Machine learning for chemical reactions
M Meuwly - Chemical Reviews, 2021 - ACS Publications
Machine learning (ML) techniques applied to chemical reactions have a long history. The
present contribution discusses applications ranging from small molecule reaction dynamics …
present contribution discusses applications ranging from small molecule reaction dynamics …
Recent advances in quantum scattering calculations on polyatomic bimolecular reactions
B Fu, X Shan, DH Zhang, DC Clary - Chemical Society Reviews, 2017 - pubs.rsc.org
This review surveys quantum scattering calculations on chemical reactions of polyatomic
molecules in the gas phase published in the last ten years. These calculations are useful …
molecules in the gas phase published in the last ten years. These calculations are useful …
High-fidelity potential energy surfaces for gas-phase and gas–surface scattering processes from machine learning
In this Perspective, we review recent advances in constructing high-fidelity potential energy
surfaces (PESs) from discrete ab initio points, using machine learning tools. Such PESs …
surfaces (PESs) from discrete ab initio points, using machine learning tools. Such PESs …
Advances and new challenges to bimolecular reaction dynamics theory
Dynamics of bimolecular reactions in the gas phase are of foundational importance in
combustion, atmospheric chemistry, interstellar chemistry, and plasma chemistry. These …
combustion, atmospheric chemistry, interstellar chemistry, and plasma chemistry. These …
Permutation-Invariant-Polynomial Neural-Network-Based Δ-Machine Learning Approach: A Case for the HO2 Self-Reaction and Its Dynamics Study
Y Liu, J Li - The Journal of Physical Chemistry Letters, 2022 - ACS Publications
Δ-machine learning, or the hierarchical construction scheme, is a highly cost-effective
method, as only a small number of high-level ab initio energies are required to improve a …
method, as only a small number of high-level ab initio energies are required to improve a …
Many-Body Permutationally Invariant Polynomial Neural Network Potential Energy Surface for N4
A potential energy surface (PES) for high-energy collisions between nitrogen molecules is
useful for modeling chemical dynamics in shock waves and plasmas. In the present work …
useful for modeling chemical dynamics in shock waves and plasmas. In the present work …
[HTML][HTML] Permutation invariant polynomial neural network approach to fitting potential energy surfaces. IV. Coupled diabatic potential energy matrices
A machine learning method is proposed for representing the elements of diabatic potential
energy matrices (PEMs) with high fidelity. This is an extension of the so-called permutation …
energy matrices (PEMs) with high fidelity. This is an extension of the so-called permutation …
Probing the activated complex of the F + NH3 reaction via a dipole-bound state
Experimental characterization of the transition state poses a significant challenge due to its
fleeting nature. Negative ion photodetachment offers a unique tool for probing transition …
fleeting nature. Negative ion photodetachment offers a unique tool for probing transition …
Accurate Global Potential Energy Surfaces for the H + CH3OH Reaction by Neural Network Fitting with Permutation Invariance
The H+ CH3OH reaction, which plays an important role in combustion and the interstellar
medium, presents a prototypical system with multi channels and tight transition states …
medium, presents a prototypical system with multi channels and tight transition states …
Slow photoelectron velocity-map imaging of cryogenically cooled anions
ML Weichman, DM Neumark - Annual review of physical …, 2018 - annualreviews.org
Slow photoelectron velocity-map imaging spectroscopy of cryogenically cooled anions (cryo-
SEVI) is a powerful technique for elucidating the vibrational and electronic structure of …
SEVI) is a powerful technique for elucidating the vibrational and electronic structure of …