Multiscale molecular engineering of a thermogelling polymer integrating quantum mechanics, polymer chemistry and artificial intelligence
Abstract
Polymeric materials are difficult to be theoretically designed in silico because the synthesis reaction spans vast spatiotemporal scales from quantum-level reaction, chain growth and diffusion to engineering-level production, and the condensed state is determined via hierarchical self-assembly. Here, we report a "4+1" strategy that combines four independent computational methods (density functional theory, kinetic Monte Carlo simulation, dynamic Monte Carlo simulation, and flowsheet synthesis) with one mapping experiment to realize a multiscale engineering study of a complex polymer system. Integration is achieved through a feedback-loop mapping experiment, which bridges calculated energy barriers (quantum chemistry) with polymerization kinetics (statistical physics), and a coarse-grained model that transforms realistic polymer chains into operable ones. Studying the polymerization of amphiphilic poly(lactide-co-glycolide)-b-poly(ethylene glycol)-b-poly(lactide-co-glycolide) with the method reveals distinct kinetic stages across 24 basic reactions (12 for ring-opening polymerization and 12 for ester exchange) spanning 19 temporal and 12 spatial scales. Both simulations and experiments show that the amphiphilic polymer products collected at different time points display varied yet controlled condensed states in water, such as sol, precipitate, and heating-induced physical hydrogel (thermogel) even at similar number-average molecular weights. Additionally, thermogellability is…
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