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- W3128176044 abstract "A promising approach for simulating rare events with rigorous kinetics is the weighted ensemble path sampling strategy. One challenge of this strategy is the division of configurational space into bins for sampling. Here we present a minimal adaptive binning (MAB) scheme for the automated, adaptive placement of bins along a progress coordinate within the framework of the weighted ensemble strategy. Results reveal that the MAB binning scheme, despite its simplicity, is more efficient than a manual, fixed binning scheme in generating transitions over large free energy barriers, generating a diversity of pathways, estimating rate constants, and sampling conformations. The scheme is general and extensible to any rare-events sampling strategy that employs progress coordinates." @default.
- W3128176044 created "2021-02-15" @default.
- W3128176044 creator A5016802018 @default.
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- W3128176044 date "2021-02-12" @default.
- W3128176044 modified "2023-10-06" @default.
- W3128176044 title "A Minimal, Adaptive Binning Scheme for Weighted Ensemble Simulations" @default.
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- W3128176044 doi "https://doi.org/10.1021/acs.jpca.0c10724" @default.
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