Using Monte Carlo to Simulate Complex Polymer Systems: Recent Progress and Outlook

Frontiers in Physics

Vlasis G. Mavrantzas¹ 

[1] Department of Chemical Engineering, University of Patras, Patras, Greece;Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology, Hellas (FORTH), Patras, Greece;Particle Technology Laboratory, Department of Mechanical and Process Engineering, ETH Zürich, Zürich, Switzerland;

关键词: Monte Carlo;    simulation;    polymers;    review;    progress;   

DOI  :  10.3389/fphy.2021.661367

来源: Frontiers

【 摘 要 】

Metropolis Monte Carlo has been employed with remarkable success over the years to simulate the dense phases of polymer systems. Owing, in particular, to the freedom it provides to accelerate sampling in phase space through the clever design and proper implementation of even unphysical moves that take the system completely away from its natural trajectory, and despite that it cannot provide any direct information about dynamics, it has turned to a powerful simulation tool today, often viewed as an excellent alternative to the other, most popular method of Molecular Dynamics. In the last years, Monte Carlo has advanced considerably thanks to the design of new moves or to the efficient implementation of existing ones to considerably more complex systems than those for which these were originally proposed. In this short review, we highlight recent progress in the field (with a clear emphasis in the last 10 years or so) by presenting examples from applications of the method to several systems in Soft Matter, such as polymer nanocomposites, soft nanostructured materials, confined polymers, polymer rings and knots, hydrogels and networks, crystalline polymers, and many others. We highlight, in particular, extensions of the method to non-equilibrium systems (e.g., polymers under steady shear flow) guided by non-equilibrium thermodynamics and emphasize the importance of hybrid modeling schemes (e.g., coupled Monte Carlo simulations with field theoretic calculations). We also include a short section discussing some key remaining challenges plus interesting future opportunities.

【 授权许可】

CC BY