J Chem Theory Comput. 2025 Dec 23. doi: 10.1021/acs.jctc.5c01509. Online ahead of print.
ABSTRACT
Statistical approaches are an increasingly powerful technique for characterizing changes in the electronic structure during reactions or molecular excitations. High-throughput studies in complex environments, in particular, benefit from methods that are both computationally efficient and require minimal pre- or postprocessing of electronic structure outputs. To address this need, we investigate optimal transport (OT), which compares probability distributions through a cost-minimizing transport plan. By applying OT to electron densities along a reaction coordinate and partitioning the resulting transport plan, we reveal how noncore electron density evolves during chemical processes. We demonstrate the approach on two systems: Bergman cyclization and proton transfer occurring within a water cluster. Along the intrinsic reaction coordinate of Bergman cyclization, OT yields chemically intuitive insights and complements information provided by the electron localization function. For the proton-transfer reaction, based on ab initio molecular dynamics, OT clearly identifies individual transfer events. Together, these studies demonstrate that optimal transport provides a promising new framework for investigating chemical reactivity.
PMID:41432932 | DOI:10.1021/acs.jctc.5c01509
