Bayesian optimization of Martini3 bonded parameters reduces density and radius-of-gyration errors for PE, PMMA, and PS melts at four degrees of polymerization, though the reported errors are in-sample fits rather than out-of-sample predictions.
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Refining Coarse-Grained Molecular Topologies: A Bayesian Optimization Approach
Bayesian optimization of Martini3 bonded parameters reduces density and radius-of-gyration errors for PE, PMMA, and PS melts at four degrees of polymerization, though the reported errors are in-sample fits rather than out-of-sample predictions.