108 citations · 255 across the 7 of their papers we have counts for
11 papers · 1 filter
AutoMeKin2021: An open-source program for automated reaction discovery
Emilio Martínez-Núñez, George L. Barnes, David R. Glowacki +8
AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922-1930). This release features a numb…
ChemDyME: Kinetically Steered, Automated Mechanism Generation Through Combined Molecular Dynamics and Master Equation Calculations
Robin J. Shannon, Emilio Martinez Nunez, Dmitrii V. Shalashilin +1
In many scientific fields, there is an interest in understanding the way in which complex chemical networks evolve. The chemical networks which researchers focus upon, have become…
Nonadiabatic kinetics in the intermediate coupling regime: comparing molecular dynamics to an energy grained master equation
Darya Shchepanovska, Robin J. Shannon, Basile F. E. Curchod +1
Here we outline and test an extension of the energy grained master equation (EGME) for treating nonadiabatic (NA) hopping between different potential energy surfaces, which enables…
Training atomic neural networks using fragment-based data generated in virtual reality
Silvia Amabilino, Lars A. Bratholm, Simon J. Bennie +2
The ability to understand and engineer molecular structures relies on having accurate descriptions of the energy as a function of atomic coordinates. Here we outline a new paradigm…
Enhancing automated reaction discovery with boxed molecular dynamics in energy space
Rafael A. Jara-Toro, Gustavo A. Pino, David R. Glowacki +2
The rare event acceleration method BXDE is interfaced in the present work with the automated reaction discovery method AutoMeKin. To test the efficiency of the combined AutoMeKin-B…
IMPRESSION -- Prediction of NMR Parameters for 3-dimensional chemical structures using Machine Learning with near quantum chemical accuracy
Will Gerrard, Lars Andersen Bratholm, Martin Packer +3
The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar Information Of Nuclei) machine learning system provides an efficient and accurate route to the prediction of NMR…