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Journal of Computer-Aided Molecular Design
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October 9, 2020
Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications
Tobias Morawietz, Nongnuch Artrith
Nano Letters
|
April 19, 2014
Understanding the composition and activity of electrocatalytic nanoalloys in aqueous solvents: a combination of DFT and accurate neural network potentials
Nongnuch Artrith, Alexie M Kolpak
The Journal of Chemical Physics
|
July 2, 2018
Constructing first-principles phase diagrams of amorphous Li<sub>x</sub>Si using machine-learning-assisted sampling with an evolutionary algorithm
Nongnuch Artrith, Alexander Urban, Gerbrand Ceder
The Journal of Chemical Physics
|
May 23, 2012
Construction of high-dimensional neural network potentials using environment-dependent atom pairs
K V Jovan Jose, Nongnuch Artrith, Jörg Behler
Chemistry of Materials : a Publication of the American Chemical Society
|
August 15, 2022
Artificial Intelligence-Aided Mapping of the Structure-Composition-Conductivity Relationships of Glass-Ceramic Lithium Thiophosphate Electrolytes
Haoyue Guo, Qian Wang, Alexander Urban, et al.
Physical Chemistry Chemical Physics : PCCP
|
October 18, 2016
Reduced overpotentials for electrocatalytic water splitting over Fe- and Ni-modified BaTiO<sub>3</sub>
Nongnuch Artrith, Wutthigrai Sailuam, Sukit Limpijumnong, et al.
Chemsuschem
|
July 29, 2015
Engineering Transition-Metal-Coated Tungsten Carbides for Efficient and Selective Electrochemical Reduction of CO2 to Methane
Sippakorn Wannakao, Nongnuch Artrith, Jumras Limtrakul, et al.
Physical Review Letters
|
December 9, 2017
Electronic-Structure Origin of Cation Disorder in Transition-Metal Oxides
Alexander Urban, Aziz Abdellahi, Stephen Dacek, et al.
The Journal of Physical Chemistry. A
|
January 1, 2009
Structure and dynamics of water confined in single-wall nanotubes
Tanin Nanok, Nongnuch Artrith, Piboon Pantu, et al.
The Journal of Chemical Physics
|
August 22, 2021
AENET-LAMMPS and AENET-TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials
Michael S Chen, Tobias Morawietz, Hideki Mori, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 18) with videos related to
Sort By:
Page
of 2
Journal of Computer-Aided Molecular Design
|
October 9, 2020
Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications
Tobias Morawietz, Nongnuch Artrith
Nano Letters
|
April 19, 2014
Understanding the composition and activity of electrocatalytic nanoalloys in aqueous solvents: a combination of DFT and accurate neural network potentials
Nongnuch Artrith, Alexie M Kolpak
The Journal of Chemical Physics
|
July 2, 2018
Constructing first-principles phase diagrams of amorphous Li<sub>x</sub>Si using machine-learning-assisted sampling with an evolutionary algorithm
Nongnuch Artrith, Alexander Urban, Gerbrand Ceder
The Journal of Chemical Physics
|
May 23, 2012
Construction of high-dimensional neural network potentials using environment-dependent atom pairs
K V Jovan Jose, Nongnuch Artrith, Jörg Behler
Chemistry of Materials : a Publication of the American Chemical Society
|
August 15, 2022
Artificial Intelligence-Aided Mapping of the Structure-Composition-Conductivity Relationships of Glass-Ceramic Lithium Thiophosphate Electrolytes
Haoyue Guo, Qian Wang, Alexander Urban, et al.
Physical Chemistry Chemical Physics : PCCP
|
October 18, 2016
Reduced overpotentials for electrocatalytic water splitting over Fe- and Ni-modified BaTiO<sub>3</sub>
Nongnuch Artrith, Wutthigrai Sailuam, Sukit Limpijumnong, et al.
Chemsuschem
|
July 29, 2015
Engineering Transition-Metal-Coated Tungsten Carbides for Efficient and Selective Electrochemical Reduction of CO2 to Methane
Sippakorn Wannakao, Nongnuch Artrith, Jumras Limtrakul, et al.
Physical Review Letters
|
December 9, 2017
Electronic-Structure Origin of Cation Disorder in Transition-Metal Oxides
Alexander Urban, Aziz Abdellahi, Stephen Dacek, et al.
The Journal of Physical Chemistry. A
|
January 1, 2009
Structure and dynamics of water confined in single-wall nanotubes
Tanin Nanok, Nongnuch Artrith, Piboon Pantu, et al.
The Journal of Chemical Physics
|
August 22, 2021
AENET-LAMMPS and AENET-TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials
Michael S Chen, Tobias Morawietz, Hideki Mori, et al.
Page
of 2