A semiflexible chain under extreme icosahedral confinement: Monte Carlo simulations on a quasi-lattice geometry

Simulating dense molecular systems, particularly a long chain under extreme confinement, remains a core challenge in molecular simulation and statistical mechanics. In this study, we identify a physics-informed approach for simulating a semiflexible chain under extreme icosahedral confinement. We proposed a quasi-lattice geometry, which was defined as a finite set of discrete sites under specific geometric constraints. Using the Metropolis algorithm as a baseline together with appropriate trial moves, we demonstrated the feasibility of performing Monte Carlo simulations on the quasi-lattice geometry. Given the difficulty of sampling a representative long chain consisting of 10 179 beads at a packing density near the bulk close-packing limit, our approach enables a rapid exploration of the accessible configuration space. Distinct low-temperature long-lived states were revealed by our approach and analyzed via orientational order parameters, suggesting richer structural possibilities than previously recognized. Possible states include weakly ordered states, an approximately uniaxial state, a biaxial-like state, and an interlayer orientational mismatch state. Our study suggests the potential of physics-informed computational strategies for simulating a long chain under extreme confinement and may provide insights into the confined chain structures in biorelevant crowded environments.