Model for flow-induced crystallization of industrial-grade LLDPEs
ORAL
Abstract
Flow-induced crystallization (FIC) is ubiquitous in the manufacturing of semi-crystalline plastic products. Generally speaking, polymer crystallization and polymer rheology operate on very different time and length scales. Therefore, modeling FIC requires a multi-scale approach.
In this work, we combine information from atomistic molecular dynamics simulations, mesoscale slip-link modeling, rheo-Raman measurements and fast scanning chip calorimetry to build a model for flowing LLDPE melts undergoing crystallization. Analysis of non-equilibrium molecular dynamics simulations motivate the use of the conformation tensor as a suitable order parameter with which to correlate FIC. The conformation tensor can be tracked during flow using a mesoscale computational model that incorporates the physics of slip-links, cross-links and suspensions to capture linear viscoelasticity and its dependence on polydispersity, entanglement dynamics and crystallinity. Crystallinity in turn evolves according to a kinetic model that depends on the conformation tensor. The combination of models is parametrized from the experimental rheo-Raman and calorimetry data and is shown to be suitable for multi-level modeling of an industrial blown-film process.
In this work, we combine information from atomistic molecular dynamics simulations, mesoscale slip-link modeling, rheo-Raman measurements and fast scanning chip calorimetry to build a model for flowing LLDPE melts undergoing crystallization. Analysis of non-equilibrium molecular dynamics simulations motivate the use of the conformation tensor as a suitable order parameter with which to correlate FIC. The conformation tensor can be tracked during flow using a mesoscale computational model that incorporates the physics of slip-links, cross-links and suspensions to capture linear viscoelasticity and its dependence on polydispersity, entanglement dynamics and crystallinity. Crystallinity in turn evolves according to a kinetic model that depends on the conformation tensor. The combination of models is parametrized from the experimental rheo-Raman and calorimetry data and is shown to be suitable for multi-level modeling of an industrial blown-film process.
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Presenters
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Marat Andreev
Department of Chemical Engineering, Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT
Authors
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Marat Andreev
Department of Chemical Engineering, Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT
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David A Nicholson
Department of Chemical Engineering, Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT
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Gregory Rutledge
Massachusetts Institute of Technology MIT, Department of Chemical Engineering, Massachusetts Institute of Technology
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Anthony Kotula
National Institute of Standards and Technology
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Kenneth Kearns
Dow Chemical Co, The Dow Chemical Company
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Jonathan Moore
Dow Chemical Co, The Dow Chemical Company
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Jaap den Doelder
Dow Benelux NV