Machine Learning-Based Nonadiabatic Dynamics Paper in JPCA!

M’s paper has been published in JPCA. This paper has been a long time coming and was one of the first things we started working on after joining Mizzou, so we are quite pleased to see its completion. In the paper, we introduce a simple modification of Wigner sampling for generating training data for machine learning-based nonadiabatic dynamics. As is hinted at in the conclusions, M is rapidly working on extending the method to electronic Hamiltonians and we hope to continue to expand and follow up on this study in the future. Link is here: https://doi.org/10.1021/acs.jpca.0c07376

Multicomponent OOMP2 Paper in JCP

Jonathan’s paper has been published in JCP! In it we show that in multicomponent OOMP2 the electron-electron correlation can be included after the orbital-optimization procedure with essentially no loss in accuracy for protonic properties relative to the original multicomponent OOMP2 method. Using the results in this paper, we hypothesize that in all multicomponent orbital-optimized methods, it is sufficient to perform the orbital-optimization procedure solely in the presence of electron-proton correlation. Link is here: https://doi.org/10.1063/5.0006743