Optimization of batch polymerization reactors:

Chemical Engineering Science. Printed in Great Britain.

Vol.

47.

No.

9-l

I, pp. 2609-2614,

1992. 0

OPTIMIZATION

OF

BATCH

POLYMERIZATION

oaw-2509/92 $5.oo+o.at 1992 Pergamon Press Ltd

REACTORS:

ModeIIing and experimental results for suspension poIymerkation of MethyIMethAcrylate Giuseppe

MASCHIO

t, Tiziaua BELL0

t

Dipartimento di Chimica Induetriale, Sal&a Sperone, 31 CP 29; Sant’Agata $ Dipartimento di Ingegneria Chimica, via Diotisalvi, 2; 1-56066 Piss

t and Claudio SCALI

t

Univereiti di Mesoina di Me8.&aa, I-98166 Messina Univereitd di Piss

Abstract

A model for the simulation

of suspension polymerization of MMA has allows to account for the effect of diffusive phenomena on reaction rate ular weight distribution under non-isothermal conditions. The model experimental runs carried out in a laboratory reactor. Obtained results

been developed, which and to evaluate molechas been validated by

show that an increase of the reaction temperature during the gel efTect time can have a favourable influence on the polymer quality. The control of temperature profiles in the reactor is indicated as an interesting operating

strategy

to be adopted

in industrial

units.

INTRODUCTION Optimization tor.

of industrial

A knowledge

phenomena),

polymerization

of fundamental

a.~ well

aspects

as of practical

units

depends

of the

process

aspects

niixing and heat transfer devices) is required. Kinetics of polymerization is characterized

(constraints

both

on design

(reaction

coming

and

operation

of the

reac-

and associated diffusive reactor geometry and from

kinetics

from

by the fact that the termination

and (at higher con-

version) the propagation and Soong, 1985). The

rates are controlled by diffusion phenomena (Louie et al., 1985; Baillagou so called gel and glues egecte play an important role affecting the reaction The gel eflect is originated from the rate and the molecular weight distribution of the polymer. fact that, termination reactions among the large polymer growing chains are controlled by diffusion. This slows termination rate, compared with propagation, and therefore causes an increase in the when the temperature is below the glass transition polymerization rate. At higher conversions, temperature of the polymer, also the propagation reaction may become controlled by diffusion: on the this glass eflect causes a sudden decrease in the reaction rate. Their direct consequences molecular weight distributions are the following: - during the gel eflect time the instantaneous molecular weight goes up rapidly; the weight average so that molecular weight (A4 w ) increases more than the number average molecular weight (MN), the polydispersity (PD = A&/MN) will be larger; - during the gloss eflect time, on the contrary, MN decrease more than Mw, but the final results will be again a larger vaIue of PD. Diffusion

phenomena

are heavily

affected

by temperature:

so the reactor

temperature

plays

an

important role on the onset and on the extent of the two effects. The global optimization of the industrial process requires attainment of a product of desired quality (high molecular weight, low values of polydispersity), minimization of batch time, achievement of high monomer conversion and preservation of safety conditions. In determining the optimum range of operating conditions many different factors must be taken into account simults neously. Being very difficult to carry out experimental runs on industrial plants, it is evident the necessity of having a simulation model which, starting from kinetic aspects of the process, will be able of giving indications on the operating strategies of the industrial unit. 2609

GIUSEPPE

2610

ef al.

MASCHIO

E6

The first step of the overall study is then the development of a model to predict the behaviour of the reactor, the second is an experimental validation of assumed hypotheses and the third is an analysis of optimal operating conditions, taking into account peculiarities of industrial plants. These will be also the three sections in which the paper is structured: new hypotheses adopted in the model, with respect to previous works (Maschio and Moutier, 1989; Maschio and Zanelli, 1991) will be presented and particular attention devoted to experimental results obtained on a laboratory unit. The suspension polymerization of MethylMethAcrylate (MMA ), initiated by azobisisobutyrroniprofiles and initiator concentration h as been studied; the effect of reactor temperature trile (AIBN) has been investigated. MODELLING Starting from the general kinetic scheme of free radicd polymerizations, a dynamic simulation model has been developed. The model must be able to predict the weight average molecular weight (Mw) and the Polydispersity of the polymer (PD) under non isothermal conditions. To improve accuracy in the estimate of these parameters, the quasi-steady state approximation (QSSA ), which have been used in previous works (Maschio and Zanelli, 1991), has been removed. The method based on the moments of the molecular weight distributions has been adopted (Ray, 1972). These moments,

are defined

by:

About the physical meaning of the leading moments: &, is the concentration of the growing chains, cl0 iz the concentration of dead polymer chains, ~1 is the number of monomer units in the polymer chains. Their values have been calculated by using the technique of the generating functions. Parameters characterizing polymer quality, as average of molecular weight and polydispersity, are obtained from the it“ order moment, by the following relations:

MN=

cl

-

M

e.

-

M

pD

=

w;

Mw

(co -

M)(z2

=

EZ +

+ slEl

61

-M

-

M

W

M)

(61 - W2 Reaction rates for all the single species acting in the polymerization, are given in Table 1. The kinetic constants: kd, ktr, kp, kt refer to typical steps of the free radical polymerization, respectively: are reaction

initiator decomposition, chain transfer, propagation and termination. parameters (apparent constants) that change as function of temperature,

k,, and

and

kt

also

8s a consequence of the onset of gel and glass eflect. For a quantitative evaluation of diffusion phenomena on the reaction rate, the free volume of the solution (vf) and its critical values (v/,=r) are the most appropriate parameters which are used in literature (Soh and Sundberg, 1982; Maschio and Moutier, 1989). Numerical verlues of all kinetic constants appearing in reaction rates are given in Table 2. k,, and kt are expressed 8s a ratio with respect to their values in the absence of diffusive phenomena (b,, and kt,,). The polymerization of MiUA is carried out in industrial units operating batchwise. The reaction mixture, consisting of water, monomer, initiator and suspending agents, is stirred by means of a Once the reaction starts, the heat continuous system and warmed up to the desired temperature. generated is removed by means of a jacket cooling system: the reactor temperature is controlled, through the inlet temperature of the cooling water in the jacket, by mixing an external flow of eubcooIed water with a recycle from the jacket. In developing the model, hypotheses of perfect mixing for the reactor and the jacket have been assumed and the thermal capacity of the jacket haa been neglected. The dynamic behaviour of the system is described by the set of balance equations reported in Table 3. A complete list of symbols is given in Table 4.

Optimization

E6 rI = rro

=

rss = r& =

=

-k& -.5kt,&

-

bMAo

2k,Mh

+ kt,&

2kdf I-

k&

Table

k,j =

1.3321016e-ze 4.67x10-2e-88*/m .108kt

Vf.m =

-025 + .061(T

Vf*F = Vf,cr =

.025 + .00048(T

Table

.186 .055

2: Kinetic

dV/dt = dPl/dt = dro/dt = CdTldt =

r’x1 =

rates for all the reacting species of the system.

700/RTm

-

2.96zlti(T

constants

387) -

+ rpx + rbO

Table

273)

kt, = k t,d = (k,,/&)

=

(W%o) (kt/kt,)

= =

fkt/kt,l

=

values for free radical

-(VoS/Mo)dM/dt cPldM/dt &odM/dt rr - I’$

k

167) -

2611

reactors

--2kdf I - (kp + kt,,,)M& + kt,dplAO + ktr,,MPr 2kcsf I + kt,,M~o - (kt,, + S)MR - W”~o 2kdf I- krr,mM(& - x0) + k,WXo - k&oh

I,“, =

1: Reaction

k +,,,, = k t,c =

V? __ =

of batch polymerization

dI/dt = dXo/dt = dcl/dt = rr =

3: Balance

6.50z107e-7es/RT .892kt 72.23e(1’6uf-7.41-40.2U~.~r)

polymerization

cIdM/dt + rI r$XodM/dt + rxO
equations

(Vf I

&r)

I (Vf 2 v>,,r) .683em*‘(“f-“~~~~) (Vf 5 Uf.cr) _135e(17.15~/-.017(T-272.16)) (Vf 2 Vfe.1

for the batch

of MMA

dM/dt dXl/dt dEz/dt

= = =

rj =

(initiator

AIBN).

r,,,/(l - CM) cXldM/dt + VA, &:tdM/dt + rsz UdAx(T - Tj)

reactor.

VALIDATION OF TIIE MODEL The model to analyze different operating strategies of the polymerization process is based on the equations describing the reaction kinetics and associated diffusive phenomena. Several operating strategies proposed in literature (Ponnuswamy et al., 1987; O’Driscoll and Ponnuswamy, 1990), refer to predictions obtained by simulation without any experimental check. Also, most reaction models Balke for.

adopted

in literature

and Hamielec

(1972):

are based on a limited number of experimental an extension of the range of examined operating

runs carried out by conditions is called

Experimental An experimental validation of the reaction model and of values assumed for the kinetic constants describing the gel and glass eflect has performed in a laboratory scale stirred tank reactor (Repaci, 1991). It consists of a jacketed glass vessel (2 liters volume), equipped with a stirrer and allows to carry out isothermal and non-isothermal runs with different monomer and initiator concentrcc tions. The reactor temperature is monitored continuously by means of two thermocouples, one for the data acquisition system and the other for the temperature control system. A thermostat is

used to maintain the desired temperature inside the reactor, by acting on the value of the jacket temperature. The stabilized

commercial

monomer

was washed with NaOH

(5’? o solution)

to remove inhibitors;

monomer and solvent were dried with anhydrous calcium chloride and distilled. The radical initiator (AIBN) was dissolved and recrystallized in ethanol. The suspending medium was a solution of Before each run, the monomer solution and the reactor were agarose (1% in weight) in water. purged with nitrogen in order to ensure an inert atmosphere. Measured quantities of monomer were introduced into the reactor and heated to the operating temperature: then a measured quantity of AIBN solution was added. The reaction was carried on under strong agitation (600 - 8OOrpm) in order to maintain the organic phase in suspension, thus obtaining small size pellets of polymer (lOO5OOpm). During the polymerization, samples were taken and conversion determined gravimetrically, while the weight average molecular weight and polydispersity were determined by gel permeation chromatography (GPC).

2612

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Comparison of Experimental and Simulation Results A comparison between experimental values and model predictions is reported in next figures, for different concentrations of initiator (A IBN) and different operating temperatures (isothermal and non-isothermal). Figure 1 shows the influence of different concentrations of initiator on the conversion X(t), on the average molecular weight Mw(X) and on the polydispersity PD(X) during batch time, for an isothermal run at T=343 K. Figure 2 shows the influence of different reactor temperatures on X(t) and Mw(X), for isothermal runs with equal concentration of initiator (M/I = 164). From the analysis of results we can conclude that a very good agreement between experimental and simulation is shown for X(t); also values of A&(X) and PD(X) are predicted by the model with good approximation. It can be noted that an increase of the reactor temperature and of the initiator concentration (lower values of M/I), have same effects of causing larger conversions and shorter batch times. These favourable aspects are counteracted by lower values of Mw. The polydispersity is not influenced very much by the two variables under isothermal runs; it atarts from 2 (minimum value) at low conversion to reach values about 10 at the end of the reaction (only one sample run is reported in Figure 2b). MW I 1000 PD ?OOO 100

-0

1

b)

X

Q)

30 Time

60 (min)

90 X

Figure 1: Comparison between predictions of the model (lines) and experimental valuea for different concentrations of initiator. T = 343; 1) M/I = 164; 2) M/I = 328; 3) M/I = 546 ; a) conversion vs. time; b) molecular weight vs. conversion; dashed line: polydispemity (case 2). MW I 1000

20

Time

(min)

40

60

80

LOO

X

Figure 2: Comparison between predictions of the model (lines) and experimental values for different temperatures; isothermal runs: M/I = 328; 1) T = 333K; 2) T = 343K; 3) T = 353K; a) conversion vs. time; b) molecular weight vs. conversion.

Optimization

E6

of batch polymerization

2613

reactors

Figure 3 shows the effect of two ramps of temperature given at different times during the course of reaction. The increase of temperature is of 10 K in both cases, but in one case (2) it starts when the gel effect is beginning, while in the other case (3) it ends when the gel effect has just started. Isothermal runs at initial (1) and final temperature (4) are also reported for comparison. About the influence of the temperature profile, we notice that if the increase happens when the gel effect is active, the decrease in the final value of A4w is less pronounced (Figure 3b). We also notice that in the two isothermal cases, the final value of PD s 10, while in the two non isothermal runs PD Cy 8. Therefore an increase of temperature during the course of the reaction can have a favourable effect on the polymer quality.

1.i:;

-

x-

0

30

15 Time

(mln)

45

1313

oL-----J 0

20

40

60

80

100

X

Figure 3: Comparison between predictions of the model (lines) and experimental values for different temperature profiles. M/1 = 164; a) conversion vs. time; b) molecular weight vs. conversion. 2) ramp of T = 343 - 353K, between to = 25 and t/ = 37 min; 1) isothermal: 7’ = 343K; 3) ramp of T = 343 - 353K between to = 15 and tf = 27 min; 4) isothermal: T = 353K. SIMULATION OF INDUSTRIAL OPERATION By using the model validated on experimental results, first indications about operating conditions of industrial reactors can be drawn. In general, in industrial size units the available cooling load is not large enough to remove completely heat generated during gel eflect time. Therefore, it is not possible to maintain isothermal conditions and an increase of reactor temperature up to about 30 K must be tolerated. By considering that the reaction is highIy exothermic, the combination of the two effects may originate runaway conditions in the reactor; the temperature control is a very critical point and a safety analysis of the process must be performed preliminarily to the optimization stage (Maschio and Zanelli, 1991). According to previous results, the non-isothermal operation has a strong influence on product quality. An industrial reactor having the following characteristics has been studied: V = 20ms; A = 25mz; Z = 2; M/I = 400; ud = 1.86KW/m2K. In Figure 4 the effect of different capacity of the cooling system is reported. These variations may be obtained, for example, acting on the jacket water temperature: the reactor temperature increases to a maximum during gel eflect time, when heat generated is larger than heat removed. Results are compared with the reference isothermal case (T = 343K). Values of Mw show an inverse dependence from values of the maximum temperature. Final values of PD initially decrease with the temperature peak (curve #2 vs. #3), but for higher values of the peak PD rise again (curve #4). This result is very interesting because, controlling the cooling load, it is possible to impose reactor temperature profiles which will result in optimal performance. CONCLUSIONS Experimental results confirm hypotheses assumed at modelling stage. This allows to predict with good approximation, not only the dynamic behaviour of the industrial polymerization, but also product quality. A strong influence of the temperature profile on process performance is shown. A controlled increase of temperature during gel efTect time allows partly to face the reduced mobility

GIUSEPPE Mascnro

2614

er al.

E6

of polymer

chains, which leads to high values of Mw and PD in isothermal operations. Therefore it is possible to obtain a product having a smaller distribution of molecular weights. Determination of an optimal temperature profile will be the object of further work, both experimentally and by simulation. PD Mwxiooe X

0

60

30 Time

90

0

20

kd kt M

tranrrfer

8urfuce[m’]

C

initiator eficiency: f = 0.4 decomposition rate constant [s-l]

I k*

ktr

Mn Mw PR T t

termination rate constant [m’/kmols] monomer concentration [kmoZ/ms] dead poZymer chain (kmoZ/ms] weight aver. mol. weight (kg/kmol] growing polymer chains [kmoi/m’] reaction temperature (K] time [8]

vo

ilzitial

?

free volume: vf = qSmvf,m + +vfg monomer molecuhr weight [kg/kmol] heat generation [W]

V X 2

ro 6 J%

Pi P +ms

volume

60

I30

X

Figure 4: Simulation of industrial operation for different cooling loads; ature vs. time; b) molecular weight and polydispersity vs. conversion. 2), 3), 4): decreasing cooling load. 1) isothermal: T = 343K; heat

40

(mln)

Ima]

vol. contraction: 6 = p~/pp - 1 total polymer chains ith order moment dead polymer chains ith order moment den&y [kg/ms] vol. fraction (monomer,poCimer) Table

4: List

M/I MN

PD ;j ud

ri AH, Xi < r X

a) conversion

and temper-

thermul capacity [J/K] initiator concentration [kmol/ms] propagation rate constant [mS/kmds] transfer rate constant (mS/kmola] ratio: monomer/initiator number aver. mol. weight [kg/kmol] polydispersity reaction rate [kmol/m’s] jacket temperature [K] global heat transfer coefi [W/m*k] volume [m’]; V = Vo(1 2 + 6X) conversion initial ratio: (aqueous/organic phase heat removal [W] heat of reaction [J/kmoZ] growing chains ith order moment

+

vol. shrinkage: vol. shrinkage:

c = 6/(Z + 1 + 6X) r = (1 + 6X)/(2 + 1)

vol. shrinkage:

x =

(1 + Z + 6X)/(2

of Symbols.

REFERENCES Balke, S.T. and Hamielec A.E., 1973, J. Appl. Pol. Sci. 17, 905. Bsillagou, P.E. and Gong, D.S., 1985, Chem. Eng. Sci. 40, 75. Louie, B.M., Carratt, G.M. and Soong, D.S., 1985, J. Appl. Pal. Sci. SO, 3985. Maschio, G. and Moutier C., 1989, J. Appl. Pol. Sci., 37, 825. Maechio, G. and Zanelli S., 1991, Ing. Chim. Ital., 1, 14. O’Driscoll K.F. and Ponnuswamy, S.R., 1990, J. Appl. Pal. Sci., 39, 1299. Ponnuewemy, S.R. et al., 1987, Ind. Eng. Chem. Res., 26, 2229. Ray, W.H., 1972, J. Macromoi. Sci. Revs., C8. Repeci P., 1991, Tesi di Laurea, Dip. Chim. Ind., Univenliti di Meeeina. Sah, S.K. and Sundbsrg, S.C., 1982, J. Pal. Sci. Chem. Ed., 20, 1299. Thia work was supported Acknowledgements: Finalizzato: Chimica Fine lr).

by Consiglio Nazionole delle Riecrche,

(Progctto

+ 1)