235 citations · 959 across the 12 of their papers we have counts for
12 papers
Machine learning the quantum flux-flux correlation function for catalytic surface reactions
Brenden G. Pelkie, Stephanie Valleau
A dataset of fully quantum flux-flux correlation functions and reaction rate constants was constructed for organic heterogeneous catalytic surface reactions. Gaussian process regre…
Low-cost prediction of molecular and transition state partition functions via machine learning
Evan Komp, Stéphanie Valleau
We have generated an open-source dataset of over 30000 organic chemistry gas phase partition functions. With this data, a machine learning deep neural network estimator was trained…
Machine Learning Quantum Reaction Rate Constants
Evan Komp, Stéphanie Valleau
The ab initio calculation of exact quantum reaction rate constants comes at a high cost due to the required dynamics of reactants on multidimensional potential energy surfaces. In…
Reaction dynamics of cyanohydrins with hydrosulfide in water
Stéphanie Valleau, Todd J. Martínez
We studied the reaction dynamics of a proposed prebiotic reaction theoretically. The chemical process involves acetone cyanohydrin or formalcyanohydrin reacting with hydrosulfide i…
Absence of selection for quantum coherence in the Fenna-Matthews-Olson complex: a combined evolutionary and excitonic study
Stéphanie Valleau, Romain A. Studer, Florian Häse +5
We present a study on the evolution of the Fenna-Matthews-Olson bacterial photosynthetic pigment-protein complex. This protein complex functions as an antenna. It transports absorb…
Machine Learning Exciton Dynamics
Florian Häse, Stéphanie Valleau, Edward Pyzer-Knapp +1
Obtaining the exciton dynamics of large photosynthetic complexes by using mixed quantum mechanics/molecular mechanics (QM/MM) is computationally demanding. We propose a machine lea…