English

Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers

Soft Condensed Matter 2024-11-26 v1 Materials Science

Abstract

We develop off-lattice simulations of semiflexible polymer chains subjected to applied mechanical forces using Markov Chain Monte Carlo. Our approach models the polymer as a chain of fixed-length bonds, with configurations updated through adaptive non-local Monte Carlo moves. This proposed method enables precise calculation of a polymer's response to a wide range of mechanical forces, which traditional on-lattice models cannot achieve. Our approach has shown excellent agreement with theoretical predictions of persistence length and end-to-end distance in quiescent states, as well as stretching distances under tension. Moreover, our model eliminates the orientational bias present in on-lattice models, which significantly impacts calculations such as the scattering function, a crucial technique for revealing polymer conformation.

Keywords

Cite

@article{arxiv.2409.15223,
  title  = {Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers},
  author = {Lijie Ding and Chi-Huan Tung and Bobby G. Sumpter and Wei-Ren Chen and Changwoo Do},
  journal= {arXiv preprint arXiv:2409.15223},
  year   = {2024}
}

Comments

16 pages, 7 figures