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• W2052512084 abstract "The use of molecular similarity to develop reliable low-cost quantum mechanical models for use in quantum mechanical/molecular mechanical simulations of chemical reactions is explored, using the H + HF → H2 + F collinear reaction as a test case. The approach first generates detailed quantum chemical data for the reaction center in geometries and electrostatic environments that span those expected to arise during the molecular dynamics simulations. For each geometry and environment, both high- and low-level ab initio calculations are performed. A model is then developed to predict the high-level results using only inputs generated from the low-level theory. The inputs used here are based on principal component analysis of the low-level distributed multipoles, and the model is a simple linear regression. The distributed multipoles are monopoles, dipoles, and quadrupoles at each atomic center, and they summarize the electronic distribution in a manner that is comparable across basis set. The error in the model is dominated by extrapolation from small to large basis sets, with extrapolation from uncorrelated to correlated methods contributing much less error. A single regression can be used to make predictions for a range of reaction-center geometries and environments. For the trial collinear reaction, separate regressions were developed for the transition region and the entrance and exit channels. These models can predict the results of CCSD(T)/cc-pVTZ computations from HF/3-21G distributed multipoles, with an average error for the reaction energy profile of 0.69 kcal/mol." @default.
• W2052512084 created "2016-06-24" @default.
• W2052512084 creator A5023428146 @default.
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• W2052512084 date "2009-11-19" @default.
• W2052512084 modified "2023-09-27" @default.
• W2052512084 title "Using Molecular Similarity to Develop Reliable Models of Chemical Reactions in Complex Environments" @default.
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• W2052512084 doi "https://doi.org/10.1021/ct9004195" @default.
• W2052512084 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26602502" @default.
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