Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers
We develop off-lattice simulations of semiflexible polymer chains subjected to applied mechanical forces by using Markov Chain Monte Carlo. Our approach models the polymer as a chain of fixed length bonds, with configurations updated through adaptive nonlocal 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 the polymer conformation.
Authors
- Bobby G. Sumpter (ORCID: https://orcid.org/0000-0001-6341-0355)
- Chi-Huan Tung (ORCID: https://orcid.org/0000-0002-2197-2074)
- Lijie Ding (ORCID: https://orcid.org/0000-0002-2745-4606)
- Changwoo Do (ORCID: https://orcid.org/0000-0001-8358-8417)
- Wei‐Ren Chen (ORCID: https://orcid.org/0000-0002-5192-0777)
Institutions
- Oak Ridge National Laboratory (US)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1021/acs.jctc.4c01260
- Citations
- 5
- Primary Topic
- Force Microscopy Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.69
Funders
- Oak Ridge National Laboratory