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The Journal of Chemical Physics
|
September 15, 2023
Synergy of semiempirical models and machine learning in computational chemistry
Nikita Fedik, Benjamin Nebgen, Nicholas Lubbers, et al.
The Journal of Physical Chemistry Letters
|
July 25, 2018
Discovering a Transferable Charge Assignment Model Using Machine Learning
Andrew E Sifain, Nicholas Lubbers, Benjamin T Nebgen, et al.
Journal of Molecular Modeling
|
May 31, 2012
Validation of a novel secretion modification region (SMR) of HIV-1 Nef using cohort sequence analysis and molecular modeling
Patrick E Campbell, Olexandr Isayev, Syed A Ali, et al.
Crystal Growth & Design
|
November 10, 2025
Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials
Kamal Singh Nayal, Dana O'Connor, Roman Zubatyuk, et al.
Angewandte Chemie (International Ed. in English)
|
July 13, 2025
Design of Tough 3D Printable Elastomers with Human-in-the-Loop Reinforcement Learning
Johann L Rapp, Dylan M Anstine, Filipp Gusev, et al.
RSC Advances
|
May 11, 2022
Adsorption of nitrogen-containing compounds on hydroxylated α-quartz surfaces
Oksana Tsendra, A Daniel Boese, Olexandr Isayev, et al.
Communications Chemistry
|
January 25, 2023
Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds
Maria Korshunova, Niles Huang, Stephen Capuzzi, et al.
Nature Reviews. Chemistry
|
April 28, 2023
Extending machine learning beyond interatomic potentials for predicting molecular properties
Nikita Fedik, Roman Zubatyuk, Maksim Kulichenko, et al.
Nature Chemistry
|
March 7, 2024
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential
Shuhao Zhang, Małgorzata Z Makoś, Ryan B Jadrich, et al.
Nature Communications
|
October 17, 2025
AQuaRef: machine learning accelerated quantum refinement of protein structures
Roman Zubatyuk, Malgorzata Biczysko, Kavindri Ranasinghe, et al.
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of 10
Search research articles
Search
Showing results (71-80 of 93) with videos related to
Sort By:
Page
of 10
The Journal of Chemical Physics
|
September 15, 2023
Synergy of semiempirical models and machine learning in computational chemistry
Nikita Fedik, Benjamin Nebgen, Nicholas Lubbers, et al.
The Journal of Physical Chemistry Letters
|
July 25, 2018
Discovering a Transferable Charge Assignment Model Using Machine Learning
Andrew E Sifain, Nicholas Lubbers, Benjamin T Nebgen, et al.
Journal of Molecular Modeling
|
May 31, 2012
Validation of a novel secretion modification region (SMR) of HIV-1 Nef using cohort sequence analysis and molecular modeling
Patrick E Campbell, Olexandr Isayev, Syed A Ali, et al.
Crystal Growth & Design
|
November 10, 2025
Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials
Kamal Singh Nayal, Dana O'Connor, Roman Zubatyuk, et al.
Angewandte Chemie (International Ed. in English)
|
July 13, 2025
Design of Tough 3D Printable Elastomers with Human-in-the-Loop Reinforcement Learning
Johann L Rapp, Dylan M Anstine, Filipp Gusev, et al.
RSC Advances
|
May 11, 2022
Adsorption of nitrogen-containing compounds on hydroxylated α-quartz surfaces
Oksana Tsendra, A Daniel Boese, Olexandr Isayev, et al.
Communications Chemistry
|
January 25, 2023
Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds
Maria Korshunova, Niles Huang, Stephen Capuzzi, et al.
Nature Reviews. Chemistry
|
April 28, 2023
Extending machine learning beyond interatomic potentials for predicting molecular properties
Nikita Fedik, Roman Zubatyuk, Maksim Kulichenko, et al.
Nature Chemistry
|
March 7, 2024
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential
Shuhao Zhang, Małgorzata Z Makoś, Ryan B Jadrich, et al.
Nature Communications
|
October 17, 2025
AQuaRef: machine learning accelerated quantum refinement of protein structures
Roman Zubatyuk, Malgorzata Biczysko, Kavindri Ranasinghe, et al.
Page
of 10