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

J Chem Theory Comput. 2024 Dec 10;20(23):10697-10702. doi: 10.1021/acs.jctc.4c01260. Epub 2024 Nov 21.

Abstract

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.