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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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Development of a coarse-grained molecular dynamics model for poly(dimethyl-co-diphenyl)siloxane.

Weikang Xian¹, Amitesh Maiti², Andrew P Saab²

¹Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706-1572, USA. yli2562@wisc.edu.

|October 15, 2024

Summary

We developed a coarse-grained molecular dynamics model to simulate polydimethylsiloxane copolymers. This model accurately captures structural and dynamic properties, enabling studies at larger scales.

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Last Updated: Jun 10, 2025

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Drawing and Hydrophobicity-patterning Long Polydimethylsiloxane Silicone Filaments

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Published on: January 7, 2019

Area of Science:

Materials Science
Computational Chemistry
Polymer Physics

Background:

Polydimethylsiloxane (PDMS) is a versatile polymer, but low temperatures can cause crystallization, altering its properties.
Phenyl-siloxane incorporation, as in poly(dimethyl-co-diphenyl)siloxane, suppresses this crystallization.
All-atomistic molecular dynamics (AAMD) is limited for studying PDMS at relevant length and time scales.

Purpose of the Study:

To develop a coarse-grained molecular dynamics (CGMD) model for poly(dimethyl-co-diphenyl)siloxane.
To enable simulations of PDMS copolymers at extended length and time scales.
To accurately predict structural and dynamic properties of PDMS copolymers.

Main Methods:

Systematic development of a CGMD model for poly(dimethyl-co-diphenyl)siloxane.
Determination of bonded and non-bonded interactions using iterative Boltzmann inversion (IBI) from AAMD.
Proposal of a lever rule for generating non-bonded potentials.

Main Results:

The CGMD model quantitatively captures the structural and dynamic properties of the copolymer.
The model successfully suppresses crystallization effects observed in PDMS at low temperatures.
The developed model extends simulation capabilities to longer time scales and larger systems.

Conclusions:

The developed CGMD model provides a computationally efficient and accurate method for studying PDMS copolymers.
This approach is valuable for investigating long-time dynamics, sequence-dependent properties, and phase behavior in entangled polymer systems.
The lever rule offers a novel method for potential generation in CGMD simulations.