J.R. Leiza - University of Waterloo · Jose R. Leiza O. Elizalde, M. Azpeitia, M.M. Reis, J.M. Asua...

Institute for Polymer Research 27th Annual Symposium

Symposium documents for

J.R. Leiza

Abstract

Presentation

Monitoring emulsion polymerization reactors: Calorimetry vs.

Raman Spectroscopy

Oihana Elizalde1, Maider Azpeitia1, Marlon M. Reis2, José M. Asua1 and Jose R. Leiza1

1- Institute for Polymer Materials (POLYMAT) and Grupo de Ingeniería Química, Departamento de Química Aplicada, The University of the Basque Country, M. Lardizabal 3, 20018 Donostia-San Sebastián, Spain

2- Universidade de Säo Paulo, Escola Politécnica, Department of Chemical Engineering, Caixa Postal 61548, CEP D5424-970, Säo Paulo, SP Brasil

Introduction

Emulsion polymers are products-by-process, which means that the final product properties and quality are defined during the polymerization. Therefore, efficient polymerization process control is needed to produce high-performance polymers. This requires the availability of on-line measurements. An adequate online sensor must be able to provide continuous (or at least frequent) measurements, must be accurate enough and has to operate over long periods of time in environments often physically and chemically aggressive. In the last three decades significant effort has been devoted both by academic and industrial research groups to the development of suitable, accurate and robust monitoring techniques for polymerization reactors. The monitoring of emulsion polymerization reactors might a priori seem easier than the homogeneous counterpart reactors because of the lower viscosity of the reaction medium, but it turned out to be much more complex1,2 Sensors for the monitoring of several properties (e.g., conversion, polymer composition, molecular weights, particle size …..) have been developed and assessed in polymerization reactors. Not all the reported techniques were accurate or robust enough as to be implemented in industrial environments. Excellent reviews about the development and applications of online sensors developed in the last three decades have been published3-6. The current trend is to use noninvasive techniques in order to avoid the complexity of manipulating viscous or reaction mediums prone to suffer coagulation. Reaction calorimetry and Raman spectroscopy are two of the most promising noninvasive techniques to monitoring emulsion polymerization reactors because of the advantages they have in comparison with other techniques. In reaction calorimetry, the measurement is noninvasive, rapid, robust, relatively simple and cheap because it is based on temperature measurements. As a consequence, it is one of the techniques that most easily can be implemented in industrial environments. Among the different spectroscopies techniques that have been applied to monitor emulsion polymerization reactors, Raman spectroscopy offers several advantages in comparison with the absorption based spectroscopies: Near-Infrared (NIR) and Mid-Range Infrared (MIR). Thus, water has a very weak signal in Raman spectroscopy and functional groups that are inactive or very weak in absorption present a strong Raman scattering, i.e., carbon-carbon double bonds. Furthermore, for industrial implementation Raman spectroscopy offers the

possibility of using silica fibers (that have a low cost) with a length of up to 100 m, to transmit the radiation to and from the sample. In this work, the performance of the noninvasive techniques (calorimetry and Raman spectroscopy) to monitoring semibatch high solids content emulsion polymerizations for two different monomer systems (vinyl acetate/butyl acrylate, VAc/BA, and butyl acrylate/ methyl methacrylate, BA/MMA) is compared. Overall and instantaneous conversions, as well as free monomer concentrations were measured. The polymerizations were carried out under starved conditions (high instantaneous conversions) for the BA/MMA system, and under non-starved conditions for the VAc/BA system. Results and Discussion

Figure 1 shows the evolution of the instantaneous conversions (as calculated by gravimetry) for the seeded semibatch experiments carried out for each comonomer system. It can be seen that the trend was similar in both cases; namely, there was an accumulation of monomer during the first stages of the process, and then the conversions were roughly steady up to the end of the feeding period. Beyond this point, the conversions increased as the process proceeded batchwise. The conversions reached during the plateau were greater than 80% for BA/MMA and under 70% for VAc/BA. The former corresponded to starved conditions, whereas the latter did not.

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Overall Conversion Figure 1. Instantaneous conversions for the semibatch emulsion copolymerizations used to compare Raman spectroscopy and calorimetry: (left) BA/MMA; (right) VAc/BA. VAc/BA system (Non-starved conditions)

Figure 2 presents the comparison of the overall conversion predicted by the two monitoring techniques and by gravimetry (reference technique). It can be seen that the predictions of both Raman and calorimetry were close to the gravimetric values.

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Raman

Gravimetry a)

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Calorimetry

Gravimetry b)

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Free VAc (wt%)

GravimetryCalorimetryRaman

Time (min) c)

Figure 2. Overall conversion(a and b) and free VAc monomer concentration(c). Comparison of calorimetry and Raman spectroscopy with the reference techniques (gravimetry and gas chromatography). Figure 2 also shows the unreacted VAc ( weight fraction based upon the total reactor mass) as measured by the reference technique (gas chromatography), and by calorimetry and Raman spectroscopy. Both techniques provided a good prediction of the free concentration of VAc in the reactor and they were comparable to the chromatographic values. Furthermore, both techniques captured well the change in the profile when the feeding period was over and monomer concentration decreased. BA/MMA system (Starved conditions)

As shown in Figure 1, the instantaneous conversion for this comonomer system was higher during the whole process. This means that monomer concentrations were also significantly lower than in the previous case, specially the concentration of MMA, which is the more reactive monomer in this system. Consequently, the heat released by polymerization was much lower too. Figure 3 presents the comparison of the overall conversion measured by gravimetry and the two online techniques for the copolymerizations experiments carried out with the MMA/BA comonomer system. As it can be seen, in general there is no much difference for both techniques, and they compared well with gravimetry.

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Gravimetry Figure 3. Comparison of the overall conversions measured by gravimetry for the BA/MMA system: Raman spectroscopy (left) and Calorimetry (right). Figures 4 show the comparison of the instantaneous conversion and the MMA and BA monomer concentrations calculated by means of the gravimetry and by Raman spectroscopy and calorimetry for one of the experiments carried out with this comonomer system.

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Instantaneous Conversion

Time (min)

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Time (min)

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Free-BA (mol)

Time (min) Figure 4. Comparison of the instantaneous conversion and free amounts of MMA and BA in the semibatch experiments as measured by the three techniques. This graph shows that the prediction of the instantaneous conversion and free monomer concentrations were better for the FT-Raman spectroscopy than for reaction calorimetry. Similar results were obtained for other experiments carried out at different monomer ratios and with different feeding times for the monomer. In conclusion the study revealed that under non-starved conditions both calorimetry and Raman spectroscopy provided comparable results. However, significant differences were found for the BA/MMA semibatch emulsion copolymerization carried out under starved conditions. The overall conversion predicted by both techniques was good, but for the instantaneous conversion and free concentrations of monomer. Raman spectroscopy was far more accurate than calorimetry.

Acknowledgements The authors acknowledge the financial support from the University of the Basque Country (Grant UPV 0021.215-13594/2001) and CICYT (project PP02000-1185). O. Elizalde and M. Azpeitia acknowledge their scholarships from the Ministerio de Educacion y Ciencia and M. M. Reis acknowledges the FAPESP (grant number: 03/06837-8 and 01/13017-1). References

(1) Leiza; J.R, J.M. Asua; J.M. Asua (ed). Polymeric Dispersions: Principles and Applications. Kluwer Academic Publishers, 1997.

(2) Dimitratos; J., G. Eliçabe; C. Georgakis. AIChE J, 1994, 40:1993. (3) Chien; D.H.C., A. Penlidis. J. Macromol. Sci., Macromol. Chem. Phys., 1990, C30:1. (4) Embirucu; M., E.L. Lima; J.C. Pinto. Polym. Eng. Sci., 1996, 36:433. (5) Hergeth; W.D., J.M. Asua (ed). Polymer Dispersions. Principles and Applications. Kluwer

Academics Publishers, 1997. (6) Kammona; O. E.G. Chatzi; C. Kiparissides. Rev. Macromol. Chem. Phys., 1999, C39:57.

May 17, 2005

Jose R. Leiza

O. Elizalde, M. Azpeitia, M.M. Reis, J.M. AsuaThe University of the Basque Country

Donostia-San Sebastián (Spain)

Monitoring of Emulsion Polymerization Reactors: Calorimetry vs Raman

Spectroscopy

May 17, 2005

Outline

•Introduction •On-line Monitoring by means of Reaction calorimetry

– Estimation of Qr and UA– Estimation of free-monomer

•On-line monitoring by means of Raman spectroscopy– VAc/BA and all acrylic systems– Calibration Models (PLS)– Calibration validation

• Raman spectroscopy vs. Reaction calorimetry• VAc/BA (non starved)• BA/MMA (starved)

• Conclusions

May 17, 2005

Produce materials in a consistent way with desired final properties meeting market needs

ProcessVariables

FinalProperties

Introduction

Common approach:Trial and Error procedures

Black box

May 17, 2005

Microstructure-PropertiesModel Equation

Final Properties

• Knowledge of the process Mathematical modeling• Accurate on-line monitoring, optimization and control

ProcessVariables

Polymer Microstructure

Introduction

May 17, 2005

Info

rmat

ion

Ultrasounds

Latex GC

Head space GC

Calorimetry

Spectroscopy

Densimeter, IR

GPC

Difficulty

Introduction

May 17, 2005

Advantages of Raman- Non invasive technique- Direct measurement of unreacted monomers, solids content- Possible in industrial reactors

Reaction Calorimetry +Raman Spectroscopy

- Non-invasive technique- Easy to implement in industrial environment and cheap- Adequate for online control- Provides continuous information of the heat of reaction

Advantages of Calorimetry

Monitoring emulsion polymerizations

May 17, 2005

Qr= Heat of ReactionQf= Heat FlowQl= Heat LossesQs= Heat due to Stirring )( ripii TTcF = Feed sensible Heat

Heat Flow Calorimetry

lsfi

rrinpiir

pR QQQQ)TT(cFdt

dTC Tjin

Tjout

Tr

QfQr

Ql

Qs

)TT(UAQ rjf

ParameterTjinTjout=TjHeat of Reaction

High flow rates of the cooling fluid SMALL SIZEREACTORS

Fi, Tin

Reaction Calorimetry

May 17, 2005

Reaction Calorimetry: Estimation of UA and Qr

0

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35

0 2000 4000 6000 8000 1 104 1.2 10 4 1.4 104

Heat of Reaction (W)

Time(s)

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700

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0 2000 4000 6000 8000 1 104 1.2 10 4 1.4 104

Heat Transfer Coefficient

Time(s)

Oscillation Calorimetry: Smart Calc Mettler-ToledoEvolution of the heat transfer monitored Accurate Heat of Reaction

67

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TrTj

Temperature (ºC)

Time (min)

j

r

pr

TT

CUA

arccostan

feedfar QQQQ

May 17, 2005

Reaction Calorimetry: Estimation of conversion

)()(_

)()(

))(()(_)(

))(()(_)(

0

,

0

,

0

f

ii

iTi

tr

ifTi

tr

f

terTotalMonomtFedMonomer

itFitPolymer

HtMdtQ

tFedMonomertPolymer

HtMdtQ

tMonomerTotaltPolymer

ConversionousInstantane

Conversion Overall

May 17, 2005

Reaction Calorimetry: Estimation of free monomers

i

iCC

iBB

iAA

rii F

DH

DH

DH

QFRp

dt

di

1)(

1)(

1)(

i=A, B, C

ppppj

ppi

j

iij ijijr

ijr

Rp

RpD

][][2)][][(

][][

Inference of unreacted amount of monomer

Accuracy of the estimation:

Reactivity ratios

Enthalpy of polymerization )( H

Partition Coefficients

May 17, 2005

Reaction Calorimetry: An example (2)VAc/BA=50/50 Semibatch Batch 55 wt% solids content

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Conversion

gravimetrycalorimetry

Time(min)

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Heat of Reaction (W)

Time (min)

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Free VAc (mol)

GC calorimetry

Time (min)

Feeding Time:

180 min240 min

rVAc=0.037rBA=6.36HVAc= 89.5kJ/molHBA=78.2kJ/mol

May 17, 2005

Raman spectroscopy

C:\Oihana\Nahasteak\MMA-BA(0-100).0 MMA/BA(0-100) FT_IR , Raman C:\Oihana\Nahasteak\MMA-BA(100-0).0 MMA/BA(100-0) FT_IR , Raman C:\Oihana\Nahasteak\MMA-BA(30-70).0 MMA/BA(30-70) FT_IR , Raman C:\Oihana\Nahasteak\MMA-BA(50-50).0 MMA/BA(50-50) FT_IR , Raman C:\Oihana\Nahasteak\MMA-BA(70-30).0 MMA/BA(70-30) FT_IR , Raman

24/11/200024/11/200024/11/200024/11/200024/11/2000

60080010001200140016001800Wavenumber cm-1

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1640C=C

1413=C-H

1015

830=C-H 812

1725C=O

1725 cm-1 BA total + MMAtotal

1640 cm-1 MMA + BA1450/1413 cm-

1MMA

1015 cm-1 MMA830/812 cm-1 MMA

812 cm-1 PMMA

MMA/BA

H2C=CH

C=O

O-(CH2)3-CH3

H2C=C

C=OO-CH3

CH3

All-acrylic emulsion polymerizations

May 17, 2005

Raman Spectroscopy : Reaction monitoring

VAc/BA copolymerization

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0500100015002000250030003500

C=C DOUBLE BOND!!!

1800

1765

1731

1696

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1592

1557

1522

1488

1453

1418

C1

C4

C7

C10C13

C16

00,0010,0020,0030,0040,0050,006

C=C DOUBLE BOND!!!

C=O

May 17, 2005

Calibration

Model

Knownproperties

Raman Spectroscopy: Calibration

1. CALIBRATION

2. PREDICTION

Model

Estimatedproperties

GCGravimetry

UnknownConcentration

May 17, 2005

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SC (%

)

Sample number

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Sample number

Calibration data: MMA/BA system

May 17, 2005

• A model using the whole normalized spectra, containing 3 PCs was considered the optimum.

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RM

SEV

(SC

)

PC

Example: Model for the SC (%)

May 17, 2005

2nd PC (X-expl,Y-expl): 4%, 2%

3rd PC (X-expl,Y-expl): 1%, 1%

4th PC (X-expl,Y-expl): 0%, 0%

1st PC (X-expl,Y-expl): 90%, 96%

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ghts

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Load

ing

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ghts

(PC

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Load

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ghts

(PC

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cm-1

Example: Model for the SC (%)

May 17, 2005

PLS Calibration models

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Pred

icte

d (S

C)

Measured (SC)

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Pred

icte

d (M

MA

wt f

ract

ion)

Measured (MMA wt fraction)

May 17, 2005

Validation of Calibration

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SC (Grav)Model 1

SC (%

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Conversion0

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BA (GC)Model 1

BA w

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Conversion

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MA

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Conversion

BA/MMA=50/50 compositionOihana Elizalde Ph.D 2005

May 17, 2005

Calorimetry vs Raman

Two comonomer systems considered: BA/MMA and VAc/BA

Overall and instantaneous conversions and Free Monomer:

Gravimetry and Gas Chromatography (as reference) Reaction Calorimetry (RC1 Mettler-Toledo) Raman Spectroscopy (RFS-100 Bruker)

Semibatch reactions of high solids content

Starved(MMA/BA) and Non-starved (VAc/BA)

May 17, 2005

Calorimetry vs Raman : Experimental Details VAc/BA/AA

BA/MMA

Ingredient Initial Charge Stream 1 Stream 2

Water 99,5 - 99,5Alipal 6,13 - 6,13Arkopal 6,13 - 6,13VAc - 600 -n-BA - 141,1 -AA - 22,9 -K2S208 2,29 - -NaHCO3 2,52 - -Seed 527 - -

Ingredient Initial Charge Stream 1 Stream 2

Water 617 - 32,5Dowfax - - 9,45K2S208 Variable - -NaHCO3 Variable - -n-BA+MMA - 540 -n-BA/MMA - Variable -Seed 63 - -

50/50(3), 70/30 and 90/10

Feeding time= 3 and 4 hours

Feeding time= 2 and 3 hour

May 17, 2005

Calorimetry vs Raman: Semibatch Operation

BA/MMA Starved Conditions 50/50 to 90/10VAc/BA Non Starved Conditions

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Overall Conversion

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Time (min)

BA/MMAVAc/BA/AA

Gravimetric data

May 17, 2005

Calorimetry vs Raman: Overall Conversion

VAc/BA copolymerization. Non-starved

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Gravimetry

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Gravimetry

Raman and Calorimetry performed well

May 17, 2005

Calorimetry vs Raman: Instantaneous conversion

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Time (min)


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In general reasonable good prediction for both

May 17, 2005

Calorimetry vs Raman: Free Monomer


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GCCalorimetryRaman

Time (min)

Free VAc (wt%)

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Free VAc (wt%)

Time (min)

Calorimetry and Raman performed well

Chromatography (reference technique) scatters probably due to presence of droplets

May 17, 2005

Calorimetry vs Raman: Overall Conversion

BA/MMA Copolymerization: Starved Conditions

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Gravimetry

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Gravimetry

Good agreement for all techniques

May 17, 2005



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gravimetrycalorimetry Raman


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Time (min)

May 17, 2005



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Time (min)

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Both, Raman and Calorimetry predictions are worseRaman is better than Calorimetry !!!

May 17, 2005



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Free-MMA (mol)

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BA/MMA=50/50

May 17, 2005



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BA/MMA=50/50

May 17, 2005



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GC Calorimetry Raman

Free-BA (mol)

Time (min)

BA/MMA=70/30

May 17, 2005



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Time (min)0

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GCCalorimetryRaman

Free-BA (mol)

Time (min)

BA/MMA=90/10

Calorimetry predicts incorrectly free monomer, specially MMARaman is superior to CalorimetryRaman suffers predicting very low concentrations!!

May 17, 2005

Calorimetry

Error is inherent to the measurement

Example:

2% Error 3% Error

Estimation of unreacted momomer when there is an error of 2% :

xexp= 60%→ xest= 61.2%

(Free monomer)exp=40% → (Free monomer)est=38.8%

May 17, 2005

2% Error 18% Error

Estimation of unreacted momomer when there is an error of 2%:

xexp= 90%→ xest= 91.8%

(Free monomer)exp=10% → (Free monomer)est=8.2%

Calorimetry

Error is inherent to the measurement

Example:

May 17, 2005

Concluding Remarks

• Raman spectroscopy in combination with chemometrics can be used to monitor high solids content reactions, even when the bands of the monomers are overlapped (all acrylic or vinyl/acrylic mixtures) and the reactions are carried out under starved conditions.

• Calorimetry and Raman predict in a similar manner overall conversion. No significant differences for starved and non starved conditions. Calorimetry is easier!

• For instantantaneous conversion and free monomer:– Raman and Calorimetry provide similar predictions under non-starved

conditions, namely, high monomer concentrations.– Raman spectroscopy gave much better predictions than reaction

calorimetry under starved reactions.

May 17, 2005

Acknowledgments• Ministerio de Educación y Ciencia (Project PPQ2000-1185 and

scholarships for Oihana Elizalde and Maider Azpeitia)• The University of the Basque Country (Project 00221.215-

13594/2001)• M.M. Reis acknowledges FAPESP (grant number : 03/06837-8 and

01/13017-1)

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