Atomistic neural network representations for chemical dynamics simulations of molecular, condensed phase, and interfacial systems: efficiency, representability, and …
Abstract Machine learning techniques have been widely applied in many fields of chemistry,
physics, biology, and materials science. One of the most fruitful applications is machine …
physics, biology, and materials science. One of the most fruitful applications is machine …
[HTML][HTML] Non-adiabatic effects in elementary reaction processes at metal surfaces
M Alducin, RD Muiño, JI Juaristi - Progress in Surface Science, 2017 - Elsevier
Great success has been achieved in the modeling of gas-surface elementary processes by
the use of the Born-Oppenheimer approximation. However, in metal surfaces low energy …
the use of the Born-Oppenheimer approximation. However, in metal surfaces low energy …
Computational approaches to dissociative chemisorption on metals: towards chemical accuracy
GJ Kroes - Physical Chemistry Chemical Physics, 2021 - pubs.rsc.org
We review the state-of-the-art in the theory of dissociative chemisorption (DC) of small gas
phase molecules on metal surfaces, which is important to modeling heterogeneous catalysis …
phase molecules on metal surfaces, which is important to modeling heterogeneous catalysis …
High-dimensional atomistic neural network potentials for molecule–surface interactions: HCl scattering from Au (111)
Ab initio molecular dynamics (AIMD) simulations of molecule–surface scattering allow first-
principles characterization of the dynamics. However, the large number of density functional …
principles characterization of the dynamics. However, the large number of density functional …
Chemical dynamics from the gas‐phase to surfaces
The field of gas‐phase chemical dynamics has developed superb experimental methods to
probe the detailed outcome of gas‐phase chemical reactions. These experiments inspired …
probe the detailed outcome of gas‐phase chemical reactions. These experiments inspired …
Constructing high-dimensional neural network potential energy surfaces for gas–surface scattering and reactions
While the ab initio molecular dynamics (AIMD) approach to gas–surface interaction has
been instrumental in exploring important issues such as energy transfer and reactivity, it is …
been instrumental in exploring important issues such as energy transfer and reactivity, it is …
Symmetry-adapted high dimensional neural network representation of electronic friction tensor of adsorbates on metals
Nonadiabatic effects in chemical reaction at metal surfaces, due to excitation of electron–
hole pairs, stand at the frontier of the studies of gas-surface reaction dynamics. However, the …
hole pairs, stand at the frontier of the studies of gas-surface reaction dynamics. However, the …
Dynamics in reactions on metal surfaces: A theoretical perspective
Recent advances in theoretical characterization of reaction dynamics on metal surfaces are
reviewed. It is shown that the widely available density functional theory of metals and their …
reviewed. It is shown that the widely available density functional theory of metals and their …
Energy dissipation at metal surfaces
Conversion of energy at the gas–solid interface lies at the heart of many industrial
applications such as heterogeneous catalysis. Dissipation of parts of this energy into the …
applications such as heterogeneous catalysis. Dissipation of parts of this energy into the …
New Perspectives on CO2–Pt(111) Interaction with a High-Dimensional Neural Network Potential Energy Surface
M del Cueto, X Zhou, L Zhou, Y Zhang… - The Journal of …, 2020 - ACS Publications
CO oxidation on transition metal surfaces is not only a prototype for studying surface
chemistry but also of critical importance in applications such as pollution control and fuel …
chemistry but also of critical importance in applications such as pollution control and fuel …