In a pioneering exploration of polymer science, this study delves into the nuanced effects of
monomer sequencing on gas sorption properties, focusing on atactic polystyrene (aPS),
poly(methyl methacrylate) (PMMA), and their diverse block and random copolymer sequences.
Utilizing Molecular Dynamics (MD) simulations paired with the Optimized Potentials for Liquid
Simulations All-Atom (OPLS-AA) force field for polymer molecules and the Elementary Physical
Model 2 (EPM2) for CO2, the research meticulously analyzes various copolymer configurations,
including alternating monomer sequences (1), dimer sequences (2), tetra blocks (5), di blocks (10),
and random equimolar PMMA-PS sequences. This comprehensive investigation highlights
significant variations in CO2 sorption capacities across these sequences, revealing enhanced
sorption in complex copolymers compared to pure PMMA and PS. The incorporation of Grand
Canonical Monte Carlo (GCMC) methods within the NPT ensemble facilitates a multi-scale
analysis, from detailed molecular interactions to macroscopic sorption behaviors. Additionally, the
integration of AI and ML algorithms for predictive modeling, combined with coarse-grained
modeling, provides a deeper understanding of the sorption dynamics and the potential for material
optimization. This research, primarily focused on understanding gas sorption variations with
polymer sequence using computational simulations, advances our knowledge in polymer science
and opens new avenues for the development of materials with tailored gas sorption properties for
a range of applications.