Analysis of Molecular Weight Distribution Using Multicomponent Models

Wesslau Distribution Model. This i s a specific case of the generalized logarithmic distribution. I t i s a log-normal distribution which allows one t...
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Analysis of Molecular Weight Distribution Using Multicomponent Models EPHRAIM BROYER Allied Corporation, Corporate Research & Development, Morristown, NJ 07960 RICHARD F. ABBOTT Allied Corporation, Allied Fibers & Plastics, Baton Rouge, LA 70805

The analysis of molecular weight distribution is an important tool in polymerization and is used widely in quality control, development of new grades, polymerization reaction engineering and in assessing the effects of processing on prop­ e r t i e s . In this work, a polymer is considered as a blend of defined components. Each component is descirbed by a molecular weight distribution model. In this study the models of Flory, Schulz-Zimm and Wesslau were used. A computer program was written, which calculates the weight fraction of each component and the parameters defining i t s distribution. Characterization of molecular weight distribution is transformed, therefore, to a non-linear regression analysis, which can be solved by any number of different techniques. The components of the blend can be related to catalyst activity or to operating con­ ditions of the polymerization reactors. The method was used to analyze GPC curves of HDPE samples. Good description of the distribution was obtained with 2-5 components. The Wesslau model requires the smallest number of components to define a mole­ cular weight distribution for HDPE. The importance of molecular weight distribu­ tion in studies of polymerization, polymer pro­ cessing and the physical and mechanical properties of polymers creates a need for mathe­ matical description of the distribution. Several models are commonly used (Flory [1], Schulz-Zimm 0097-6156/82/0197-0045$06.00/0 © 1982 American Chemical Society In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

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[ 2 ] , W e s s l a u [3] and Tung [ 4 ] ) . Often these s i m p l e m o d e l s do n o t d e s c r i b e a d e q u a t e l y the m e a s u r e d d i s t r i b u t i o n of C o m m e r i c a l p o l y m e r s . T h e o r e t i c a l d e r i v a t i o n s f o r the b l e n d i n g of two components w i t h known d i s t r i b u t i o n s have been reported [5]. T h e s e s t u d i e s c o n c e n t r a t e d on the e f f e c t o f t h e p a r a m e t e r s on t h e MWD of t h e blend. T h i s work o r i g i n a t e d from the need to r e p r o ­ duce m a t h e m a t i c a l l y t h e MWD as m e a s u r e d by GPC. The p r o p o s e d m e t h o d d e s c r i b e s a p o l y m e r as a b l e n d of c o m p o n e n t s ; e a c h of them i s d e f i n e d by i t s p a r a m e t e r s and w e i g h t f r a c t i o n . I t provides the i n f o r m a t i o n needed i n the development and e n g i n e e r i n g of a p o l y m e r i z a t i o n p r o c e s s and can be r e l a t e d t o o p e r a t i n g c o n d i t i o n s a n d catalyst performance• MULTI-COMPONENT

MODELS

A p o l y m e r i n t h i s s t u d y i s a s s u m e d t o be a b l e n d of s e v e r a l components. Each component i s d e f i n e d b y i t s w e i g h t f r a c t i o n a n d a MWD, which i s d e s c r i b e d by a m o d e l . A g e n e r a l e q u a t i o n f o r the w e i g h t f r a c t i o n of m o l e c u l e s of s i z e P (P d e g r e e of p o l y m e r i z a t i o n ) i s g i v e n by N = E g. w.

W(P)

(1) (C.,P)

where N ^

g

i

=

1

N i s the number of components i n g± i s the w e i g h t f r a c t i o n of the

(2) the l t

blend

and

h

component• wj i s t h e e q u a t i o n d e s c r i b i n g t h e MWD of the i ^ h component c a l c u l a t e d f o r m o l e c u l e s of s i z e P, w i t h p a r a m e t e r s g i v e n by t h e v e c t o r C. Equation 2 i s a mass b a l a n c e f o r the system. Use of a l i n e a r combination of the m o d e l s l e a d s to a s i m p l e e v a l u a t i o n of the m o l e c l a r w e i g h t averages of the s y s t e m . I n t h i s s t u d y t h e MWDs o f the c o m p o n e n t s a r e d e s c r i b e d by t h e m o d e l s p r o p o s e d by F l o r y , S c h u l z and Zimm, and W e s s l a u . A brief d e s c r i p t i o n of e a c h m o d e l and i t s c h a r a c t e r i s t i c s is given. The equations of t h e a v e r a g e molecular weights of the b l e n d s are a l s o presented.

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

BROYER AND ABBOTT

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Flory

Models for MW Distribution

Distribution

Analysis

Model

The F l o r y d i s t r i b u t i o n i s a random distribution u s e f u l i n s e v e r a l modes o f p o l y m e r i z a t i o n . This distribution results from a d d i t i o n polymeriza­ t i o n r e a c t i o n s when t h e o n l y s i g n i f i c a n t pro­ cesses that i n t e r r u p t macromolecular growth are either or both of chain t r a n s f e r ( t o any s p e c i e s b u t t h e p o l y m e r ) o r t e r m i n a t i o n by d i s p r o p o r ­ tionation. Likewise, this molecular weight d i s t r i b u t i o n describes linear condensation poly­ m e r i z a t i o n when e q u a l r e a c t i v i t y i s a s s u m e d f o r a l l ends o n l y when t h e r e a c t i o n i n v o l v e s an e q u i l i b r i u m between p o l y m e r i z a t i o n and depolymerization. The model d e s c r i b e s t h e d i s t r i b u t i o n w i t h one p a r a m e t e r w h i c h i s t h e number a v e r a g e molecular weight. The d i s t r i b u t i o n e q u a t i o n i s : W(P)

= y

2

P exp (-yP)

(3)

where y - P - p - p (4) n w z y i s the reciprocal o f t h e number a v e r a g e degree of p o l y m e r i z a t i o n . T h e i n d i c e s n , w, a n d z a r e f o r t h e number, w e i g h t s , and z m o l e c u l a r weight averages. The s i m p l i c i t y of t h e F l o r y distribution (1 p a r a m e t e r ) , the constant ratio between t h e a v e r a g e s , and i t s t h e o r e t i c a l deriva­ t i o n a r e t h e main reasons f o r i t s u s e . I n a b l e n d o f N c o m p o n e n t s , each d e f i n e d by a F l o r y d i s t r i b u t i o n , the weight f r a c t i o n of molecules of s i z e P i s given by: N

W(P)

2 = E g.y.^P e x p ^ y . P )

(5) K

D

}

Equation 5 results from combining Equations 3 and 1. A molecular weight d i s t r i b u t i o n i s defined, a c c o r d i n g t o t h i s scheme, by (2N-1) p a r a m e t e r s . The r e d u c t i o n of one p a r a m e t e r r e s u l t s from imposing t h e c o n s t r a i n t of Equation 2. Schulz-Zimm

Distribution

Model

This i s a s p e c i f i c case of the g e n e r a l i z e d expo­ nential distribution. I t was d e r i v e d t o d e s c r i b e polymerization with a constant rate of i n i t i a t i o n and t e r m i n a t i o n by s e c o n d o r d e r i n t e r a c t i o n with American Chemical Society Library 16thPolymer St., N.W.Science; Provder, Theodore; In Computer Applications in 1155 Applied Washington, DC 20036 ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

48

COMPUTER APPLICATIONS IN APPLIED POLYMER SCIENCE

t h e monomer. I t p r o v i d e s d e s c r i p t i o n f o r v i n y l and c o n d e n s a t i o n p o l y m e r s . I t i s a two p a r a ­ meter model g i v e n by:

a+1 a T(aTiy Y

W ( P )

=

e x

(

Y P )

p -

(6)

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where

Y

=

a P

a+1

=

=

a+2

P w

n

P

(7)

z

The r e c i p r o c a l of a measures t h e b r e a d t h of t h e d i s t r i b u t i o n a n d T i s t h e gamma f u n c t i o n . A l t h o u g h t h i s m o d e l p r o v i d e s an a d e q u a t e f i t for the d i s t r i b u t i o n curves, the calculated parameters may l e a d t o e r r o n e o u s molecular weight averages. I f a p o l y m e r i s c o n s i d e r e d as a b l e n d components, the d i s t r i b u t i o n equation i s : N

a

g.Y. i

+ 1

of

a

p i (8)

w ( p )

= j n ^ f i ) —

(3N-1) parameters the MWD. Wesslau

must

Distribution

e

x

p

(

Y

p

- i >

be d e t e r m i n e d

to describe

Model

T h i s i s a s p e c i f i c case of the g e n e r a l i z e d logarithmic distribution. I t i s a log-normal d i s t r i b u t i o n w h i c h a l l o w s one t o c o v e r a w i d e range of m o l e c u l a r w e i g h t s . The w e i g h t fraction of t h e l o g a r i t h m of t h e m o l e c u l a r s i z e i s assumed t o be n o r m a l l y d i s t r i b u t e d . The d i s t r i b u t i o n i s d e f i n e d by two p a r a m e t e r s and i s g i v e n by:

W(P) =

1 BP/5?

exp^

ln(P/Po)

(9)

where

°

exp( 3 /4) 2

r

exp(3 /4) 2

exp(36 /4) 2

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

(10)

BROYER AND ABBOTT

Models for MW Distribution

Analysis

P i s t h e median v a l u e of t h e d i s t r i b u t i o n , that i s , one h a l f o f t h e v a l u e s o f P a r e l e s s t h a n P , a n d i t i s t h e s t a n d a r d d e v i a t i o n o f I n P. A c o n s t a n t r a t i o o f e x p (6^/2) i s o b s e r v e d b e t w e e n the molecular weight averages. The peak of t h e MWD i s l o c a t e d a t P„ I n case t h e p o l y m e r i s c o n s i d e r e d t o be a b l e n d , t h e w e i g h t d i s t r i b u t i o n i s given by: 0

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0

,

?! J i

-I

N

w(p)

r fln(P/Poi)1

^?7¥

e x p

{

\

- [ X j

As w i t h t h e S c h u l z - Z i m m m o d e l , one n e e d s t o e v a l u a t e (3N-1) parameters t o c h a r a c t e r i z e a blend. A graph of the blend cumulative d i s t r i b u ­ t i o n on p r o b a b i l i t y l o g p a p e r w i l l r e s u l t i n a c u r v e composed o f s e v e r a l s t r a i g h t segments. Average

Molecular

Weights

E v a l u a t i o n o f t h e number, w e i g h t and Z mole­ c u l a r w e i g h t a v e r a g e s of t h e b l e n d i s done a f t e r these m o l e c u l a r averages a r e c a l c u l a t e d f o r each component. E q u a t i o n s 4 , 7 , a n d 10 p r o v i d e r e l a ­ t i o n s between t h e parameters of t h e models and the m o l e c u l a r averages of the components. The m o l e c u l a r weight averages of t h e blend a r e c a l ­ c u l a t e d a c c o r d i n g t o a d d i t i o n r u l e s and a r e a f u n c t i o n o n l y of t h e m o l e c u l a r a v e r a g e s and the weight f r a c t i o n of each component.

The

number

average

N

-T

M

The

•1

=IE g, g

^

weight

M

The

n

x

/ M

(12)

ni

average

molecular weight i s :

N = E g. M . w ^ 1 wi

Z average M

molecular weight i s :

molecular weight i s :

N = E g.M M ./M z i wi z i w &

1

(13)

. . (14)

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

COMPUTER APPLICATIONS IN APPLIED POLYMER SCIENCE

CALCULATION

OF

THE

PARAMETERS

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Molecular weight distribution is usually m e a s u r e d by GPC or o t h e r f r a c t i o n a t i o n tech­ niques. The a c c u r a c y of f r a c t i o n separation d e p e n d s on f a c t o r s l i k e t h e l e n g t h o f the c o l u m n , f l o w r a t e and c o n c e n t r a t i o n . A common GPC measurement d e s c r i b e s a d i s t r i b u t i o n by 20-30 fractions. E v a l u a t i o n of the p a r a m e t e r s i n e q u a t i o n s 5 , 8 a n d 11 c a n be d o n e b y : A. I n t e g r a t i o n of t h e s e e q u a t i o n s and comparison w i t h a c u m u l a t i v e d i s t r i b u t i o n or the differen­ t i a l d i s t r i b u t i o n a s p r o v i d e d by t h e normalized GPC chromatogram. JB. Differentiation of the c o m m u l a t i v e d i s t r i b u ­ t i o n to weight fractions o f one u n i t o f d e g r e e o f p o l y m e r i z a t i o n , and d i r e c t l y c o m p a r e them w i t h e q u a t i o n s 5, 8 a n d 11. In both methods, a n o n - l i n e a r r e g r e s s i o n proce­ dure i s needed to e v a l u a t e the parameters. The use of the i n t e g r a t i o n p r o c e d u r e may require long computation times, especially i f a model cannot be integrated analytically. We, therefore, decided to use the d i f f e r e n t i a l form of the distribution and n u m e r i c a l l y d i f f e r e n t i a t e d the cumulative distributions. The cumulative d i s t r i b u t i o n was p i e c e - w i s e i n t e r p o l a t e d and f o r e a c h f r a c t i o n the d i f f e r e n t i a l was c a l c u l a t e d as t h e w e i g h t fraction of molecules o f s i z e P. The differentiating procedure i s described schematically in Figure 1. Differentiating by s u c h a n u m e r i c a l t e c h n i q u e i s d o n e o n c e f o r e a c h GPC reading. The fitting of these data p o i n t s i s t e s t e d w i t h the v a r i o u s models. Numerical d i f f e r e n t i a t i n g through this interpolation procedure provides adequate a c c u r a c y , but o t h e r i n t e r p o l a t i o n procedures may be used. T h e m a i n p u r p o s e o f t h i s w o r k was to r e p r o ­ d u c e t h e w h o l e MWD and t h e o b j e c t i v e f u n c t i o n o f t h e n o n - l i n e a r r e g r e s s i o n was to minimize t h e sum o f r e l a t i v e e r r o r s . Determination of e a c h b a s i c m o d e l s t a r t s w i t h one c o m p o n e n t and t h e number of c o m p o n e n t s i s i n c r e a s e d u n t i l an a c c e p t a b l e f i t i s o b t a i n e d between the computed c u r v e and m e a s u r e d one. A g r e e m e n t h a s t o be reached a l s o b e t w e e n the v a l u e s of the computed and e x p e r i m e n t a l m o l e c u l a r averages.

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

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4.

BROYER AND ABBOTT

Figure 1.

Models for MW Distribution

Analysis

Schematic description of the calculation of the differential weight fraction.

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

51

COMPUTER APPLICATIONS IN APPLIED POLYMER SCIENCE

ANALYSIS

OF T H E G P C OF H D P E

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The chromatograms o f three samples of high d e n s i t y p o l y e t h y l e n e were a n a l y s e d according to t h e p r o c e d u r e s o u t l i n e d i n t h ep r e v i o u s s e c t i o n s . The parameters c a l c u l a t e d f o r each model a r e l i s t e d on t h er e s p e c t i v e g r a p h s . Sample 1 i sa polymer w i t h a r e l a t i v e l y n a r r o w m o l e c u l a r w e i g h t d i s t r i b u t i o n w h i c h was c h a r a c t e r i z e d by 115 f r a c t i o n s . I t s weight a v e r a g e Mw= 6 . 2 2 X 1 0 * a n d i t s d i s p e r s i t y i s g i v e n by M /M = 2.68 a n d M /M = 3 . 0 7 . A l l t h e multicomponents models give adequate f i t t o t h e molecular weight averages, but the Wesslau m o d e l s p r o v i d e i t w i t h t h e l e a s t number o f components. F i g u r e s 2-5 a r e p l o t s o f s e v e r a l r e p r o d u c t i o n attempts w i t h t h et e s t e d models. The W e s s l a u model, which i s c o n s i d e r e d as t h e b e s t d e s c r i p t i o n f o r MWD o f Z i e g l e r t y p e p o l y m e r i z a t i o n , p r o v i d e d t h eb e s t reproduction of t h ed i s t r i b u t i o n c u r v e . A one component W e s s l a u model ( F i g u r e 2) p r o v i d e s good agreement with the molecular weight averages, but there are l a r g e d e v i a t i o n s between t h ee s t i m a t e s and the measurements. A two component Wesslau model ( F i g u r e 3 ) p r o v i d e s e x c e l l e n t f i t t o t h e MWD curve and t h ea v e r a g e s . The a d d i t i o n of t h e c o m p o n e n t o f h i g h m o l e c u l a r w e i g h t ( o n l y 1% w e i g h t ) and s m a l l changes i n t h e parameters of the main component r e s u l t e d i n t h i s e x c e l l e n t f i t . The S c h u l z - Z i m m ( F i g u r e 4) o r t h e F l o r y m o d e l s ( F i g u r e 5) do n o t p r o v i d e a g o o d f i t t o t h e MWD w i t h t h e s a m e n u m b e r o f c o m p o n e n t s . w

n

z

w

H D P E S a m p l e 2 i s a p o l y m e r w i t h a w i d e MWD, where M = 7.34 X 1 0 , M / M = 6.33 a n d M / M = 15.9. The l a s t d i s p e r s i t y r a t i o i s l a r g e be­ cause of t h et a i l of high molecular weight fractions. A 3 component F l o r y model ( F i g u r e 6) d e s c r i b e s w e l l t h e h i g h m o l e c u l a r weight t a i l b u t t h e r e p r o d u c t i o n o f t h e MWD i s n o t satisfactory. 2 component Schulz-Zimm model ( F i g u r e 7) does n o t a d e q u a t e l y reproduce the distribution. Figure 8 describes the results of a 2 component Wesslau model. Although a one component model p r o v i d e s good f i t t o most o f t h e MWD, t h e h i g h m o l e c u l a r w e i g h t t a i l (which 4

w

w

n

z

w

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982. 0

4

Figure 2. Analysis of MWD of polyethylene sample 1 by 1-component Wesslau model . Key: • , experiment and O, model β = 1.42; M — 3.93 χ 10 .

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5

55'

Î

«·* s*

s

δ

δ:

ετ "3*

δ·

Ο

W W Ο Η Η

>

Ό

>

w

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 3. Analysis of MWD of polyethylene sample 1 by 2-component Wesslau model. Key: • , experiment and O, model.

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w

Ο

Q W

w

Η-

ο r

w ο

I—I

>

23

t—ι

oo

δ

Η

δ >

r

>

H W

a

8

-Ρ»

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 4. Analysis of MWD of polyethylene sample 1 by 3-component Schulz-Zimm model. Key: • , experiment and O, model.

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5

U\

5>*

f

o'

•s.

s

δ

S!'

"3*

δ·

I

Η Η

w w ο

>

a

>

w

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 5.

Analysis of M WD of polyethylene sample 1 by 3-component Flory model. Key: • , experiment and O, model.

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Q w o w

W

m α hd O r

>

2

O 2!

H

Π δ >

>

W

cH

π ο

as

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 6.

Analysis of MWD of polyethylene sample 2 by 3-component Flory model. Key: • , experiment and O, model.

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2

U\

f

I"

δ «•·».

O

ετ

1 a-

0 H H

> w w

α

>

W

«

4^

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 7. Analysis of MWD of polyethylene sample 2 by 2-component Schulz-Zimm model. Key: experiment and O, model.

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In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 8. Analysis of MWD of polyethylene sample 2 by 2-component Wesslau model. Key: • , experiment and O, model.

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COMPUTER APPLICATIONS IN APPLIED POLYMER SCIENCE

a f f e c t s the rheology of the p o l y m e r ) i s not q u a t e l y a c c o u n t e d f o r . A d d i t i o n o f 1.3% o f high molecular weight f r a c t i o m improves the r e p r o d u c t i o n o f t h e MWD remarkably.

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HDPE S a m p l e 3 i s a p o l y m e r w i t h a b i m o d a l d i s t r i b u t i o n , c h a r a c t e r i z e d by M = 3.10xl0 and d i s p e r s i t y d e f i n e d by M / M = 3 9 . 3 a n d M / M =6. The b i m o d a l s h a p e a f f e c t s c o n s i d e r a b l y t h e r h e o l o g i c a l and t h e m e c h a n i c a l p r o p e r t i e s of t h e d i s t r i b u t i o n and a good r e p r o d u c t i o n of t h e distribution i s therefore essential. Vast dif­ ferences are found between averages c a l c u l a t e d f r o m t h e GPC a n d t h e r e g r e s s e d parameters. E x a m i n a t i o n o f F i g u r e s 9-11 shows, however, t h a t acceptable f i t was o b t a i n e d between the m u l t i c o m p o n e n t m o d e l s and t h e e x p e r i m e n t s . The 3 com­ p o n e n t F l o r y m o d e l ( F i g u r e 9) a n d t h e 2 c o m p o n e n t Schulz-Zim m o d e l ( F i g u r e 10) g i v e o n l y a f a i r f i t . The 2 component W e s s l a w m o d e l ( F i g u r e 11) p r o v i d e s ; h o w e v e r , v e r y good r e p r o d u c t i o n of t h e MWD . 5

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In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

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Analysis of MWD of polyethylene sample 3 by 3-component Flory model. Key: • , experiment and O, model.

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In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.

Figure 11. Analysis of MWD of polyethylene sample 3 by 2-component Wesslau model. Key: • , experiment and O, model.

Downloaded by UNIV OF CALIFORNIA SAN DIEGO on January 15, 2016 | http://pubs.acs.org Publication Date: September 24, 1982 | doi: 10.1021/bk-1982-0197.ch004

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64

Acknowledgment The authors are grateful to H. D. Oltmann and A. M. Kotliar for their valuable advice.

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Literature Cited 1. P.J. Flory, Principles of Polymer Chemistry, Cornell University Press, Ithaca New York, (1953). 2. G.V. Schulz, Z Physik. Chem., B43, 25 (1939). 3. H. Wesslau, Makromol. Chem., 20, 111 (1956). 4. L.H. Tung, J . Polym. S c i . , 20, 495 (1956). 5. A.M. K o t l i a r , J . Polym. S c i . , A2, 1057 (1964). RECEIVED May 4, 1982.

In Computer Applications in Applied Polymer Science; Provder, Theodore; ACS Symposium Series; American Chemical Society: Washington, DC, 1982.