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Transferability of a coarse-grained atactic polystyrene model: the non-bonded potential effect
1Beijing National Laboratory for Molecular Sciences, Joint Laboratory of Polymer Sciences and Materials, State Key Laboratory of Polymer Physics and Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China. hxguo@iccas.ac.cn and University of Chinese Academy of Sciences, Beijing 100049, China.
We developed a coarse-grained (CG) model for atactic polystyrene (PS) using a 1:1 mapping. Harder Lennard-Jones potentials in the CG force field improve temperature transferability and glass transition temperature (Tg) predictions.
Area of Science:
- Computational chemistry
- Materials science
- Polymer physics
Background:
- Coarse-grained (CG) models simplify complex atomistic systems for efficient simulations.
- Developing accurate CG models requires careful parameterization of inter-particle interactions.
- Atactic polystyrene (PS) is a widely used polymer whose properties are of significant interest.
Purpose of the Study:
- To construct an efficient and simple CG model for atactic polystyrene (PS).
- To derive bonded and non-bonded potentials for the CG force field (FF).
- To investigate the influence of non-bonded potential choice on model accuracy and transferability.
Main Methods:
- A 1:1 mapping scheme was used to create CG beads from atomistic PS.
- Direct Boltzmann inversion and a combined structure-based/thermodynamic method were employed for FF parameterization.
- Lennard-Jones (LJ) potentials were used for non-bonded interactions, parameterized using radial distribution functions (RDF) and bulk density.
Main Results:
- The derived CG model exhibits good temperature transferability from 300 K to 600 K.
- Models with harder LJ potentials show improved density response and temperature transferability.
- The glass transition temperature (Tg) increases with LJ repulsion strength, and thermal expansion coefficients decrease.
Conclusions:
- The CG model with harder LJ potentials provides a more realistic representation of excluded volume interactions.
- This CG model has the potential to accurately predict higher Tg values compared to atomistic systems.
- The chosen FF parameterization method allows for good transferability without temperature-dependent corrections or pressure optimization.
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