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The Journal of Chemical Physics
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October 10, 2014
Vibronic coupling in asymmetric bichromophores: theory and application to diphenylmethane-d(5)
Benjamin Nebgen, Lyudmila V Slipchenko
The Journal of Physical Chemistry. A
|
April 20, 2023
Machine Learning Models Capture Plasmon Dynamics in Ag Nanoparticles
Adela Habib, Nicholas Lubbers, Sergei Tretiak, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
July 1, 2022
Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics
Guoqing Zhou, Nicholas Lubbers, Kipton Barros, et al.
The Journal of Chemical Physics
|
September 1, 2019
The effects of site asymmetry on near-degenerate state-to-state vibronic mixing in flexible bichromophores
Nathanael M Kidwell, Benjamin Nebgen, Lyudmila V Slipchenko, et al.
Physical Chemistry Chemical Physics : PCCP
|
July 25, 2023
Neural network atomistic potentials for global energy minima search in carbon clusters
Nikolay V Tkachenko, Anastasiia A Tkachenko, Benjamin Nebgen, et al.
The Journal of Chemical Physics
|
May 9, 2023
Lightweight and effective tensor sensitivity for atomistic neural networks
Michael Chigaev, Justin S Smith, Steven Anaya, et al.
Nature Computational Science
|
January 4, 2024
Uncertainty-driven dynamics for active learning of interatomic potentials
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Scientific Data
|
May 3, 2020
The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules
Justin S Smith, Roman Zubatyuk, Benjamin Nebgen, et al.
Journal of Chemical Theory and Computation
|
May 10, 2023
Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Journal of Chemical Theory and Computation
|
August 2, 2018
Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks
Benjamin Nebgen, Nicholas Lubbers, Justin S Smith, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 21) with videos related to
Sort By:
Page
of 3
The Journal of Chemical Physics
|
October 10, 2014
Vibronic coupling in asymmetric bichromophores: theory and application to diphenylmethane-d(5)
Benjamin Nebgen, Lyudmila V Slipchenko
The Journal of Physical Chemistry. A
|
April 20, 2023
Machine Learning Models Capture Plasmon Dynamics in Ag Nanoparticles
Adela Habib, Nicholas Lubbers, Sergei Tretiak, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
July 1, 2022
Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics
Guoqing Zhou, Nicholas Lubbers, Kipton Barros, et al.
The Journal of Chemical Physics
|
September 1, 2019
The effects of site asymmetry on near-degenerate state-to-state vibronic mixing in flexible bichromophores
Nathanael M Kidwell, Benjamin Nebgen, Lyudmila V Slipchenko, et al.
Physical Chemistry Chemical Physics : PCCP
|
July 25, 2023
Neural network atomistic potentials for global energy minima search in carbon clusters
Nikolay V Tkachenko, Anastasiia A Tkachenko, Benjamin Nebgen, et al.
The Journal of Chemical Physics
|
May 9, 2023
Lightweight and effective tensor sensitivity for atomistic neural networks
Michael Chigaev, Justin S Smith, Steven Anaya, et al.
Nature Computational Science
|
January 4, 2024
Uncertainty-driven dynamics for active learning of interatomic potentials
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Scientific Data
|
May 3, 2020
The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules
Justin S Smith, Roman Zubatyuk, Benjamin Nebgen, et al.
Journal of Chemical Theory and Computation
|
May 10, 2023
Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Journal of Chemical Theory and Computation
|
August 2, 2018
Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks
Benjamin Nebgen, Nicholas Lubbers, Justin S Smith, et al.
Page
of 3