Particle Size Distribution II - ACS Publications - American Chemical

Chapter 5

On-Line Latex Particle Size Determination by Dynamic Light Scattering Design for an Industrial Environment David F. Nicoli , Theodora Kourti , Paul Gossen , Jau-Sien Wu , Yu-Jain Chang , and John F. MacGregor

Downloaded by NORTH CAROLINA STATE UNIV on August 2, 2012 | http://pubs.acs.org Publication Date: September 24, 1991 | doi: 10.1021/bk-1991-0472.ch005

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Nicomp Particle Sizing Systems, 75 Aero Camino, Santa Barbara, CA 93117 Department of Chemical Engineering, McMaster University, Hamilton, Ontario L8S 4L7, Canada 1

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The use of on-line dynamic light scattering (DLS) in monitoring latex particle growth in a continuous pilot scale reactor isreported.The weight average diameter of the latex is measured simultaneously using on-line turbidimetry and theresultsfrom the two methods are compared. A new design for the on-line DLS apparatus involving the use of aremotesensor andfiberoptics, for a more robust performance in industrial environments, is described. D y n a m i c light scattering ( D L S ) also k n o w n as photon correlation spectroscopy ( P C S ) has been w i d e l y used during the past twenty years for the determination o f the mean particle size o r the particle size distribution ( P S D ) o f suspensions w i t h particle diameters i n the submicrometer size range (1-16). T h i s technology was confined exclusively to off-line quality control m e a surements i n laboratories. H o w e v e r , the need for on-line measurements has increased recently, especially i n the latex industry where the P S D determines the p h y s i c a l properties and therefore the end use o f the latex p r o d u c t Recently, a device for automatic sample acquisition and d i l u t i o n was developed, designed to interlace w i t h a D L S based particle s i z i n g instrument, permitting the on-line use o f the method to monitor particle growth during latex production. Results from an on-line application o f D L S to a batch latex reactor were shown i n o u r previous publications (17.18) where an average particle diameter was monitored during the production o f a polyvinyl acetate) latex w i t h a narrow particle size distribution. With a short time o f data collection the D L S method c a n provide reasonable size information for such narrow distributions (12). B y contrast to batch reactors the P S D s o f latexes produced i n continuous reactors are usually broad (sometimes b i m o d a l o r multimodal) and longer times o f data collection are required to analyze these more c o m p l e x distributions. Furthermore, application o f the D L S method to continuous reactors requires continuous use o f the sampling system for several hours (or days), without clogging o f the components o f the f l u i d circuit. Here w e test the capability o f this on-line D L S system to function successfully i n monitoring latex particle growth i n a continuous pilot scale reactor. Results are s h o w n for 10 hours o f continuous operation w i t h samples withdrawn every 10 m i n for particle size analysis b y D L S . T h e particle growth was also monitored independently using on-line turbidimetry, and results from the t w o methods are compared. I n both the batch and continuous applications the automatic sampler diluter was used i n conjunction w i t h a m o d i f i e d N i c o m p 370/Autodilute S u b m i c r o n Particle S i z e r ( N I C O M P Particle S i z i n g Systems, Santa Barbara, C A ) . Instruments used for on-line industrial applications must be robust and able to endure harsh environments. W e also report here a new design for the D L S apparatus used for on-line particle size determination w h i c h i s better suited f o r industrial environments. T h i s design involves the p h y s i c a l separation o f the sampling and sensing system ( w h i c h includes sampling 0097-6156/9iyO472-O086$06.00/0 © 1991 American Chemical Society

In Particle Size Distribution II; Provder, T.; ACS Symposium Series; American Chemical Society: Washington, DC, 1991.

5. N I C O L I E T A L .

On-Line Determination by Dynamic Light Scattering

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valves, autodiluter, laser source and scattering cell) from the photomultiplier detector, autocorrelator and computer that controls the system and computes the particle size distribution. T h e sampling and sensing system is located near the reactor i n the plant w h i l e the central controller is i n the analytical laboratory; the two systems communicate w i t h fiber optics.


Theoretical Background O f D L S D y n a m i c light scattering is used to measure the size o f submicrometer particles suspended i n a l i q u i d m e d i u m . T h e suspension is illuminated b y a beam o f light and the scattered light intensity is measured as a function o f time. T h e suspended particles diffuse i n random w a l k fashion due to collisions w i t h molecules o f the surrounding l i q u i d m e d i u m ( B r o w n i a n motion). A s a result, w h e n the c o l l o i d a l dispersion is illuminated b y a coherent light source the phases o f each o f the scattered waves (arriving at a detector at fixed angle) fluctuate randomly i n time due to the fluctuations o f the positions o f the particles responsible for scattering. Because these waves mutually interfere, the net intensity o f the scattered light, I(t), fluctuates randomly i n time around a mean value. T h e technique makes use o f the fact that the time dependence o f the intensity fluctuations (calculated from the autocorrelation function o f the scattered intensity) c a n be related to the translational diffusion coefficient o f the particles and then to the particle size through the Stokes-Einstein equation. Details o f the theory o f D L S and the experimental setup and examples o f applications o f the technique c a n be found i n a number o f texts (1-4). Here w e present o n l y a brief review. T h e autocorrelation function G \f) o f the scattered light intensity c a n be expressed i n terms o f the normalized first order autocorrelation function, g ^ t ) Q

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GV)

= s y m b o l indicates a running sum o f products taken at different times, t. F o r t ^ o o , G ( « > ) = , w h i c h is the square o f the average scattered intensity and it is equal to the baseline o f the autocorrelation function, B . (1) p is an instrument related constant ( ( k j k l ) . F o r suspensions o f uniform particle size, g (0 is a simple exponentially decaying function o f t': a)

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* V ) = exp(-rr)

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T h e decay constant r is proportional to the translational diffusion coefficient D b y : t

(3)

T = DK t

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where K i s the scattering wavevector, w h i c h depends o n the wavelength o f the light source ( X J , the solvent refractive index (n) and the scattering angle, 6: K=4nn

sin(e/2y^

(4)

F o r random diffusion o f non-interacting particles, the single particle diffusion coefficient (D,) i s obtained from the above equations. I f the m e d i u m is a newtonian fluid, and the particles are spheres, D , can be related to die hydrodynamic radius R v i a the Stokes-Einstein equation: (5)

R=kT/6m\D

t

where k i s B o l t z m a n n ' s constant, T i s the temperature (°K) and T| is the shear viscosity o f the m e d i u m . T h u s , the particle size o f a monodisperse suspension c a n be easily obtained from the measured autocorrelation function v i a equations (1) to (5). F o r suspensions w i t h broad u n i m o d a l or w i t h m u l t i m o d a l distributions, the conversion o f the autocorrelation data to P S D is a relatively difficult task and remains an area o f active research (4-14). F o r a polydisperse suspension, g ( f ) is a weighted sum o f exponentially decaying functions, each o f w h i c h corresponds to a different particle diffusivity w i t h decay constant r . (1)

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* (O= f " F ( n e x ( - n y r Jo 0)

P

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(6)

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P A R T I C L E S I Z E D I S T R I B U T I O N II

F ( T ) is the normalized distribution o f the decay constants o f the scatterers i n the suspension. T h e problem o f obtaining the P S D from the raw data, i n effect, reduces to s o l v i n g equation (6) for F(D. an i l l conditioned problem. A number o f algorithms for inverting this equation have been proposed (4-13). There have been also several attempts to improve the resolution o f the method (10.11.14). T h e approach used w i t h significant success i n commercially available instruments ( N i c o m p 370 and others) is based o n a L a p l a c e transform inversion o f g ' (0 using a nonlinear least squares procedure ( w i t h a n o n negative constraint). A review o f most o f the available algorithms for the determination o f F(D from D L S data and an evaluation o f their performance for suspensions o f unimodal and b i m o d a l distributions c a n be found i n Stock and R a y (12). T h e particle size distribution o f the suspension, o n mass o r number basis c a n be easily calculated from the estimated distribution o f the decay constants (3.4.14). Fortunately, i n practice one often encounters simple unimodal particle size distributions for w h i c h F(H i s approximately Gaussian i n shape. F o r these cases the m u c h simpler method o f cumulants analysis Q f i ) usually provides a good fit to the autocorrelation function data, a) y i e l d i n g moments o f the distribution F ( T ) . In this approach, In g (0. (a linear function for a monodisperse sample) is fitted to a quadratic o r cubic function o f t/. T h e advantage o f the cumulants analysis is that it is computationally fast and settles rapidly w i t h i m p r o v i n g statistical accuracy i n the autocorrelation function. T h e method gives very accurate results for decay distributions w i t h negligible h i g h order central moments (15). C o m m e r c i a l l y available D L S instruments usually employ two approaches to convert the autocorrelation data to P S D : i) the method o f cumulants and i i ) an algorithm that inverts equation (6), solves for ¥(T) and yields an estimate o f the f u l l particle size distribution. T h e N i c o m p 370 computes distributions u t i l i z i n g both o f these approaches and selects one o f the computed d i s tributions based o n a goodness o f fit criterion (19). T h e first approach is termed Gaussian analysis and the second, N i c o m p distribution analysis. T h e former uses a second order cumulants fit to the data. A chi-squared fitting error parameter (x) is used to test whether this assumption is reasonable. T h e analysis is a two parameter fit, to estimate the mean diffusivity and a coefficient o f variation (measure o f the variance) o f the distribution o f the diffusion coefficients. T h e mean diffusivity is converted to an intensity weighted mean diameter ( D ^ ) . T h e resulting distribution o f diffusion coefficients is converted to a particle size distribution based o n intensity, v o l u m e (mass), o r number weighting and the corresponding average diameters are calculated. T h e N i c o m p distribution analysis employs an algorithm based o n a variation o f Provencher's technique (7-9). T h i s approach makes no assumption about the shape o f the distribution and utilizes a non-linear least squares parameter estimation. It requires longer times to settle because o f its greater sensitivity to the noise i n the autocorrelation function.


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A variety o f polydisperse latexes w i t h k n o w n particle size distributions were previously analyzed (off-line) i n a N i c o m p 370 i n order to test the accuracy o f the above techniques. F o r unimodal distributions (both broad and narrow) the Gaussian analysis gave a good estimate o f the location o f the m a i n body o f the true particle size distribution o n a weight (volume) basis and a g o o d estimate o f the weight (volume) average diameter (the estimated value was always w i t h i n 8% o f the true one). T h e mean diffusion coefficient estimated from the cumulants analysis was correct even for distributions for w h i c h the Gaussian assumption does not h o l d (for example, b i m o d a l distributions). T h e weight average diameter estimated from the N i c o m p analysis was sometimes substantially different from the true one (10-15% error). Furthermore, w h e n the estimated distribution was overlaid w i t h the true one, the larger particles were correctly estimated, but the smaller ones were not included. Detailed discussions and explanations for this behavior c a n be found i n K o u r t i (19). T h e N i c o m p analysis c a n detect some b i m o d a l distributions (two populations o f particles w i t h significantly different diameters) i n a short time, and this i s useful w h e n analyzing samples from processes where secondary nucleation m a y take place. T h e results from the Gaussian analysis showed better reproducibility and, as expected, settled faster than those obtained from the N i c o m p distribution analysis. It was concluded that whenever the v a l u e o f x is s m a l l and at the same time the N i c o m p analysis does not y i e l d a b i m o d a l distribution w i t h w i d e l y separated peaks, the Gaussian analysis c a n be used to obtain a reliable estimate o f the weight average diameter and the m a i n location o f the P S D i n a short time. F i n a l l y , it was shown (12) that for routine analysis, D ^ (calculated from the mean diffusion coefficient) together w i t h the coefficient o f variation estimated from the Gaussian analysis c a n be used successfully to monitor particle growth during latex production (both for monodisperse and polydisperse latex). In processes where secondary nucleation is l i k e l y to occur, the display from the N i c o m p analysis can be used, i n parallel w i t h the Gaussian analysis to detect the presence o f a second generation o f particles. 2





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A n o t h e r objective o f our earlier study was to determine h o w fast the estimated averages o f the P S D settle to final values using the two approaches. T h e N i c o m p 370 instrument collects scattered intensity data continuously w i t h a particle size distribution estimated and displayed approximately every 30-45 seconds. It was shown (17.18.19) that 4-5 m i n o f data acquisition is enough for both and the weight average diameter from the Gaussian analysis to settle. W h e n the true distribution was b i m o d a l it was observed (12) that the N i c o m p analysis displayed two peaks (i.e., gave an indication that the distribution is bimodal) at time less than 2 m i n . ( A b i m o d a l is generally detected immediately. I f the intensity contribution o f one o f the peaks is very s m a l l (less than 2%), this peak may later disappear, due to an unfavorable signal to noise ratio)). A l t h o u g h short times o f analysis i n the N i c o m p approach usually y i e l d the correct shape o f the P S D , it is very difficult to resolve the correct sizes for the b i m o d a l distribution. Determination o f the correct size requires longer analysis times. It is more difficult to resolve accurately the exact volume (mass) ratio o f the two populations; more than one solution is possible. H o w e v e r , a l l o f these solutions ( w h i c h fluctuate w i t h time around a correct mean value) y i e l d the same mean diffusion coefficient (12) and the same intensity average diameter. T h e results obtained from a variety o f latexes showed that the D L S method c a n provide estimates o f the P S D for polydisperse latexes w i t h narrow o r broad continuous distributions i n less than 5 - 1 0 m i n , at any monomer conversion. F o r w i d e l y separated bimodals, the shape o f the distribution is displayed to w a r n for possible secondary generations. T h e method is fast, consistent and reproducible and (as discussed below) possesses some other advantages that make it an excellent candidate for on-line applications. Suitability O f D L S F o r O n - L i n e Applications In order to qualify for on-line applications, a particle s i z i n g technique must possess certain characteristics. It must be fast; the time required for the particle size measurement must be short enough to a l l o w sufficient time for the appropriate control action to be calculated and implemented. Second, the instrumentation must be simple; complicated parts w i l l c l o g w i t h latex over time (latex j made to adhere). F i n a l l y , the measurements must have good reproducibility and no drift should occur w i t h time due to clogging or other malfunction o f the components o f the f l u i d circuit. T h e D L S technique for particle s i z i n g has a number o f inherent advantages over other methods, w h i c h make it w e l l suited for automated, on-line applications. First, it is an absolute technique, requiring no calibration. T h e particle diffusion coefficient and the corresponding particle radius can be calculated directly from the theory. Furthermore the scattering wavevector K (Equations 3,4) w h i c h relates the time scale o f the intensity fluctuations to the particle d i f fusivity, £>„ depends o n three parameters (laser wavelength, scattering angle and refractive index o f diluent), a l l o f w h i c h c a n be h e l d constant over time. T h e calculation o f the corresponding hydrodynamic particle radius R from D, (Equation 5) depends o n two additional parameters w h i c h c a n also be held constant over time (temperature, T , and viscosity o f diluent, T)). Hence, any w e l l designed D L S instrument should y i e l d consistent, reproducible results over extended periods o f time, requiring no calibration. s

Second, the diffusion coefficient D depends o n l y o n the size o f a particle (Equation 5) and is independent o f its composition (density, molecular weight and refractive index). W h i l e the refractive index o f the particles w i l l certainly influence the average scattered intensity, it w i l l not affect the particle diffusivity (i.e., the behavior o f the intensity fluctuations). F i n a l l y , the measured particle diffusivity (and hence the computed particle size, or f u l l P S D ) is independent o f the concentration o f the particles i n the suspension, provided that the o r i g i n a l suspension is diluted sufficiently to eliminate the effects o f multiple scattering and interparticle interactions (either electrostatic repulsions or V a n der W a a l s attractions) o n the autocorrelation function. C l e a r l y , these three intrinsic characteristics o f the D L S technique make it ideally suited for on-line measurements, where acquisition and d i l u t i o n o f fresh concentrated samples must be performed automatically and must be immune from maintenance requirements over l o n g periods o f time. F o r suspensions o f submicron particles D L S has a significant advantage over another particle s i z i n g method based o n turbidimetry. F o r latexes o f submicron particles for w h i c h the ratio o f the refractive index o f the particles to that o f the m e d i u m is approximately 1.1, specific turbidity i s the o n l y turbidimetric technique that provides reliable results. T h i s technique requires t



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knowledge o f the solids fraction i n the sample (12=21). T o apply the specific turbidity technique on-line for particle s i z i n g , a k n o w n quantity o f latex sample must be captured and diluted to a k n o w n final volume. A weight average particle diameter can be determined from the optical turbidity o f the resulting dilute suspension, provided that the degree o f dilution and the optical properties o f the suspension are k n o w n . B y contrast, D L S does not require that the particle concentration i n the suspension be k n o w n (i.e., i t does not require exact dilution o f the o r i g i n a l latex). Because o f the need o f exact dilution the sampling system required for turbidimetry i s more complicated than that required b y D L S . In case o f clogging o f the metering v a l v e i n the former, the dilution factor m a y change and the calculated particle size w i l l be wrong. In D L S the sampling device is simple and very r o b u s t The second advantage o f D L S over turbidimetry is that the latter method is extremely sensitive to errors i n the value o f the refractive index, rip, o f the particles. D L S is independent o f np for most latexes. M o r e specifically, the estimated particle size is independent o f the refractive index o f the particles for monodisperse suspensions. F o r polydisperse suspensions w i t h any type o f P S D , the intensity weighted distribution is independent o f a , . F o r distributions expressed o n volume o r number basis, the error due to uncertainties i n the value o f the refractive index w i l l be very s m a l l i n two cases : i ) for any type o f distribution (unimodal o r b i m o d a l continuous o r w i t h separated peaks) w i t h particle sizes smaller than approximately 350 n m (for a laser wavelength o f 670 n m ) , and i i ) for any continuous submicron P S D . T h e error w i l l be larger (but not as large as i n turbidimetry) for w i d e l y separated b i m o d a l distributions covering regimes beyond 300 n m . Sampling Device A n d Autodilution O n - l i n e particle size analysis using D L S instrumentation requires a proper sampling device capable o f automatically acquiring a quantity o f concentrated suspension from the reactor and diluting to an optimal final concentration T h i s concentration must be sufficiently l o w to a v o i d multiple scattering and interparticle interactions but large enough to y i e l d a h i g h signal to noise ratio i n the autocorrelation function after a relatively short time o f data acquisition (typically, just several minutes). T h e optimal d i l u t i o n factor c a n be expected to vary significantly w i t h the properties o f the starting concentrated suspension. T h e average intensity o f the scattered light from a diluted sample depends strongly o n the P S D , the particle concentration and the ratio o f the refractive index o f the particles to that o f the diluent (water). T h i s requires that the automatic d i l u t i o n system possess a very wide dynamic range, capable o f achieving dilution factors ranging from 100:1 o r smaller to 1 0 0 , 0 0 0 : 1 o r greater. F o r example, early i n the polymerization i n a batch reactor the size o f particles is s m a l l and the p o l y m e r concentration l o w ; i n this case a relatively l o w d i l u t i o n factor i s needed. N e a r the end o f the reaction, w h e n the particles have g r o w n and the mass o f p o l y m e r has increased, higher dilution factors are needed. Furthermore, for the same polymer concentration and the same P S D , different degrees o f dilution m a y be needed for different polymers. O n - l i n e application o f D L S was made possible b y using a combination o f a sampling device and autodilution mechanism w h i c h were described i n detail i n previous reports (17- 19V T h e autodilution mechanism is w e l l suited to meet the requirements discussed above. A m o d i f i e d version o f this computer controlled mechanism, designed to operate i n industrial environments, is described later. I n f u l l y automatic mode the sampling cycle commences w i t h the capture o f an arbitrary s m a l l quantity o f concentrated sample from the latex reactor. F o l l o w i n g a short predilution step, the partially diluted sample is then passed to the Autodiluter, where the d i l u t i o n factor is allowed to increase continuously until the scattering intensity falls to a preset l e v e l appropriate for the digital autocorrelator. A f t e r a predetermined delay to achieve temperature equilibration i n the scattering c e l l , the autocorrelation function is measured b y the N i c o m p analyzer. A t a predetermined time the particle size distribution results are printed, the raw data stored o n diskette and the system is flushed w i t h fresh d i l u e n t T h e computer controller then awaits the preprogrammed start o f the next measurement cycle. Because o f its design, o u r o n - l i n e D L S based system w i t h A u t o d i l u t i o n should y i e l d results o f comparable accuracy and reproducibility to those obtained i n an off-line laboratory setting. That i s , once a fresh latex sample has been captured and prediluted b y the sampler / prediluter device, its treatment b y the A u t o d i l u t i o n / D L S device is identical to that w h i c h occurs o n a lab bench w h e n concentrated samples are introduced manually into the system.




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O n - L i n e A p p l i c a t i o n O f D L S T o A Continuous L a t e x Reactor In our previous w o r k the D L S technique was used to monitor on-line the particle growth d u r i n g the production o f polyvinyl acetate) latex i n a batch reactor (17.18). T h e sampling cycle i n that first application was 17 m i n , o f w h i c h approximately 5 minutes were devoted to data c o l lection and analysis. Here, we report the use o f on-line D L S to monitor particle growth d u r i n g polyvinyl acetate) latex production i n a continuous stirred tank reactor. O n - l i n e turbidimetry is also used to measure the size o f the latex particles simultaneously w i t h D L S , and the results from the t w o methods are compared (22). A simplified schematic diagram o f the experimental setup is shown i n Figure 1. T h e reactor is a 5 0 0 m l jacketed stainless steel vessel. Steam heated water circulates i n the j a c k e t T h e reaction temperature is controlled b y manipulating the f l o w o f steam to the j a c k e t T h e reactants (initiator solution, emulsifier solution, monomer and water) are pumped from storage tanks to the reactor using four positive displacement pumps; they are m i x e d i n the reactor b y a pitched blade agitator. T h i s s m a l l reactor is the first i n a series (train) o f continuous pilot scale reactors used for the production o f polyvinyl acetate) latex. T h i s reactor is used as a "seed" reactor. I n simple terms tins is the reactor where the particles are nucleated. T h e other reactors where the latex particles grow have larger volume (1 g a l l o n ) . T h e rationale for the use o f a seed reactor has been discussed elsewhere (24) and is beyond the scope o f this report F o r this w o r k w e used the seed reactor o n l y to produce a l o w solids latex, at relatively h i g h conversion (90 to 100 % ) . T h e residence time i n this seed reactor was approximately 8 minutes, and the reaction temperature was 60 * C . T h e latex exits from an overflow tube at the top o f the reactor and then flows through an on-line densitometer. T w o sampling devices are used to withdraw latex samples from the exit o f the densitometer for on-line particle size analysis b y turbidimetry and D L S . A detailed description o f the reactor setup and the apparatus used for sampling and measurements b y turbidimetry, can be found i n Gossen (23). T h e sampling system for on-line D L S measurements has been described before (17.18) and w i l l also be shown later i n Figure 3. Filtered, deionized, distilled water (which m a y also contain hydroquinone, a radical scavenger) is the diluent for D L S and turbidimetry. T h i s water is at room temperature and quenches the reaction i n the sample; w e assume no further growth o f the particles after sampling. T h e sampling cycle was 5 m i n for turbidimetry and 10 m i n for D L S , w i t h 4 minutes o f the latter devoted to data collection and analysis. T h e remaining time is devoted to sample autodilution, temperature equilibration and flushing o f the system. T h e particle size o f the produced latex depends o n several parameters, such as the t e m perature o f the reaction, the concentrations o f monomer, emulsifier and initiator and the presence o f impurities. D u r i n g this experiment, w e deliberately manipulated some o f these parameters i n order to cause changes i n the mean particle size o f the latex and thus to ascertain whether turbidimetry and D L S c o u l d detect these changes. I n F i g u r e 2 we plot the measured variables (solids v o l u m e fraction and average particle diameters ( i n nm) as measured b y D L S and turbidimetry) and the manipulated variables (concentrations o f emulsifier and initiator, and the monomer fraction i n the feed streams), as a function o f elapsed time. T h e diameters plotted are weight average diameters obtained b y turbidimetry and intensity ( D c J and weight average diameters (calculated from the Gaussian analysis), obtained b y D L S . T h e fact that the weight and intensity averages are significantly different from each other indicates that the particle size distributions are relatively broad, as expected for latex produced i n a continuous reactor. Initially, the manipulated variables were kept constant for several hours, from the start o f the reaction to the point at w h i c h the reactor reached steady state. A t time t = 4 hours (point A ) w e increased the emulsifier concentration and the monomer feed fraction. T h e combination o f these two changes seems to have no significant net effect o n the weight average diameter, w h i l e the solids fraction increases, as expected, due to the monomer fraction increase. (The net effect o n the particle size was not significant because the two step changes had an opposite effect o n the particle size: higher monomer concentration should result i n larger particles but higher emulsifier concentration should result i n smaller particles). A t t = 5 hours (point B ) a large decrease i n the emulsifier concentration combined w i t h a s m a l l decrease i n the monomer feed fraction, resulted i n an increase i n the average particle size, as expected. (Decreasing the emulsifier concentration results i n a decrease i n the concentration o f free soap and therefore i n a decrease i n the concentration o f micelles, w h i c h i n turn results i n a smaller number o f generated particles and therefore larger particles). T h e change i n the solids fraction (due to the decrease



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F i g u r e 1. S i m p l i f i e d schematic diagram o f the experimental setup for on-line density measurements and particle size measurements, using D L S and turbidimetry, during latex production.

ON-LINE MEAN DIAMETERS [nm]

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Particle Size Distribution II - ACS Publications - American Chemical

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