results varied between the
experiments, it is obvious that the majority of the reactions provided a solid phase product that
was measurably lower in pH than the original RM.
45
The lowest observed pH for a recovered solid phase was from reaction 15 at 8.60,
approximately two and half units lower than the initial pH value of RM at 11.14. The
accompanying pH measurement for the aqueous phase of the same reaction was 8.13 which is
only a half unit higher than the original reading of 7.58 for the BL as used (i.e., with absorbed
CO2). The pH of the aqueous phases also showed a variety of readings with the lowest value of
7.64, from reaction 8, being virtually unchanged from the observed initial BL reading of 7.58
with the accompanying pH for the solid phase of the same reaction being 8.97. These readings
and indeed all the pH readings shown in Table 3-10 support the idea that it is possible to reduce
the pH of RM using BL as a reagent.
Nonetheless, there is a great variability in the values obtained and maintaining consistent
results could prove challenging. Reactions 17-19 were replicate reactions meant to provide a
measure of reproducibility to all the response factors, but the various analytical measurements
shown in Table 3-10 fluctuate with no discernible pattern. Therefore, narrowing down a root
cause for the variability in the values would prove difficult in such a complex system. For
example, there were persistent issues with stirring throughout the study as the mixture of BL and
RM became viscous when the compounds were combined. The magnetic stir bar/stir plate
combination was not sufficient to maintain proper agitation which led to an intermittent coking
problem for which the solid phase needed to be chiseled out of the reactor during the postreaction workup.
3.2.1.4 Coloured aqueous phase
The majority of reactions in the study produced aqueous phases that were light to dark
brown in colour with varying opacity. However, a few reactions in both the factorial design (rxn
#: 6, 8, 10, 16) and the central composite design (rxn #: 10, 11, 13) produced aqueous phases that
46
were highly coloured; a couple additional reaction possessed a slight hue but were largely brown
in colour. Only a couple of select colours were perceived during the workup such as pink,
orange/red, and purple; over time the colours darken to a deep red, rusty red, and dark purple
respectively. The different colours are illustrated in Figure 3-1, as well as the observed darkening
of an aqueous phase over the course of five minutes during the reaction workup. The exact cause
of these observations is not known but it can be surmised that some organic compounds formed
from the lignin fragments during the reaction produce the colour. The colours are similar to those
produced from lignin staining experiments used in studying plants. The staining process, also
called the Wiesner test, uses phloroglucinol (1,3,5-trihydroxybenzene) in HCl to stain any
coniferyl aldehyde compounds a red-violet colour similar to the solutions in Figure 3-1.36 While
the staining in the test is temporary (~30-60 minutes) it is possible something similar is occurring
in a more permanent fashion during the reaction. On the basis of the low solubility product of
iron oxides (e.g., Ksp = 6 × 10-38 for Fe(OH)3 at neutral pH and even lower in alkaline medium),
iron compounds can likely be excluded as the cause of these colour evolutions.
The NMR spectral data for the red and purple aqueous phases can be found in Appendix
C. The proton spectra were collected using water suppression NMR techniques to remove the
large water peak that was present. The spectra were surprisingly simple considering the complex
nature of molecules present from the lignin fragments. While it would prove difficult to strictly
define the presence of specific molecules, it can be said that portions of the lignin structure
remain intact even after the aggressive treatment of high temperature and pressures encountered
in the study. The 1H NMR spectra show the presence of many different proton signals between
0.7 and 3.5 ppm from various alkyl chains which link the lignin monomers together in the upper
47
field regions and the expected presence of aromatic protons further downfield between 7.0 and
8.5 ppm; The 13C NMR spectra match these observations.
Figure 3-1: Pictures of the coloured aqueous phases recovered from various reactions. Examples
of the darken colours (Top), dark red (Top Left), rusty red (Top Middle), dark purple
(Top Right); observed darkening of coloured solution during reaction workup
(Bottom), initial colour (Bottom Left), after five minutes (Bottom Right)
3.2.1.5 Recovered Solid Phase
The solid phases that were recovered post-reaction were dark brown in colour and
acquired magnetic properties which is a pronounced change compared to the rusty red colour and
lack of magnetism the original RM material. The masses of the recovered products were also
heavier, on average twice the mass of the RM that was placed in the reactor. These observations
are similar to results achieved in previous studies.24,29-32,34,35
48
Table 3-10: Mass, water content, and pH of aqueous phases; mass, pH values, carbon content and magnetic susceptibility of solid
phases and degree of reactor coking observed.
Reaction
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
pH of
Solid
Phase
10.07
9.94
8.68
9.04
9.69
10.24
8.86
8.97
9.69
9.10
8.88
8.73
9.39
8.65
8.60
8.80
10.00
9.22
8.99
pH of
Aqueous
Phase
8.45
9.54
7.96
8.13
8.34
9.58
7.98
7.64
8.25
7.98
8.01
7.63
8.14
8.36
8.13
7.88
8.09
7.85
8.13
Mass of
Aqueous
Phase (g)
24.6
18.3
91.6
71.8
20.5
16.4
68.0
60.2
27.9
18.1
93.9
74.5
26.2
15.9
85.6
59.0
52.2
45.2
50.4
Mass of
Solid
Phase (g)
14.1
15.7
21.6
19.8
14.2
16.1
21.4
32.0
14.5
16.4
22.3
27.2
13.8
17.8
21.2
30.4
13.3
20.3
18.8
Carbon
Content
(%)
20.9
29.6
39.3
38.0
20.6
17.1
39.5
32.9
22.5
21.7
39.2
31.8
21.9
20.3
41.2
32.3
27.9
28.5
29.0
49
H2 O
Content
(%)
69.98
80.44
72.24
72.33
68.96
91.20
76.52
74.95
74.57
74.18
69.82
78.92
72.01
78.92
69.17
75.22
77.48
75.10
71.63
Χlf x 10-5
(m3 kg-1)
1.690
3.570
0.356
1.170
1.900
3.930
0.813
0.860
1.320
2.040
0.437
1.440
1.410
5.500
0.645
1.300
1.250
0.991
1.180
[Na] of
Solid Phase
(ug/g)
68000
92000
59000
74000
69000
87000
48000
120000
62000
95000
55000
110000
44000
110000
52000
110000
87000
120000
93000
Reactor
Coking
Observed
Minimal
Minimal
Moderate
Excessive
Minimal
Minimal
Excessive
None
None
None
Excessive
None
Minimal
None
Excessive
None
Excessive
Excessive
Moderate
3.2.2 Significant Factors and Interactions
Using the DoE software Minitab® 14 to analyze the data enabled the identification of the
main factors as well as any interactions bertween main factors that have a significant influence
upon the chosen response factors. The coefficients of the model were calculated and used to
quantify the effect the main factors have on the studied responses. Each factor has higher or
lower impact upon a particular response based on the significance of the coefficient values. The
ranking of each factor, based upon its significance, is illustrated visually in the Pareto charts
shown in Appendix D. For each response there are two Pareto charts, the first chart ranks all of
the factors and interactions, while the second chart displays only the most important terms. The
authenticity of the model for the regression residuals was verified in graphical distribution tests
shown alongside the Pareto charts. By decreasing the number of terms involved in the coefficient
calculations, additional degrees of freedom become available to better estimate the residual error
and improve the form of the residual plots. The values shown in Table 3-11 are the results of
linear regression calculations on the coefficients of the model after the number of examined
terms was reduced.
A Student’s t-test was used to evaluate the significance of each variable in the model.
Any p-values below 0.05 indicate a given variable is considered to be significant and thus
considered to yield a substantial contribution to the response factor. Highlighted in bold red in
Table 3-11 are the statistical coefficients at the 95% confidence level. The significance value
from the t-test at a given specific degrees of freedom is also shown in the Pareto charts as a red
vertical line. Any model variable that crosses the line is deemed to have a major influence upon
the response.
50
Table 3-11: Linear regression results and significant effects of regression coefficients from the
24 factorial design in coded units.
Source
X0
X1
X2
X3
X4
X1 X2
X1 X3
X1 X4
X2 X3
X2 X4
X3 X4
X1 X2 X3
X1 X2 X4
X1 X3 X4
Curvature
R2 b
Radj2 c
pHsolid
Coeff.
9.2100
-0.0225
-0.3862
-0.2262
-0.0913
-0.1338
0.1625
0.1933
80.61
68.28
%Csolid
Source
Coeff.
X0
29.308
X1
-1.340
X2
7.469
X3
-1.078
X4
-0.426
X1 X2
-1.687
X1 X3
-1.236
X1 X4
-0.996
X2 X3
0.775
X2 X4
X3 X4
1.130
X1 X2 X3
X1 X2 X4
X1 X3 X4
0.945
Curvature -0.805
R2 b
99.25
Radj2 c
98.07
pa
0.771
<10-3
0.012
0.251
0.103
0.054
0.330
a
p
0.002
<10-3
0.005
0.158
<10-3
0.003
0.008
0.024
0.004
0.010
0.273
pHaq
Coeff.
8.2500
0.0925
-0.3300
-0.2025
-0.1925
-0.1775
0.1950
0.1200
-0.2267
94.08
89.34
%H2Oaq
Coeff.
74.965
3.305
-1.318
0.904
-0.864
-1.596
-1.176
-1.488
2.676
-0.225
89.99
79.98
pa
0.055
<10-3
0.001
0.001
0.002
0.001
0.018
0.060
a
p
<10-3
0.050
0.156
0.173
0.023
0.075
0.031
0.001
0.881
maq
Coeff.
49.375
-5.421
28.370
-5.395
0.765
-2.845
-4.157
-0.114
98.37
97.33
Χlf
Coeff.
1.7738
0.7024
-0.8962
0.2709
-0.0123
-0.3876
-0.2441
-0.2897
-0.6335
89.81
81.65
pa
0.001
<10-3
0.001
0.523
0.032
0.004
0.969
a
p
0.001
<10-3
0.082
0.932
0.020
0.112
0.065
0.102
[Na]solid
Coeff.
80500
23375
-2000
3625
-750
7500
4000
-4375
19500
92.36
84.73
X1: Temperature; X2: BL/RM ratio; X3: Reaction time; X4: Hydrogen
a
p-value. b R2 = Sums of squares regression/sums of squares total.
c
Radj2 = 1 − (1 − 𝑅 2 ) × (𝑛 − 1)/(𝑛 − 𝑝), n is the number of runs, p is the number of coefficients
51
pa
<10-3
0.460
0.195
0.779
0.018
0.157
0.125
0.015
3.2.2.1 pH of Solid Phase
Examining Table 3-11 it is clear that only 2 factors affect the outcome for the pH of the
recovered solid phase. The BL/RM ratio (X2) had an obviously large influence on the response;
the more alkaline material present, the more difficult it may be to reduce the pH. However, at the
same time the more organic material present means more CO2 will be produced to assist in
reducing the pH in manners previously discussed. The latter of those ideas is supported as the
cube plot and the main effect plot for BL/RM ratio on page 98 show a lower pH reading when
there is more material present. The main effects plots can be interpreted based on the angle of the
line shown in the plots. If there is no main effect the line is horizontal, if an effect is present the
line is not horizontal. The magnitude of the effect is illustrated by the slope of the line; a steeper
slope indicates a larger effect and the sign of the slope (+ or –) indicates if it increases or
decreases the value of the response.
An intriguing result is that the presence of hydrogen gas has an influence on the pH.
Looking that the cube-plot on page 98 it is easy to see that the presence of Hydrogen (X4) helps
to reduce the pH value. It is possible that a hydrogen molecule is activated in either a homolytic
or heterolytic fashion on the surface of the reduced Red Mud with the resulting hydrogen atoms
or hydride donating two electrons to the iron present in Red Mud generating two protons in the
process. This hydrogen activation would be consistent with the known catalytic activity of iron
suboxides FexOy (x = 1or 3; y = 1 or 4) for hydrogenations and the WGSR. The protons
generated could then react with hydroxide ions present in solution to generate water and lower
the pH. Furthermore, the interaction effect (X2X4) sits just outside the requirements to be
classified as a major influence but its borderline nature means that varying either of the
52
aforementioned main factors could affect the response in possibly non-linear manners; additional
study would be required to identify the exact consequences.
H2 + 2 Fe3+ → 2H+ + 2 Fe2+
2 H+ + 2 OH- → 2 H2O
Scheme 3-4: Proposed hydrogen gas reaction with iron species in Red Mud.
3.2.2.2 pH of Aqueous Phase
The same factors and interactions that had an influence upon the pH of the solid phase
also had an impact on the pH of the aqueous phases but to a somewhat larger extent. There were
also other interactions such as (X1X2) and (X1X4) that affected the response. While it is difficult to
know the true manner in which the interactions shape the response beyond the positive or
negative nature of the coefficients, by simple observation it appears that the cube plot show that
the interaction of (X1X4) assists in lowering the pH when both factors are set to their “+” value.
The interaction plots shown on page 99 help illustrate the magnitude of the interaction.
Interpreting these plots is similar to the main effects plots; if the lines are parallel there is no
interaction, the further the lines differ from the parallel state the stronger the interaction between
the factors. Unfortunately, these interaction plots are limited to displaying only two-factor
interactions.
It is interesting to note that the interactions are more statistically relevant than the
temperature factor alone, which is regarded as a borderline influence. Even a three-factor
interaction involving Temperature, BL/RM ratio, and Hydrogen (X1X2X4) has a major impact
upon the system. It is not common for a higher order interaction to be statistically relevant and
have a coefficient magnitude that is comparable to lower order effects. This is a sign that there
53
are complex relations occurring within the reaction system, which given the complexity of
composition of both feed components is perhaps not surprising.
3.2.2.3 Mass of Aqueous Phase
The mass of the aqueous phase produced was influenced by the first three main factors
which were temperature (X1), the ratio BL/RM (X2), and reaction time (X3), with X2 being the
largest influence by a large margin. This result is not a surprise as the only major source of water
would be the BL, thus the more material added the larger the mass of aqueous phase produced.
While the other two main factors and the interactions of (X2X3) and (X1X4) are technically
significant by statistical analysis, the magnitude differential seen in the coefficients in Table 3-11
between them and the main factor of BL/RM ratio means their actual effects, whether positive or
negative, are basically negligible.
3.2.2.4 Carbon Content of Solid Phase
The carbon percentage of the solid is largely determined by the amount of BL in a given
reaction similar to the mass of aqueous phase generated as described in the previous section. It is
also dependent upon the factors of X1 and X3, i.e., the longer and hotter a reaction is, the more
CO2 will be produced reducing the amount of carbon within the solid phase. There are also
interactions involving X1, X3, and X4. The magnitudes of the interactions are small so identifying
what specific role(s) hydrogen has on the system is difficult. It is conceivable that at high
temperature, the hydrogen reacts with the BL through hydrogenation pathways to attack double
bonds and using hydrodeoxygenation pathways breaks down the ether linkages in the lignin
fragments. These reactions may be catalyzed by one or more of the metals in RM, particularly
the iron species, as they are – as already stated – known to be catalytically active in
hydrogenation chemistry. There is however no concrete analytical evidence to support that these
54
reactions are taking place and even if they did occur the magnitude of the interactions is too
small to have much effect upon the system.
3.2.2.5 Water Content of Aqueous Phase
The data for water content of the recovered aqueous phases shows that the response is
highly dependent on the temperature of the reaction: the higher the temperature the higher the
water content. The second most influential term is a complex three-factor interaction, X1X2X4 (T
× BL/RM × pH2). Table 3-11 shows that the interaction has a positive coefficient meaning it does
help to increase the water content of the aqueous phase. The interactions of X1X2 (T × BL/RM)
and X1X2X3 (T × time × pH2) both have negative coefficients which suppress the response. The
discrepancy between the sign of the coefficients of the interactions X1X2X4 (+) and X1X2 (–)
suggests that the H2 added ends up as water, which supports the earlier argument made while
discussing the pH of the solid and aqueous phases. The main factor of BL/RM ratio is regarded
as a borderline term as it sits exactly on the cusp of the 95% confidence cut-off. It is interesting
this factor is not more significant given the fact that the BL would introduce the inorganic and
organic material into the aqueous phase.
3.2.2.6 Magnetic Susceptibility
The influences on the magnetic susceptibility are relatively simple in comparison to the
responses discussed so far. Temperature and BL/RM ratio and their two-factor interaction are the
only important effects that affect the magnetic susceptibility of the RM in the solid phase. The
importance of temperature was expected as high temperatures promote the reduction of hematite
(Fe2O3) and goethite (FeO(OH)) into magnetite (Fe3O4) and Wuestite (FeO). In addition, an
increase in the quantity of BL in the reaction dramatically decreases the value of magnetic
susceptibility according to the cube plot on page 103. An intriguing observation is that the
55
presence of hydrogen, which forms a reducing atmosphere in the reactor, has virtually no impact
on the response. This is an indication that the gas does not interact with any iron species to
promote the formation of ferromagnetic material which is congruent with the currently accepted
reduction pathway of hematite to iron suboxides, which depends on CO(g) as the reductant. As
the amount of CO(g) in the system is determined by the position of the WGSR equilibrium in the
reactor, higher amounts of BL and hence a higher relative concentration of water in the reaction
mixture after deposition of some of the organic phase into the Red Mud matrix may lead to less
CO(g) being available as a reductant possibly explaining this response.
3.2.2.7 Sodium Concentration in the Solid Phase
The only influential terms for the concentration of sodium in the solid phase were X1 and
the two-factor interaction X1X3. Increasing the temperature causes the sodium concentration to
rise in the solid phase. It was originally thought that the trend was related to the amount of
coking observed, as it is conceivable that excessive coking could trap and contain large
quantities of sodium and prevent it from transferring into the aqueous phase. This idea would
also support why X1X3 is a major influence, as long reaction times and high temperature would
increase coking. However, there does not appear to be a pattern to link reactor coking to the
sodium concentrations seen in Table 3-10.
56
3.2.2.8 Summary
The 24 factorial design study allowed for the identification of the most influential main
factors. This information enabled a well informed decision on which factors to include in the
central composite design optimization study. Decisions had to be made as to which factors to
eliminate and which ones to keep. It would have been possible to keep all four factors, however,
due to time constraints it was decided the best option was to limit the central composite design
study to only three main factors. Scrutinizing the data presented in Table 3-11 it is easy to see
that the BL/RM ratio was a major participant in six of the seven monitored responses and
therefore must be included in the optimization study. The temperature was also a major
contributor in five of the seven responses and again must therefore be included in the next study.
The difficult decision arose when examining the results for the factors of Reaction Time and
Hydrogen; both factors were significant in only two responses each. Reaction Time was a major
aspect of the mass of aqueous phase and the carbon content of the solid phase whereas Hydrogen
was an influence on the pH values of both the solid and aqueous phases.
Determining which factor was to be dropped came down to considering an industrial
scale operation. While there are costs associated with heating and maintaining the reaction over
short and long periods of time, supplying hydrogen to the reaction would be far more costly,
especially on a large scale. Therefore, it was decided to remove the factor of hydrogen from the
experimental design specifically locking in the “–” value of 0 psi. Thus, the chosen factors for
the central composite design study are Temperature, BL/RM ratio, and Reaction time. Keeping
three of the original four factors allows for some of the factorial design reactions to be used in
the central composite study effectively cutting the number of required reactions left to test in
half.
57
3.3 Central Composite Design
The Central Composite Design builds on the Factorial Design approach by allowing for
the optimization of reaction conditions based upon the combined data from the Factorial Design
study (rxns 1-8) and some additional experiments (rxns 9-17). Normally this type of design
incorporates points that rest outside the selected coordinates comprised of “–” and “+” values.
Doing so allows for a better estimation of the response values when calculating the response
surface plots, usually locating local maxima/minima and possibly global maxima/minima.
Unfortunately, due to parameter restrictions on some of the factors, such as non-negative
reaction times, these extra points could not extend beyond the faces of the cube formed by the
initial reaction parameters and thus had to reside on the faces of the cube.
Table 3-12: Reaction parameters for Central Composite Design. (cf.
Table 3-5 for actual values of +/0/-).
Reaction Temperature
X1
1
2
+
3
4
+
5
6
+
7
8
+
9
10
+
11
0
12
0
13
0
14
0
15
0
16
0
17
0
BL/RM Ratio
X2
+
+
+
+
0
0
+
0
0
0
0
0
58
Reaction Time
X3
+
+
+
+
0
0
0
0
+
0
0
0
Table 3-13: Mass, water content, and pH of aqueous phases, pH values, carbon content, and magnetic susceptibility of solid phases.
Reaction
pH of
Solid
pH of
Aqueous
Phase
Mass of
Aqueous
Phase (g)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
10.07
9.94
8.68
9.04
9.69
10.24
8.86
8.97
8.84
8.84
9.18
8.55
9.24
9.25
9.09
9.03
9.69
8.45
9.54
7.96
8.13
8.34
9.58
7.98
7.64
7.96
7.95
8.63
7.68
8.61
7.70
7.96
7.79
7.79
24.6
18.3
91.6
71.8
20.5
16.4
68.0
60.2
47.2
41.0
17.2
80.6
41.9
52.0
52.1
48.2
50.4
Mass of
Solid Phase
(g)
14.1
15.7
21.6
19.8
14.2
16.1
21.4
32.0
17.7
25.9
16.3
23.7
17.6
20.0
19.4
19.4
19.8
59
Carbon
Content
(%)
H2 O
Content
(%)
Χlf x 10-5
(m3 kg-1)
20.9
29.6
39.3
38.0
20.6
17.1
39.5
32.9
32.7
28.0
20.0
33.1
31.9
27.3
27.7
26.9
27.7
69.98
80.44
72.24
72.33
68.96
91.20
76.52
74.95
73.26
83.91
77.64
76.45
73.26
76.95
74.40
74.63
73.50
1.690
3.570
0.356
1.170
1.900
3.930
0.813
0.860
0.971
1.500
2.730
0.749
1.480
1.370
1.390
1.260
1.420
[Na] of
Solid
Phase
(ug/g)
68000
92000
59000
74000
69000
87000
48000
120000
49000
120000
84000
92000
59000
74000
110000
130000
74000
Starting on page 105 in Appendix D, the residual plots, contour plots, and response
surface plots are shown for each of the studied response factors. The nature of the quadratic
equations used to model the responses shown in Table 3-14 means there is no need to reduce the
number of terms being calculated as there was in the factorial design; the residual plots show the
models fit the data well. The contour plots and the response surface plots illustrate the same
information but in different manners which makes identifying certain trends more obvious. The
contour plots are 2D plots that use colour coded regions to illustrate changing response values
depending on the settings of the chosen main factors on the x and y axes, similar to how
elevation changes are shown on a topographical map. The black dots on each plot represent
actual experimental coordinates and the related response values achieved. The response surface
plots display the data in a 3D curved grid format to highlight any maxima/minima formation in
the response.
3.3.1.1 pH of Solid Phase
Examining the pH values shown in Table 3-13 there is less variation than in the previous
study most likely from the lack of hydrogen present with the lowest reading being ~8.5. The
contour plot demonstrates the variation in achievable pH values, the region for the lowest
possible values of < 8.5 is very small and only seen in the BL/RM ratio-Temperature plot. It
should be noted that in that particular plot the displayed factor of Reaction Time is held at 1.75
hrs (105 minutes); the appropriate “hold values” are displayed on each plot. The Reaction TimeBL/RM ratio plot also shows a wide variety of achievable pH values for the solid phase,
however, the final contour showing Reaction Time-Temperature plot reveals that the majority of
experimental conditions for those two factors would result in a solid phase pH value of 9 – 9.25.
The results of Table 3-15 point out that only the BL/RM ratio has a significant influence upon
60
the pH values of the solid phase which explains why the one plot that held a fixed value for the
ratio did not show a variety of achievable pH values.
The response surface plots begin to show a valley forming for the pH of the solid phase
on the Reaction Time-BL/RM ratio and Reaction Time-Temperature plots. The valley sits
perpendicular to the reaction time axis at ~1.5 – 1.75 hrs; looking back on the corresponding
contour plots the evidence of a local minimum was present but could easily be missed. The final
surface plot is difficult to interpret due to the way the data slopes away from the point of view.
The lowest point is found on the bottom right tip of the grid at approximately 365 °C and a 12:1
BL/RM ratio.
61
Table 3-14: Experimental model fitted to the responses from the 17 reactions in Table 3-12 with uncoded factors.
Eq
R2
𝑌1 = 8.19 + 0.0160𝑋1 − 0.160𝑋2 − 1.325𝑋3 − 2.394𝑥10−5 𝑋12 − 1.760𝑥10−5 𝑋22 + 0.243𝑋32 + 4.808𝑥10−5 𝑋1 𝑋2 + 0.00132𝑋1 𝑋3 + 0.00475𝑋2 𝑋3
2
79.16
52.37
pHaq
𝑌2 = 7.706 − 0.0108𝑋1 − 0.427𝑋2 − 0.253𝑋3 + 5.807𝑥10−5 𝑋12 − 0.0163𝑋22 + 0.167𝑋32 − 0.00240𝑋1 𝑋2 − 0.00111𝑋1 𝑋3 − 0.0100𝑋2 𝑋3
3
92.06
81.85
maq
𝑌3 = −252.042 + 1.523𝑋1 + 6.993𝑋2 + 7.994𝑋3 − 0.00239𝑋12 + 0.141𝑋22 + 0.182𝑋32 + 4.81𝑥10−5 𝑋1 𝑋2 + 0.00132𝑋1 𝑋3 + 0.00475𝑋2 𝑋3
4
96.79
92.66
%Csolid
𝑌4 = 184.084 − 1.188𝑋1 + 7.332𝑋2 + 11.267𝑋3 + 0.00204𝑋12 − 0.103𝑋22 + 0.919𝑋32 − 0.0125𝑋1 𝑋2 − 0.0537𝑋1 𝑋3 + 0.198𝑋2 𝑋3
5
97.82
95.01
%H2Oaq
𝑌5 = 151.822 − 0.81𝑋1 + 10.374𝑋2 − 4.444𝑋3 + 0.00173𝑋12 + 0.0178𝑋22 − 1.060𝑋32 − 0.0329𝑋1 𝑋2 + 0.0311𝑋1 𝑋3 − 0.0713𝑋2 𝑋3
6
90.48
78.23
𝑌6 = −17.928 + 0.0947𝑋1 + 0.324𝑋2 + 0.523𝑋3 − 7.758𝑥10−5 𝑋12 + 0.0264𝑋22 + 0.0688𝑋32 − 0.00293𝑋1 𝑋2 − 0.00190𝑋1 𝑋3 − 0.0106𝑋2 𝑋3
7
97.78
94.92
𝑌7 = 32986.8 + 61.4651𝑋1 − 8775.09𝑋2 − 40892.8𝑋3 + 0.166681𝑋12 + 229.754𝑋22 − 11407.3𝑋32 + 11.5385𝑋1 𝑋2 + 258.462𝑋1 𝑋3 + 150. 000𝑋2 𝑋3
8
72.20
36.45
[Na]solid
Fb
2.02
12.04
0.35
1.38
0.00
0.08
1.89
0.04
1.96
0.01
0.38
pc
0.183
0.010
0.570
0.278
0.990
0.785
0.212
0.847
0.205
0.923
0.832
Response
Experimental model
pHsolid
Χlf
[Na]solid
𝑋1 : Temperature (°C); 𝑋2 : BL/RM ratio (g/g); 𝑋3 : Reaction time (hrs)
Table 3-15: Analysis of variance for the response factors for the neutralization of Red Mud using Strong Black Liquor.
Source
Model
X1
X2
X3
X12
X22
X33
X 1 X2
X 1 X3
X 2 X3
LOFd
a
DF
9
1
1
1
1
1
1
1
1
1
5
pHsolid
Fb
2.95
0.66
21.06
0.00
0.01
0.00
3.23
0.00
0.19
0.04
0.86
c
p
0.084
0.443
0.003
0.972
0.908
0.999
0.115
0.961
0.674
0.852
0.616
pHaq
Fb
9.02
7.29
41.84
3.32
0.16
2.89
2.89
12.32
0.26
0.32
8.81
c
p
0.004
0.031
<10-3
0.111
0.702
0.133
0.133
0.010
0.629
0.592
0.105
maq
Fb
23.45
1.66
197.14
5.40
0.39
0.32
0.00
0.00
0.03
6.25
15.80
c
p
<10-3
0.239
<10-3
0.053
0.550
0.592
0.946
0.988
0.872
0.041
0.061
%Csolid
Fb
34.88
2.42
247.56
22.09
5.56
3.22
2.46
9.45
16.91
3.47
14.77
a
c
p
<10-3
0.164
<10-3
0.002
0.051
0.116
0.161
0.018
0.005
0.105
0.065
%H2Oaq
Fb
7.39
28.15
3.98
6.65
1.44
0.03
1.18
23.46
2.06
0.16
23.74
c
p
0.008
0.001
0.086
0.037
0.270
0.857
0.313
0.002
0.195
0.698
0.041
Χlf
Fb
34.23
59.11
205.08
0.78
0.38
10.04
0.65
24.45
1.00
0.47
8.80
c
p
<10-3
<10-3
<10-3
0.408
0.558
0.016
0.446
0.002
0.350
0.515
0.105
Degrees of freedom. b F-value = mean squares regression/mean squares residual error. c p-value. d Lack of fit with F = mean
squares regression/mean squares pure error.
62
Radj2
3.3.1.2 pH of Aqueous Phase
The factors of Temperature and BL/RM ratio are significant in determining the pH value
of the aqueous phase and the interaction between them is also important. A large portion of the
contour plots is dedicated to a pH range of 7.6 – 8.0 meaning that the values would mostly likely
be a value to expect from most reactions. The plots of BL/RM ratio-Temperature and Reaction
Time-BL/RM ratio both have a small area that would yield an almost neutral aqueous phase at
similar experimental settings as the pH of the solid phases. A somewhat circular pattern can be
seen in the Reaction Time-BL/RM ratio contour plot possibly suggesting the presence of an
overall minimum value slightly outside the current set of parameters.
The surface plot appears to show a valley at the same reaction time of 1.5 – 1.75 as
previously pointed out but it also shows somewhat of a possible valley perpendicular to the
BL/RM ratio just above the value of 12.5. The surface plot of Reaction Time-Temperature again
shows the valley along a reaction time of 1.5 – 1.75 hours, moreover the pH decreases as the
temperature decreases and it appears the pattern would continue if the temperature was lowered
beyond the 300 °C threshold. The response surface of BL/RM ratio-Temperature has the same
value for almost ¾ of the grid resulting in a mostly flat surface however, the lowest achieved
value is in the same place as in the previous response at 365 °C and 12:1 ratio.
A final observation made was that the model used to predict the response surface has a pvalue less than 0.05 thus it is above the 95% confidence level based the variance calculations and
a good fit to the data. Unlike the previous response where the model did not fit well at all, this
can also be seen in the R2 values in Table 3-14.
63
3.3.1.3 Mass of Aqueous Phase
The contour plot showing Reaction Time-Temperature has virtually no change across all
but a tiny part of the possible experimental parameters highlighting that neither of them have an
effect on the response of the system. This is supported by the other two contour plots which
show that only major variation that occurs is along the BL/RM ratio axis; there are only minor
affects from the other two factors. The variance testing supports that only the BL/RM ratio is a
factor for the mass of the aqueous phase but it also shows that the interaction between BL/RM
ratio and the Reaction Time is also a prominent force in determining the response.
3.3.1.4 Carbon Content of Solid Phase
The contour plots for the carbon content have similar patterns to those of the mass of
aqueous phase. It appears that the ratio of BL/RM has the most impact; it is the only carbon
source after all so its influence should be obvious and expected. The effect of Temperature does
not provide much stimulus to improve the carbon content until higher temperatures and material
ratios. Longer reaction times are beneficial for higher BL/RM ratios as it provides more time for
the thermal decomposition of the lignin fragments and impregnation of carbon within the crystal
matrix of RM. However the extended times have little effect with a change in temperature. The
surface plots seem to show that the reaction time does not affect the response as much as the pvalue would indicate. There is little change in the carbon content in the Reaction Time-BL/RM
ratio and Reaction Time-Temperature surface plot as the time is increased.
The interaction of Temperature and Reaction Time appears to affect the system in a
statistically significant way but it is difficult to see where this interaction is beneficial in
comparison to the two main factors.
64
3.3.1.5 Water Content of Aqueous Phase
The ANOVA shows that the Temperature and Reaction Time are now the significant
factors controlling the result of the water content. This is an interesting change from the factorial
design results which had shown the Temperature and BL/RM ratio to be the determining
elements; it is however easy to see that the ratio of BL/RM no longer has much of an impact.
Judging by the contour plots, high temperatures are the most favorable. That result coupled with
the reaction time of 1.5-1.75 hours, that other responses have shown to be an optimum length of
time, allows for the maximum values to be realized. The surface plot for Reaction TimeTemperature shows the highest achievable value of ~85% H2O at 365 °C and 3 hrs.
3.3.1.6 Magnetic Susceptibility
The results for the magnetic susceptibility were identical to the factorial design study
showing the Temperature, BL/RM ratio and the interaction effect between those factors strongly
influences the response. High temperatures and low material ratios yield the best result and the
length of time at process temperature does not enhance the magnetization. The surface plot for
Reaction Time-BL/RM ratio really demonstrates this point with a long smooth slope with
minimal curvature along the y-axis; the plot to the right of it also shows a similar shape.
3.3.1.7 Sodium Concentration in Red Mud
The results for the sodium concentration show the same trend in optimum reaction time
of 1.5-1.75 hrs as seen in several other responses; the trend is obvious in the surface plot of
Reaction Time-BL/RM ratio . The same plot also draws attention to the lack of influence varying
the BL/RM ratio has upon the system. The contour plot for Reaction Time-Temperature
highlights the interaction between those two terms that the factorial design deemed to be
65
significant. While no longer statistically important, the highest values for the response can be
achieved at high temperature and long reaction times.
3.3.1.8 Statistical relevance of the data
The analysis of variance (ANOVA) for the regression shown in Table 3-15 revealed that
the model was statistically relevant (p-value <0.05) for all but one of the responses, that being
the pH of the solid phase. The calculated F-values are higher than the tabulated F-value at the
0.05 confidence level which is F0.05,9,7 = 3.68. With Fα,DF(m),DF(r) where α = confidence interval,
DF(m) is the degrees of freedom of the model equal to p – 1, and DF(r) is the degrees of freedom
for the residual error equal to n – p .The number of coefficients to be determined is p = 10 and
the number of experiments is n = 17.
A lack of fit (LOF) test was also conducted to determine whether the model was adequate
to describe the data. At the 95 % confidence interval, all p-values were insignificant except for
the value associated with the water content of the aqueous phase (%H2Oaq). The conclusion is
that the quadratic model currently in use is sufficient to describe the data.
66
3.3.2 Optimum Reaction Conditions
Minitab 16® possesses two ways to identify possible optimum experimental parameters.
There is a function built into the program called the “Response Optimiser,” it uses the fitted
models shown in Table 3-14 to compute the ideal settings taking in to account the desired result
programmed by the user. The criteria for the optimum response values were:
 Neutralization the pH (pH 7) for the solid phase and the aqueous phase.
 Minimization of the mass of aqueous phase while maximizing the water content
of the same phase.
 Maximization of the carbon content, magnetic susceptibility, and the sodium
concentration of the recovered solid phase.
Each response was weighted equally so that no response was treated differently than the others.
The resulting data is shown on page 112 of Appendix D; the experimental parameters calculated
to be the optimum settings are a Temperature of 365 °C, a BL/RM ratio of 7.5:1, and a Reaction
time of 1.5 hrs. The expected response values are also shown but were not confirmed through
experimental testing.
The second way Minitab can determine the optimum parameters is by constructing an
overlaid contour plot. For each response, a desired upper and lower boundary was selected for
the corresponding contour plot. Two of the three factors were then chosen to be continuous
variables to be plotted on the x axis (Temperature) and the y axis (BL/RM ratio). The contours
were then plotted together using the Reaction Time as a fixed variable generating three separate
plots. The white area (if present) indicates a region of experimental parameters that satisfies the
boundaries imposed upon the responses; the three plots are shown on page 113. The first plot
67
which has a fixed reaction time of 0.5 hrs (30 minutes) shows there are no possible combination
of parameters that would satisfy all the contour requirements. The other two plots, which have
fixed times of 1.75 hrs (105 minutes) and 3 hrs (180 minutes), do show an area where the chosen
parameters are fulfilled. The experimental coordinates are similar to those produced by the
Response Optimiser function as shown in Table 3-16.
Table 3-16: Comparison of optimum reaction conditions between response optimizer function
and overlaid contour plots.
Temperature (°C)
BL/RM ratio (g/g)
Reaction Time (hrs)
Response
Optimiser
365
7.5
1.5
Overlaid Contour Plot
352-365
6.5-7.5
1.75 (fixed term)
68
352-365
7.5-8.5
3 (fixed term)
3.3.3 Summary
The results from the factorial design study enabled the main factor of hydrogen to be
removed from the study, as it was recognized to be not influential enough to warrant the cost
expenditure if the reactions were conducted on a larger scale. Supplementary experiments were
then conducted with the remaining factors. Once complete the data gathered was subjected to the
same form of statistical analysis (ANOVA) as before and with the additional data points, contour
plots were generated to identify the parameters needed to achieve a specific range of values for
each response. 3D response surface plots were also created to aid in the identification of data
trends such as local or global maxima/minima. They can also identify areas where the chosen
boundaries for a main factor may not be sufficient to fully explore a developing trend in a
response and should be expanded to explore trends outside of the studied range.
The data was eventually combined to predict optimum reaction conditions for the study
using two different methods. The first method made use of a function within Minitab that
calculates the conditions required to satisfy a user controlled range of values for each response.
The calculations were then combined to achieve a set of parameters that best fulfills the response
requirements. The second method utilized the contour plots generated by overlaying the
individual plots onto a single large plot. To perform this action, two factors had to be chosen to
be continuously variable (Temperature and BL/RM ratio) while the remaining factor (Reaction
Time) was fixed at a specific value; a range of achievable values for each response were chosen
as well. A total of three overlaid contour plots were generated, one for each of the reaction times
tested, the white areas on the plots signify the restrictions that must be placed on the system to
achieve the desired result.
69
Both methods provided similar optimised experimental parameters at Temperature: 365 °C,
BL/RM ratio: 7.5:1, and Reaction Time: ~1.5 hrs.
While both methods provide the optimum reactions conditions, using the response
optimiser function has an added benefit of predicting the values for each of the responses. As
described previously the figure on page 112 shows the expected response values. Comparing
these expected values to the achieved values shown in Table 3-13, the values are all very similar
however there is a reaction where the realized response values are better than any other possible
reactions, predicted or otherwise, in the central composite design. Reaction #12 produced a solid
phase which had a measured alkalinity 2.5 units lower (pH 8.55) than the original Red Mud (pH
11.14); the pH measurement of the recovered aqueous phase remained unchanged at 7.68
compared to the starting value of the Black Liquor (pH 7.58). Those values were reached while
at the same time adding ~32 % w/w carbon to the recovered solid phase. These values and
observations are very encouraging evidence that synergistically co-processing Red Mud and
Black Liquor form a material with a reduced alkalinity and increased carbon content that may
make it a viable soil additive and/or allow for the remediation and revegetation of Red Mud
storage sites.
70
3.4 Experimental
3.4.1 Factorial Design Calculations
As previously stated the 24 factorial design matrix for the experiments was defined using the
reaction conditions outlined in Table 3-3 and the coded experimental levels in
Table 3-5. The heating rate and the heating duration for the reactions to achieve process
temperature varied substantially (4–6 °C min-1 and 40–60 min, respectively) depending on the
amount of material in the reactor. The restrictions imposed upon the experimental domains were
derived from established values from previous studies. The mass ratios were chosen based upon
test experiments conducted before the start of the project to ensure workable amounts of
materials were available.
The statistical calculations utilized coded dimensionless values (Xi) instead of the real
values of the independent variables. The three replicate reactions at the centre point were added
(runs 17-19) to determine the experimental error and the data reproducibility as mentioned
before. Then, the response surface was determined using the values and the coded levels of Table
3-3 and Table 3-12 with the hydrogen pressure dropped as an independent variable for the
central composite.
For 4 factors, the full factorial model is shown in equation 8, and for 3 factors, the central
composite model is shown in equation 9 where Y is the predictive response, Xi are the input
variables and bi are constant. The term b0 is the intercept term, bi are the linear terms, βii are the
squared terms, and βij, βijk, and βijkl are the interaction terms.
𝑌 = 𝛽0 + 𝛽1 𝑋1 + 𝛽2 𝑋2 + 𝛽3 𝑋3 + 𝛽4 𝑋4 + 𝛽12 𝑋1 𝑋2 + 𝛽13 𝑋1 𝑋3 + 𝛽14 𝑋1 𝑋4 + 𝛽23 𝑋2 𝑋3 + 𝛽24 𝑋2 𝑋4 +
𝛽34 𝑋3 𝑋4 + 𝛽123 𝑋1 𝑋2 𝑋3 + 𝛽124 𝑋1 𝑋2 𝑋4 + 𝛽134 𝑋1 𝑋3 𝑋4 + 𝛽234 𝑋2 𝑋3 𝑋4 + 𝛽1234 𝑋1 𝑋2 𝑋3 𝑋4
71
[9]
𝑌 = 𝛽0 + 𝛽1 𝑋1 − 𝛽2 𝑋2 − 𝛽3 𝑋3 − 𝛽11 𝑋12 − 𝛽22 𝑋22 + 𝛽33 𝑋32 + 𝛽12 𝑋1 𝑋2 + 𝛽13 𝑋1 𝑋3 + 𝛽23 𝑋2 𝑋3 [10]
The determination of the coefficients β in the mathematical model was performed by
regression analysis. The coefficients were obtained by solving the matrix system of equation 10,
with X being the matrix of the level of the independent variables, 𝑋 ′ being the transpose matrix
of X, y being the vector of the observations, β being the vector of the regression coefficients and
ϵ being the vector of random errors.
𝑦 = 𝑋𝛽 + 𝜖, 𝛽 = (𝑋 ′ 𝑋)−1 𝑋 ′ 𝑦
[11]
The competences of the models were tested by analysis of variance (ANOVA) at a 95%
level of confidence using the Fisher F-test and the Student t-test. The coefficient of
determination (R2) and the adjusted coefficient (Radj2) were evaluated for the linear and quadratic
models. The R2 value indicates how much variation in the response is explained by the fitted
model. The Radj2 is more relevant because it accounts for the number of factors in our model. The
values of the R coefficients indicate the models accurately evaluate the contributions of each
influential factor.
3.4.2
General Procedure for Co-processing Reactions
All DoE reactions were performed in a 300 mL Parr batch reactor (T316 Stainless Steel)
with a standard K-type thermocouple modified with a Setra pressure transducer (model 206, 010,000 psi, 0.1-5.1 VDC) and an Omega USB data acquisition system (OM-DAQ-USB-2400
series) for real-time data recording; stirring was performed using a glass coated magnetic stir bar
and standard stir plate. The BL was shaken for 30 seconds before being slowly transferred to a
glass dish and weighed; it was then poured into the reactor with slow stirring. The RM was pre72
dried in a large batch at 110 °C (drying oven) and stored in an airtight glass jar until needed. It
was weighed and slowly added to the BL already in the reactor with continued stirring. The
reactor was then sealed and flushed with hydrogen once to remove the majority of any normal
atmosphere contained within. If the reaction required initial hydrogen pressure, the reactor was
flushed three times and then pressurized to the required starting pressure.
3.4.3 Analytical Instrumentation
The Red Mud, Black Liquor and the product phases obtained after each reaction were
characterized using several different analytical techniques. CHNS/O Elemental Analysis was
conducted using a Thermo Scientific Flash 2000 Elemental Analyzer. The Magnetic
Susceptibility was determined using a Bartington MS2 meter equipped with the MS2B Dual
Frequency sensor, capable of taking measurements at both low (χlf at 0.46 kHz) and high (χhf at
4.6 kHz) frequencies. The water content of the Black Liquor and the resulting aqueous phases
was determined by Karl Fischer Titration using a Metrohm 870 KF Titritino Plus titroprocessor.
The pH values for the Red Mud, Black Liquor, aqueous and solid phases were determined using
a Denver Instrument UB-5 UltraBasic pH meter equipped with a Fisher Scientific Accumet Pulp
and Paper Double Junction Combination gel-filled epoxy electrode (13-620-299A) calibrated
using three buffer solutions (Metrohm 6.2307.100, pH 4 at 25 °C; Metrohm 6.2307.110, pH 7 at
25 °C, Metrohm 6.2307.120, pH 9 at 25 °C). To determine the pH of the Red Mud and the
recovered solid phases, ~1.0 g of material is placed in 10 mL water then sonicated for 1 hr and
centrifuged for 30 minutes at 1500 rpm. The resulting solution was then transferred to a clean
dry vial using a Pasteur pipette before measurement at ambient temperature. Nuclear Magnetic
Resonance (NMR) analysis of select liquid products was performed using a Bruker Avance III
400 Mhz NMR spectrometer. Gas samples from the headspace of the reactions were analyzed
73
using an SRI 8610C Micro-GC fitted with a TCD and calibrated against authentic samples (1000
ppm in Helium, Grace Davison Discovery Sciences) of the linear C1–C6 alkanes and C2–C6
terminal alkenes; each gas sample was collected in a balloon and injected with a 2.5 mL syringe.
74
4
Summary of Results
In principle, the intent of this thesis was to address an industrial waste disposal issue
which has a direct impact on Canada and the global ecosystem at large. For this reason, the waste
products Red Mud and Black Liquor were obvious choices as both the Aluminium and Pulp and
Paper Industry have a large presence in the country.
In the first project, which was the design and construction of the high pressure
hydrogenation facility, which to our knowledge, was unique to a Canadian post-secondary
educational institution. This provided an excellent learning opportunity for all personnel
involved and allowed for the expansion of the research capabilities of the University. As with all
new developments, there are always problems occurring and this project had its fair share of
them. From overlooked power requirements during the design of the lab to the various issues that
accompanied the new reactors, there was always a chance to learn from the mistakes that were
made so that they would not be repeated if another such facility were to be built at the University
of Guelph. The same statement can be applied to all the safety training and consultations that
took place and documentation that had to be created. A foundation now exists that can be further
built upon and improved over time.
With all of the delays that accompanied the first project, in the end amounting to almost
whole year, the second project and ultimately the main project of this thesis could not be
conducted using the new lab and equipment. Instead, this project was carried out using
equipment already existing in the Schlaf lab. This, however, did not lessen the impact or validity
of the research conducted, as there have not been any published previous attempts to co-process
the two aforementioned waste products or to apply a DoE approach to the co-processing study.
75
DoE studies are routinely deployed throughout the chemical industry to perform cost benefit
analysis on chemical processes to help control yields, waste production, and ultimately costs.
Choosing to use a combination of a factorial design and a central composite design allowed for
the identification of important reaction parameters and the prediction of optimum reaction
conditions.
Through the factorial design portion of the study, the influence of the chosen main factors
was analyzed and the most statistically relevant factors were identified to be Temperature,
BL/RM ratio, and Reaction Time. The benefit of identifying the most influential factors is that
those factors could have a major impact on the viability and feasibility of the process if it were
increased to a more industrially relevant scale. The central composite portion of the study
utilized the data from the factorial study and built upon the data allowing for the isolation of a
set of conditions that would optimize the measured responses further assisting in determining if
the study should progress further (i.e., reaction scale-up). Possessing a set of optimum process
conditions can also assist in providing a more accurate cost-benefit analysis or life cycle analysis
if either type of study was deemed to be a requirement.
76
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78
Appendix
79
Appendix A: Select Micro-GC Traces
80
A1: Micro-GC trace of 1000ppm C1 – C6 alkane standards
A2: Micro-GC trace of 1000 ppm C2 – C6 alkene standards
81
A3: Micro-GC trace of lab atmosphere reference
A4: Micro-GC trace of DoE reaction, representative over all reactions conducted
82
A5: Micro-GC trace of acid digestion white precipitate recovered from aqueous phase postreaction using 2M HCl (representative of all applicable reactions)
83
Appendix B: 3D Autogenic Pressure Response as a Function of Time and
Temperature for Multi-Reactor System and REFPROP Water Vapour Pressure
Plots
84
B1: Bach autogenic pressure response as a function of time and temperature with 50, 100
and 150mL of water
85
B2: Escher autogenic pressure response as a function of time and temperature with 50, 100
and 150mL of water
86
B3: Gödel autogenic pressure response as a function of time and temperature with 50, 100
and 150mL of water
87
Theoretical Pressure-Temperature Reponse for Water Vapour in an
Ideal Closed System
1000
Critical Point
Pressure (psig)
Saturation Line
Density 0.1 g/cm^3
Density 0.2 g/cm^3
100
Density 0.3 g/cm^3
Density 0.4 g/cm^3
Density 0.5 g/cm^3
Density 0.6 g/cm^3
Density 0.7 g/cm^3
10
Density 0.8 g/cm^3
Density 0.9 g/cm^3
1
0
100
200
300
400
500
Temperature (°C)
B4: Theoretical Pressure-Temperature Response for Water vapour contained in an ideal closed system within the range of the
High Pressure Reactor specifications.
88
Theoretical Pressure-Temperature Response for Water Vapour in an
Ideal Closed System
5000
4000
Critical Point
Pressure (psig)
3000
Saturation Line
Density 0.1 g/cm^3
Density 0.2 g/cm^3
Density 0.3 g/cm^3
2000
Density 0.4 g/cm^3
Density 0.5 g/cm^3
Density 0.6 g/cm^3
1000
275
325
375
425
475
525
Temperature (°C)
B5: Theoretical pressure-temperature response for water vapour contained in an ideal closed system near the limits of the
high pressure reactor specifications.
89
Appendix C: Spectral data for aqueous phases
90
C1: 1H NMR of red aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent.
91
C2: 1H NMR of red aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent and water
suppression NMR program.
92
C3: 13C NMR of red aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent
93
C4: 1H NMR of purple aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent
94
C5: 1H NMR of purple aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent and water
suppression.
95
C6: 13C NMR of purple aqueous phase obtained on a 400 MHz spectrometer using D2O as the solvent
96
Appendix D: Pareto charts, residual plots, main effects plots, interaction
plots, and cube plots from DoE analysis
97
24 Factorial Design
Residual Plots for pHsolid
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is pHsolid, Alpha = 0.05)
AD
0.50
90
Residual
BD
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
B
D
50
AB
1
-0.50
ABD
-0.25
0.00
0.25
Residual
CD
0.00
-0.50
0.50
8.5
9.0
Histogram
C
BC
A
BCD
ACD
0
1
2
3
Standardized Effect
4
12
8
4
0.25
0.00
-0.25
0
-0.4
-0.2
0.0
0.2
Residual
0.4
-0.50
0.6
2
4
Normal Probability Plot
(response is pHsolid, Alpha = 0.05)
Versus Fits
90
D
50
0.25
0.00
-0.25
10
1
-0.50
BD
-0.25
0.00
Residual
0.25
-0.50
0.50
8.5
9.0
Histogram
AD
A
2
3
Standardized Effect
4
5
0.50
3.6
0.25
2.4
1.2
0.0
-0.4
-0.2
0.0
0.2
Residual
0.00
0.4
-0.50
0.6
2
4
4
Point Ty pe
Corner
Center
9.6
9.4
8
12
0.50
1.75
3.00
0
250
10.0
9.5
9.0
9.2
10.0
9.0
Mean
9.5
BL/RM Ratio
8.8
9.6
18
500
Temperature
8
Hydrogen
16
Data Means
BL/RM Ratio
4
6
8
10 12 14
Observation Order
Interaction Plot for pHsolid
Data Means
365.0
10.0
-0.25
Main Effects Plot for pHsolid
Temperature
9.5
Fitted Value
Versus Order
4.8
Residual
Frequency
AB
332.5
Reaction Time
18
0.50
Residual
N ame
Temperature
BL/RM Ratio
H y drogen
Percent
F actor
A
B
D
B
300.0
16
99
2.201
1
6
8
10 12 14
Observation Order
Residual Plots for pHsolid
Pareto Chart of the Standardized Effects
0
10.0
0.50
Residual
Frequency
ABC
9.5
Fitted Value
Versus Order
16
AC
Term
0.25
-0.25
10
ABCD
Term
Versus Fits
99
4.303
12
9.0
10.0
9.5
9.4
Reaction Time
9.0
9.2
Temperature
300.0
332.5
365.0
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
9.0
Hydrogen
8.8
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for pHsolid
Centerpoint
Factorial Point
8.8600
12
8.6800
8.9700
8.6000
9.0400
8.8800
8.8000
8.7600
9.4033
BL/RM Ratio
9.6900
10.0700
10.2400
3
9.3900
Reaction Time
9.9400
4
9.6900
8.6500
9.1000
0.5
300
Temperature
365
0
500
H y drogen
D1: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for pH of
solid phase before (Top) and after (Middle) reduction of terms for calculation
98
Residual Plots for pHaq
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is pHaq, Alpha = 0.05)
4.303
0.1
90
Residual
AB
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
B
D
BD
50
10
AD
1
-0.2
ABD
Term
Versus Fits
99
A
-0.1
0.0
Residual
CD
-0.2
0.1
7.5
8.0
Histogram
ABC
ACD
AC
C
0
1
2
3
4
5
6
Standardized Effect
7
8
Residual
BC
8
4
9
0
-0.15
-0.10
-0.05 0.00
Residual
0.05
0.0
-0.1
-0.2
0.10
2
4
6
8
10 12 14
Observation Order
Normal Probability Plot
(response is pHaq, Alpha = 0.05)
Versus Fits
D
0.2
90
Residual
N ame
Temperature
BL/RM Ratio
H y drogen
Percent
F actor
A
B
D
B
50
10
BD
1
0.1
0.0
-0.1
-0.2
-0.30
-0.15
0.00
Residual
AB
0.15
0.30
7.5
8.0
Histogram
ABD
4.5
A
2
3
4
5
Standardized Effect
6
7
8
1.5
0.1
0.0
-0.1
-0.2
0.0
-0.2
-0.1
0.0
Residual
0.1
0.2
2
4
4
Point Ty pe
Corner
Center
8
12
0.50
1.75
3.00
0
250
9.0
8.5
8.0
8.2
9.0
8.0
8.5
Mean
BL/RM Ratio
4
8
Reaction Time
8.6
18
500
Temperature
365.0
16
Data Means
BL/RM Ratio
8.4
332.5
6
8
10 12 14
Observation Order
Interaction Plot for pHaq
Data Means
300.0
9.5
Versus Order
3.0
Main Effects Plot for pHaq
Temperature
8.5
9.0
Fitted Value
0.2
Residual
6.0
Frequency
AD
8.6
18
99
2.228
1
16
Residual Plots for pHaq
Pareto Chart of the Standardized Effects
0
9.5
0.1
12
Frequency
ABCD
8.5
9.0
Fitted Value
Versus Order
16
BCD
Term
0.0
-0.1
12
8.0
Hydrogen
9.0
8.5
Reaction Time
8.4
8.0
8.2
8.0
Temperature
300.0
332.5
365.0
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
Hydrogen
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for pHaq
Centerpoint
Factorial Point
7.98000
12
7.96000
7.64000
8.13000
8.13000
8.01000
7.88000
7.63000
8.02333
BL/RM Ratio
8.34000
8.45000
9.58000
3
8.14000
Reaction Time
9.54000
4
8.25000
8.36000
7.98000
0.5
300
Temperature
365
0
500
H y drogen
D2: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for
pH of aqueous phase before (Top) and after (Middle) reduction of terms for
calculation
99
Residual Plots for maq
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is maq, Alpha = 0.05)
4.30
BC
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
2
90
Residual
C
Percent
F actor
A
B
C
D
B
A
50
10
AD
-4
BCD
-2
0
Residual
ABD
2
20
40
Histogram
AB
ABC
80
100
Versus Order
2
BD
ABCD
0
5
10
15
20
25
Standardized Effect
30
Residual
12
Frequency
AC
ACD
8
4
35
0
-2
-4
0
-4
-3
-2
-1
0
Residual
1
2
3
2
4
6
Normal Probability Plot
(response is maq, Alpha = 0.05)
A
90
50
5
0
10
1
C
-5
-10
-5
0
Residual
5
10
0
25
Histogram
BC
20
Residual
D
2.4
5
0
-5
0.0
-5.0
-2.5
0.0
2.5
Residual
5.0
7.5
2
4
6
8
10 12 14
Observation Order
4
Point Ty pe
Corner
Center
8
12
0.50
1.75
3.00
0
250
500
90
60
Temperature
30
90
40
60
20
BL/RM Ratio
332.5
365.0
4
8
Reaction Time
80
18
Data Means
BL/RM Ratio
60
300.0
16
Interaction Plot for maq
Data Means
Temperature
100
1.2
25
Main Effects Plot for maq
80
75
Versus Order
3.6
Frequency
AD
50
Fitted Value
10
4.8
10
15
Standardized Effect
18
10
Residual
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
B
5
16
Versus Fits
99
2.20
0
8
10 12 14
Observation Order
Residual Plots for maq
Pareto Chart of the Standardized Effects
Mean
60
Fitted Value
16
D
Term
0
-2
-4
1
CD
Term
Versus Fits
99
12
30
90
Hydrogen
60
Reaction Time
60
30
Temperature
300.0
332.5
365.0
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
40
Hydrogen
20
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for maq
Centerpoint
Factorial Point
67.9702
12
91.5747
60.2229
85.6100
89.1609
93.9327
58.9669
74.5198
49.2606
BL/RM Ratio
20.5476
24.6515
16.4289
3
26.1753
Reaction Time
18.3200
4
27.9061
15.9171
18.0967
0.5
300
Temperature
365
0
H y drogen
500
D3: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for
mass of aqueous phase before (Top) and after (Middle) reduction of terms
for calculation
100
Residual Plots for C%
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is C%, Alpha = 0.05)
4.30
AC
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
90
50
10
CD
0.25
0.00
-0.25
-0.50
1
C
-0.50
AD
-0.25
0.00
Residual
ACD
0.25
0.50
20
D
Frequency
ABC
BD
BCD
ABD
0
10
20
30
40
Standardized Effect
50
0.50
12
0.25
8
4
60
0.00
-0.25
-0.6
-0.4
-0.2 0.0
0.2
Residual
0.4
0.6
2
4
6
8
10 12 14
Observation Order
16
18
Residual Plots for C%
Normal Probability Plot
Versus Fits
99
2.36
1
90
Residual
A
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
B
AB
50
10
AC
1
CD
0
-1
-2
-1
0
Residual
C
1
2
20
25
Histogram
AD
D
5
10
15
20
Standardized Effect
25
Residual
BC
2.4
1.2
30
-1.5
-1.0
-0.5
0.0
0.5
Residual
0
1.0
1.5
2
4
6
4
Point Ty pe
Corner
Center
36
8
12
0.50
1.75
3.00
0
250
30
Temperature
28
20
40
24
30
BL/RM Ratio
20
8
Hydrogen
18
500
40
32
4
16
Data Means
BL/RM Ratio
365.0
8
10 12 14
Observation Order
Interaction Plot for C%
Data Means
332.5
Reaction Time
40
-1
0.0
Main Effects Plot for C%
Temperature
35
1
3.6
Frequency
ACD
30
Fitted Value
Versus Order
4.8
300.0
40
-0.50
0
(response is C%, Alpha = 0.05)
0
35
Versus Order
16
Pareto Chart of the Standardized Effects
Mean
25
30
Fitted Value
Histogram
BC
ABCD
Residual
Term
0.50
Residual
A
Percent
F actor
A
B
C
D
B
AB
Term
Versus Fits
99
12
20
40
36
30
Reaction Time
32
20
28
Temperature
300.0
332.5
365.0
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
24
Hydrogen
20
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for C%
Centerpoint
Factorial Point
39.4930
12
39.2890
32.9000
41.2270
37.9830
39.2080
32.2750
31.8390
28.5027
BL/RM Ratio
20.6100
20.9220
17.1030
3
21.8970
Reaction Time
29.5720
4
22.5420
20.3380
21.7310
0.5
300
Temperature
365
0
H y drogen
500
D4: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for
carbon content of solid phase before (Top) and after (Middle) reduction of
terms for calculation
101
Residual Plots for H2O%aq
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is H2O%aq, Alpha = 0.05)
AB
ABC
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
1.5
10
B
0.0
-1.5
-3.0
1
-3.0
C
-1.5
0.0
Residual
AC
1.5
3.0
70
75
Histogram
D
AD
Frequency
BD
ACD
BCD
ABCD
0
1
2
3
Standardized Effect
4
90
1.5
8
4
0.0
-1.5
-3.0
0
-3
-2
-1
0
1
Residual
2
3
2
4
6
8
10 12 14
Observation Order
16
18
Residual Plots for H2O%aq
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is H2O%aq, Alpha = 0.05)
Versus Fits
99
2.262
2
90
Residual
ABD
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
A
50
10
AB
1
ABC
-4
-2
B
0
Residual
2
0
-2
-4
4
70
75
80
Fitted Value
Histogram
85
90
Versus Order
8
C
D
0
1
2
3
4
Standardized Effect
5
6
2
6
Residual
Frequency
CD
4
2
0
-3
-2
-1
0
1
Residual
Main Effects Plot for H2O%aq
Temperature
2
0
-2
-4
3
2
4
6
4
Point Ty pe
Corner
Center
76.5
8
12
0.50
1.75
3.00
0
250
75
75.0
70
80
73.5
72.0
BL/RM Ratio
365.0
4
8
Hydrogen
18
500
80
Temperature
332.5
Reaction Time
16
Data Means
BL/RM Ratio
78.0
300.0
8
10 12 14
Observation Order
Interaction Plot for H2O%aq
Data Means
Mean
85
Versus Order
12
5
80
Fitted Value
3.0
16
BC
Residual
Term
90
50
CD
Term
Versus Fits
3.0
Residual
F actor
A
B
C
D
A
ABD
Percent
4.303
99
75
12
70
80
78.0
Reaction Time
76.5
75
75.0
70
Temperature
300.0
332.5
365.0
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
73.5
Hydrogen
72.0
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for H2O%aq
Centerpoint
Factorial Point
76.5233
12
72.2436
74.9492
69.1661
72.3333
69.8212
75.2206
78.9248
74.7401
BL/RM Ratio
68.9651
69.9829
91.2022
3
72.0076
Reaction Time
80.4381
4
74.5704
78.9208
74.1765
0.5
300
Temperature
365
0
H y drogen
500
D5: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for
water content of aqueous phase before (Top) and after (Middle) reduction
of terms for calculation
102
Residual Plots for Xlf
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is Xlf, Alpha = 0.05)
4.30
0.1
90
Residual
ABC
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
B
A
AB
50
10
C
-0.1
ACD
0.0
Residual
BCD
0.1
0.0
1.5
Histogram
CD
ABCD
D
ABD
0
5
10
15
20
Standardized Effect
25
Residual
BD
8
4
30
-0.15
0.0
-0.10
-0.05
0.00
Residual
0.05
0.10
2
4
6
8
10 12 14
Observation Order
1.0
90
Residual
A
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
B
50
10
AB
1
-1.0
-0.5
0.0
Residual
ABC
0.5
0.5
0.0
-0.5
-1.0
1.0
0
1
Histogram
BC
6
0.5
6
7
Residual
1.0
Frequency
8
D
4
2
0
-1.0
-0.5
0.0
Residual
0.5
Main Effects Plot for Xlf
0.0
-0.5
-1.0
1.0
2
4
6
8
10 12 14
Observation Order
4
Point Ty pe
Corner
Center
8
12
0.50
1.75
3.00
0
250
2
1
1.5
3
Mean
1.0
2
BL/RM Ratio
365.0
4
18
500
3
Temperature
2.0
332.5
Reaction Time
16
Data Means
BL/RM Ratio
2.5
300.0
4
Interaction Plot for Xlf
Data Means
Temperature
2
3
Fitted Value
Versus Order
C
3
4
5
Standardized Effect
18
Versus Fits
99
2.228
2
16
Residual Plots for Xlf
Normal Probability Plot
(response is Xlf, Alpha = 0.05)
1
6.0
-0.1
0
Pareto Chart of the Standardized Effects
0
4.5
0.1
12
Frequency
AD
3.0
Fitted Value
Versus Order
16
AC
Term
0.0
-0.1
1
BC
Term
Versus Fits
99
8
Hydrogen
12
1
3
2.5
2
Reaction Time
2.0
1
Temperature
300.0
332.5
365.0
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
1.5
1.0
Hydrogen
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for Xlf
Centerpoint
Factorial Point
0.81300
12
0.35600
0.86000
0.64500
1.17000
0.43700
1.30000
1.44000
1.14033
BL/RM Ratio
1.90000
1.69000
3.93000
3
1.41000
Reaction Time
3.57000
4
1.32000
5.50000
2.04000
0.5
300
Temperature
365
0
H y drogen
500
D6: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for
magnetic susceptibility before (Top) and after (Middle) reduction of terms
for calculation
103
Residual Plots for [Na] ug/g
Pareto Chart of the Standardized Effects
Normal Probability Plot
(response is [Na] ug/g, Alpha = 0.05)
4.303
BD
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
90
50
10
ABCD
10000
0
-10000
1
C
-10000
AD
0
10000
Residual
ACD
20000
40000
Frequency
D
BC
BCD
ABD
20000
12
10000
4
1
2
3
4
Standardized Effect
5
6
-1
00
00
50
00
-1
0
0
00
-5
0
2
0
0
0
00
00
00
00
50
10
15
20
4
20000
90
50
10
CD
0
-10000
1
-20000
BD
10000
Residual
AC
N ame
Temperature
BL/RM Ratio
Reaction Time
H y drogen
Percent
F actor
A
B
C
D
A
-10000
0
Residual
ABCD
10000
20000
40000
60000
Histogram
B
D
20000
6
10000
4
2
8
9
-1
00
00
50
00
-1
0
00
-5
0
0
2
0
0
0
00
00
00
00
50
10
15
20
4
6
8 10 12 14
Observation Order
16
18
Residual
Main Effects Plot for [Na] ug/g
Interaction Plot for [Na] ug/g
Data Means
Temperature
120000
-10000
0
7
80000
100000
Fitted Value
Versus Order
8
Residual
Frequency
C
3
4
5
6
Standardized Effect
18
Versus Fits
99
2.262
2
16
Residual Plots for [Na] ug/g
Normal Probability Plot
(response is [Na] ug/g, Alpha = 0.05)
1
6
8 10 12 14
Observation Order
Residual
Pareto Chart of the Standardized Effects
0
120000
-10000
0
0
80000
100000
Fitted Value
Versus Order
16
8
ABC
Data Means
BL/RM Ratio
4
Point Ty pe
Corner
Center
100000
8
12
0.50
1.75
3.00
0
250
500
100000
90000
Temperature
75000
80000
Temperature
300.0
332.5
365.0
Point Ty pe
Corner
Center
Corner
50000
70000
Mean
60000
Histogram
B
AB
Residual
Term
20000
Residual
CD
Percent
F actor
A
B
C
D
A
AC
Term
Versus Fits
99
100000
60000
BL/RM Ratio
300.0
332.5
Reaction Time
365.0
4
8
Hydrogen
75000
12
50000
100000
100000
Reaction Time
90000
75000
80000
50000
BL/RM
Ratio
4
8
12
Point Ty pe
Corner
Center
Corner
Reaction
Time
0.50
1.75
3.00
Point Ty pe
Corner
Center
Corner
70000
Hydrogen
60000
0.50
1.75
3.00
0
250
500
Cube Plot (data means) for [Na] ug/g
Centerpoint
Factorial Point
48000
12
59000
120000
52000
74000
55000
110000
110000
100000
BL/RM Ratio
69000
120000
44000
110000
3
Reaction Time
92000
68000
4
62000
95000
0.5
300
Temperature
365
0
H y drogen
500
D7: Pareto chart, residual plot, main effects plot, interaction plot, and cube plot for
sodium concentration in the solid phase before (Top) and after (Middle)
reduction of terms for calculation
104
Central Composite Design
Residual Plots for pHsolid
Normal Probability Plot
Contour Plots of pHsolid
Versus Fits
99
Residual
Percent
3
Reaction Time*Temperature
0.50
90
50
10
1
BL/RM Ratio*Temperature
12
0.25
10
0.00
8
-0.25
-0.50
-0.25
0.00
0.25
Residual
-0.50
0.50
2
6
8.5
9.0
9.5
Fitted Value
Histogram
10.0
1
4
300
Versus Order
315
330
345
360
300
315
330
345
360
Reaction Time*BL/RM Ratio
3
pHsolid
< 8.50
– 8.75
– 9.00
– 9.25
– 9.50
– 9.75
> 9.75
8.50
8.75
9.00
9.25
9.50
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
8
6
Residual
Frequency
0.50
4
2
0
0.25
2
0.00
-0.25
-0.4
-0.2
0.0
0.2
Residual
0.4
1
-0.50
0.6
2
4
6
8
10
12
Observation Order
14
16
4
Surface Plot of pHsolid vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of pHsolid vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
9.6
10.0
pH solid
9.4
9.5
pH solid
9.2
9.0
3
3
9.0
2
8.5
5.0
7.5
BL/RM Ratio
1
10.0
2
Reaction T ime
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of pHsolid vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
9.5
pH solid
9.0
12.5
10.0
8.5
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D8: Residual plot, Contour plots, and response surface plots for pH of solid phase
105
Residual Plots for pHaq
Normal Probability Plot
0.4
Residual
Percent
90
50
10
-0.25
0.00
Residual
0.25
0.2
6
8.0
8.5
9.0
Fitted Value
Histogram
2
1
-0.2
-0.1
0.0
0.1
Residual
0.2
345
360
300
315
330
345
360
2
1
0.3
2
4
6
8
10
12
Observation Order
14
16
4
Surface Plot of pHaq vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of pHaq vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
8.7
9.0
pH aq
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
0.0
-0.2
-0.3
330
Reaction Time*BL/RM Ratio
3
0.2
315
pHaq
< 7.6
– 8.0
– 8.4
– 8.8
– 9.2
> 9.2
7.6
8.0
8.4
8.8
1
4
300
Versus Order
Residual
Frequency
9.5
0.4
3
Reaction Time*Temperature
2
8
7.5
4
3
10
0.0
0.50
BL/RM Ratio*Temperature
12
-0.2
1
-0.50
0
Contour Plots of pHaq
Versus Fits
99
8.4
8.5
pH aq
8.0
8.1
3
3
7.8
2
7.5
5.0
7.5
BL/RM Ratio
1
10.0
2
Reaction T ime
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of pHaq vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
9.0
pH aq
8.5
12.5
8.0
10.0
7.5
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D9: Residual plot, Contour plots, and response surface plots for the pH of aqueous
phase
106
Residual Plots for maq
90
5
50
10
1
-5
0
Residual
5
2
8
-5
6
20
40
60
Fitted Value
80
100
1
4
300
Versus Order
315
330
345
360
300
315
330
345
360
maq
<
20 –
40 –
60 –
>
20
40
60
80
80
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
Reaction Time*BL/RM Ratio
3
10
5
3.6
Residual
Frequency
Reaction Time*Temperature
10
10
4.8
3
0
-10
-10
BL/RM Ratio*Temperature
12
Histogram
2.4
1.2
0.0
Contour Plots of maq
Versus Fits
10
Residual
Percent
Normal Probability Plot
99
2
0
-5
1
-10
-10
-5
0
Residual
5
2
4
6
8
10
12
Observation Order
14
16
4
Surface Plot of maq vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of maq vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
55
80
maq
50
60
maq
40
45
3
3
40
2
20
5.0
7.5
BL/RM Ratio
1
10.0
2
Reaction T ime
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of maq vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
80
60
maq
40
12.5
10.0
20
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D10: Residual plot, Contour plots, and response surface plots for the mass of
aqueous phase
107
Residual Plots for C%
90
1
50
10
1
-2
-1
0
Residual
1
1
Residual
Frequency
3
-1.5 -1.0 -0.5
0.0 0.5
Residual
1.0
1.5
6
20
25
30
Fitted Value
35
40
1
4
300
315
330
345
360
300
315
330
345
360
Reaction Time*BL/RM Ratio
3
20
24
28
32
36
36
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
2
-1
1
2
4
6
8
10
12
Observation Order
14
16
4
Surface Plot of C% vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of C% vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
35
35
C%
C%
<
–
–
–
–
>
0
-2
2.0
20
24
28
32
2
8
Versus Order
2
1
Reaction Time*Temperature
-1
Histogram
2
3
10
-2
2
BL/RM Ratio*Temperature
12
0
4
0
Contour Plots of C%
Versus Fits
2
Residual
Percent
Normal Probability Plot
99
30
C%
25
30
3
20
3
2
5.0
7.5
BL/RM Ratio
1
10.0
2
25
Reaction T ime
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of C% vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
35
C%
30
25
12.5
10.0
20
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D11: Residual plot, Contour plots, and response surface plots for the carbon content
of solid phase
108
Residual Plots for H2O%
Normal Probability Plot
Residual
Percent
50
10
1
-2
0
Residual
2
6
70
75
85
90
1
4
300
Versus Order
315
330
345
360
300
315
330
345
360
Reaction Time*BL/RM Ratio
3
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
2
2
Residual
Frequency
80
Fitted Value
H2O%
< 72
– 75
– 78
– 81
– 84
– 87
> 87
72
75
78
81
84
2
8
Histogram
1
1
2
0
-1
1
-2
0
Reaction Time*Temperature
10
4
3
3
0
-1
-2
-4
BL/RM Ratio*Temperature
12
2
90
1
Contour Plots of H2O%
Versus Fits
99
-2
-1
0
Residual
1
2
2
4
6
8
10
12
Observation Order
14
16
4
Surface Plot of H2O% vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of H2O% vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
85
77.5
H 2 O % 75.0
H2O%
72.5
2
70.0
5.0
7.5
BL/RM Ratio
1
10.0
80
75
3
3
2
70
Reaction T ime
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of H2O% vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
85
H 2 O % 80
12.5
75
10.0
70
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D12: Residual plot, Contour plots, and response surface plots for the water content
of aqueous phase
109
Residual Plots for Xlf
90
0.15
50
10
1
-0.4
-0.2
0.0
Residual
0.2
6
1
2
Fitted Value
Residual
Frequency
3
4
-0.2
-0.1
0.0
Residual
0.1
315
330
345
360
300
315
330
345
360
Reaction Time*BL/RM Ratio
3
Xlf
<
–
–
–
–
>
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
2
-0.15
1
2
4
6
8
10
12
Observation Order
14
16
4
Surface Plot of Xlf vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of Xlf vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
2.0
3
1.5
Xlf
2
Xlf
1.0
3
1
2
5.0
7.5
BL/RM Ratio
1
10.0
0.6
1.2
1.8
2.4
3.0
3.0
0.00
-0.30
0.2
1
4
300
0.15
-0.3
0.6
1.2
1.8
2.4
2
8
Versus Order
1
Reaction Time*Temperature
-0.15
0.30
2
3
10
0.00
Histogram
3
BL/RM Ratio*Temperature
12
-0.30
0.4
4
0
Contour Plots of Xlf
Versus Fits
0.30
Residual
Percent
Normal Probability Plot
99
3
2
0.5
Reaction T ime
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of Xlf vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
4
3
Xlf
2
12.5
1
10.0
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D13: Residual plot, Contour plots, and response surface plots for the magnetic
susceptibility
110
Residual Plots for [Na] ug/g
Normal Probability Plot
40000
Residual
90
Percent
Contour Plots of [Na] ug/g
Versus Fits
99
50
20000
10
0
8
10
1
-40000
0
Residual
20000
40000
40000
60000
Histogram
120000
6
4
330
345
360
300
315
330
345
360
Reaction Time*BL/RM Ratio
Hold Values
Temperature
332.5
BL/RM Ratio
8
Reaction Time
1.75
2
0
2
0
315
[Na] ug/g
<
60000
–
75000
–
90000
– 105000
– 120000
> 120000
60000
75000
90000
105000
1
3
20000
Reaction Time*Temperature
2
4
300
40000
Residual
Frequency
80000
100000
Fitted Value
Versus Order
8
3
6
-20000
-20000
BL/RM Ratio*Temperature
12
1
-20000
-20000 -10000
0
10000
20000
30000
40000
2
Residual
4
6
8
10 12
Observation Order
14
16
4
Surface Plot of [Na] ug/g vs Reaction Time, BL/RM Ratio
6
8
10
12
Surface Plot of [Na] ug/g vs Reaction Time, Temperature
Hold Values
Temperature 332.5
Hold Values
BL/RM Ratio 8
125000
100000
[Na] ug/g
90000
[Na] ug/g
80000
70000
2
5.0
7.5
BL/RM Ratio
1
10.0
100000
75000
3
3
50000
Reaction T ime
2
300
12.5
320
1
340
T emper atur e
Reaction T ime
360
Surface Plot of [Na] ug/g vs BL/RM Ratio, Temperature
Hold Values
Reaction Time 1.75
120000
[Na] ug/g 100000
80000
12.5
10.0
60000
7.5
300
320
340
T emper atur e
BL/RM Ratio
5.0
360
D14: Residual plot, Contour plots, and response surface plots for the sodium
concentration in the solid phase
111
TemperatBL/RM Ra Reaction
Optimal
High
365.0
12.0
3.0
D
Cur [365.0] [7.4747] [1.5354]
0.67665 Low 300.0
4.0
0.50
pHsolid
Targ: 7.0
y = 9.1694
d = 0.45766
pHaq
Targ: 7.0
y = 8.3022
d = 0.67444
C%
Maximum
y = 29.3126
d = 0.39083
H2O%
Maximum
y = 81.8131
d = 0.81813
maq
Minimum
y = 39.9720
d = 1.0000
Xlf
Maximum
y = 1.9741
d = 0.65802
[Na] ug/
Maximum
Note: The response of sodium
concentration [Na] in Red Mud could not be displayed due
y = 1.132E+05
to limitations on the number of line items the function can display (max. of 6). The
response of sodium concentration was set to maximum.
D15: Optimized reaction parameters predicted by Minitab®’s response optimizer
112
Contour Plot of pHsolid, pHaq, C%, H2O%, maq, Xlf, [Na] ug/g
pHsolid
8
9.5
12
11
pHaq
7.5
8.5
BL/RM Ratio
10
C%
25
35
9
H2O%
80
85
8
7
maq
35
45
6
Xlf
1.5
2
5
4
300
310
320
330
340
Temperature
350
360
[Na] ug/g
50000
120000
Hold Values
Reaction Time 0.5
Contour Plot of pHsolid, pHaq, C%, H2O%, maq, Xlf, [Na] ug/g
pHsolid
8
9.5
12
11
pHaq
7.5
8.5
BL/RM Ratio
10
C%
25
35
9
H2O%
80
85
8
7
maq
35
45
6
Xlf
1.5
2
5
4
300
310
320
330
340
Temperature
350
360
[Na] ug/g
50000
120000
Hold Values
Reaction Time 1.75
Contour Plot of pHsolid, pHaq, C%, H2O%, maq, Xlf, [Na] ug/g
pHsolid
8
9.5
12
11
pHaq
7.5
8.5
BL/RM Ratio
10
C%
25
35
9
H2O%
80
85
8
7
maq
35
45
6
Xlf
1.5
2
5
4
300
310
320
330
340
Temperature
350
360
[Na] ug/g
50000
120000
Hold Values
Reaction Time 3
D16: Overlaid contour plots of response factors highlighting the optimum results
while holding reaction time fixed at 0.5 hrs (Top), 1.75 hrs (Middle), and 3
hrs (Bottom)
113
Appendix E: SOP for High Pressure Reactors
114
Multi-Reactor System Standard Operating Procedure
THIS SOP IS NOT MEANT TO REPLACE HANDS-ON TRAINING FROM
QUALIFIED PERSONNEL!
This SOP describes the basic procedure for using the multi-reactor system, routine
maintenance, common problems, and their solutions. There are three Autoclave
Engineers (AE) High Pressure reactors: Gödel, Escher, Bach. They are nearly identical
visually. Any differences in procedure between them will be described below.
Important Comments
No operator is allowed to set up a reaction or take a reaction down without the
presence of a second person.
For overnight experiments operator must be reachable by cell phone/landline and
the number must be posted on the whiteboard of the Hydrogenation Lab and the
door into the vestibule.
No dynamic hydrogen uptake experiments, i.e., runs with an open mass flow
controlled connection between H2 tank and reactor unless OPERATOR AND A
SECOND PERSON (!) are in the lab/building. No overnight/weekend experiments
of this type are allowed.
General Comments
Treat the pressure reactors with respect at all times. If you are at all unsure of something,
ask for help. NEVER WORK ON A HOT and/or PRESSURIZED SYSTEM!
The volume of the large reactor vessels is 300 mL. Maximum reaction volume is 150 mL.
Available interchangeable conversion kits for the reactors allow for a reactor vessel
volume of 100 mL. Maximum reaction volume in those kits is 50 mL.
The reactors have a burst disc rated to approximately 4781-5000 psi at room temperature.
Maximum working pressure should be no more than 90% of the lower pressure rating;
therefore do not exceed 4200 psi. The usual operating pressure for the high-pressure
reactors is 700 or 1200 psi at room temperature. This translates to slightly more than
1100 or 1800 psi at 200 °C, respectively. Note that these pressure estimates do not
account for the additional pressures generated by any reaction substrates present or
products formed during a given reaction.
Hydrogenation experiments are usually performed under STATIC pressure; the massflow units on Bach and Escher are able to inject hydrogen into the reactor at up to 1500
psi and the hydrogen regulators on the tanks are also rated for a maximum of 1500 psi on
the outlet. However, for safety the outlet pressure of the regulators is set for ~90% of
their maximum rating which is ~1300 psi. Therefore, it is not possible to run a high
pressure experiment and add in hydrogen at temperature if the system pressure exceeds
1300 psi. The reaction pressure must be below the outlet pressure of the regulators in
order to actively add in hydrogen to the reaction, ideally the system pressure at
115
temperature should not exceed 1100 psi. Get permission from Marcel Schlaf or acting
supervisor before starting the experiment and inform follow group members that a
DYNAMIC pressure reaction will be taking place.
A single hydrogen tank is connected to each high-pressure reactor with an inline 2-way
valve between each tank and associated reactor. Escher and Bach are attached to normal
2300 psi K size hydrogen tank available from Linde Gas that weigh ~120 lbs when full.
Gödel is attached to a special 6000 psi K size high pressure hydrogen tank from Praxair
that weighs ~310 lbs when full. This tank must NEVER be mixed up with the Linde
tanks as only the stainless steel regulator from Praxair is capable of handling the delivery
pressure from the tank. When empty the tank is to be returned to Chem-Stores where it is
stored until Praxair replaces it. For experiments not requiring the use of the high pressure
tank, the line from Escher’s regulator can be switched over to Gödel’s check valve. The
high pressure regulator is not compatible with normal H2 tanks; also, the line from the
high pressure regulator should only be attached to the check valve clearly marked as
being for Gödel.
When changing the tank the user must be actively aware of the crush hazards associated
with this tank; when moving the tank always have a second person available to assist if
and when necessary.
The tanks for Escher and Bach are generally regulated to 1300 psi and the tank for Gödel
is regulated at 4000 psi, as pressure in the reactor is controlled via the computer controls.
Once the regulators are attached, open the valve to the tank and check for leaks using
Snoop. Turn the 2-way valve to the “open” position to pressurize the line. The 2-way
valve should be in the “close” position, the main tank valve closed, and pressure bled
from the regulator (if possible) at all other times.
Familiarize yourself with the Multi-Reactor System documentation and the engineering
drawings of the reactors. This information is contained in a binder in the hydrogenation
lab (SSC 5106J) and available as a pdf document on the Schlaf Group Server or on a
physical CD/DVD.
Spare parts (ferrules, nuts, O-rings, bearings, etc.) are stored in a multi-drawer plastic box
on the workbench or in packaging in the cabinet and drawers under the sink in SSC
5106J. Order more if/as needed from Autoclave Engineers.
116
The Multi-Reactor System
Initializing Sentinels and Computer Control Software
Turn on the INSTRUMENT power switch on each sentinel, located on the front panel.
Press the START button on the sentinel touch screens.
Open the DSLaunch4 software located in the taskbar.
Open the DataServer software located in the taskbar.*
Right click on the WatchTower icon on the Desktop and click “Run as Administrator.”**
*Note: This program should not be closed for any reason while any of the Sentinels are in
use.
**Note: If the WatchTower software is opened without the “Run as Admin” permission,
it will be impossible to record any data using the software without re-initializing the
system.
Setup
Combine the substrate solution and the catalyst in the reactor vessel. Ensure hastelloy Oring and mating surfaces are clean and undamaged.
Be careful handling the O-ring, as they are ~ $500 apiece. Any damage to the O-ring
effectively makes it a very expensive paperweight.
Place the O-ring into the groove on the reactor vessel; the O-rings are NOT orientation
specific. Damage to the O-ring can/will occur if not seated properly.
Carefully raise the reactor vessel using the lab jack and align it with the bolts. There are
only two possible orientations of the vessel that ensure the heater jacket can bolt onto the
vessel; the best orientation is shown below.
Tighten the bolts by hand using the supplied tool from Autoclave Engineers. Then using
the torque wrench, tighten opposing bolts to 20 ft. lbs., then 30 ft. lbs., and finally to the
spec’d 42 ft. lbs for the 300 mL vessels. For the 100 mL vessels, initially tighten the bolts
to 20 ft. lbs. and then to 27 ft. lbs.
117
Bolt on the heating mantle to the reactor body and install the insulting jackets over the
reactor head and upper body. If the desired experiment is to be conducted at a
temperature >250 °C the insulting jacket for the heating mantle must also be attached.
Type in the desired file name for the data recorder; any alphanumeric combination is
allowed however, no spaces or special symbols are allowed. In addition, the backspace
key cannot be used to delete a mistyped letter or name. The mistake must be highlighted
and typed over to correct it. Select the desired time interval for recording data points
(default is every 10 seconds) and click START STORING. A green circle will begin to
blink next to the file name if data is being recorded.
ENABLE the pressure module and pressurize to 500 psi with H2 gas, and let equilibrate
for 2 minutes. The temperature will increase a few degrees with the rapid increase in
pressure. The pressure will drop slightly as the temperature returns to ambient. A more
rapid decrease in pressure indicates a leak in the system. Set the pressure set point to
ZERO or DISABLE the module before venting the reactor. Failure to do so will result in
the system trying to maintain the desired set point by continually feeding in hydrogen
gas.
LEAKS: Use Snoop to find them. Close the main valve on the hydrogen tank. Vent the
reactor. Snoop will not be effective in finding leaks caused by a misaligned O-ring, this
may require unbolting the reactor vessel and checking the O-ring position or ensuring all
bolts are torqued to spec. Pressurize and check for leaks again. NEVER WORK ON A
PRESSURIZED SYSTEM!
Repeat the evacuation/pressurization cycle twice more, then pressurize the reactor to the
desired initial pressure.
NOTE: To run a DYNAMIC pressure reaction the pressure set point will have to be
changed once the reaction mixture has been heated to the process temperature set point.
Once the reaction is at temperature and the pressure is stable, enter the current system
pressure reading as the set point value and zero the mass flow counter. The system will
now maintain the current pressure and track how much hydrogen the reaction has
consumed provided the pressure does not increase beyond the set point due to the
formation of gaseous products.
No dynamic hydrogen uptake experiments, i.e., runs with an open mass flow
controlled connection between H2 tank and reactor unless OPERATOR AND A
SECOND PERSON (!) are in the lab/building. No overnight/weekend experiments
of this type are allowed.
Check that the MIXER and HEATER switches are on and the controllers have been
ENABLED.
118
Set the mixer speed (usually 750 rpm), the reaction temperature, and a ramp profile if
needed. To prevent overshooting the desired reaction temperature is often necessary to
set the reaction temperature initially 50 °C below the desired temperature set point and
then increase the setting as the reactor gets closer to operating temperature. The reaction
temperature may need to be set a few degrees higher to achieve the desired temperature.
Once the temperature has been programmed TURN ON THE COOLING WATER!!!
(See note below).
NOTE: Cooling water MUST be used when the process temperature is set to 149 °C or
higher or the stirring rate is 1500 rpm or higher. Failure to turn on the cooling water
will result in damage and possible demagnetization of the Magnedrive® agitators making
them useless and resulting in a very costly repair/replacement of the drive(s) and several
weeks/months of reactor downtime.
See the Series 0.75 MagneDrive® II Operation and Maintenance Manual on page 54 of
the AE Databook for more information.
Wait until the temperature begins to rise. By using the remote login software and the
cameras in the room, there is no need to wait in the room while the reactor reaches
temperature. However, the reactors should be monitored constantly during the heating up
phase for any potential alarm conditions or leaks that may develop. Record the pressure
of the reactor once at the desired process temperature.
BEFORE LEAVING THE HYDROGENATION LAB, ensure the main valve is closed
on the hydrogen tank, the check valve is in the “closed” position, the fumehood sash is
lowered and sliding panels spaced evenly, and the cooling water is running.
For a 24 hour experiment with sampling, samples are typically taken at 1, 2, 4, and 8
hours from reaching the set operating temperature via the sample tube (not currently
installed on reactors). Record the pressure, turn the stirrer off, and flush the sample line
with about 1.0 mL of the reaction mixture into a waste vial to ensure cross-contamination
from an earlier sample does not occur. Collect 1.0 mL in a vial for analysis. Turn the
stirrer back on. Record the pressure again.
Sampling settings in WatchTower software for ~1.0 mL of reaction mixture; this will
result in ~1.0 mL sample to be expelled every 9s if not turned off after taking a sample.
Interval
Duration
1
4
NOTE: DO NOT program sampler settings using the sentinel control screen. See
Sampling Valve Operational Instructions for more details.
Ensure to close the sliding panels of the fume hood door, ensuring they are spaced
evenly.
119
At the end of the reaction, record the pressure, turn the heater off, and remove the heating
mantle if the temperature is below 250 °C, otherwise leave it attached until it has cooled
to 250 °C or less. Take a gas headspace sample from the vent line and run it through the
Micro GC before venting the reactor completely. Vent the reactor, open it, and take a
final sample for GC analysis. Transfer the remainder of the reaction solution to large
vials for storage. Vials can eventually be discarded, for example, upon degree
completion.
Clean the reactor by rinsing it several times with methanol and wiping the vessel, stirrer
shaft, reactor head, etc. with a Kimwipe. Rinse the sample tube and sample line (if
installed) by partially filling the reactor vessel with methanol, pressurizing to 300 psi,
and expelling the solution through the sample line. Continue sampling until no liquid
flows out of the sampling valve. Vent through the sample line to blow out the methanol.
Remove the reactor vessel and allow the reactor assembly to air dry overnight. Disable all
controllable functions and turn all switches off except for the INSTRUMENT switch.
MAKE SURE THE HYDROGEN TANKS ARE CLOSED AND THE CHECK
VALVES ARE IN THE “CLOSED” POSITION.
120
Sampling Valve Operational Instructions
Due to a programming error, the units for the INTERVAL between samples and
DURATION the valve is open are displayed with incorrect units. While the INTERVAL
and DURATION fields show units of “minutes” the values entered into the INTERVAL
field are interpreted as 1/10 minutes and in the DURATION field the values are
interpreted as 1/100 minutes.
A duration setting of 4 will allow ~1 mL of reaction mixture to be removed from inside
the reactor.
To operate the valve, follow the instructions below:
Open the manual needle valve on the reactor to allow sample to flow freely
Enter 1 into the interval field; press the enter key.
Enter 4 into the duration field; press the enter key.
Ensure there is a flask under the end of the sampling tube.
Switch the mode of the valve from manual to automatic; the valve will automatically
open, close and dispense the sample.
Switch the mode of the valve back to manual or else it will continue to dispense sample
at the programmed interval.
DO NOT press the manual sample button. While this would technically allow for
sampling, the switch does not respond fast enough to allow for the controlled dispensing
of a small amount of reaction mixture. Most if not all of the reaction mixture will be shot
out of the reactor at temperature and pressure. This will create a very dangerous situation,
as hot fluid and gases will spray in all directions once the sample vial is full.
Auto tune Instructions
The autotune function can be found in the WatchTower software under the tab
SystemTools > SentenialControlDetails.
To Autotune the system:
It is best to start the tuning process with the system at ambient temperature; the system
can be tuned at setpoint if necessary. The system should be as close to actual operating
conditions as possible. If using the magnedrive in actual process conditions it should be
on while autotuning. If there will be liquid in the reactor during a run there should be the
same amount of liquid for autotuning.
Set the ramp rate to zero, enter the desired setpoint, and press the Autotune button.
The system will bring the process variable (temperature or pressure) to roughly 10%
above setpoint three times. At the end of the third cycle, the Autotune will shut off and
new Gain, Reset, and Rate values will be loaded. The system is now tuned, for the best
control use a ramp rate value to prevent overshoot.
121
Summary of Settings and Parameters
Max Process
Pressure
Max H2 Feed
Pressure
Usual H2 Feed
Pressure
Bach
Escher
Gödel
4200
4200
4200
1500
1500
4500
1300
1300
4000
300 mL Vessel
500 °C
42 ft. lbs.
Max temp
Torque required
Max Reaction
Volume
150 mL
100 mL Vessel
343 °C
27 ft. lbs.
Max temp
Torque required
Max Reaction
Volume
Normal Mixer
Speed
Max Mixer
Speed
Sample Valve
Interval
Sample Valve
Duration
50 mL
750 rpm
3300 rpm
(sheaved for 2970 rpm)
1
(interpreted as 1/10 minutes)
4
(interpreted as 4/100 minutes)
122
Routine Maintenance
Re-grease the bolt threads on the reactor vessel and the retaining bolts for the heating
jacket every 5 experiments or as needed using the Nickel Anti-Seize. A little goes a long
away! More anti-seize can be ordered from Motion Canada.
Polish the reactor vessel, sample tube, stirrer shaft, thermocouple well, vortex preventer,
and impeller after every experiment. The sample tube, thermocouple well, vortex
preventer and stirrer shaft are polished by hand using fine sandpaper or preferably
Scotch-Brite abrasive pads (located in the toolbox in the hydrogenation lab; more can be
obtained from the machine shop). The vessel is polished by clamping it in the vice in the
lab and using the drill and pads. If a reaction is running in the lab the vessel must be
cleaned using the lathe (machine shop) and using an abrasive pad or. The impeller is
sandblasted (machine shop). Do not sandblast the threads of the screw used to attach the
impeller to the reactor as will result over time (use masking tape to cover the threads if
desired). Only sandblast the part of the impeller that goes into solution.
A hastelloy O-ring is used to seal the reactor vessel for all reactions. There is no correct
orientation (i.e. “up”) for the O-ring – either way will work. This O-ring should not need
replacing for many years. They are very expensive (~ $500/each) so do not drop them!
When not in use, they should be kept in the marked O-ring Storage box identified by the
corresponding Reactor Name. If the O-ring is replaced there is a break-in procedure
marked out in the Autoclave Engineers Bolted Enclosure reference material that should
be followed; record in the log book when the O-ring has been changed and why.
The bearings should be inspected at 500 hours, 1000 hours and every 1000 hours
thereafter. Replace the bearings as necessary and reset the hours of operation clock on the
stirring module. The High Pressure Reactors are equipped with Purebon 658 RCH/HAST
C-276 spring bearings, DO NOT confuse them with the Graphite or Teflon bearings of
the mini reactor systems. The Multi-Reactor System documentation thoroughly describes
the procedure for replacing the bearings. Use the bearing tool to push the bearings out of
the reactor body; record in the log book when the bearings have been replaced and why.
See the Series 0.75 MagneDrive® II Operation and Maintenance Manual on page 54 of
the AE Databook for more information.
Control experiments using no catalyst should be run periodically to determine the
baseline activity of the reactor (typically < 2% hydrogenation).
123
Problems & Their Solutions
LEAKS: Use Snoop to find any apparent leaks in joints. Close the main valve on the hydrogen
tank. Vent the reactor. Tighten the fitting(s). Pressurize and check for leaks again. NEVER
WORK ON A PRESSURIZED SYSTEM!
CLOGS: Occasionally a piece of solid may be stuck either in the sample tube, the curved tubing
connecting the reactor body to the sample valve, or in the sample line. First, remove the sample
tube and sample line & attempt to flush methanol through manually. If that does not work,
sonicate the tube and line in a beaker of methanol for at least 30 minutes. Force air through the
tube and line. If solvent and air flow freely through the sample tube and line, then the clog is in
the tubing between the reactor body and valve. Disconnect the tubing from the reactor body and
the valve from the support arm. Remove the tubing from the valve. Force methanol through
manually or sonicate repeatedly. If this does not clear the blockage, then use a thin piece of wire
and try to break up the solid, as the tubing is fairly large then repeat the washing procedure to
ensure the tubing is clean. If this does not resolve the issue, the valve body may have a blockage;
consult with others before dissembling the valve.
REPLACING TUBING: The tubing is custom made for the reactors out of Hastelloy C-276 and
should not need replacing. The tubing is held in place either by a combination of left-handed
collar and right-handed nut that form metal-on-metal bonds or a nut and ferrule combination that
also form two metal-on-metal bonds to seal the joint. Once the ferrule has been compressed onto
the tubing, it will not come off. The tubing can be unscrewed from and screwed into the reactor
repeatedly. If a piece of tubing needs to be replaced, consult with Marcel and the CPES Machine
Shop to see if the tubing can be made on site; otherwise tubing will have to be ordered from AE.
Spare ferrules are included in the maintenance kits. Cut and bend new piece of tubing and slide
the screw and a new ferrule onto the tubing. Screw the tubing into the valve or reactor body. For
a valve, it is easier to clamp it in the vice and then screw the tubing into it. Use a wrench to
tighten the screw. BE SURE TO PRESSURE TEST THE REACTOR AFTER REPLACING
ANY TUBING!
Spare stainless steel gas line tubing rated for 8000 psi is stored in the Hydrogenation Lab (1/8 in.
outer diameter × 0.014 in. wall thickness). The machine shop has a limited supply of stainless
steel ferrules; do not be surprised if ordering some will be required. DO NOT USE BRASS
FERRULES. They are not rated for the sustained system pressures being used. Double-check
that you have the right size by comparing the old lines/ferrules to the new ones.
VALVES: The handles on the valves wear out after a while. The valve needs to be replaced
when it is difficult to completely close. Autoclave Engineers sells a replacement valve assembly,
rather than valve parts individually. Use common sense and good judgment to determine if
repairing the valve is possible as it will be cheaper than replacing the entire unit.
BURST DISC: Have the machine shop replace the burst disc if it blows. Bring the valve with the
burst disc attachment and a new burst disc from the plastic parts box to the machine shop. Check
the reactor manuals for the required torque—the entry is highlighted. Make sure the burst disc is
installed in the correct orientation (convex towards pressurized side). Replace the old tag on the
reactor with the new one.
124
Spare Parts in Maintenance Kits
Magnedrive® Agitator (Drawing: 30B-0382; Kit Part #: SPKMAG07502HC)
– 3 kits (Cost as of Jan. 2014: $415 US each)
Part
Retaining ring
O-ring (Teflon)
O-ring (Viton)
Gasket
Retaining ring
Low Pressure Plug
Gland
Purebon 658 RCH/HAST C-276 Bearing
Burst disc
Part Number
P-0231
P-0926
P-10015
P-0745HC
P-1956
SP20-HC
SMN20
105B-7324
62204
Quantity
4
1
2
1
2
1
1
2
2
Pressure Vessel (Drawing: 40C-1375; Kit Part #: SPK401C-1375)
– 3 kits (Cost as of Jan. 2014: $2040 US each)
Part
Part Number
Seal (HAST C-276 O-ring)
1040-7717
Sleeve
SSL20-HC
Gland
1070-6706
Adapter, M437FB TO SF250CX
15M74E6-HC
3/16F Rupture Disk 4781-5000 PSI @72F
61285
Low Pressure Plug
SP20-HC
Thermocouple (Type K)
MTCSK04012
Thermocouple (Type K)
101D-0147
Quantity
1
5
5
5
1
2
1
2
Valves (Drawing: 40C-1363; Kit Part #: SPK401C-1363)
– 1 kit (Cost as of Jan. 2014: $5735 US each)
Part
Part Number Quantity
Valve Assembly
20SM4082-HCGY
3
Air Operated Sample Valve Assembly 20SM4082O1SHCGY 1
O-ring Check Valve
CXO4400-HC
2
Other parts: Look at the explosion drawing to locate the part. Find the name and part number in
the table on the explosion drawing.
Snoop can be ordered from Swagelok (part # MS-SNOOP-8OZ)
125
Appendix F: Gas Sensor Alarm Response Procedures and Hydrogenation Lab
Information distributed to EHS, Physical Resources and Campus Police/Fire
Dispatch Centre
Names and sensitive information have been redacted
126
Gas Sensor Alarm and Hydrogenation Lab
Background Information
(Updated September 2014)
SCIE room5106J is a small lab dedicated to high temperature and high pressure reactions
using hydrogen. This room has been specifically designed for this purpose with a set blow-out
panels, explosion proof fixtures and high flow fume hoods. Hydrogen flow to the reactors can be
shut off at the cylinder, at the check valve manifold and at the reactors through computer
software. The three High Pressure Reactors are controlled via individual control towers and a
networked computer with a specially designed software package. The room is monitored via a
networked video camera and the remotely accessible computer.
Air flow into the room is set at 1300 CFM and the exhaust rate is equal to that volume of
air or more. With the available air flow numbers and the approximate volume of the room
calculated to be ~ 1600 cu. ft., the volume of air equal to the volume of the room is exhausted in
less than 2 minutes continuously under normal operation. Therefore as calculated from the
approved air balance report, building air supply documentation received and approximate room
dimensions it can be safely estimated that air exchanges occur every 2 – 5 minutes (12-30
exchanges per hour)
Gas sensors are located in the room and will alarm under the following conditions:
Gas Sensor
Alarm A
Alarm B
Alarm C
Carbon Dioxide1
1400 ppm
N/A
N/A
Carbon Monoxide
25 ppm
50 ppm
225 ppm
25% LEL
50% LEL
90% LEL
10 ppm
15 ppm
20 ppm
Methane
25% LEL
50% LEL
90% LEL
Oxygen
19.5% vol.
22% vol.
22.5% vol.
Hydrogen
2
Hydrogen Sulphide
3
4.
5.
6.
Default set points are 0.4% vol. and 0.8% vol.
Lower Explosion Limit (LEL) for Hydrogen is 4%
Lower Explosion Limit (LEL) for Methane is 5%
Campus Police will see a Gas Sensor Alarm under the following conditions:
 Gas Level reaches or surpasses the above set points.
 Power Failure (once emergency power is on or full power is restored the alarm will
reset).
Should any gas exceed its alarm limit (with the exception of Oxygen which is a lower limit
alarm), a visual and audible alarm horn will be enabled.
 Outside the lab entrances visual red light strobes will flash.
127

Inside the lab, the triggered sensor will sound an audible alarm and visually
display gas level.
Note that gas alarms will reset once gas concentrations return to levels below 95% of the sensor
set points
Campus Police will also see an alarm in the case of a Fume Hood Fan Failure or Fire Alarm
 Inside the lab, a red light strobe will flash and an alarm will sound.
Campus Police will see an alarm from the gas sensors but will not be able to determine
which gas alarm limit has been exceeded. To determine which alarm limit has been exceeded the
listed contacts will login to the Building Automation System (BAS) at:
IP address: 000.000.00.000
User ID: 00000
Password: 000 000
Note the space must be included in the password
Note the IP address is only valid on campus therefore remote login to the networked computer in
SCIE 5106J or any computer on campus will be required to view the BAS controls.
The Room Contacts will assess the situation in the lab and indicate required action and
actions taken to the Campus Dispatch.
Actions taken by the Room Contacts will include remote shutdown of reactors, remote
observation of lab via network camera to determine failures, remote confirmation of ventilation
system. Based on the results of this assessment, further action may be taken including but not
limited to the following:




Shut off of cylinder valves, shutoff of gas manifold valves if deemed safe to do so
Increase of ventilation through Building Controls (viability still being assessed)
Evacuation of the floor and/or building
Communication with Campus Dispatch to contact of City of Guelph emergency
responders; Room contacts will identify their location to campus dispatch in order to be
available to provide further information for emergency responders
128
Gas Sensor Alarm Response Procedure
(Valid from May 2014 until otherwise updated)
During Normal Operating hours (Monday to Friday: 9am – 5pm)
1. Call the lab at ext. 58708 (SCIE 5106J).
2. If there is no answer, call Marcel Schlaf at ext. 53002
3. If there is no answer, call Chris Gissane at 000-000-0000
4. If there is no answer, call Group Office at ext. 53753
5. Dispatch Operator can log in to the Network Camera (if they choose to do so) at the
following IP to view if there is anyone inside the lab that needs emergency
assistance. Simply type the IP address into an internet browser’s URL space and a
log in window will open, enter the user ID and password and the camera and
controls will appear.
IP address: 000.000.00.000
User ID: 00000
Password: 00000
6. ... From that point on it depends on the situation in the lab.
Note: If the gas sensors are sending out an alarm, emergency personnel SHOULD NOT enter
the lab until the atmosphere has been deemed non-explosive.
Note: If someone calls from the lab requiring emergency assistance, the lab can be
presumed “safe to enter” unless otherwise stated. Responders should not hesitate to
contact Marcel Schlaf, Chris Gissane, Tom Minard, or Ryan Sullivan if any doubt is present.
129
Overnight (Monday to Friday: 5pm – 9am) and On Weekends
(Saturday & Sunday: all Hours)
1. Call Marcel Schlaf at Home: (000) 000-0000 or Cell: (000) 000-0000
2. Call Chris Gissane at 000-000-0000
3. If there is no answer, call either of the following lab personnel
a. 00000000000000000000000
b. 00000000000000000000000
4. Dispatch Operator can log in to the Network Camera (if they choose to do so) at the
following IP to view if there is anyone inside the lab that needs emergency
assistance. Simply type the IP address into an internet browser’s URL space and a
log in window will open, enter the user ID and password and the camera and
controls will appear.
IP address: 000.000.00.000
User ID: 00000
Password: 00000
5. ... From that point on it depends on the situation in the lab.
Note: If the gas sensors are sending out an alarm, emergency personnel SHOULD NOT enter
the lab until the atmosphere has been deemed non-explosive.
Note: If someone calls from the lab requiring emergency assistance, the lab can be
presumed “safe to enter” unless otherwise stated. Responders should not hesitate to
contact Marcel Schlaf, Chris Gissane, Tom Minard, or Ryan Sullivan if any doubt is present.
130