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Controlling Polymer Rheological Properties Using Long-Chain Branching

PI: Ronald LarsonUniv. of Mich., Dept of Chem. Eng., Macromolecular Science and

Engineering ProgramPossible co-PI: Michael Solomon

Univ. of Mich., Dept of Chem. Eng., Macromolecular Science and Engineering Program

Possible co-PI: Jimmy MaysUniv. of Tennessee, Dept of Chemistry

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Industrial Relevance

“The flow behavior (‘rheology’) [of polymers] is enormously sensitive to LCB [long chain branching] concentrations far too low to be detectable by spectroscopic (NMR, IR) or chromatographic (SEC) techniques. Thus polyethylene manufacturers are often faced with ‘processability’ issues that depend directly upon polymer properties that are not explainable with spectroscopic or chromatographic characterization data. Rheological characterization becomes the method of last resort, but when the rheological data are in hand, we often still wonder what molecular structures gave rise to those results.”

Janzen and Colby, J. Molecular Structure, 1999

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Rheology, Processing and Long-Chain Branching

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10-2 10-1 100 101 102101

102

103

104

105

106

G' (

Pa

)

(rad/s)

AFFINITYTM PL1880 PL1880_80 PL1880_60 PL1880_40 PL1880_20 PL1880_05 PL1880_02 Exact 3128

< 1 LCB’s per million carbons significantly affects rheology!

branched thread-like micelles

branched polymers

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Project Goals

• Develop industrially useful tools for inferring long-chain branching levels from rheology

• Develop optimization strategies for improving processing and product properties through control of long-chain branching

• Provide software tools and training as needed for industrial applications

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Objectives & Research Methods• Measure rheology of commercial polymers • Combine this with conventional

characterization by SEC, light scattering, and knowledge of reaction kinetics

• Use “Hierarchical model”, a computational tool, to determine a long-chain branching profile of commercial polymers.

• Determine how changes in the long-chain branching profile could alter rheological properties in desirable ways.

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Hierarchical Model

Larson et al., (2001, 2006, 2011)

comb

H

star

linear

• A complex commercial branched polymer is represented by an ensemble of up to 10,000 chains.

• This ensemble represents the range of branching structures and the molecular weight distribution of the commercial polymer.

•The ensemble is generated from a combination of GPC characterization, knowledge of reaction kinetics, and rheology.

•The ensemble is fed into the “Hierarchical Code,” and a prediction of the linear rheology (G’ and G”) emerges.

Das, Inkson, Read, Kelmanson, J. Rheol. (2006)

Relaxation of each molecule is tracked in the time domain, as it relaxes from the tips of the branches, inwards towards the backbone. At long times, branches act as drag centers, slowing down motion of the branch or backbone to which they are attached. The contributions of all molecules in the ensemble to the rheology are combined, and converted to the frequency domain to predict G’ and G’’.

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Example 1: Characterization of Anionically Synthesized “H” Polymer

Synthesized by Rahman and Mays

LinearMw/Mn=1.01

StarMw/Mn=1.03

HMw/Mn=1.07

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Chemically Likely Structures

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Identification of Structures

0 5 10 15 20 25 30 35

n (

a.u

.)

tR (min)

17

18

19

20

21

22

T (

oC)

Mw 38.5k

54.8k

73.6k

Unfractionated Star

0 5 10 15 20 25 30

n (a

.u.)

tR (min)

T (oC

)

14

16

18

20

22

24

26

28

30

32Fractionated H

71k

129k95k

114k

Star (Semi-H):

H:

TGIC from Hyojoon Lee and Taihyun Chang

Using TGIC: Temperature Gradient Interaction Chromatography

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Identification of Structures

0 5 10 15 20 25 30 35

n (

a.u

.)

tR (min)

17

18

19

20

21

22

T (

oC)

Mw 38.5k

54.8k

73.6k

Unfractionated Star

0 5 10 15 20 25 30

n (a

.u.)

tR (min)

T (oC

)

14

16

18

20

22

24

26

28

30

32Fractionated H

71k

129k95k

114k

Star (Semi-H):

H:

TGIC from Hyojoon Lee and Taihyun Chang

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Comparisons of theoretical predictions and experimental measurements

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04

Freq (rad/s)

G',

G''

(Pa)

Me=1620,Gn0=1.095MPa, tau_e=5E-7

Star (semi-H)

H

blend

from Chen, Rahman, Mays, Lee, Chang, Larson

Xue Chen

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Example 2: Blends of Linear Exact 3128 and Branched PL1880 Polyolefins

Sample name AFFINITY™

PL1880 (branched)

Exact 3128

(linear)

LCB (n/1000C) cn Mw

(kg/mol)

AFFINITY™ PL 1880

100% 0% 0.0177 0.0482 116

PL1880_80 80% 20% 0.0142 0.0502 116 PL1880_60 60% 40% 0.0106 0.0521 116 PL1880_40 40% 60% 0.00709 0.0541 116 PL1880_20 20% 80% 0.00355 0.0560 115 PL1880_05 5% 95% 0.000887 0.0575 115 PL1880_02 2% 98% 0.000355 0.0578 115 Exact 3128 100% 0% 0 0.0580 115

X.Chen, C. Costeux, R. Larson. J. of Rheology 54(6) 1185-1206, 2010

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Rheology of Blends of Linear Exact 3128 and Branched PL1880 Polyolefins

10-2 10-1 100 101 102101

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103

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G

' (P

a)

(rad/s)

AFFINITYTM PL1880 PL1880_80 PL1880_60 PL1880_40 PL1880_20 PL1880_05 PL1880_02 Exact 3128

T=150C

Increasing LCB

0.3 LCB’s per million carbons!

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Start

Generate randomnumber R: U(0,1)

R>ppPropagation Termination

Save molecule

Add monomer Add macromonomer

Generate randomnumber R: U(0,1)

R>lp

NO YES

NO YES

monomer addition

addition of unsaturated chain

generation of dead structured chain

-hydride elimination

Reaction kinetics of LCB PE using single-site catalyst

Algorithm for Monte Carlo simulation of LCB PE using

single-site catalyst

Monte Carlo probabilities

Costeux et al., Macromolecules (2002)propagation probability

monomer selection probability

Generating an Ensemble of Chains for a Commercial Single-Site Metallocenes

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A Priori Predictions of Commercial Branched Polymer Rheology

101

102

103

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105

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107

108

PL1880_60

PL1880_40PL1880_80

G

' & G

'' (P

a)

AFFINITYTM PL1880

10-2 10-1 100 101 102101

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107

108

10-2 10-1 100 101 102101

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103

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105

106

107

108

PL1880_20

PL1880_05

G' &

G''

(Pa)

(rad/s)

10-2 10-1 100 101 102101

102

103

104

105

106

107

108

Exact3128

PL1880_02

(rad/s)

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Outcomes/Deliverables• Measurements of rheological properties of

commercial polymers• Measurement of SEC curves for select commercial

polymers• Computer software and training for predicting

rheological properties• Assessment of impact of changing • branching structure on rheology

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Impact

• Improved ability to design and control polymer processing properties

• Ability to infer likely branching characteristics from rheology

• Develop methods of extracting “hidden” features of molecular structure through rheology of samples blended with simpler linear polymers

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Project Duration and Proposed Budget

• 1-4 years, depending on polymer to be tackled, number of samples to be studied, availability of industrial data, such as GPC data, and the solvents/conditions required for characterization

• Budget: $75,000/year

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