Controlling Polymer Rheological Properties Using Long-Chain Branching

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Controlling Polymer Rheological Properties Using
Long-Chain Branching

• PI Ronald Larson
• Univ. of Mich., Dept of Chem. Eng.,
  Macromolecular Science and Engineering Program
• Possible co-PI Michael Solomon
• Univ. of Mich., Dept of Chem. Eng.,
  Macromolecular Science and Engineering Program
• Possible co-PI Jimmy Mays
• Univ. 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
lt 1 LCBs per million carbons significantly
affects rheology!
branched polymers
branched thread-like micelles
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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

• 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.

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.
Larson et al., (2001, 2006, 2011)
Das, Inkson, Read, Kelmanson, J. Rheol. (2006)
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Example 1 Characterization of Anionically
Synthesized H Polymer
Linear Mw/Mn 1.01
Star Mw/Mn 1.03
H Mw/Mn 1.07
Synthesized by Rahman and Mays
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Chemically Likely Structures
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Identification of Structures
Using TGIC Temperature Gradient Interaction
Chromatography
TGIC from Hyojoon Lee and Taihyun Chang
Star (Semi-H)
H
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Identification of Structures
TGIC from Hyojoon Lee and Taihyun Chang
Star (Semi-H)
H
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Comparisons of theoretical predictions and
experimental measurements
H
Xue Chen
Star (semi-H)
blend
from Chen, Rahman, Mays, Lee, Chang, Larson
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Example 2 Blends of Linear Exact 3128 and
Branched PL1880 Polyolefins
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
T150C
Increasing LCB
0.3 LCBs per million carbons!
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Generating an Ensemble of Chains for a Commercial
Single-Site Metallocenes
Algorithm for Monte Carlo simulation of LCB PE
using single-site catalyst
Reaction kinetics of LCB PE using single-site
catalyst
monomer addition
addition of unsaturated chain
generation of dead structured chain
?-hydride elimination
Monte Carlo probabilities
propagation probability
monomer selection probability
Costeux et al., Macromolecules (2002)
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A Priori Predictions of Commercial Branched
Polymer Rheology
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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