Quantitative Lattice Simulations of the Dense Amorphous Phase in Semicrystalline Polymers : Size and Energy Effects in 2-D Lattices

TL;DR

This paper introduces a novel Monte Carlo simulation method for dense amorphous polymer systems on 2-D lattices, addressing challenges in sampling large lattice configurations and providing extensive thermodynamic and conformational data.

Contribution

The work advances lattice simulation techniques by implementing simulated annealing and parallel tempering to improve sampling accuracy in large 2-D lattice models of polymers.

Findings

Effective sampling of large lattice configurations achieved

Accurate prediction of chain conformations and thermodynamics in the thermodynamic limit

Enhanced Monte Carlo methods reduce trapping in local minima

Abstract

In this work we illustrate our novel quantitative simulation approach for dense amorphous polymer systems, as discussed in our previous work[Kulkarni et al., A Novel Approach for Lattice Simulations of Polymer Chains in Dense Amorphous Polymer Systems: Method Development and Validation with 2-D Lattices, arXiV, 2008] in applications involving large lattice sizes and high energetic bias. We first demonstrate how the topology of the microstate ensemble in 2-D lattices presents a serious challenge for the collection of accurate and reliable quantitative results (i.e., with simultaneous determination of error bars) for large lattices. This necessitates a further enhancement of our Monte Carlo simulation scheme to sample effectively a meaningful 2-D lattice configurational subspace. Two techniques were investigated: simulated annealing and parallel tempering, to avoid trapping near a local free energy minimum in simulations at high energetic bias. Extensive results of the prediction of various chain conformation statistics and thermodynamic quantities, in the thermodynamic limit (i.e. infinite lateral sizes) are presented.