Visualisation de l`écoulement dans un système vis

Transcription

Chapter IV
PROCESSING
Real-time monitoring of mixing
The experimental device presented in this chapter has been recently overviewed
in an article came out in June 2008 (JEC Composites Magazine n°41) [1].
Polymer-clay nanocomposites became truly marketable only some time after the
registration of the first industrial patents [2]: the ability to properly and reproducibly
disperse nanofillers in a polymer was, and still is, considered to be a strict requisite for
their profitable commercialization. Although inorganic moieties are generally required
to perfectly disaggregate, disperse and distribute into the organic matrix, clays are often
affected by distribution and/or dispersion problems of their elementary and primary
particles [3]. We’ve already insisted on the fact that a method capable of monitoring the
evolution of the morphology during processing would greatly help the development of
polymer-clay nanocomposites. Indeed, as previously said (§ I-2.1), if filler aggregation
depends essentially on the physico-chemical interactions of its particles, filler dispersion
and/or distribution into the matrix is directly influenced by processing efficiency. The
morphology of polymer composite materials changes throughout the manufacturing
Antonella ESPOSITO
175
Chapter IV
process but seems primarily influenced, in the case of thermoplastic matrices, by the
extrusion of formulated composite pellets and the injection molding of final objects.
Such steps of the manufacturing chains are often performed by means of devices which
have a complex geometry and, thus, are particularly difficult to monitor.
In this chapter we’ll present a novel and innovating equipment entirely designed,
assembled and developed in our laboratories over a period of about 5 years – including
a little more than two years of a previous PhD project (Maël Moguedet) and the whole
duration of three years of the following PhD project (Antonella Esposito). As suggested
by the name itself, Visiovis is a tool exclusively devoted to processing visualization.
Why processing? Because it consists essentially of a screw/barrel system (French vis =
English screw) in which – and this is the real innovation – the barrel is entirely made of
a transparent material, which permits to continuously visualize (visio-) the flow from all
the possible directions of observation. This property encouraged the exploration of all
the potentialities of such a novel tool – and that’s the topic of this chapter. In particular,
we slightly changed its original configuration to adapt it to the real-time investigation of
mixing between a polymer matrix and a lamellar inorganic filler and, thus, to in-line
monitoring of nanocomposite processing which still is, as previously observed, the
crucial factor for polymer-clay nanocomposites. The photo-functional inorganic/organic
complexes (which are the topic of Chapters II and III) have been prepared expressly to
be used as photo-active lamellar fillers for Visiovis experiments.
IV-1
VISIOVIS
Visiovis has been entirely assembled in our laboratories for the first time in 2003.
This tool was originally designed to visualize the 3D trajectories of a single fluorescent
particle plunged in a transparent fluid [4][5]. During these last three years, we further
developed such an original equipment in order to adapt it to the analysis of nanofiller
dispersion/distribution in viscous media (e.g. molten thermoplastic polymers or uncured
thermoset resins) flowing in a geometrically complex system which is comparable, in
the case of Visiovis, to the meter section of typical screw/barrel systems of industrial
devices for extrusion and injection molding.
PhD INSA de Lyon (2008)
176
PROCESSING
IV-1.1
Original configuration
Visiovis is an experimental device designed and assembled by Maël Moguedet
during his PhD at the Ecole Supérieure de Plasturgie in Oyonnax1 (2002-2005) with the
precious help of the technician Jean Balcaen. The “nucleus” of Visiovis is the assembly
composed of a transparent barrel hosting a screw, but the real advantage – essential for
a complete in-line 3D visualization of the speed cartogram of a fluid evolving in the
space in-between a helicoidal screw and its cylindrical envelop – is the transparency of
the barrel. Indeed, transparency is the property which chiefly rendered the Visiovis
project innovative and interesting for in-line monitoring of the processing of polymers
and polymer-based composites.
The total transparency of Visiovis barrel allowed Moguedet and coworkers [4] to
employ – in an absolutely innovative way – a technique which is relatively common in
the field of fluid dynamics. They specifically designed Visiovis with the perspective of
using it for Particle Tracking Velocimetry (PTV), a technique allowing to originate the
speed cartogram by following the discrete movements of few particles plunged in a
fluid over a finite period of time – under the hypothesis of low particle concentration,
which is the condition permitting to follow the movements of each single particle. The
principle of PVT is schematized in Figure IV-F1 [4].
The main objective of Moguedet’s work was to find a new method to visualize
the entire 3D trajectory of a single particle plunged in a fluid and then to compare the
results obtained by Visiovis with the results obtained by computer simulation. Indeed,
computer simulation is very common in fluid dynamics since it is capable of deducing
information generally not accessible via traditional experiments. On the other hand, a
considerable effort has been done by several groups of researchers to find a practical
method capable of collecting “real” data (although concerning model materials on pilot
implantations) to be compared to the “predicted” ones and to be later “extrapolated” to
1
In February 2005 the Ecole Supérieure de Plasturgie (which up to that moment was a private institution)
was integrated by INSA Lyon and, nowadays, the whole center in Oyonnax (laboratories and educational
facilities) represents the Site de Plasturgie INSA – in particular, the laboratory and all the technical staff
and researchers working therein are now labelled Laboratoire des Matériaux Macromoléculaires (LMM).
Antonella ESPOSITO
177
Chapter IV
the real, industrial systems. In particular, Moguedet and coworkers had been inspired by
some works in which industrial extruders were equipped with one or more windows and
(at least) one camera: they found the idea interesting but underlined the limits of such
systems and looked for a better solution. Acquiring photos and videos on industrial
systems equipped with one or more windows is certainly a good method to visualize the
melting mechanisms of polymer pellets during processing – particularly because such
observations can be directly correlated to other information acquired by conventional
captors for temperature and pressure; however, Moguedet and coworkers were looking
for something more complete (3D rather than 2D), more precise (quantitative rather
than qualitative), more specific (the ultimate aim was to position a particle in the space
and then to reconstruct 3D speed cartograms). Doubtless, that was a first hard challenge.
t1
z
x
tn
Lighting
for tracer
excitation
z
x
y
x
t1
Camera shifting to follow the
particles continuously in time
y
x
tn
Flow direction
Figure IV-F1 Scheme of the principle of PVT technique, chosen by Moguedet and coworkers
to design and develop Visiovis [4].
178
PROCESSING
IV-1.1.1
Components and utilization
In its original configuration (Figure IV-F2), Visiovis is composed of a squarepitched2 screw adjusted in a transparent barrel made of poly methyl methacrylate
(PMMA), deliberately treated against UV radiation3 and assuring a transparency of
about 80% for
44 rpm, torque
> 380 nm [4]. The screw is actuated by an electrical motor (speed max =
max
= 9 N·m). An aperture allows to fill the system with the fluid of
choice, to introduce the tracing particle and to empty the circuit at the end of the
experiments; a tube connected in close circuit permits to virtually prolong the duration
of each experiment by making the fluid continuously circulate into the system. The
screw/barrel system is surrounded by a mobile framework supporting all the other
components, in particular four CCD cameras (Basler A301F), equipped with yellow
filters4 and able to record up to 80 images/s with a resolution of 640 × 480 pixels and a
depth of 8 bits (256 grey levels). Two of the cameras are aligned horizontally and two
vertically, face-to-face on opposite sides of the screw/barrel system – configuration
which, thanks to the mobility of the framework, allows to follow the tracing particle at
each instant with at least two cameras, meaning that at any time it is possible to deduce
its 3D coordinates. Four UV diodes (emission 400 ± 5 nm) are placed around the
screw/barrel system, assuring a 3D lightening. A calibrator, consisting of two
perpendicularly crossing matrices of perpendicular filaments made of fluorescent nylon
(5mm × 5mm), is fixed at one end of the screw/barrel system and allows to measure and
then adjust any difference in the orientation, translation and/or rotation, zoom and/or
focus of the four cameras. The images are recorded thanks to an acquisition circuit
composed of two PCs and an external clock (to assure the synchronization of the
cameras and to set the acquisition time). Visiovis geometrical parameters [4] are listed
in Table IV-T1 and compared to the typical design parameters of the meter section of
industrial screw/barrel systems for extrusion and injection molding [6] (Figure IV-F3).
2
A screw is square-pitched when its pitch is fairly similar to its external diameter (Table IV-T1).
The choice of PMMA treated against UV radiation is justified by the original external light source (four
UV diodes).
4
The yellow filters cut-off the excitation light coming from the diodes and make the cameras visualize
only the fluorescence emission of the tracing particle.
3
Antonella ESPOSITO
179
Chapter IV
UV diodes
Electrical
motor
Aperture
PMMA barrel
Calibrator
CCD
camera
Screw flight
Tube for
closed circuit
Mobile
framework
Figure IV-F2 Visiovis in its original configuration – as it was designed, assembled and used by
Moguedet and coworkers [4].
Table IV-T1 Visiovis geometrical parameters [4] compared to the typical design parameters of
the meter section of industrial screw/barrel systems for extrusion and injection molding [6].
Geometrical parameters
Visiovis
Meter section
Barrel diameter
Db
40 mm
120 mm
Screw root diameter
Ds
30 mm
110 mm
40 mm
120 mm
5 mm
5 mm
34.6 mm
109 mm
20°
18.37°
6.9
21.8
Curvature
0.44
0.15
Torsion
0.16
0.05
Tan( )
0.33
0.33
250 mm
n.a.
Screw pitch
Channel depth
Channel width
Screw angle
(measured in the middle of the channel)
Aspect ratio
Screw length
2
Ph
H
W
L
180
PROCESSING
Ds
H
2
Ph
Db
Figure IV-F3 Schematic of a typical screw/barrel system and the parameters which characterize
its geometry [1].
Moguedet and coworkers [4] chose poly dimethylsiloxane (PDMS) as the model
fluid – a transparent silicone oil having a viscosity of about 100 Pa·s and characterized
by a Newtonian rheological behavior. As a tracing particle, they used a small fragment
of the same filament employed for the calibrator, made of fluorescent nylon (diameter
0.4 mm). This small particle has a density similar to those of the PDMS fluid, which has
allowed to presuppose that the particle was going to perfectly follow the flow lines.
The acquisition of data in Moguedet’s work was simplified by the fact that it was
aimed to the detection of a single point showing the highest luminosity in comparison
with the deep black of the background – and of course this single point corresponded to
the particle of fluorescent nylon. For this reason, Moguedet and coworkers designed an
in-line image processing which noticeably reduced the amount of collected data: once
realized that the fluorescent point representing the detected particle occupied an area of
4×4 pixels on each image acquired by the cameras, they designed a simple software
(C++ environment) capable of acquiring exclusively the image corresponding to an area
of 60×60 pixels centered on the most luminous point visualized by the cameras.
Successively this image, the 3D coordinates of the most luminous point and the date and
time of the acquisition (reduced to a binary code) were recorded in a bitmap format. The
performances of such acquisition system were reduced to the acquisition of 7 images/s
on average. A sample of the data acquired with the Visiovis in its original configuration
is shown in Figure IV-F4.
Antonella ESPOSITO
181
Chapter IV
Figure IV-F4 Typical format of the data acquired by Moguedet and coworkers [4] with the
Visiovis in its original configuration. This example represents a series of five images, acquired
consecutively by a single camera. One can see, in each picture, the detected fluorescent particle
and (encircled at the bottom) the date and time of acquisition encoded in a binary format.
If the acquisition of data in Moguedet’s work was facilitated by the detection of
the brightest point associated to the single fluorescent particle, the processing of such
data was definitely more complicated. In addition to a double real-time data processing
executed in a C++ environment (selection of the 60×60 pixels area centered around the
brightest point and reduction of the noise intrinsically associated to the CCD cameras),
a labor-intensive processing of the acquired data was necessary to finally reconstruct the
3D trajectories of the single fluorescent particle. This second part of data processing
was realized in the Matlab environment and included image filtering, image adjusting
on the basis of the information given by the calibrator, position adjusting on the basis of
the refraction index of the air (atmosphere), the PMMA (barrel) and the PDMS (model
fluid), as well as any other correction imposed by the optical effects due to the fact that
the barrel represents a cylindrical surface (which interfere with any optical acquisition).
More details about the whole data processing can be found in the PhD manuscript by
Moguedet [4].
IV-1.1.2
Advantages and limitations
As already mentioned, since the beginning the Visiovis project presented a great
interest in the field of fluid dynamics and, indirectly, of polymer processing. However,
Moguedet and coworkers had to cope with several problems before achieving their
objectives. If the filament made of fluorescent nylon solved several of their problems
(individuation of a proper tracing particle and realization of the calibrator for the correct
182
PROCESSING
alignment and regulation of the cameras), the idea of a totally transparent barrel hosting
a rotating screw rapidly became a problem much more difficult to be solved. Indeed, the
barrel couldn’t have been made of glass because glass stops UV radiation; couldn’t have
been made of some special glass (e.g. quartz) because, no matter how good its optical
properties would be, it’d always have been too fragile to support the radial pressure
originated by the movement of the screw and by the presence of the fluid (moreover, a
barrel entirely made of quartz would have been excessively expensive). They realized
soon that the only cheap and practicable solution was a barrel made of plastic.
PMMA seemed to represent a rapid and cheap solution, primarily thanks to its
transparency – but, of course, PMMA cannot tolerate high temperature (even if the glass
transition temperature of PMMA is around 100°C, any temperature increase may render
the barrel enough malleable to get susceptible of deformation under the action of the
internal pressure). In addition, the fact that the barrel is made of plastic imposes to pay a
particular attention to the chemical compatibility of any fluid introduced into the system
(or any solvent used to wash it) with the material used for the barrel: only inert oils can
be chosen as the model fluid, and only solvents which neither swell nor dissolve PMMA
can be used for cleaning.
By the way, the barrel wasn’t the only source of problems. If a tracing particle
was already available, Moguedet had still to find a suitable model fluid, which should
have had the following properties: (1) being a macromolecular fluid; (2) resisting UV
radiation without degrading; (3) being optically transparent (to UV radiation but also to
visible radiation); (4) being inert and, more specifically, being compatible with PMMA;
(5) being capable of flowing at room temperature (since any experience with Visiovis
had to be realized at room temperature). After having tried (unsuccessfully) to fill the
closed circuit of Visiovis with a solution of water and poly ethylene oxide (PEO), they
finally found a compromise in poly dimethylsiloxane (PDMS), a transparent and inert
silicone oil, commercially available in different molar weight and, thus, different
viscosities. At least, for the purposes of Moguedet’s work, an advantage of the fact that
PDMS is Newtonian is that this property authorized to perform experiments at relatively
low rotational speeds, as Newtonian fluids aren’t sensitive to shear and, consequently,
Antonella ESPOSITO
183
Chapter IV
their speed cartogram is supposed to stay unchanged even when the screw speed is
increased. The independence of the flow speed profile from the rotational speed induced
Moguedet to choose the slowest speed available for the screw (1 rpm), in order to
optimize the acquisition procedure which, in addition, was slowed down by real-time
data processing5.
Height (mm)
Length (mm)
Width (mm)
Figure IV-F5 Three-dimensional trajectory of a single fluorescent particle in the channel of the
screw/barrel system of Visiovis (screw rotational speed 1 rpm) [4]. The fact that points are
missing for all the positions close to the cylindrical surface of the barrel witnesses the
limitations due to refraction.
The experiments performed with this first version of Visiovis have been positive
in terms of concretization of the project and demonstration that this original tool works
as expected. These first measurements could produce the approximate 3D trajectory of a
particle plunged in a transparent Newtonian fluid evolving into the screw/barrel system
(Figure IV-F5). In particular, they revealed the presence of two speed comportments –
slow close to the barrel surface and rapid close to the screw surface. These observations,
along with the trajectory of the particle, have been successfully confirmed by computer
5
Some information about the real-time data processing during acquisition can be found in § IV-1.1.1. For
more details, please refer to Moguedet’s work [4].
184
PROCESSING
simulations (Figure IV-F6). More in detail, a particle introduced into the system and
starting its progression close to the axis of the system, proceeds rapidly and then moves
towards the surface of the barrel, thus its progression slows down [4]. By the way, the
system still presents several optical problems (once more due to the refraction at the
cylindrical surface of the barrel – coupled to the fact that the four UV diodes create an
isotropic-like lightening which is prone to reflection and diffraction phenomena). These
residual optical problems caused an intensive loss of observed data any time that the
particle got close to the surface of the barrel. The first results obtained by Visiovis and
confirmed by computer simulations have been published in 2004 [7] and the same group
of researchers actually keeps developing the initial model [8].
Experimental radial position
Simulated final radial position
Extrapolation of the simulation
Barrel internal surface
Radial position
(mm)
Screw root surface
Time (s)
Figure IV-F6 Evolution of the radial position of the particle in the channel of the screw/barrel
system of Visiovis (screw rotational speed 1 rpm) [4]. Experimental observations correlate well
with the results of simulation.
Antonella ESPOSITO
185
Chapter IV
IV-1.2
Evolutions of the configuration
It was Moguedet himself who firstly proposed, at the end of his PhD manuscript
[4], some possible modifications of Visiovis:
 the replacement of the four CCD cameras with some more recent “intelligent
cameras”, capable of performing an automatic image processing for the detection of the
brightest point without employing the resources of the computers’ processors – which
could ameliorate the performances of the acquisition of data;
 the realization of an additional computer-controlled system for the automatic
translation of the mobile framework, so that the cameras could follow the advancement
of the tracing particle – which could allow to follow more than one single particle;
 the replacement of the cylindrical barrel by another barrel with an internal
cylindrical surface and an external rectangular shape – which would significantly reduce
the problems caused by refraction.
Our objective is to adapt Visiovis to the real-time monitoring of the dispersion
and distribution of lamellar fillers in a polymer matrix during nanocomposite
processing. To achieve our objective, we unavoidably had to modify Visiovis original
configuration because of some additional difficulties linked to the multiplicity of the
tracing particles to be followed and to their reduced dimensions, as well. Anyway, we
haven’t necessarily followed the lines suggested by Moguedet and coworkers – meaning
that many other possibilities of evolution, ameliorations and diversification are still left.
In fact, we passed through several changes of the configuration, trying to adapt step-bystep this tool to our objectives. The easiest and cheapest changes we could attempt on
Visiovis concerned: (1) the position of the CCD cameras, (2) the form of the lightening
for fluorescence excitation and (3) the addition of the most sensitive instrument for the
characterization of the fluorescence behavior of the photo-functional fillers previously
described6 – a spectrofluorimetry relied to the system by an optical fiber.
6
See Chapter II for more details about the photo-functionalization of lamellar mineral fillers and Chapter
III for the description of the photo-functional inorganic/organic complexes realized with the perspective
of using them with Visiovis.
186
PROCESSING
IV-1.2.1 From 3D lighting to 2D laser plan
At the real beginning of our experimental work – even before the development of
a photo-functionalization method for lamellar fillers – we were quite determined to keep
Visiovis in its original configuration, thus we tried to find a suitable photoluminescent
nanofiller to continue investigating the flow behavior of the same Newtonian matrix
(PDMS) filled with several particle (not just a single tracing particle) evolving in the
same geometrical system (i.e. without modifying the screw profile, since we already had
some information about the existing one).
Indeed, we found a rather good solution for our problems: a cheap, commercially
available phosphorescent pigment (GT5700, GloTech Inc., New Zealand) consisting of
an alkaline rare-earth aluminate, easily excitable by UV radiation, white or any visible
light (240-440 nm), emitting in the yellow/green range (520 nm), with an intense and
persistent emission (>12 hours, certified by the provider on the basis of the measuring
protocol DIN 67510). Two images of this pigment taken by light microscopy are given
in Figure IV-F7 and their excitation and phosphorescence spectra are shown in Figure
IV-F8 (data provided by GloTech Inc.).
100 m
100 m
Figure IV-F7 Two images of GT5700 particles taken by light microscopy (magnification 20x).
Antonella ESPOSITO
187
Chapter IV
Figure IV-F8 Absorption and phosphorescence spectra of the pigment GT5700.
GT5700 chemical, physical and luminescent properties are resumed in Table IVT2. This photoluminescent pigment is employed for many applications, including brush
painting, spray painting, candle making and glass moulding.
Table IV-T2 Main chemical, physical and luminescent properties of GT5700 pigment.
Chemical properties
Composition Alkaline Rare-Earth Aluminate
Insoluble in Water, Alkalis and Organic Solvents
Decomposition Acids
Physical properties
Appearance
Specific Gravity
Particle Size Distribution
(Laser Granularity)
Yellowish
3.6 g/cm3
45-55 m
(D50)
Luminescent properties
Excitation
Excitation Wavelength
Peak Value
Glow Color
Glow Duration
UV radiation, white or any visible light
240-440 nm
520 nm
Yellow-Green
> 12 hours
We performed a test of visualization of the GT5700 pigment by Visiovis and we
actually got some interesting results: the intense brightness due to the phosphorescence
emission is effectively sufficient to visualize the particles with the CDD cameras. We
could easily distinguish the dark zones (pure PDMS) from the zones containing the
188
PROCESSING
phosphorescent particles. In addition, we could clearly visualize any difference in the
spatial distribution of the particles during mixing, as shown by Figure IV-F9.
barrel
differences
in focus
screw flight
pure PDMS
GT5700
particles
barrel
barrel
Figure IV-F9 Some examples of the test of visualization of the GT5700 pigment by Visiovis.
Isotropic-like lightening and excitation by the four UV diodes.
However, the test of visualization of the GT5700 pigment highlighted once more
the great limitations of the system in its actual configuration and of the chosen pigment,
as well. As previously reported, Moguedet and coworkers [4] were aware of the optical
problems created by the cylindrical PMMA barrel and by the isotropic-like lighting of
the four diodes. Their acquisitions and measurement greatly suffered from something
they mainly recognized as a refraction phenomenon. The images collected during our
test of visualization of the GT5700 pigment (Figure IV-F9) clearly show that refraction
isn’t the only optical phenomenon affecting Visiovis in its original configuration: most
of the visualization problems come from a strong reflection of the light by the surface of
the barrel – to a point that no particle can be visualized in the upper and lower portions
of the screw/barrel system, i.e. in the channel sections perpendicular to the cameras.
Moreover, as the particles are phosphorescent, once they’re excited they all emit at the
same time, in any point of the visualized portion of the screw/barrel system: this means
that the cameras should properly (viz. correctly focused) visualize all the particles, even
if they’re placed on different focalization plans. This is obviously impossible, as shown
by the differences in focus visible on the examples in Figure IV-F9.
Antonella ESPOSITO
189
Chapter IV
The same images shown in Figure IV-F9 are presented again in Figure IV-F10,
but in their negative version: the negative version of such images, in which the only
contrast is given by a bright phosphorescence emission on a dark background, greatly
helps the evaluation of the visualization limits of Visiovis in its original configuration.
Two other negative images are added to support the observations done on the basis of
the first two images. It is unambiguous that the zones close to the barrel surface are
“critical” for visualization – besides, this area is probably the most interesting, since it
could help understanding the dependency of the particle distribution on the radial
position, i.e. on the distance from the axis of the screw/barrel system (relative distance
from the barrel surface and/or from the screw root surface).
barrel
differences
in focus
screw flight
pure PDMS
GT5700
particles
barrel
barrel
barrel “critical”
zones
Figure IV-F10 Some examples of the test of visualization of the GT5700 pigment by Visiovis.
The negative version greatly helps the evaluation of the test images. The first two images (upper
side) are the same images already shown in Figure IV-F9.
190
PROCESSING
Taking into account the problems encountered by Moguedet and coworkers in
relation with isotropic-like lightening and the refraction phenomena at the cylindrical
surface of the barrel, and being aware of the fact that changing the shape of the barrel
would have required a deep reorganization of Visiovis configuration, we estimated that
the first thing to do was rather to modify the lightening system. Therefore, we planned
to fabricate an optical system which, coupled to a laser source, would create a thin sheet
of light – a virtual, optical section of Visiovis screw/barrel system. In the presence of
such a bidimensional lightening, the fact that GT5700 pigment is phosphorescent not
only has no more interest, but appear even inappropriate: indeed, the main interest of a
2D lightening is the possibility of visualizing exclusively the particles included in the
thin sheet of light – which requires that the particles are excited by the laser sheet and
produce a fluorescent response exclusively when excited, whereas the glow duration of
the phosphorescent pigment means that the particles emit even if they aren’t anymore
excited.
Although GT5700 pigment has good performances when visualized by Visiovis,
abandoning its usage hasn’t been too much disappointing for several reasons:
 the pigment isn’t a lamellar nanofiller – the particles have an almost unitary
shape factor, which means that they are spherical (see the D50 value in Table IV-T2);
 the pigment has a density (3.6 g/cm3, Table IV-T2) which is inadequate for
the PDMS (0.97 g/cm3) – a filler which is much denser than the matrix is more prone to
sedimentation by gravity;
 the pigment is phosphorescent – a property which, as previously explained, is
no more appropriate for the lightening system we were planning to assemble.
The new lightening system will have to be chosen on the basis of several criteria:
(1) the commercial availability and the price of the laser source; (2) the wavelength of
laser emission – for the optimum excitation of the photo-functionalized filler; (3) the
fact that the PMMA barrel must be transparent (but also resistant) to the light emitted by
the laser. More details about the new lighting system will be given in § IV-1.3.
Antonella ESPOSITO
191
Chapter IV
IV-1.2.2
Position of the CCD cameras
We’ve already highlighted that the zones close to the barrel surface are “critical”
and may be particularly interesting for the visualization of particle distribution during
mixing. We’ve also stressed, when presenting Visiovis and its geometrical parameters,
that our screw/barrel system may be compared to the meter section of the industrial
screw/barrel systems for extrusion and injection molding – thanks to the fact that most
industrial devices has a meter zone characterized by a square-pitched screw and a
shallow channel (see Figure IV-F3 for a schematic representation of the meter section of
a screw/barrel system, as well as Table IV-T1 for a comparison of Visiovis geometrical
parameters with the typical design values of the meter section of industrial devices).
Once understood that the screw profile adjusted in our transparent barrel has a shallow
channel (5mm deep), one realizes how much important is an accurate visualization of
the zones close to the barrel surface. The choice of a new lighting system, consisting of
a thin laser sheet creating an optical slice of the system, is absolutely coherent with this
new criterion of visualization. By making the laser sheet pass exactly by the axis of the
screw/barrel system, we’re planning to visualize the longitudinal section of the channel,
in which the fluid and its filler are supposed to mix up (see Figure IV-F11).
laser sheet
Figure IV-F11 Schematic representation of a laser sheet passing by the axis of the screw/barrel
system of Visiovis. Only the particles lying on the optical plan lightened by the laser sheet are
excited and have a detectable fluorescence emission (similarly to PIV, see Figure I-F18).
192
PROCESSING
It is obvious that, in such a configuration, the camera placed on the same side of
the laser source and the one placed on the opposite side (viz. the cameras lying onto the
optical plan created by the laser sheet) become totally useless. Only one camera – those
placed on the plan perpendicular to the laser sheet – continues accomplishing its task of
visualization (the camera on the opposite side being useless as well, because the data
collected by this second, perpendicular camera would be redundant). In other words, the
fact that we changed the lightening system forced us to change the position of the CCD
cameras, as well. Since the only interesting position for visualization was, at the present,
the plan perpendicular to those traced by the laser sheet, we estimated that the best thing
to do was to align the four cameras axially, alongside the screw/barrel system, right in
face of the visualized longitudinal section of Visiovis channel (Figure IV-F12).
laser source
mobile framework
cameras
laser sheet
Figure IV-F12 Position of the CCD cameras in relation to the laser sheet passing by the axis of
the screw/barrel system of Visiovis.
IV-1.2.3
Optical fiber and in-line spectrofluorimetry
The first test of visualization performed with the luminescent GT5700 pigment
and the original configuration of Visiovis allowed us to estimate the accuracy of our
system – limits that for the moment we could not ameliorate, since we weren’t planning
to change either the CCD cameras or the screw/barrel system itself. Thanks to the
Antonella ESPOSITO
193
Chapter IV
images acquired during the test of visualization, we calculated that the CCD cameras
can detect approximately 83
m per pixel – a sensitivity which could be probably
acceptable for the phosphorescent pigment (D50 = 45-55 m as reported in Table IV-T2)
but surely not enough for lamellar fillers, which have a multiscale structure (Figure IF23) with a minimum dimension of 1 × 100 nm (isolated clay platelets) and a maximum
dimension of about 10
m. More specifically, the typical dry particle size of the
commercial clays selected to perform photo-functionalization is described by the
following distribution7: 10% of the particles measure less than 2 m, 50% less than 6
m and 90% less than 13 m. It is evident that the sole cameras aren’t adequate and
anymore sufficient for a proper visualization of the complex phenomena occurring
during nanocomposite processing. This is the reason why, in addition to the visual
detection performed by the CCD cameras, we decided to equip Visiovis with another
detection system – a spectrometer connected to an optical fiber probe able to collect the
intensity of fluorescence emission during polymer/clay mixing. Spectrofluorimetry is a
technique sensitive to phenomena occurring at a different scale in comparison with the
CCD cameras – the latter performing a global in-line monitoring of mixing, the former
providing more specific and space-restrained information. The main advantage of this
additional technique is that fluorescence is extremely sensitive to several properties of
the environment in which the tracing molecule is positioned – including temperature,
pH, chemical composition, molecular arrangement and physical confinement – as
previously stressed in Chapters II and III.
Of course, we had to check the visualization limits and the sensitivity of both the
CCD cameras and the spectrometer with the photo-active complexes previously
prepared by photo-functionalization of commercial clays. These tests of visualization
will also be useful to calibrate both the detection systems (cameras and spectrometer)
for any future experience with Visiovis. The results of calibration will be discussed in
the following paragraph.
7
These values are provided by the supplier. Percentages are expressed by volume.
194
PROCESSING
IV-1.2.4
Calibration of the detection systems
Before performing any significant experience with Visiovis, we had to assure a
satisfactory calibration of the old and new detection systems with the photo-active
lamellar fillers prepared ad hoc for our visualization tool. The best calibration would be
enough accurate to allow a direct correlation between the concentration of fluorescent
molecule and the luminosity detected for each pixel of the CCD cameras, or the
intensity of the fluorescence emission detected by the spectrometer. Such a scheme of
correlation would allow to obtain a real-time concentration cartogram of the optical
sections created by the laser sheet longitudinally with respect to the screw/barrel
system. Unluckily, such a fortunate calibration would require many measurements and
would surely be complicated for the following reasons: (1) when penetrating the fluid,
the intensity of the planar laser sheet decreases (the higher the concentration of tracer,
the quicker it decreases); (2) the initial concentration of the injected masterbatch is well
known, but unfortunately there’s no way to predict its spatial and temporal evolution
during mixing; (3) we haven’t yet designed an efficient method to get some samples of
the fluid evolving in the screw/barrel system, in order to confirm by some other
technique the results obtained by the cameras and the spectrometer.
Thus, for the moment we could only perform a kind of “qualitative calibration”
of the cameras and of the spectrometer with the first photo-functional inorganic/organic
complex prepared by cation exchange process: the photo-active filler based on Cloisite
® 30B (C30B 0.25MC RhP)8. Even though any calibration is quantitative by nature, we
hazarded called it “qualitative” simply because, in our case, we performed calibration
just to understand whether the photo-active fillers are detected or not, and which is the
optimum concentration to be used for any future experience made on Visiovis.
The calibration of the detection systems required the preparation of a certain
amount of mixtures of the photo-active lamellar filler with the transparent model fluid.
We prepared 11 mixtures having a controlled concentration (0%, 0.001%, 0.0025%,
0.005%, 0.01%, 0.025%, 0.05%, 0.1%, 0.25%, 0.5%, 1%, where percentages are to be
8
More information about the preparation of this photo-active lamellar filler can be found in Chapter II.
Antonella ESPOSITO
195
Chapter IV
intended by weight) starting from an initial 1% wt mixture and proceeding by dilution.
The initial mixture has been prepared by a mixer equipped with a 60 mm
dilacerator
disk – which is supposed to facilitate mixing by breaking the eventual aggregates and
better dispersing the filler into the matrix – rotating at 1000 rpm for 20 min (Disperser
TurboTest Rayneri 33/300P). We mixed the 10 Pa·s PDMS9 (Siliconöl M10000, Carl
Roth, Germany) with a proper amount of the photo-active lamellar filler C30B 0.25MC
RhP10. These controlled mixtures have then been poured in 4.5 mL disposable PMMA
cuvettes11 (Rotilabo ® Plastibrand Elumal-Küvetten) specific for spectrofluorimetry,
assuring a perfect optical permeability (wavelength range 300-900 nm, std dev ≤ 0.004
extinction units starting from 320 nm). All the mixtures are shown in Figure IV-F13.
Figure IV-F13 Controlled-concentration mixtures (C30B 0.25MC RhP in PDMS) prepared for
the “qualitative calibration” of Visiovis detection systems.
9
We used this silicone oil for all our experiences with Visiovis. The reasons why we chose a 10 Pa·s
PDMS instead of a 100 Pa·s PDMS (as Moguedet and coworkers did [4]) deal only with practical aspects
and will be given in the following.
10
We decided to firstly focus on C30B 0.25MC RhP because it was the first photo-active lamellar filler
ready to be used and, parenthetically, it showed a good photo-activity since the first tests of visualization.
11
We purposely chose such special cuvettes since they are made of the same material as Visiovis barrel.
196
PROCESSING
The calibration procedure for the spectrometer essentially consisted in recording
a fluorescence emission spectrum for each mixture (Figure IV-F14) and the calibration
of the CCD cameras in taking an image of each cuvette (Figure IV-F15).
Figure IV-F14 “Qualitative calibration” of the spectrometer connected to the optical fibre: test
performed with 11 mixtures (C30B 0.25MC RhP in PDMS) having different concentrations
(from 0% to 1%). Concentration is expressed in percentages by weight. Integration time 3s.
The results of the calibration for the spectrometer (fluorescence emission spectra,
Figure IV-F14) are unsurprising and, somehow, reassuring. Pure PDMS isn’t excited by
the laser sheet and doesn’t produce any parasite fluorescence phenomenon, as expected.
A concentration of 0.001% wt of C30B 0.25MC RhP doesn’t show any significant
fluorescence response, as well. This could seem weird if compared to the extremely low
concentrations of fluorescent dye used for traditional tracing experiments (only some
parts per million); indeed, we should keep in mind that Visiovis experiences are quite
different from traditional tracing experiments, since:
 we’re not using a pure fluorescent dye to trace an homogeneous fluid in which
the dye is perfectly soluble – we’re rather introducing a photo-functional lamellar filler
Antonella ESPOSITO
197
Chapter IV
in a macromolecular fluid, we’re not sure that mixing will be successful and to which
extent and, in any case, the fluorescent molecules are supposed to be intercalated into
clay galleries, thus clay platelets could engender a barrier effect for fluorescence
excitation and emission, analogously to what happen during thermal degradation or gas
permeation;
 the device we coupled the spectrometer to is pioneering – we’re not using a
fluorescence microscope or any other commercially available equipment to observe the
fluorescence behavior of the photo-active lamellar filler in its environment, thus we risk
to have to cope with some additional optical limitations probably unknown to the people
who perform traditional tracing experiments.
As the concentration reaches a value of 0.0025% wt of C30B 0.25MC RhP, we
observe a first slight fluorescence response around 600 nm – a value of wavelength
which is not exactly the same observed for pure RhP (553 nm, Figure II-F8b) and for
the photo-functional complex (553 nm, Figure II-F11b) in ethanol. This shift may be
due to the medium in which the spectra have been collected (PDMS for the calibration
and ethanol for the other characterizations) but also to the global environment in which
the measurements have been performed, viz. to the fact that the spectra in Figure IV-F14
have been recorded by a spectrometer and collected by an optical fiber placed in front of
the PMMA tub, whereas the spectra in Figure II-F8b and II-FB11b have been recorded
by a commercial spectrometer in standard measurement conditions.
For the values comprised between 0.01 and 0.1% wt, the fluorescence response
seems to be perfectly proportional to the concentration of C30B 0.25MC RhP. Starting
from the concentration value equal to 0.1% wt, a saturation-like phenomenon seems to
occur and the intensity of the main emission peak stop increasing (on the other hand, it
doesn’t start decreasing either, as usually observed in case of fluorescence saturation).
The results obtained for the calibration of the CCD cameras (images taken in the
dark, planar laser source irradiating from top to bottom Figure IV-F15) could a priori
confirm the results obtained for the calibration of the spectrometer, but the eventuality
of obtaining different (i.e. complementary and/or less precise) results shouldn’t be
surprising since, as previously explained, the two detection systems aren’t sensitive to
198
PROCESSING
the same phenomena and cover two different length scales (macro-scale global view for
the CCD cameras, micro- and/or nano-scale local view for the spectrometer). First of
all, the images confirm that pure PDMS isn’t excited by the laser sheet and doesn’t
produce any parasite fluorescence phenomenon. On the other hand and unsurprisingly,
the CCD cameras look less sensitive to fluorescence emission than the spectrometer –
observation which justifies our choice of adding another detection system to Visiovis12.
Indeed, nothing appears on the collected images until the concentration reaches a value
of at least 0.01% wt, afterward the quality of the acquired images gets better and better
up to a concentration value of 0.1-0.25% wt. When the concentration gets higher than
0.25% wt, the local saturation of the fluorescence emission causes a remarkable
degradation of the image quality – as well as a considerable loss of data, particularly
evident for the highest concentration value (1% wt). Besides, another optical problem
arises when the concentration is too high: the mixture becomes less and less transparent
and the penetration depth of the laser sheet rapidly decreases: a further good reason to
be cautious about concentration issues. It’s worthy underline that the optimum
excitation requires the planar laser source to penetrate to a depth at least equal to the
maximum flight depth: as the channel of Visiovis profile is constant and swallow like
most meter sections (5 mm), this requirement is easily fulfilled (Figure IV-F15). This
constraint would have been certainly stricter if Visiovis had a profile similar to the feed
section (constant but deeper channel) or to the transition section (variable channel
depth)13 – one more reason to be careful about acquiring and interpreting data on the
very first portion of Visiovis – containing the connection between the transition and the
meter sections. Indeed, this portion is primarily concerned by concentration and laser
penetration issues: the highest concentration (the lowest laser penetration depth) is
observed right after the injection of the tracing masterbatch, viz. where screw channel is
variable (and surely deeper).
12
13
See § IV-1.2.3.
The typical screw profile and its different sections are described in Chapter I (see Figure I-F2).
Antonella ESPOSITO
199
Chapter IV
L
A
S
E
R
pure PDMS
45 mm
0.001 %
0.0025 %
0.005 %
0.01 %
0.025 %
0.05 %
0.1 %
0.25 %
0.5 %
L
A
S
E
R
1%
L
A
S
E
R
critical
laser
depth
Figure IV-F15 “Qualitative calibration” of the CCD cameras: test performed with 11 mixtures
(C30B 0.25MC RhP in PDMS) having different concentrations (from 0% to 1%). Laser source:
from top to bottom. Percentages are expressed by weight.
200
PROCESSING
In conclusion, the choice of the correct concentration value of the photo-active
lamellar filler to be mixed with PDMS by Visiovis is quite complicated and must be
done on the basis of several parameters – but typically the main criteria for choosing are
the detection limits of the CCD cameras and of the spectrometer, as well as the laser
penetration depth. An acceptable compromise must be found between an insufficient
concentration for the visualization by the CCD cameras and an excessive concentration
which would cause a saturation of the fluorescence emission and, therefore, a loss of
information. The best compromise would be to accept that the data recorded by the
spectrometer are slightly under their optimum of detection so that the images are
acquired by the cameras in their optimum conditions of detection. Therefore, the best is
to assure a concentration of about 0.05-0.1% wt. By the way, as previously underlined,
concentration issues about Visiovis are always more complicated than expected: indeed,
even if the initial concentration of the injected masterbatch is well known, it is
impossible to predict its spatial and temporal evolution during mixing: one can only
predict that, after the injection of a tracing masterbatch into the pure PDMS used to fill
the closed circuit of Visiovis screw/barrel system, mixing will be accompanied by a
dilution of the initial concentration – but such dilution won’t be constant in time and,
even worse, it will have a complicated spatial dependence reflecting the mixing
efficiency of the system. This means that: (1) injecting an initial masterbatch which is
too concentrated will surely hinder the visual detection by the CCD cameras at the very
first moments of the experience because of luminosity saturation, as shown in Figure
IV-F15 (whereas the fluorescence detection won’t be affected because Figure IV-F14
doesn’t show any decrease of the fluorescence emission intensity, but rather a plateau at
the highest concentration values); (2) injecting an initial masterbatch which isn’t enough
concentrated will almost certainly make the fluorescence detection less clear (the
emission peak won’t be at its maximum intensity, as shown in Figure IV-F14) and, as a
consequence of the dilution, will force us to stop the experience sooner than in the
previous case (the concentration would drop sooner under the detection limits), but at
least the absence of an initial luminosity saturation (Figure IV-F15) would allow us to
collect all the visual data by the cameras.
Antonella ESPOSITO
201
Chapter IV
On the basis of some early tests of visualization with the photo-active lamellar
fillers, we observed that the efficiency of visualization by Visiovis seemed to decrease
with the degree of homogeneity of the mixture evolving into the screw/barrel system –
in other words, the most interesting moments of any experience performed by Visiovis
seem to be the very first ones. For such reason, we judged necessary to assure a correct
visualization of the first part of any future experience and, after several trials, we found
that the best compromise is to inject (in pure PDMS) 10 mL of an initial masterbatch
having a concentration of photo-active lamellar filler of 0.25% wt. More details about
the experimental protocol will be given in § IV-2.
IV-1.3
Actual configuration
After the modifications we operated, Visiovis consists of some old components
in their previous configuration, some old components in a new configuration and some
new components. The screw/barrel system (which can be considered as the “nucleus” of
Visiovis) is the main old component kept in its original configuration. Analogously, the
electrical motor, the aperture (to introduce the fluid and the tracers), the tube (for close
circuit) and the mobile framework – all these components stay unchanged in their initial
configuration. On the other hand, the CCD cameras are now disposed differently on the
mobile framework (they’re aligned axially, alongside the screw/barrel system)14, their
yellow filters have been replaced by new filters (better adapted to the new light source),
the diodes have been substituted by a green laser source ( = 532 nm, nominal power 20
mW CW15, Figure IV-F16 (a) and (b)), the acquisition circuit has been simplified (no
more external clock and D-latch memories). The new components are: an optical system
which creates, from the linear laser source, a bidimensional laser sheet (Figure IV-F16
(c) and (d)); an electromechanical output transducer (a trigger, basically a switch),
which couples the image acquisition to the screw rotation (the cameras are controlled by
the movement, since they acquire one image per screw revolution); the spectrometer
(USB2000+ miniature, Oceanoptics), interfaced to the screw/barrel system by an optical
14
15
More details and the reasons for such change of configuration are available in § IV-1.2.2.
Continuous Wave.
202
PROCESSING
fiber (600 m
with a resolution of 2.5 nm) positioned in front of the channel of the
screw/barrel system, on the opposite side of the cameras and perpendicularly to the laser
sheet; a tap in the middle of the tube for close circuit, facilitating the draining of the
system after each experiment. The calibrator has been simply removed.
(a)
(c)
(b)
(d)
Figure IV-F16 Thin laser sheet ( = 532 nm, nominal power 20 mW CW) passing by the axis
of the screw/barrel system.
A global picture of Visiovis in its actual configuration, accompanied by some
more detailed pictures of its actual components, is shown in Figure IV-F17 [1].
Antonella ESPOSITO
203
Chapter IV
Laser sheet @ 532 nm
Aperture
Electrical motor
CCD cameras
Screw/barrel system
Tube for
close circuit
Spectrometer
Trigger
Optical fiber
Figure IV-F17 Visiovis in its actual configuration – after the modifications we made to the
lighting system, the change of position of the CCD cameras and the addition of the optical fiber
and the spectrometer [1].
IV-1.3.1
Objectives
Once the modifications made and the detection systems calibrated, we could plan
how to perform experiments on Visiovis in its actual configuration and, in particular, we
could finally consider the following questions:
 Which model materials would it be better to use to perform the visualization
experiences (in other words, which model fluid and which photo-active lamellar filler)?
 How should we prepare the masterbatches to be injected into the screw/barrel
system from the apposite aperture?
 Which method should we use to inject the masterbatches?
204
PROCESSING
 How will we exploit the experimental data collected by the cameras and the
spectrometer?
 Shouldn’t we conceive a system which would allow us to validate the results
eventually obtained by Visiovis (e.g. sampling and coupling to other characterization
techniques)?
Aware of the multiplicity of problems to be solved and questions to be answered
to, we realized that the objectives with the highest priority were, at present: (1) planning
a correct experimental protocol able to give some interesting results and (2) performing
some early visualization tests on the freshly-reconfigured Visiovis, in order to prepare
the way to the future experiments. With these targets in mind, we tried to answer to as
many questions as possible – anyway, some of them will rather remain a perspective –
and we attempted to suggest some realistic solutions.
IV-2
EXPERIMENTAL PROTOCOL
As previously announced, our optimization vocation starts with finding a first,
realistic and practicable experimental protocol which would allow exploiting the freshly
reconfigured Visiovis to obtain some interesting and – of course – interpretable results.
We’ll firstly describe the experimental protocol used to perform the visualization tests:
the interpretation of the experimental results is an issue to be considered soon after.
With reference to the model materials to be used for the visualization test (model
fluid and photo-active lamellar filler): as we haven’t yet found an appropriate substitute
for the transparent PDMS, we decided to continue using such macromolecular viscous
fluid as the model matrix (Siliconöl M1000016, Carl Roth, Germany); about the photoactive lamellar filler, we decided to perform some rapid visualization tests of the four
16
We used Siliconöl M10000 (10 Pa·s) rather than Siliconöl M100000 (100 Pa·s) because, contrarily to
Moguedet and coworkers [4], the way we were going to use Visiovis required to change the model fluid
after each experiment – whereas Moguedet and coworkers could use the same fluid for longer time. The
need for frequently changing the fluid is a key parameter for the feasibility of a given experimental
protocol: the steps of filling and empting the screw/barrel system are the slowest and the most delicate, as
all the air bubbles must be carefully evacuated before performing any visualization activity – indeed, the
presence of air bubbles significantly affects optical phenomena.
Antonella ESPOSITO
205
Chapter IV
photo-functional inorganic/organic complexes prepared by cation exchange process 17 of
commercial clays (Cloisite ® Na+, Cloisite ® 30B, Cloisite ® 10A and Cloisite ® 15A)
to be sure that they’re correctly detected by the cameras and the spectrometer. The
results of the visualization test performed on the four photo-functional complexes is a
little bit surprising (not all the photo-active lamellar fillers can be efficiently visualized
by the cameras) but, after all, it shouldn’t astonish that much: as previously commented,
fluorescence is a sensitive but fickle technique, about which one can never be confident
of getting for sure some good results. Indeed, several reasons could explain the fact that
three of the four photo-active lamellar fillers can be perfectly detected (C30B 0.25MC
RhP, C10A 0.25MC RhP and C15A 0.25MC RhP) whereas one cannot (CNa+ 0.25CEC
RhP). A first reason could be the chemical composition of the commercial clays used to
prepare the photo-functional complexes: the photo-active lamellar fillers which can be
easily visualized by both the cameras and the spectrometer are the ones prepared from
organoclays – contrarily to the one which doesn’t show any visible fluorescence, rather
prepared from a natural clay. However, such explication doesn’t really persuade, since
the characterizations of the dry photo-functional inorganic/organic complexes by
spectrofluorimetry didn’t reveal any relevant difference in the fluorescence emission of
the four samples. Another possible reason must be searched, then, in the interactions of
the photo-active lamellar fillers with the silicone oil: the presence (or, we should better
say, the absence) of an organic surfactant in clay galleries could play a significant role
in the formation of a positive (negative) interaction of the photo-active filler with the
PDMS, assisting (hindering) the fluorescence emission by the RhP cations.
Definitely, finding an explication isn’t that easy. We’ll just observe that some
difference has been visually detected even before performing the visualization test by
Visiovis: when preparing the masterbatches with the four photo-active lamellar fillers,
we noticed that the aspect of the mixture prepared with CNa+ 0.25CEC RhP was
different (visibly less homogeneous, meaning a less intimate mixture) with reference to
17
More details about the photo-functionalization method are available in Chapter II. On the other hand,
Chapter III deals with the characterization of the four photo-functional inorganic/organic complexes.
206
PROCESSING
the other mixtures18, as shown by Figure IV-F18. In any case and whatever the reason
for such behavior, this supplementary visualization test made us exclude one of the four
photo-active fillers: no further experiments will be performed with CNa+ 0.25CEC RhP.
zoom
zoom
Figure IV-F18 Visual comparison of the masterbatches prepared mixing Siliconöl M10000
with two of the four photo-active lamellar fillers (CNa+ 0.25CEC RhP and C30B 0.25 MC RhP)
to perform a preliminary visualization test by Visiovis. The aspect of the mixture prepared with
CNa+ 0.25CEC RhP (left) is visibly different from the aspect of the mixture prepared with C30B
0.25MC RhP (right) at the same concentration (0.1% wt).
With reference to the method used to prepare the masterbatches: all the mixtures
have been prepared by a mixer equipped with a 60 mm
dilacerator disk rotating at
1000 rpm for 20 min (Disperser TurboTest Rayneri 33/300P) – exactly the same method
used to prepare the controlled mixture for the calibration of the detection systems. We
mixed the selected PDMS (Siliconöl M10000) with a proper amount of the photo-active
lamellar filler in order to assure a concentration of photo-active lamellar filler of 0.25%
wt, as determined by the calibration of the detection systems (§ IV-1.2.4).
It is worthy to observe that, after a certain time, the masterbatches prepared with
the described method undergo decantation and a significant portion of (not all) the filler
sediments. Undoubtedly, this is not a good sign – a suspension of nanosized particles is
18
Parenthetically: as we’ve also prepared some photo-functional inorganic/organic complexes by cation
exchange processing with Nile Blue A Perchlorate (Chapter II), we tried to prepare some mixtures of
PDMS with CNa+ 0.25CEC NBAP and CNa+ 1CEC NBAP and we compared them to the mixtures of
PDMS with C30B 0.25MC RhP and C30B 1MC RhP (the homologue complexes, but functionalized with
Rhodamine 6G Perchlorate). We noticed the same differences shown in Figure IV-F18.
Antonella ESPOSITO
207
Chapter IV
supposed to be stable, since gravity effects should be negligible for very fine particles.
The dry photo-active lamellar fillers are certainly characterized by a size distribution19
including more or less fine particles – this would explain the fact that only a portion of
filler undergoes sedimentation. In reality, when a lamellar filler is mixed with a polymer
matrix and if these two components of the mixture have a high affinity, a certain degree
of “spontaneous” exfoliation of the filler (and, thus, an induced reduction of the average
particle size) can be observed. In this case, a partial sedimentation of the masterbatches
made us early foresee that no driving forces exist for our photo-active lamellar fillers to
spontaneously exfoliate into the selected PDMS – neither related to the chemistry of the
mixture, nor produced by the shearing effects of mixing. Such forethought will be later
proved by rheology measurements20. For the moment we just underline that, if GT5700
pigment was too dense (3.6 g/cm3, Table IV-T2) to avoid sedimentation when mixed up
with PDMS (0.97 g/cm3), our photo-active lamellar fillers are less denser but certainly
not perfectly compatible – at least in terms of density – with the selected model fluid.
Indeed, the clays used to prepare the photo-active lamellar fillers have a density of 2.86
g/cm3 (Cloisite ® Na+), 1.98 g/cm3 (Cloisite ® 30B), 1.90 g/cm3 (Cloisite ® 10A) and
1.66 g/cm3 (Cloisite ® 15A)21. Therefore, their sedimentation is unavoidable (maybe
just slower) in the absence of a massive exfoliation.
With reference to the method used to inject the masterbatch into the screw/barrel
system: we conceived two different modes of injection but only one practical procedure
(the only available at the moment).
The first mode of injection could be used to model an extrusion step – mixing up
pure polymer pellets (which gradually melt) with the dry filler, to formulate composite
pellets to be successively used for the fabrication of the final objects. This first injection
mode requires the preparation of a three-layer “unmixed masterbatch” composed of a
layer of dry filler stacked between two layers of PDMS (total volume 10 mL, equivalent
concentration 0.25%wt as previously indicated), to be injected into the system via a 20
19
We couldn’t characterize their particle size distribution because of the tiny amounts of sample we could
produce by cation exchange process with the fluorescent molecule (rather expensive).
20
See § V-4.1.
21
Even if the photo-functionalization process could have slightly changed such values, they still represent
a good reference for comparisons.
208
PROCESSING
mL syringe (previously cut at its extremity to avoid shearing). We tested this injection
mode only once, then we had to suspend it because of some problems due to the model
materials (poorly compatibles) and the geometry of the screw/barrel system (the actual
profile of Visiovis screw has a poor mixing efficiency – unsurprisingly, as we showed
that it rather models a meter zone22). Briefly, the filler couldn’t properly be mixed up
with the PDMS and, consequently, showed a strong tendency to sediment during – and
particularly after – the experiment. Sedimentation resulted in serious problems about the
complete purge of the system.
The second mode of injection is more adapted to model a portion of the injection
molding devices (the meter zone, of course) – melting again the composite pellets
previously formulated by extrusion and using the molten mixture for the fabrication of
the final objects. This second injection mode requires the preparation of a masterbatch
having a good quality of mixing (following the method of the disperser) and a volume
of 10 mL, to be injected in the system via the same 20 mL syringe previously described
(Figure IV-F19). This is the mode of injection we focused our attention on.
Figure IV-F19 Method used to inject the masterbatch (here, the second injection mode is
shown) into the screw/barrel system: via the appropriate aperture, using a 20 mL syringe
previously cut at its extremity to avoid shearing.
In summary, the experimental protocol to test the novel configuration of Visiovis
is the following:
22
The geometrical parameters of Visiovis screw/barrel system are listed in Table IV-T1.
Antonella ESPOSITO
209
Chapter IV
Preparation of the masterbatch. PDMS (Siliconöl M10000) is mixed up with a
suitable amount of photo-active filler (target concentration 0.25% wt) then intensive
mixing is performed by a mixer equipped with a 60 mm
dilacerator disk rotating at
1000 rpm for 20 min (Disperser TurboTest Rayneri 33/300P). We prepared a masterbatch
for all the photo-active lamellar fillers that looked suitably detectable (C30B 0.25MC
RhP, C10A 0.25MC RhP and C15A 0.25MC RhP).
Preparation of the syringe for the masterbatch injection. A standard 20 mL
syringe is previously cut at its extremity to avoid shearing while injecting, then it is filled
up with 10 mL of the previously prepared masterbatch.
Injection of the masterbatch into the system. Once the syringe prepared, the
screw/barrel system filled up with neat PDMS (Siliconöl M10000) and purged of all the
air bubbles, the room light switched off, the spectrometer zeroed for the black
background, the screw rotation set at about 20 rpm (corresponding to a voltage of 15V)
and the laser sheet switched on, the syringe is plunged vertically in the aperture and the
injection is rapidly achieved in the lowest accessible point.
IV-2.1
Acquisition of data
Once the injection of the masterbatch into the system executed as previously
described, the experiment is officially started and experimental data are automatically
acquired: one image per screw revolution is recorded by each CCD camera thanks to the
trigger, and a fluorescence emission spectrum is regularly recorded every three seconds
by the spectrometer thanks to the optical fiber. The images are stocked sequentially in a
*.bmp file named by a code composed by the date and the hour of data recording. At the
end of the experiment, each sequence of images can be used to reconstruct the
corresponding video. The fluorescence spectra are recorded individually in *.txt files.
210
PROCESSING
IV-2.1.1
Images
Figure IV-F20 shows a series of consecutive images (top to bottom) acquired by
one CCD camera (the first in the progression of the fluid, i.e. the closest to the point of
injection – which parenthetically is the camera showing the portion of screw profile in
which there’s the transition from the compressing to the pumping zone23) in the dark,
after the injection of a masterbatch of C30B 0.25MC RhP (left), C10A 0.25MC RhP
(middle), C15A 0.25MC RhP (right). Only the first images are shown, thus these series
represent just the beginning of mixing (6 screw revolutions, corresponding to a lapse of
time of 18 seconds ca).
It is clear that any interpretation of such images would be extremely subjective –
unless a suitable image processing is found to “translate” the qualitative information
given by the serial images in, at least, some quantitative trends. Obtaining quantitative
and absolutely reliable results won’t probably be easy – maybe won’t even be possible –
and our present objective is actually to extract some general but provable information.
By the way, the possibility of a direct visualization of the mixing progression in any
point of the screw/barrel system is innovative and certainly original.
IV-2.1.2
Videos
As previously said, the series of consecutive images shown in Figure IV-F20 can
be also used to reconstruct videos. The same reflections made about the single images
(any interpretation would be extremely subjective and certainly biased, somehow) can
be transposed to the videos reconstructed from the complete sequences of images.
However, no processing algorithms are available to get some quantitative information
directly from a video – one would rather use the sequence of images which compose it
to perform any quantitative analysis – therefore talking about video processing is here
meaningless, as our first source of data are the images.
23
More details about a typical screw profile for injection moulding devices – melting zone, compressing
zone and meter zone – are available in Chapter I.
Antonella ESPOSITO
211
Chapter IV
C30B 0.25MC RhP
0.25% wt
C10A 0.25MC RhP
0.25% wt
C15A 0.25MC RhP
0.25% wt
Figure IV-F20 Three series of consecutive images (top to bottom) acquired by one of the CCD
cameras in the dark after the injection of a masterbatch containing C30B 0.25MC RhP (on the
left), C10A 0.25MC RhP (in the middle) and C15A 0.25MC RhP (on the right).
212
PROCESSING
IV-2.1.3
In-line fluorescence spectra
Figure IV-F22 shows some examples of in-line fluorescence-spectra regularly
recorded by the spectrometer, interfaced with Visiovis by means of an optical fiber
which, as previously explained24, is placed perpendicularly to the laser sheet, in front of
the screw/barrel series but on the opposite side of the CCD cameras. The emplacement
of the optical fiber is better shown in Figure IV-F21.
Figure IV-F21 Two pictures illustrating the position of the optical fiber used to interface the
spectrometer with Visiovis and, thus, to regularly collect in-line fluorescence spectra.
The fluorescence spectra shown in Figure IV-F22 have been recorded during the
visualization tests performed by injection of a masterbatch of C30B 0.25MC RhP (top),
C10A 0.25MC RhP (middle), C15A 0.25MC RhP (bottom). The fluorescence emission
– whose spectrum is recorded every 3s (integration time 3s) by the spectrometer 25 –
cannot support the information supplied by the images and the videos (the phenomena
associated to the detection are absolutely different and occur at a totally different length
scale) but could eventually complete it. In fact, as previously argued in § IV-1.2.3, the
sole CCD cameras are neither adequate nor sufficient for a correct visualization of the
phenomena occurring during nanocomposite processing. Spectrofluorimetry, on the
other hand, is a technique capable of giving some information which are, surely, spacerestrained, but which could imply a deeper assessment of clay exfoliation mechanisms.
24
25
The actual configuration of Visiovis has been described in § IV-1.3.
See § IV-1.2.3.
Antonella ESPOSITO
213
Chapter IV
Photo-active
lamellar
filler
Laser 532 nm
Photo-active
lamellar
filler
Laser 532 nm
Photo-active
lamellar
filler
Laser 532 nm
Figure IV-F22 In-line fluorescence spectra acquired by Visiovis (details in the text). From top
to bottom: C30B 0.25MC RhP, C10A 0.25MC RhP and C15A 0.25MC RhP.
214
PROCESSING
IV-3
PROCESSING OF THE ACQUIRED DATA
The serial images acquired by each CCD camera (an example is shown in Figure
IV-F20) are useful to evaluate visually the temporal evolution of nanofiller distribution
in the volume of fluid comprised in between the screw flights, the screw root surface
and the barrel surface – in other words, they are useful to estimate the efficiency of the
visualized screw profile in terms of distributive mixing. Moreover, images can be used
to reconstruct videos which straightforwardly show such temporal evolution – certainly,
videos represent a pure qualitative result, but somehow they could help understanding
mixing dynamics. We’ve previously avowed that talking about some processing method
to get quantitative information from a video is actually meaningless, whereas for serial
images (time-related sequence of images) it is possible to conceive some procedure to
“translate” the qualitative information in a quantitative trend. With the precious and
irreplaceable help of Jean Balcaen we implemented two Matlab programs which process
the serial images acquired in presence of the photo-active lamellar fillers on the basis of,
respectively, (1) the integral standard deviation of the luminosity of the images, and (2)
the Fourier transform of textured images. All the Matlab functions we developed are
available in the Appendix.
In relation to the collected fluorescence emission spectra, we estimated that their
simple visualization as a function of processing time is already a valuable information,
thus for the moment we haven’t searched through the possibility of further processing.
IV-3.1
Images
The images shown in Figure IV-F20 as an example of the data acquired by
Visiovis have been taken by one of the four CCD cameras – more specifically by the
first camera in the progression of the fluid, i.e. the closest to the point of injection of the
masterbatch. Indeed, as previously explained, this first camera shows the portion of the
screw profile in which the transition from the compressing to the pumping zone occurs.
This zone is certainly interesting; nevertheless, the corresponding visualized volume has
a shape which is too complex and inadequate for the image processing we conceived –
Antonella ESPOSITO
215
Chapter IV
which is actually more adapted to the analysis of a regular rectangular area. Thus, the
images in the field of the first camera have been collected, but they won’t be used for
any further image processing other than the reconstruction of the videos. The first
channel section useful for image processing (i.e. entirely visualized by a single camera)
falls in the field of the second camera and, just to begin, we decided to focus on one
channel section – as a result, the first and second cameras will be largely enough to
perform preliminary visualization experiences by Visiovis.
When introducing the topic of the acquisition of data, we said that the images are
stocked sequentially in a single *.bmp file named by a code composed by the date and
the hour of data recording26. The preliminary procedure for image processing is, thus, to
extract each single image from the unique *.bmp file recorded by Visiovis acquisition
circuit. This step can be executed by using the Matlab function decoupe.m (available in
the Appendix). After that, as a biggest portion of each image is completely black 27 and
we’re rather interested to the channel section, a further cutback of the serial images is
necessary, in order to reduce the area of the images to be processed just to the rectangle
around the channel section: the Matlab function performing this operation is fenetre.m
(available in the Appendix). Right after these two basic steps, Visiovis images are ready
to undergo the two aforementioned processes28. Figure IV-F23 shows an example of the
input (on the left) and output (on the right) images for the function fenetre.m.
fenetre.m
Figure IV-F23 Example of an input (left) and output (right) image for the function fenetre.m.
26
See § IV-2.1.
The black portions of the images correspond to the flight silhouette and the body of the screw.
28
See § IV-3.
27
216
PROCESSING
IV-3.1.1
Standard deviation of image luminosity
The image processing performed by the Matlab function ecrtype.m (the M-file is
available in the Appendix) is based on the integral standard deviation of the luminosity
of Visiovis images. For each picture of a given sequence (input), this function calculates
the local values of the luminosity29 and their standard deviations, integrates the values
of standard deviation on the whole surface of the picture and then plots the logarithm of
the integral standard deviation of the luminosity as a function of the image number in
the sequence (i.e. the number of screw revolutions, as each camera acquires one image
per screw revolution). Of course, the temporal dependence can be deduced by the
rotational speed of the screw – in other words, since the screw turns at 20 rpm ca, one
revolution takes 3s and, consequently, the cameras acquire one image every 3s.
Interpretation’s key. In theory, the smaller the integral standard deviation of the
luminosity is, the more homogeneous the mixture and the more efficient the distributive
mixing will be.
Limitations. The integral standard deviation will never be smaller than a certain
value because of to the difference of the mixture (never completely black) in comparison
with the screw profile (always completely black).
Moreover, this image processing is not morphology sensitive: two images with
different textures may give the same results in terms of standard deviation of luminosity.
An example of the plot which can be obtained by this image processing based on
the integral standard deviation of the luminosity of the images is shown in Figure IVF24 [1]. Several successive passages of the masterbatch containing the photo-active
filler in the field of the camera are easily recognizable. The fact that the first peak
rapidly lowers indicates that the masterbatch is gradually diluted by the neat PDMS and
29
We just remind, here, that Visiovis cameras acquire 8bit images, i.e. Visiovis images are represented by
a colormap having 28=256 grey levels. Each pixel can assume one of these 256 grey levels, and each level
corresponds to a different light intensity (luminosity).
Antonella ESPOSITO
217
Chapter IV
mixes up with the matrix. In this example, the fluid evolving into the screw/barrel
system effectuates 2.5 recirculations in the closed circuit, as it passes three times in the
visual field of the acquiring camera.
Figure IV-F24 Typical result obtained by the image processing based on the integral standard
deviation of the luminosity of Visiovis images – output of the Matlab function ecrtype.m. As the
screw rotational speed is 20 rpm ca, the temporal dependence can be derived by multiplying the
number of screw revolutions by 3 (one screw revolution every 3s).
IV-3.1.2
Discrete Fourier Transform (DFT)
of textured images
The image processing performed by the Matlab function normft.m (the M-file is
available in the Appendix) is motivated by the fact that the Fourier transform (FT) can
codify a textured image by the frequencies of repetition of its elementary textural units
(e.g. spirals or twisted fluorescent volutes on a homogeneously black background). As
any image can be expressed as a function of two discrete spatial variables, the FT of an
image is the sum of complex exponentials having different amplitudes, frequencies and
218
PROCESSING
phases, and indeed such representation plays a critical role in a broad range of image
processing applications (including enhancement, analysis, restoration and compression).
If f ( x, y ) is a function of two spatial variables x and y , then we can define the
two-dimensional Fourier Transform of f ( x, y ) by the following relationship:
F(
where (
x
F(
x
,
,
y
x
y
)
x
j
f ( x, y)e
y
xx
e
j
yy
dxdy
(IV-E1)
) are frequency variables associated to the spatial variables ( x, y ) .
,
y
) , which can be called the frequency-domain representation of f ( x, y ) ,
is a complex-valued function periodic in both
usually only the range
x
,
x
and
(period 2 ); for such reason,
y
of the function is displayed. F (0,0) is the sum
y
of all the values of f ( x, y ) and, thus, is often called the constant component of the FT.
The inverse two-dimensional FT is given by
f ( x, y)
1
4
2
F(
x
x
,
y
)e j
xx
e
j
yy
d
x
d
y
(IV-E2)
y
Roughly speaking, this expression proves that f ( x, y ) can truly be represented as
a sum of an infinite number of complex exponentials (i.e. sinusoids) having different
frequencies. The amplitude and the phase spectra of the contributions at the frequencies
(
x
,
y
) are given by F (
x
,
y
).
Just to give an example: let’s consider a function f (m, n) which equals 1 within a
rectangle and 0 everywhere else in the plan (Figure IV-F25a): Figure IV-F25b shows
the plot of the magnitude spectrum of its FT F (
plot is F (0,0) . The plot shows that F (
m
,
n
m
,
n
) . The peak at the centre of the
) has more energy at high horizontal than at
high vertical frequencies: this means that f (m, n) horizontal cross sections are narrower
pulses than vertical cross sections (narrow pulses have more high-frequency content
Antonella ESPOSITO
219
Chapter IV
than broad pulses). Please note that small dimensions in the Euclidean space correspond
to high frequencies in the Fourier space, and vice versa (m vs. n rectangle dimensions).
(a)
(b)
Figure IV-F25 A simple rectangular function (a) and the amplitude of its Fourier transform
represented as a mesh plot (b).
Another common way to visualize the FT is to display the log F (
m
,
n
) as an
image (Figure IV-F26): the fact of using the logarithm helps to bring out more details of
the FT in regions where F (
m
,
n
) is very close to 0.
Figure IV-F26 The logarithm of the Fourier transform of a simple rectangular function (Figure
IV-F25a) represented as an image.
Figure IV-F27 shows two additional examples of the FT amplitude spectra for
simply-shaped functions (a tilted rectangle, on the left, and a circle, on the right). These
additional examples show that the FT is sensitive not only to the eventual presence of
image textures, but also to their position and orientation (i.e. to the image symmetry).
220
PROCESSING
Figure IV-F27 Two additional examples of Fourier transform for simply-shaped functions. The
FT is sensitive to the symmetry of the image, i.e. to the position and orientation of its textural
features.
Actually, the amplitude spectra given by the FT are invariant to translation – a
simple translation of a given textural feature doesn’t modify the amplitude but only the
phase of the sinusoidal contributions. On the other hand, the TF is sensitive to rotation.
Let’s consider a sinusoid of period T having a given initial orientation (Figure
IV-28a): its FT is represented by two peaks aligned in the same direction, corresponding
to the frequencies 1 T and 1 T . A rotation of an angle
makes the FT analogously
rotate, without changing its global appearance (Figure IV-28b).
Figure IV-F28 Sinusoidal surface of period T parallel (left top) and tilted (left bottom) with
respect to the x axis, and the corresponding FT (on the right).
Antonella ESPOSITO
221
Chapter IV
Evidently, we took into account these properties (which are typical of the FT)
when we conceived the Matlab function normft.m for Visiovis image processing.
Working on a computer with digital images (i.e. constituted by pixels) requires
using a form of the transform which is known as the Discrete Fourier Transform (DFT).
There are two principal reasons for using this form: (1) the input and output of the DFT
are both discrete, which makes it convenient for computer manipulations; (2) there is a
fast algorithm for computing the DFT, known as the Fast Fourier Transform (FFT). The
DFT is defined for a discrete function f (m, n) that is nonzero only over a finite region
0 m
M 1 and 0 n
N 1 (which is exactly the case of a digital image). The two-
dimensional M-by-N DFT and inverse M-by-N DFT relationships are given by:
M 1N 1
F ( p, q)
f (m, n)e
j
2
pm
M
e
j
2
qn
N
where
m 0n 0
2
f (m, n)
2
qn
j
pm j
1 M 1N 1
F ( p , q )e M e N
where
MN p 0 q 0
p 0,1,..., M 1
(IV-E3)
q 0,1,..., N 1
m
0,1,..., M
1
n
0,1,..., N 1
(IV-E4)
The Matlab built-in functions fft, fft2 and fftn implement the FFT algorithm for
computing the one-dimensional, two-dimensional and N-dimensional DFT respectively.
As we were going to deal with images (two-dimensional discrete functions), we were
mainly interested in the 2D-DFT Matlab built-in function. The DFT of a digital image
gives a spectrum of all the frequencies comprised between a maximum frequency
and a minimum frequency
30
m in
MAX
. The maximum frequency which can be associated to a
textured digital image is the frequency intrinsically generated by the regular presence of
pixels (maximum of details), whereas the minimum frequency is related to the physical
image dimensions31 (minimum of details). The scheme in Figure IV-F29 clarifies the
idea of image maximum and minimum frequencies.
30
In other words, the DFT associates a power value (i.e. a value of squared amplitude) at each frequency
comprised between the maximum and the minimum frequency.
31
If the image is rectangular, it is related to its biggest dimension.
222
PROCESSING
MAX
480 pixels
m in
640 pixels
Figure IV-F29 The maximum and minimum frequencies which can be associated to a digital
image (the dimensions of Visiovis images are 640 × 480 pixels and each pixel visualizes an area
having a maximum dimensions of about 83 m, as previously said in § IV-1.2.3).
Knowing the nature of the information that a FT can give about a textured digital
image, the image processing performed by the Matlab function normft.m is aimed to the
codification of the Visiovis images by the frequencies of their elementary textural units
(namely, spirals or twisted fluorescent volutes in a homogeneously black matrix). The
higher the main coding frequencies, the finer the texture of the digital image: an image
which is finely textured is coded by high frequencies, since the highest frequencies are
able to represent the finest details. We saw how the FT highlights any regular, repetitive
structure which appears in a digital image considered as a 2D signal, function of the two
spatial coordinates; we underlined, as well, that the FT is sensitive to image symmetry
and that the minimum frequency depends on the maximum physical dimension of the
image. Indeed, Visiovis images are rectangular (their biggest dimension is the diagonal
of the rectangle, whereas their smallest dimension is their height, i.e. 480 pixels) and
only circles are perfectly symmetric in all the directions, which means that only circles
can be frequentially isotropic. These observations let guess that a preliminary
processing step is necessary to get rid of any dimensional incongruity before calculating
the FT of our images. This is the reason why, before doing any other action, the
anamorphosis of each picture of a given series is operated, thus eliminating any problem
of aspect ratio of the rectangular images and “forcing” Visiovis images to be
frequentially isotropic. The Matlab function performs then the FT of each anamorphous
image, calculates the logarithm of the squared norm log F ( p, q) , subtracts the noise
previously calculated on a reference image, calculates the average amplitude for each
Antonella ESPOSITO
223
Chapter IV
frequency and plots the averaged values as a function of the frequency. Finally it
associates, to each image of a given sequence, the most representative frequency (i.e.
the mean frequency weighted by the intensities, in other words the frequency
statistically most probable) and plots such values as a function of the number image in
the sequence (i.e. the number of screw revolutions, as each camera acquires one image
per screw revolution). The temporal dependence is deduced by the screw rotational
speed – as the screw turns at 20 rpm ca, one revolution takes 3s and, thus, the cameras
acquire one image every 3s.
Interpretation’s key. Theoretically, a zero frequency should correspond to the
perfect mixture homogeneity; on the contrary, high frequencies reflect the presence of
regular and fine textural units.
In case of perfect miscibility. The lower the representative frequency, the more
homogeneous the mixture, the more efficient the distributive mixing will be.
In case of reduced miscibility. The higher the representative frequency, the finer
the texture, the more efficient (though incomplete) the distributive mixing.
Limitations. It is actually impossible to obtain a truly zero frequency since
images have, by definition, finite dimensions (indeed, only an infinite image could have a
zero minimum frequency). Hence, if a zero frequency is obtained, it should be certainly
interpreted as a relative value.
Moreover, the contrast between the mixture (never completely black) and the
screw profile (always completely black) produces a Heaviside (i.e. a step-like) function,
which corresponds to an artifactual permanent texture of the image.
An example of the plot which can be obtained by this image processing based on
the Discrete Fourier Transform of textured images is shown in Figure IV-F30 [1]. Once
again, several successive passages of the masterbatch containing the photo-active filler
in the field of the camera are easily recognizable, but the physical meaning of the
observed phenomena is not the same as the previous image processing (§ IV-3.1.1). By
224
PROCESSING
the way, the fact that the first peak rapidly lowers still indicates that the masterbatch is
gradually diluted by the neat PDMS and mixes up with the matrix.
Figure IV-F30 Typical result obtained by the image processing based on the Discrete Fourier
Transform (DTF) of textured Visiovis images – output of the Matlab function normft.m. As the
screw rotational speed is 20 rpm ca, the temporal dependence can be derived by multiplying the
number of screw revolutions by 3 (one screw revolution every 3s).
IV-3.1.3
Validation of data processing
As Moguedet and coworkers [4] developed an analytical model to describe the
flow of a viscous Newtonian fluid in the helical rectangular channel of a screw [7]
(validated by three-dimensional finite elements calculations in the Matlab environment),
we solicited Yves Béreaux to collaborate to validate our methods for data processing.
By adapting the Matlab code previously developed, Yves Béreaux generated a sequence
of images showing the deformation of a blob of tracing masterbatch into the helical
rectangular channel of Visiovis screw/barrel system. Under the hypothesis that the blob
is initially spherical, Béreaux represented, in the longitudinal section of the screw/barrel
system, a white circle on a black background: as the model is supposed to reproduce the
trajectories of a particle in the screw channel, it also allows to trace its position in a
Antonella ESPOSITO
225
Chapter IV
given longitudinal section of the screw channel as a function of time. By modeling the
initial spherical blob as a given number of particles disposed to form a filled circle,
Béreaux could reconstruct the deformation of the blob reproducing by computer
simulation the trajectories of the particles but rather tracing their reciprocal distances in
conditions of pure recirculation, i.e. under the hypotheses that:
 molecular diffusion can be neglected32;
 the global flow rate is nil and the mixing of the blob of tracing masterbatch
with the neat fluid occurs in a single screw channel, viz. in the space confined between
two adjacent flights, the screw root surface and the barrel surface33. Some of the images
obtained by this method are shown in Figure IV-F31 (reproduced with the permission of
the author). We validated only the second method for data processing – the one based
on the DFT of textured images – since the first one, based on the standard deviation of
image luminosity, is more intuitive and its principle is easier to understand. In addition,
the hypothesis made about the absence of molecular diffusion makes the images
generated by computer simulation rather inadequate to be compared with the images
acquired by Visiovis: a comparison of Figure IV-F20 and Figure IV-F31 reveals that the
obtained images cannot represent the gradients of luminosity (in terms of brightness and
fuzziness of the white spirals on the black background) which, on the contrary, are
unavoidable in any image acquired during the experiments. Indeed, this difference could
affect also the validation of the second method (it actually does, as we’ll show later on),
but certainly to a lesser extent. The result obtained by the DFT method on the numerical
images designated as the reference is shown in Figure IV-F32 (a): this curve has to be
compared to the first part of the graph in Figure IV-F30 (reported in Figure IV-F32 (b)
to ease the comparison), as the curve in its entirety actually represents an experiment
which includes three passages of the tracing blob in front of the camera (recirculation
operated by the tube for closed circuit34).
32
This hypothesis is deduced from the absence of fuzziness from numerical images: Figure IV-F20 shows
that this hypothesis is unrealistic for the system observed by Visiovis. Even if slow, molecular diffusion
should not be neglected in real systems. Besides, high concentrations of the tracing masterbatch produce a
significant diffusion of the laser source, which definitely is the main cause of dizziness (see § IV-4.2).
33
These conditions could be approximately reproduced experimentally by duly tuning the back pressure:
indeed, back pressure facilitates the recirculation flow and decreases the global flow rate (§ IV-4.3).
34
A description of the actual configuration of Visiovis has been given in § IV-1.3 (Figure IV-F17).
226
PROCESSING
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
…30
…35
…40
…45
…50
Figure IV-F31 Sequence of numerical images generated by Yves Béreaux (by means of a code
previously developed [7] and suitably adapted to our requirements), showing the deformation of
a spherical blob of tracing masterbatch in Visiovis screw channel, under the hypothesis of pure
recirculation and absence of molecular diffusion. These images validated the data processing
based on the DFT of textured images. Images reproduced with the author’s permission.
Antonella ESPOSITO
227
Chapter IV
(a)
(b)
Figure IV-F32 Comparison of the typical results obtained by the processing based on the DTF
method (Matlab function normft.m) applied to (a) the images generated by numerical simulation
(Figure IV-F31) and (b) the images acquired during Visiovis experiments (Figure IV-F20). The
comparison validates data processing but shows some slight divergences – surely based on the
different origin of the processed images (more details in the text).
The only difference in Figure IV-F32 is that the average representative frequency
as a function of the image number for the images generated by computer simulation (a)
is characterized by two slope values, whereas the homologous curve obtained for the
images acquired by Visiovis (b) presents a slope which varies continuously and assumes
at least three different values. By the way, one could deliberately decide to fit the curves
obtained by processing acquired images (Figure IV-F32 (b)) with the model revealed by
the curve obtained with numerical images (double-slope curve, Figure IV-F32 (a)) – so
that two main parameters35 could be deduced and used to compare different systems.
A further validation of the DFT method for Visiovis data processing is provided
by the frequency distribution obtained for each numerical image of the reference series
(Figure IV-F33)36. A visual explication of the features appearing in the graph of Figure
IV-F33 is given in Figure IV-F34. At the beginning, the peak represents the minimum
35
Indeed, it is the results obtained applying the DFT data processing to the ideal case of numerical images
that proved that mixing could be probably described by two parameters: the slope values of the curve
showing the average representative frequency as a function of the number of screw revolutions.
36
The color scale is just an arbitrary scale which shows only the relative “importance” of all the possible
frequencies present in each image of the reference series.
228
PROCESSING
frequency which could ever be due to morphological features – related to the maximum
dimension of the blob (i.e. initial diameter) (see Figure IV-F34 (a)). Since the blob gets
stretched and thinner, the white circle is gradually transformed in a lengthening lamella
and its characteristic dimension decreases (as expected for a laminar flow, the thickness
of the striations decreases): the width of the features in the frequency distribution graph
increases (Figure IV-F34 (b)) as shown by the boundary identified by line C. Moreover,
as the lamellae stretch and form spirals because of recirculation, the statistical number
of intersections observed in any cross section increases and their frequency of repetition
increases as well: an additional component in the frequency distribution appears (Figure
IV-F34 (c)) producing the peak represented by line B. Indeed, any regular distribution
of white features (spiral intersections) on a black background produces, in the frequency
domain, a Dirac impulsion whose position varies with the distance (and thus, indirectly,
with the number and thickness) of the spirals – in particular, as their reciprocal distance
decreases (i.e. as their number increases and their thickness decreases), the DFT gives a
peak which shifts towards higher frequencies (Figure IV-F34 (d)): line B bends towards
higher frequencies. Concurrently, a further phenomenon occurs: the augmentation and
thinning of the lamellae gradually expand the percentage of occupation of the black
background by the white features. A better occupation of the space by repeating features
is visualized, in the DFT frequency distribution, by an increased intensity of the peak
associated to the minimum frequency (see Figure IV-F35), corresponding to line A. This
phenomenon helps understanding why, in the graphs of Figure IV-F32, the average
frequency diminishes in spite of the appearance of higher-frequency features in the DFT
domain and of their further shifts towards higher frequencies: like any averaged value,
the representative frequency depends on the whole distribution. An increased intensity
of line A (Figures IV-F33 and IV-F35) indicates an improvement of global distributive
mixing (repartition of the striations), whilst the appearance and gradual shift of peaks at
higher frequencies (lines B and C) represent an improvement of local distributive
mixing (striation thickness).
Antonella ESPOSITO
229
Chapter IV
A
B
C
Figure IV-F33 Frequency distribution obtained for the numerical images (Figure IV-F31) by
the DFT method (§ IV-3.1.2). The explications given in the text are illustrated in Figure IV-F34.
1 intercept
initial blob
(a)
1 intercept
thinner
striation
decreasing width
increasing width
(b)
2 intercepts
(c)
7 inter.
increasing frequency
shift towards
higher frequencies
(d)
Figure IV-F34 Visual explication of the features in the graph of Figure IV-F33.
230
PROCESSING
A
B
C
low
frequencies
image number
high
Figure IV-F35 Three-dimensional visualization of the frequency distribution shown in Figure
IV-F33. Note that line B undergoes just a frequency shift, whereas line A increases in intensity.
IV-3.2
Videos
Once the single images extracted and isolated from the sole *.bmp file recorded
by Visiovis acquisition circuit (§ IV-3.1), the obtained images can be considered (since
they are!) as the frames of a temporal sequence and, thus, used to reconstruct a video.
This operation can be executed by running the Matlab function video.m (available in the
Appendix).
This function also generates a montage of the video, i.e. a panel visualizing at a
glance all the frames used for the reconstruction. The montage is particularly interesting
when the video is reconstructed from the windows cutback around the channel section,
as shown on the example in Figure IV-F36.
Antonella ESPOSITO
231
Chapter IV
Figure IV-F36 Example of montage of a video reconstructed from the windows cutback around
the channel section – one of the output of the Matlab function video.m. Acquisition done by the
second camera in the dark after the injection of a masterbatch containing C30B 0.25MC RhP.
IV-3.3.
Fluorescence spectra
The easiest way to visualize the regularly acquired in-line fluorescence emission
spectra as a function of processing time is to convert the temporal sequence of (intensity
of fluorescence emission vs. frequency) curves in a 3D shaded surface plot to show the
results on a rectangular region delimited by the processing time [s] and the wavelength
[nm], as shown in Figure IV-F22. The Matlab function used for the visualization of the
fluorescence spectra is called spctr.m and is available in the Appendix.
If the images (and the results of image processing) can be used to evaluate the
distributive mixing into the screw/barrel system, the fluorescence spectra may rather
inform about dispersive mixing – since the emission signature of the fluorescent dye
232
PROCESSING
used to photo-functionalize clay is sensitive to any change of its molecular environment
due to clay intercalation and/or exfoliation, and such morphological changes are a direct
consequence of dispersive mixing. Manifestly, all the detection systems the Visiovis is
equipped with are complementary and useful to characterize nanocomposite processing.
IV-4
SOME EARLY RESULTS
Conscious that the development of a tool for the visualization of nanocomposite
processing, along with the conception of brand new detection and/or characterization
systems, are far from being easy, we kept testing Visiovis with different systems and in
different conditions (when and if possible), hopeful to recognize its advantages and its
limitations. Keeping in mind that any test, by definition, may give negative results (or,
even, may not give any result), we performed some experiments in order to evaluate:
 the behavior of three different photo-active lamellar fillers – namely C30B
0.25MC RhP, C10A 0.25MC RhP and C15A 0.25MC RhP37;
 the possibility of using Visiovis to perform conventional tracing experiences –
that is, injecting a masterbatch containing a given amount of the pristine commercial
clay and a smaller amount of the same clay previously rendered photo-active;
 the influence of the back pressure on the visualization executed by Visiovis –
thanks to an additional van capable of regulating the flow in the closed circuit.
IV-4.1
Comparison of different photo-active lamellar fillers
While dealing with the modification of Visiovis configuration and planning how
to perform the first visualization tests, we dwelled on clay modification since we needed
to prepare a suitable photo-active lamellar filler to be used with Visiovis – coherently
with the main objective of our work. In Chapter II we detailed the actions we went
through to establish an efficacious (and efficient) photo-functionalization protocol and,
in Chapter III, we characterized four inorganic/organic complexes that we succeeded to
37
More details about the preparation and the characterization of the three photo-active lamellar fillers are
available in Chapters II and III.
Antonella ESPOSITO
233
Chapter IV
render photo-functional by cation exchanging four commercial clays with a rhodamine
dye. However, we remind that during the tests performed to establish an appropriate
experimental protocol for Visiovis in its new configuration38, we realized that CNa+
0.25CEC RhP couldn’t be used in the visualization conditions imposed by Visiovis. In
conclusion, for the moment we disposed of three different photo-active lamellar fillers,
namely C30B 0.25MC RhP, C10A 0.25MC RhP and C10A 0.25MC RhP. It is with
these photo-active lamellar fillers that we performed our first visualization experiences
– respecting the experimental protocol previously established. The videos showing the
three experiences are available in the multimedia CD-Rom accompanying the PhD
manuscript.
As expected, images and videos are captivating but really can’t help interpreting
the results of the visualization experiences. Figure IV-F37 and Figure IV-F38 show the
trends revealed by the image processing previously described and based, respectively,
on the integral standard deviation of the image luminosity (§ IV-3.1.1) and on the DFT
of textured images (§ IV-3.1.2).
In all the curves of Figure IV-F37 the passages of the masterbatch containing the
photo-active filler (0.25% wt) in the field of the camera are easily recognizable. During
the first passage (which occurs more or less at the same time after the injection of the
masterbatch – unsurprisingly, since the pumping effect of the screw is the same for all
the samples) the C30B 0.25MC RhP appears less homogeneously distributed than the
other samples, as its integral standard deviation is higher meaning that there are intense
variations of luminosity in the visualized channel section. We can also observe that the
first peak for all the samples is, actually, a double peak: this reflects the fact that the
fluorescent masterbatch doesn’t proceed as a block but is stretched, plied and deformed
by the action of the screw, thus at the moment of passing in the field of the acquiring
camera (which is the second one, thus closer to the middle of the screw rather than to
the point of injection) several of its portions arrive with a slight temporal shift. Anyway,
this curve doesn’t inform about the actual morphology of the mixture at the right instant
of the acquisition (the other image processing will probably do). After this first passage,
38
See § IV-2.
234
PROCESSING
the standard deviation of luminosity of course decreases, then increases again at the
moment of the second passage in front of the camera, after a complete recirculation. As
expected, the second peak is lower than the first one, witnessing the homogenization of
the masterbatch with the neat PDMS. One could notice that at the first passage the most
similar behaviors were those of C10A 0.25MC RhP and C15A 0.25MC RhP; at the
second passage, on the other hand, C30B 0.25MC RhP got closer to C10A 0.25MC RhP
whereas C15A 0.25MC RhP makes the difference. First of all, in the case of C30B and
C10A fillers, even the second peak seems to be double while the second peak of C15A
is clearly single and broad; besides, the whole curve of C15A is constantly lower than
the other two curves. These early results don’t show any major difference in distributive
mixing for different photo-active lamellar fillers, even if some slight details can anyway
be perceived.
Figure IV-F37 Processing based on the integral standard deviation of luminosity. Comparison
of different photo-active fillers (C30B 0.25MC RhP, C10A 0.25MC RhP, C15A 0.25MC RhP)
following the experimental protocol previously established (rotational speed 20 rpm ca).
Antonella ESPOSITO
235
Chapter IV
Figure IV-F38 Processing based on the DFT of textured images. Comparison of different
photo-active fillers (C30B 0.25MC RhP, C10A 0.25MC RhP, C15A 0.25MC RhP) following
the experimental protocol previously established (rotational speed 20 rpm ca). Inside: y-zoom of
the background plot. 75 is the arithmetical mean value of frequency (reference max value 150).
In all the curves shown in Figure IV-F38 the two passages of the masterbatch in
the visual field of the camera are easily recognizable as well, and occur at the same
moment as it has been previously detected (Figure IV-F37). In the frequency-domain,
the image processing produces an additional feature whose explanation is in the
processing itself. A point having a frequency of 75.00 is present in all the curves and is
the same for all the photo-active fillers: indeed, it doesn’t mean anything as it just
represents the image chosen as the reference (i.e. the image just before the arrival of the
very first portion of the fluorescent masterbatch in front of the acquiring camera) and,
thus, it corresponds to the sole image which is really, completely black (for the
background numerical noise is spotlessly subtracted). Therefore, we zoomed to the
upper portion of the curves and we showed them again in the inner graph in Figure IV-
236
PROCESSING
F38. It is rather upsetting (even if probably expected) to find, in these curves, most of
the features previously observed and commented about Figure IV-F37. We’ve already
explained, however, that the physical reasons of such observed phenomena aren’t the
same – and this can be directly deduced from the fact that the two image processing
don’t derive from the same intuition. We preferred think, then, that no significant
difference exist between the mixtures processed with the three different photo-active
lamellar fillers – at least not in the conditions offered by Visiovis (matrix, screw profile,
speed, temperature). At least, these early results have the merit of illustrating Visiovis
potentiality.
With reference to the in-line fluorescence spectra: the data acquired during these
experiences with the three photo-active lamellar fillers have been previously shown in
Figure IV-F22. Effectively, no significant differences can be detected by comparing the
fluorescence emission spectra either – apart the behavior of C15A 0.25MC RhP, which
looks slightly different. Finally, we could just observe that the three photo-active fillers
seem to be more similar in terms of “morphology of the mixture” (Figure IV-F38) than
in terms of “distribution into the channel section” (Figure IV-F37).
IV-4.2
Comparison of different amounts of filler
In preparation of the “qualitative calibration” of Visiovis detection systems 39 we
announced that we were planning to focus essentially on the first photo-active lamellar
filler produces by the photo-functionalization protocol described in Chapter II. The
results obtained by comparing the three different photo-active lamellar fillers we
disposed of convinced us to continue testing the system only (at least for the moment)
with C30B 0.25MC RhP. Manifestly, the factors influencing these early results are
several and not always easy to control. We should remind, here, that owing to the
calibration, we found that the optimum concentration of the photo-active lamellar filler
in the masterbatch for the injection in Visiovis screw/barrel system is 0.25% wt. We
decided, however, to test the visualization capability of Visiovis with masterbatches
39
The calibration of the detection system has been detailed in § IV-1.2.4.
Antonella ESPOSITO
237
Chapter IV
containing different amounts of filler. As we didn’t want to change the optimum
concentration of photo-active filler, we simply prepared three masterbatches following
the procedure previously described but adding, besides the photo-active filler, a given
amount of the corresponding pristine clay. Apart from this, we didn’t change the
experimental protocol. Briefly, we tested the system with the following masterbatches:
 Siliconöl M10000 + C30B 0.25MC RhP (0.25% wt)
= total amount of filler 0.25% wt
 Siliconöl M10000 + C30B 0.25MC RhP (0.25% wt) + C30B (0.75% wt)
= total amount of filler 1% wt
 Siliconöl M10000 + C30B 0.25MC RhP (0.25% wt) + C30B (2.75% wt)
= total amount of filler 3% wt
We must admit that these tests were risky: the calibration of the system already
revealed that an excessively high concentration of filler (whether photo-active or not)
can cause some optical problems, since as the concentration increases the mixture with
PDMS becomes less and less transparent and the penetration depth of the laser sheet
rapidly decreases. Nevertheless, we thought that it could be worthy trying. Figure IVF39 shows the trends revealed by both our image processing approaches.
The integral standard deviation of luminosity doesn’t show any particular trend
in relation with the presence of the pristine clay and to the fact that we made its amount
vary. The only remarkable points would be the shape of the first peak obtained for the
injection of C30B/C30B 0.25MC RhP 2.75/0.25% wt (i.e. the masterbatch containing
the highest total amount of filler), as well as the shape of its second peak, which is more
similar to a single than to a double peak. Otherwise, adding an amount of pristine clay 3
times higher than the amount of the photo-functionalized clay (C30B/C30B 0.25MC
RhP 0.75/0.25% wt) doesn’t significantly change the shape of the curve – which is a
rather good conclusion in the future eventuality of using Visiovis to perform real tracing
experiences, viz. experiences in which only a fraction of the filler acts as a tracer.
The same observations can be made about the results of the image processing
based on the DFT of textured images (Figure IV-F39, bottom).
238
PROCESSING
Figure IV-F39 Processing based on the integral standard deviation of luminosity (top) and on
the DFT of textured images (bottom). Comparison of three masterbatches containing different
total amounts of filler (0.25%, 1% and 3% wt) but always the same amount of the photo-active
filler C30B 0.25MC RhP (0.25% wt). Injection executed following the standard experimental
protocol (rotational speed 20 rpm ca).
Antonella ESPOSITO
239
Chapter IV
We previously stated that no significant differences could be perceived upon the
addition of different amounts of pristine clay to the initial masterbatch (0.25% wt photoactive filler). Indeed, the fact that nothing seems to change (or even any little change we
could discover) may have an explanation which cannot be found uniquely in the curves.
This is a typical example of situation in which, even if we’re aware that Visiovis images
and videos can’t really provide quantitative information on our experiences, we realize
that they efficiently support the interpretation, e.g. by suggesting the causes which could
possibly be attributed to ambiguous features present on the curves.
1st camera
2nd camera
(a)
(b)
(c)
Figure IV-F40 Selected images acquired by the first (on the left) and the second camera (on the
right) after the injection of C30B/C30B 0.25MC RhP 0.00/0.25% wt (a), 0.75/0.25% wt (b) and
2.75/0.25% wt (c), respectively. A zoom is made on the processed image window.
240
PROCESSING
The images and the videos reconstructed for the visualization experiences we’re
trying to interpret actually reveal the significant consequences of adding an increasing
amount of pristine clay to the standard masterbatch – containing the optimum amount of
filler. Here we reported some selected frames (Figure IV-F40) to support our comments,
but the videos are also available in the CD-Rom accompanying the PhD manuscript.
The uncertainties claimed at the beginning of this paragraph (and justified by the
observations made during the calibration of the detection systems) concretized, and with
the help of the visualization experiences here presented we could finally proved them.
The concentration of filler in the tracing masterbatch has to be attentively controlled and
reduced, when possible, for the highest the concentration of filler, the worst the optical
clarity of the system will be.
(a)
(b)
(c)
Figure IV-F41 In-line fluorescence spectra acquired after the injection of C30B/C30B 0.25MC
RhP 0.00/0.25% wt (a), 0.75/0.25% wt (b) and 2.75/0.25% wt (c), respectively.
Antonella ESPOSITO
241
Chapter IV
By the way, at least theoretically, the in-line fluorescence spectra aren’t affected
by such concentration issues: when a tracing experiment has to be performed, in which
a higher concentration of filler is supposed to be used, spectrofluorimetry is a valuable
alternative to the image acquisition and processing (Figure IV-F41).
IV-4.3
Regulation of the back pressure
The last visualization test we performed on Visiovis was aimed to verify whether
our tool is capable or not to detect the effect of the application and regulation of a back
pressure to the system. In reality, any screw/barrel system is subjected to an intrinsic
back pressure due to the presence of a restrained section at the exit of the system. The
back pressure represents an obstacle to the flow – it increases the residence time of the
fluid into the screw/barrel system and is partially responsible of the recirculation within
the screw channel. Sometimes, the back pressure has to be increased to accentuate these
phenomena and consequently ameliorate the quality of mixing.
Keeping in mind the relevance of such processing parameter, we performed three
tests to visualize the effects of an eventual variation of the back pressure on mixing. We
preferred varying this parameter (instead of the rotational speed of the screw and/or the
viscosity of the model fluid) since, for several reasons, we estimated that it was the only
factor capable of influencing the mixing process in the conditions imposed by Visiovis.
Indeed, PDMS is a Newtonian fluid40 and the screw profile we dispose of41 isn’t the
best for mixing.
To increase the back pressure (and also to be able to regulate it), we equipped the
existing tube for closed circuit of an additional van, which doesn’t alter the circuit if
fully opened but can almost completely arrest the flow when fully closed. Besides, any
intermediate position is also possible. With such additional van, we could perform three
tests in the presence of different back pressures, namely: (1) a test in which the van is
fully open (100% OPEN), (2) a test in which the van is half open (50% OPEN) and (3) a
40
Newtonian fluids are characterized by a value of viscosity which doesn’t depend on the shear rate.
We remind, here, that Visiovis geometrical parameters are comparable to the typical design parameters
of the meter section of industrial devices. The meter section of a screw isn’t, by definition, the most
suitable for mixing.
41
242
PROCESSING
test in which the van is fully closed (100% CLOSE). All these tests have been carried
out, as usually, by injecting a masterbatch (PDMS Siliconöl M10000 + 0.25% wt C30B
0.25MC RhP) prepared as previously described42.
Figure IV-F42 show the results of the tests 100% and 50% OPEN. We couldn’t
show the results of the three tests all together, for the test 100% CLOSE lasted 9 times
longer than the other tests. The longer duration of the last test is quite obvious, as 100%
CLOSE means that the van almost stops the flow and accentuate to the maximum extent
the recirculation within the screw channel, as the corresponding video shows (available
in the CD-Rom accompanying the PhD manuscript). It’s interesting to observe that,
when the van is half open (50% OPEN), the first peak of the curve (log integral std dev
of luminosity vs. time) doesn’t really change, but the second one looks smoothed and
the whole curve is markedly lowered. However, the fact that the van is half opened must
have produced only a slight increase of the back pressure, because the residence time of
the fluid into the screw barrel system is basically the same (the position of the peaks
hasn’t changed). The same comments can be made for the curve (average representative
frequency vs. time).
On the contrary, when the van is fully closed (100% CLOSE) (Figure IV-F43)
the back pressure is at its greatest value and the prevalent phenomenon is the
recirculation within the screw channel: the fluid proceeds very slowly and has enough
time to mix up with the neat matrix before arriving in the field of the acquiring camera.
This is the reason why the curves for the last test are completely different than the
curves for the former ones. The limits of mixing are achieved when the curves reach
their asymptote. Note that, apart from the time scale, these graphs have the same scale
as the graphs shown in Figure IV-F42 to facilitate the comparison.
For all the performed tests, the fluorescence spectra reflect the same behaviors
observed by the cameras.
42
See § IV-2.
Antonella ESPOSITO
243
Chapter IV
Figure IV-F42 Processing based on the integral standard deviation of luminosity (top) and the
DFT of textured images (bottom), respectively. The masterbatch contains 0.25% wt of a photoactive filler (C30B 0.25MC RhP). The position of the van for the regulation of back pressure is:
fully open (100% OPEN) and half open (50% OPEN). Rotational speed 20 rpm ca.
244
PROCESSING
Figure IV-F43 Processing based on the integral standard deviation of luminosity (top) and the
DFT of textured images (bottom), respectively. The masterbatch contains 0.25% wt of a photoactive filler (C30B 0.25MC RhP). The position of the van for the regulation of back pressure is:
fully close (100% CLOSE). Rotational speed 20 rpm ca. Note the duration of the test (45 min).
Antonella ESPOSITO
245
Chapter IV
IV-5
CONCLUSIONS
In this chapter we presented Visiovis, an original and innovative tool suitable for
visualizing viscous fluids flowing in a geometrically complex system – more precisely a
screw/barrel system. After a brief summary of Visiovis origins – who assembled it, for
which applications and in which initial configuration – we went through all the steps we
had to traverse to suitably modify its configuration in order to adapt it to our new needs.
Indeed, we were planning to adapt the existing tool to the analysis of nanofiller
dispersion/distribution mechanisms in molten thermoplastic polymers or, eventually, in
uncured thermoset resins. To attain our objectives, we certainly had to change Visiovis
original configuration – but we decided to do it steadily for both practical and economic
reasons. The choice of gradually but incessantly change Visiovis configuration made us
work in a situation in constant evolution, being ceaselessly faced to new and unexpected
problems to be solved. Notwithstanding, we dared developing two detection systems
and tried to exploit the acquired data as much as possible. In this chapter we described
how we performed the visualizations, how the CCD cameras and the spectrometer are
integrated on Visiovis, how we collected and processed the experimental data. All the
results shown in this chapter required a lot of work and sometimes didn’t result as
expected. Our main objective was, realistically, to increase Visiovis potentialities and to
suggest a further, possible employment for a tool which has already demanded large
efforts. Have we fulfilled such requirements?
In the next and last chapter we’ll rapidly summarize the technical progresses
already achieved on Visiovis and we’ll discuss of some possible further ameliorations.
246
PROCESSING
IV-R REFERENCES
[1] Esposito A, Balcaen J, Duchet-Rumeau J, Charmeau JY. Visiovis: monitoring nanofiller
dispersion/distribution in molten polymers. JEC Composites Magazine 2008, 41, 67-71.
[2] Gao, F. Clay-polymer composites: the story. Materials Today 2004, November, 50-55.
[3] Liu, J., Boo W.-J., Clearfield A. et al. Intercalation and exfoliation: a review on
morphology of polymer nanocomposites reinforced by inorganic layer structures.
Mater. Manuf. Processes 2006, 20, 143-151.
[4] Moguedet M. Développement d'un outil d'aide à la conception et au fonctionnement
d'un ensemble vis-fourreau industriel – Application à l'injection de thermoplastiques
chargés fibres de verre longues. Thèse. Lyon: INSA de Lyon, 2005, 124 p.
[5] Esposito A, Charmeau JY, Duchet-Rumeau J. Analyse des mécanismes de dispersion de
nanocharges dans un polymère fondu. Conséquences sur la morphologie de
nanocomposites obtenus par injection. CR des 15èmes Journées Nationales AMAC sur
les Composites (JNC15), 361. Marseille, 2007, 1216 p. ISBN: 978-2-87717-090-1.
[6] Agassant J.-F., Avenas P., Sergent J.-P. et al. La mise en forme des matières plastiques.
3rd Ed. Paris: Tec & Doc Lavoisier, 1996, 640 p. ISBN: 9782743000165.
[7] Béreaux Y., Moguedet M., Raoul X. et al. Series solutions for viscous and viscoelastic
fluids flow in the helical rectangular channel of an extruder screw. J. Non-Newtonian
Fluid Mech. 2004, 123 (2-3), 237-257.
[8] Béreaux Y., Charmeau J.Y., Moguedet, M. A simple model of throughput and pressure
development for single screw. J. Mater. Process. Technol. 2009, 209 (1), 611-618.
[9] Ottino J.M. The kinematics of mixing: stretching, chaos, and transport. 1st Ed.
Cambridge: Cambridge University Press, 1989, 364 p. ISBN 0-521-36878-2.
Antonella ESPOSITO
247

Visualisation de l`écoulement dans un système vis

Transcription

Similar documents

bis tristar - LUCKINSlive

MAMAC SYSTEMS® Convinced that all temp sensors are same?

File

Power Lead screw for 7x12 lathes

Model TF Shaftless Screw Conveyor

Hand Balancing Trainer Project

Feedscrews - Davis

Brown Bess Musket Field Cleaning 101

Intrafuse Mini 14/Mini Thirty Rifle System