Papers › Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers
Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers
Lijie Ding, Chi-Huan Tung, Bobby G. Sumpter, Wei-Ren Chen, Changwoo Do
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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.
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