presentation

Advances in Hard-Modelling of
Chemical Processes
Marcel Maeder
Department of Chemistry
University of Newcastle
Australia
What is Chemometrics?
The art of extracting
information from
measurements
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
What are the options?
Soft
Firm
(Statistical)
Hard
EFA, ALS etc
Classification
/PLS type
Model fitting
Based on
restrictions
Based on
calibration set
Based on
chemical model
Resolution of
chromatogram
Octane rating of
petrol
Reaction
A→B→C
3.500
3.5
3.000
2.500
3
2.000
2.5
1.500
2
1.000
1.5
0.500
0.000
-0.500 0
1
20
40
60
80
100
120
0.5
0
400
420
440
460
480
500
520
540
560
580
600
k1 = 0.21 ±0.02
0
50
100
400
500
600
700
0
Introduction
Thermostatting
Ionic Strength
pH
5
10
15
k 2 = 0.057 ±0.005
20
25
400
450
500
550
600
Application CO2
What are the options?
Soft
Firm
(Statistical)
Hard
EFA, ALS etc
PCR/PLS type
Model fitting
Literature (Chemometrics)
intermediate
large
very small
Literature (Chemistry)
very small
Introduction
Thermostatting
small
Ionic Strength
very large
pH
Application CO2
Why hard-modelling,
why not soft-modelling?
M F Delaney, Analytical Chemistry, 1984, 56, 261R - 277R
“ The methods can be classified into two groups - those in
which assumptions about the system are made (e.g., number
or identity of components, line shapes) and those in which
no assumptions are made, other than (perhaps) linear
system behavior. In the former case you get back what you
assumed, in the latter you get what you get. “
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Advantages of Hard-Modelling
Analysis generally
much more robust
than model-free
analyses
3.5
3
2.5
2
1.5
1
0.5
0
Numerical values for
essential constants,
they can be
• tabled
• compared with
other values
• interpreted
• analysed
• etc.
Introduction
Thermostatting
400
0
420
5
440
10
460
15
480
20
500
25
400
520
540
450
560
500
580
550
600
600
k1 = 0.21 ±0.02
k 2 = 0.057 ±0.005
Ionic Strength
pH
Application CO2
Hard-Modelling
1.2
k1
A
k2
B
C
1.2
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
400
The model:
450
500
-0.2
[A] = -k1[A]
550
600
0
1000
2000
3000
4000
5000
-0.2
The parameters to be fitted:
[B] = k1[A] - k 2 [B]
[C] =
k 2 [B]
integration
[A] = [A]0 e-k1t
[B] = [A]0
Introduction
k1
(e-k1t -e-k 2t )
k 2 -k1
Thermostatting
• k1, k2
• molar absorptivities of all
species at all wavelengths
(e.g. 3 11=33)
• total 35 parameters
Difficult ?
Ionic Strength
pH
Application CO2
Hard-Modelling
k1
A
B
1.2
1
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
400
Introduction
C
1.2
1
-0.2
k2
450
500
550
600
0
-0.2
Thermostatting
1000
2000
3000
4000
5000
Fitted, using solver in
excel,
• only 2 parameters, k1, k2
• molar absorptivities
‘eliminated’
Ionic Strength
pH
Application CO2
Advances in Hard-Modelling of
Chemical Processes
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Industry
-
Research Laboratory
50% reaction
1% reaction
50% support
99% support
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
What is left to be done in
Hard-Modelling ?
Temperature Control
→
thermostatting
Ionic Strength Control →
inert salts
pH Control
buffers
Introduction
Thermostatting
→
Ionic Strength
pH
Application CO2
Temperature Control
Why do we thermostat ?
useless answer :
• to keep the temperature constant
better answer :
• to keep the rate constants constant
real answer :
• to keep the computations simple
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Computations
How difficult is it to accommodate
temperature changes during a process?
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Example:
A
k1
k2
B
k3
C
Differential equations:
[A]
=-k1[A] + k 2[B]
[B]
= k1[A] - k 2[B]- k 3 [B]
[C]
= k 3 [B]
Matlab code as part of ODE solver:
c_dot(1,1)=-k(1)*c(1)+k(2)*c(2);
c_dot(2,1)= k(1)*c(1)-k(2)*c(2)-k(3)*c(2);
c_dot(3,1)= k(3)*c(2);
Introduction
Thermostatting
Ionic Strength
pH
% A_dot
% B_dot
% C_dot
Application CO2
2 very short programs do the computations
AeqBtoC.m
c0=[1;0;0];
% initial conc of A, Cat, B and C
k=[.2;.1;.01];
% rate constants k1 and k2
times=[0:1:300]';
[times,C] = ode45('ode_AeqBtoC',times,c0,[],k);
figure(1); plot(times,C)
% call ode-solver
% plotting C vs t
xlabel('time');ylabel('conc.');
ode_AeqBtoC.m
function c_dot=ode_AeqBtoC(t,c,flag,k)
% A <-> B -> C
Introduction
c_dot(1,1)=-k(1)*c(1)+k(2)*c(2);
% A_dot
c_dot(2,1)= k(1)*c(1)-k(2)*c(2)-k(3)*c(2);
% B_dot
c_dot(3,1)= k(3)*c(2);
% C_dot
Thermostatting
Ionic Strength
pH
Application CO2
1
A
0.9
0.8
k1
k2
B
k3
C
0.7
conc.
0.6
0.5
0.4
0.3
0.2
0.1
0
Introduction
0
50
Thermostatting
100
150
time
Ionic Strength
200
250
pH
300
Application CO2
How to accommodate
temperature changes?
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Arrhenius equation
Arrhenius equation describes rate constant k as a
function of the temperature (Eyring equation could
be used as well)
- Ea
k = Ae RT
A = pre-exponential factor
Ea = activation energy
R = gas constant ( = 8.314 J K-1 mol-1 )
T = temperature in K
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Example:
A
k1
k2
k3
B
[A]
k1[A ]
k2[B ]
[B ]
k1[A ]
k2[B ]
[C ]
k3 [B ]
k3[B ]
[A]
k1(T) [A ]
k2 (T) [B ]
[B ]
k1(T) [A ]
k2 (T) [B ]
[C ]
k3 (T) [B ]
Introduction
Thermostatting
Ionic Strength
C
k3 (T) [B ]
pH
Application CO2
•
•
•
The parameters are the Arrhenius parameters, A, Ea, not the rate
constants
The rate constants are computed using the Arrhenius parameters
and the temperature
The temperature has to be interpolated from the measured
temperatures
ode_AeqBtoC_T.m
function c_dot=ode_AeqBtoC_T(t,c,flag,k,temp,A,Ea,times)
% A <-> B -> C
R=8.314;
% gas constant J K-1 mol-1
T=lolipop(times,temp,t,2,5);
% interpolation to comp T at particular time t
k=A.*exp(-Ea./(R*(T+273)));
% rate constants at T
c_dot(1,1)=-k(1)*c(1)+k(2)*c(2);
% A_dot
c_dot(2,1)= k(1)*c(1)-k(2)*c(2)-k(3)*c(2);
% B_dot
c_dot(3,1)= k(3)*c(2);
% C_dot
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
A side issue, lolipop.m
lolipop.m
function y1=lolipop(x,y,x1,nd,npoints)
%
%
%
%
General Polynomial Inter/Extrapolation, degree nd, using npoints
x,y,x1,y1 vectors - x,y do not have to be the same length as x1,y1
nd: degree of polynomials
npoints: number of total points to define each polynomial
for i=1:length(x1)
N=sortrows([x y abs(x-x1(i))],3); % sort x,y by abs(x-x1(i))
x_npoints=N(1:npoints,1);
y_npoints=N(1:npoints,2);
% npoints nearest nodes
a=polyfit(x_npoints-mean(x_npoints),y_npoints,nd); % polyn. par.
y1(i)=polyval(a,x1(i)-mean(x_npoints));
% interpolate
end
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
1
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.6
conc.
conc.
1
0.5
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0
50
100
150
time
200
250
300
0
0
at 20 C
50
100
150
time
200
250
300
at 20-80 C
Compression of process, similar to temperature program in GC
or non-isocratic mobile phase in HPLC
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Cyanoacetic acid + ethanol in equilibrium with the ester
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Activity coefficients
Why do we add inert salts ?
useless answer :
• to keep the ionic strength constant
better answer :
• to keep the rate constants constant
real answer :
• to keep the computations simple
Introduction
Thermostatting
Ionic Strenght
pH
Application CO2
Example:
[A]
A B
[B ]
[C ]
[A]
k1[A ][B ]
k1[A ][B ]
[B ]
[C ]
k1
k2
C
k 2[C ]
k2[C ]
-k1 { A }{ B }
k 2 {C }
k1 { A }{ B } - k2 {C }
{A} = activity of species A
Introduction
Thermostatting
Ionic Strenght
pH
Application CO2
Activity coefficients
{ A}
A [ A]
For Ionic compounds, activity coefficients can be approximated
in reasonably dilute solutions as (Debye-Hückel):
log
A z2
1
With A parameter depending on dielectric constant of solvent, in water A~0.51
zi charge of species
1
[Ci ]zi2
Ionic strength of solution, computed as:
2
Introduction
Thermostatting
Ionic Strenght
i
pH
Application CO2
function c_dot=ode_AplusBeqC_I(t,c,flag,k,c_I,charges,mode,A)
% A + B <--> C
mu
log_gamma
gamma
act
=
=
=
=
including activities
sum(1/2*([c;c_I].*(charges.^2)));
(-A*(charges.^2)*(mu^0.5))/(1+(mu^0.5));
10.^log_gamma;
c.*gamma(1:length(c));
c_dot(1,1)= -k(1)*act(1)*act(2)+k(2)*act(3)
c_dot(2,1)= c_dot(1,1);
c_dot(3,1)= -c_dot(1,1);
Introduction
Thermostatting
%
%
%
%
ionic strength
log gamma
gamma
activities
% A_dot
% B_dot
% C_dot
Ionic Strength
pH
Application CO2
Ni
2+
+ ox
d[Ni 2+ ]
=
dt
=
2-
k+
k-
0+
Ni(ox)
k + × {Ni 2+ }{ox 2- } + k - × {Ni(ox)}
k + × γNi2+ [Ni 2+ ] × γox 2- [ox 2- ] + k - × [Ni(ox)]
γNi2+ , γox 2continuously change as the ionc
strength decreases during the reaction
γNi(ox) is 1, no charge
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
k+ as a function of ionic strength
5.5
d[Ni2+ ]
= k+ × {Ni2+ }{ox 2- } + k- × {Ni(ox)}
dt
log k(+)
5
4.5
4
3.5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
d[Ni2+ ]
= k+ × [Ni2+ ][ox 2- ] + k- × [Ni(ox)]
dt
sqrt(IS)
k- is not -dependent, as Ni(ox)
has no charge
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
pH control
Why do we add buffers ?
useless answer :
• to keep the pH constant
better answer :
• to keep the rate constants constant
real answer :
• to keep the computations simple
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
No Matlab files today,
they are too complex to be
discussed here.
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Application:
saving the planet by absorbing
CO2 from power plants,
post combustion capture PCC
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
The Scale of the Problem
The mass of CO2 produced by
human activities (~25Gt/y as
CO2; ~7Gt/y carbon) is about the
same as the mass of everything
else produced by humans
(including waste) put together.
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
CO2 output of power station
11.8 106 t/y
33000 t/d = 4.4 106 m3/d
100m
CO2 / day
100m
100m
+
N2
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
The Principle of PCC
CO2 N2
CO2
N2
time
heat
base,
e.g. NaOH
Na2CO3
NaOH
or better R-NH2
RNH3+, HCO3-
R-NH2
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
schematic diagram of PCC plant
N2
CO2-free
gas
CO2
high temp
stripper
(100-140 C)
low temp
absorber
(40-60 C)
CO2 lean
solution
flue gas
CO2 N2
CO2 rich solution
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
First questions a chemist is
asking:
• What are the molecules that
interact in PCC ?
• How do they interact with each
other ?
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
What are the molecules that
interact in PCC ?
{CO2}
amine, {RNH2}
CO2(aq), H2CO3
HCO3-, CO32-
RNH2, RNH3+
carbamate, {RNHCO2-}
RNHCO2-, RNHCO2H
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
How is the carbamate formed?
{CO2}
CO2(aq), H2CO3
HCO3-, CO32-
+
amine, {RNH2}
carbamate, {RNHCO2-}
RNH2, RNH3+
RNHCO2- , RNHCO2H
1 molecule
CO2 (aq)
H2CO3
HCO-3
CO2-
+
+
1 molecule
RNH2
RNH+
3
1 molecule
RNHCO-2
RNHCO2H
3
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k-2
k1
k8
k-7
CO2 +H2O
k9
K3
HCO-3
k2
k-8
H2O
-
KW/K6
CO2 (aq)+OH
k-9
RNHCO2H
K10
RNH2
RNHCO-2
RNH+3
Introduction
Thermostatting
CO23
Ionic Strength
K5
RNH2
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k1
k-2
k8
k-7
CO2 +H2O
k9
K3
HCO-3
H2O
k2
k-8
KW/K6
CO2 +OH-
k-9
RNHCO2H
K10
RNH2
RNHCO-2
RNH+3
Introduction
Thermostatting
CO23
Ionic Strength
K5
RNH2
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k1
k-2
k8
k-7
CO2 +H2O
k9
K3
HCO-3
H2O
k2
k-8
KW/K6
CO2 +OH-
k-9
RNHCO2H
K10
RNH2
RNHCO-2
RNH+3
Introduction
Thermostatting
CO23
Ionic Strength
K5
RNH2
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k1
k-2
k8
k-7
CO2 +H2O
k9
K3
HCO-3
H2O
k2
k-8
KW/K6
CO2 +OH-
k-9
K10
Introduction
RNH2
RNHCO-2
RNHCO2H
Thermostatting
CO23
RNH+3
Ionic Strength
K5
RNH2
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k1
k-2
k8
k-7
CO2 +H2O
k9
K3
HCO-3
H2O
k2
k-8
KW/K6
CO2 +OH-
k-9
K10
Introduction
RNH2
RNHCO-2
RNHCO2H
Thermostatting
CO23
RNH+3
Ionic Strength
K5
RNH2
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k1
k-2
k8
k-7
CO2 +H2O
k9
K3
HCO-3
H2O
k2
k-8
KW/K6
CO2 +OH-
k-9
K10
Introduction
RNH2
RNHCO-2
RNHCO2H
Thermostatting
CO23
RNH+3
Ionic Strength
K5
RNH2
pH
Application CO2
pH
K4
H2CO3
k-1
k7
k1
k-2
k8
k-7
CO2 +H2O
k9
K3
HCO-3
H2O
k2
k-8
KW/K6
CO2 +OH-
k-9
K10
Introduction
RNH2
RNHCO-2
RNHCO2H
Thermostatting
CO23
RNH+3
Ionic Strength
K5
RNH2
pH
Application CO2
The complete reaction scheme
CO (aq) + RNH
RNHCO H
H CO + RNH
RNHCO H
2
2
3
2
2
2
2
HCO + RNH
3
RNHCO
RNHCO
2
2
+
2
H+
RNHCO H
2
+
CO2(aq) + H2O
H2CO3
CO2(aq) + OH-
HCO3
CO23
H+
HCO3
HCO3 + H+
H2CO3
RNH2 + H+
RNH3
+
Reactions
involving
carbamates
Other, known
reactions
To be determined:
• 6 rate constants
• 1 equilibrium constants
• - 3 due to microscopic reversibility
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Measurement techniques
•
•
•
•
•
p(CO2) partial pressure in gas phase (slow)
Ba(CO3) precipitation (slow)
Conductometry (fast, not specific)
pH, indicator (fast)
NMR
– 13C-NMR (slow, not quantitative)
– 1H-NMR (intermediate, quantitative)
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Side issue:
translation of model into Matlab code
A
k1
k3
B
k2
c_dot(1,1)=-k(1)*c(1)+k(2)*c(2);
c_dot(2,1)= k(1)*c(1)-k(2)*c(2)-k(3)*c(2);
c_dot(3,1)= k(3)*c(2);
C
% A_dot
% B_dot
% C_dot
pH
K4
H2CO3
k-1
HCO-3
k1
k7
K3
k-2
CO23
H2O
k2
?
k8
k-7
k-8
CO2 +H2O
k9
KW/K6
CO2 +OH-
k-9
RNH2
RNHCO-2
RNHCO2H
K10
Introduction
RNH+3
K5
RNH2
Thermostatting
Ionic Strength
pH
Application CO2
User interface based on
Excel, model parser
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Example 1:
Ammonia, NH3
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Measurements, stopped-flow
[CO2] = 3.8 mM
[NH3] = 2-10 mM
[ThB] = 12.5 M
0.9
0.4
0.8
Abs @ 590 nm
0.3
Abs @ 590 nm
0.7
0.6
10 mM
0.2
0.1
2 mM
0.5
0
0
0.5
0.4
1
1.5
2
time, s
0.3
10 mM
8 mM
0.2
6 mM
0.1
4 mM
2 mM
0
0
3 mM
20
40
60
80
time, s
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Measurements, stopped-flow
[CO2] = 3.8 mM
[NH3] = 3 mM
[ThB] = 12.5 M
different temp.
Abs @ 590 nm
0.4
0.3
0.2
0.1
o
o
45 C
o
35 C
25 C
0
0
10
20
30
40
time, s
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Analysis:
NH3 + CO2
NH4+
NH3
log(concentration)
HCO3-
CO32NH2CO2-
CO2
NH4+
Concentration (M)
NH3
NH2CO2H
HCO3-
NH4+
CO2
NH2CO2CO32-
Concentration (M)
NH3
CO2
HCO3-
NH2CO2-
CO32-
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Measurements, stopped-flow
[NH3] = 44 mM
[HCO3-] = 94 mM
equilibration
[NH3] = … M
[HCO3-] = … M
[NH2COO-] = … M
[HCl] = 65 mM
[BTB] = 12 M
[AlRed] = 50 M
different temp
0.4
45 oC
Abs @ 520 nm
35 oC
25 oC
0.3
15 oC
0.2
0.1
0
0
0.3
0.6
0.9
1.2
1.5
time, s
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Analysis: NH2COO- + H+
HCO3NH4+
CO2
NH4+
CO2
NH2CO2-
log(concentration)
Concentration (M)
HCO3-
H2CO3
NH3
CO32NH2CO2NH2CO2H
H+
H2CO3
log(time)
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Very important aspect:
all measurements were analysed
together,
global analysis!
There are no experimental conditions
where one experiment contains sufficient
information for a fit of the model.
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
The Results:
rate and equilibrium constants as a
function of the temperature
T [oC]
k7 [M-1 s-1]
k-7 [s-1]
15.0
23.5(3)
4.6(1)
10-3
9.3(9)
25.0
49(6)
1.3(1)
10-2
35.0
69(5)
2.3(1)
45.0
97(14)
4.4(7)
T [oC]
Introduction
k8 [M-1 s-1]
k-8 [s-1]
k9 [M-1 s-1]
10-4
2.8(3) 10-4
2.07(1)
1.4(2)
10-3
6.0(9) 10-4
4.5(1)
10-2
2.5(6)
10-3
1.3(3)
10-2
6(2)
10-3
K7 [M-1]
5(1)
10-3
10-3
102
102
k-9 [s-1]
logK10
32.2(5)
6.71(2)
84(16)
6.73(7)
9.25(4)
102
1.88(5)
1.53(6)
103
3.8(3)
102
102
6.70(2)
6.88(4)
K8 [M-1]
K9 [M-1]
15.0
5.1(1)
103
3.3(1)
6.4(1)
25.0
3.7(6)
103
2.29(4)
5.6(9)
35.0
3.0(1)
103
2.02(3)
4.9(1)
45.0
2.2(2)
103
1.05(5)
4.0(3)
Thermostatting
Ionic Strength
pH
Application CO2
The Results:
Arrhenius and van t’Hoff plots
10
8
6
6
lnk 9
4
4
lnk 7
2
ln(k -i)
lnk i
8
2
0
-2
0
-2
-6
lnk 8
-6
0.0032
0.0033
0.0034
Thermostatting
ln(k - 8)
-8
0.0035
-10
0.0031
1/T
Introduction
ln(k -7 )
-4
-4
-8
0.0031
ln(k - 9)
0.0032
0.0033
0.0034
0.0035
1/T
Ionic Strength
pH
Application CO2
The Results:
complete set of thermodynamic
parameters
Arrhenius
Ea
A
[kJ mol ]
k7
NH 3 +HCO 3-
k
-
NH 2 COO +H 2 O
NH 3 +CO 2
NH 2 COOH
Introduction
k9
k
mol-1]
K-1]
33(2)
-104(7)
56(2)
6.9
10
7
53(2)
-103(7)
NH 2 COO - +H 2 O
45(4)
1.2
105
42(4)
-156(12)
-
72(5)
2.8
10
9
70(5)
-72(2)
51(1)
4.2
1011
49(1)
-31(3)
7.7
12
7
8
H 2 CO 3 +NH 3
NH 3 +HCO 3
NH 2 COOH
9
[J mol-1
107
k
k8
[kJ
6.0
NH 2 COOH+H 2 O
NH 2 COOH+H 2 O
S‡
‡
-1
NH 3 +H 2 CO 3
van’t Hoff
Eyring
NH 3 +CO 2
Thermostatting
35(2)
63(2)
10
Ionic Strength
60(2)
S
[kJ mol-1]
[J mol-1 K1
]
-21(2)
-1(5)
-27(2)
-84(7)
-59(8)
-152(26)
-7(6)
pH
Application CO2
Example 2:
morpholine
O
H2C
CH2
H2C
CH2
N
H
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
1H-NMR
O
H2C
CH2
H2C
CH2
spectra
morpholine
N
H
O
H2C
CH2
H2C
CH2
N
COO-
morpholine
+
carbamate
Introduction
Thermostatting
O
O
H2C
CH2
H2C
CH2
O
H2C
CH2 H2C
H2C
CH2 H2C
CH2
N
N
COO-
COO-
N
H
Ionic Strength
CH2
O
H2C
CH2
H2C
CH2
N
H
pH
Application CO2
spectra of Morpholine at 25˚C
(Morpholine/Na2CO3 1/2 with different volumes of 5M HCl)
1H-NMR
O
O
H2C
CH2
H2C
CH2
H2C
CH2
H2C
CH2
N
N
H2+
COO-
0.1
0.09
0.08
0.07
0.06
0.05
4.5
0.04
O
H2C
4
CH2
0.03
0.02
3.5
0.01
3
H2C
CH2
2.5
Introduction
0
vol added (mL)
ppm
N
H
Thermostatting
Ionic Strength
pH
Application CO2
Analysis of the data
Calculated Vs Measured Concentrations
0.025
Concentration (M)
0.02
0.015
0.01
0.005
0
6
7
8
9
10
11
pH
Introduction
Thermostatting
Ionic Strength
pH
Application CO2
Collaborations with
•
Department of Chemistry, University of Newcastle, Australia
Prof. Geoff Lawrance
Dr. Bob Burns
Dr. Raylene Dyson
Dr. Nichola McCann
Dr. Sarah Norman
Dr. Xiaoguang Wang
Will Conway
Debra Fernandes
Azadeh Golshan
Yaser Beyad
•
Institute of Inorganic Chemistry, University of Basel, Switzerland
Prof. Andreas Zuberbühler
•
Institute for Chemical and Bioengineering, ETH Zürich, Switzerland
Dr. Yorck-Michael Neuhold
Prof. Konrad Hungerbühler
•
University of Kaiserslautern
Prof. Hans Hasse
Dr. Nichola McCann
•
CSIRO Energy Technology, Newcastle, Australia
Dr. Graeme Puxty
Dr. Paul Feron
Thank you for your attention