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Olexandr Isayev

Showing results (51-60 of 93) with videos related to

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Journal of Molecular Modeling|July 8, 2011
Evaluation of natural and nitramine binding energies to 3-D models of the S1S2 domains in the N-methyl-D-aspartate receptorJason Ford-Green, Olexandr Isayev, Leonid Gorb, et al.
Scientific Reports|March 20, 2026
Interpretable machine learning for thermoelectric materials design with Kolmogorov-Arnold networksMarco Fronzi, Michael J Ford, Kamal Singh Nayal, et al.
Journal of Computational Chemistry|March 5, 2015
Are the reduction and oxidation properties of nitrocompounds dissolved in water different from those produced when adsorbed on a silica surface? A DFT M05-2X computational studyLiudmyla K Sviatenko, Olexandr Isayev, Leonid Gorb, et al.
Journal of Chemical Theory and Computation|July 8, 2026
Electron Alchemy with Machine-Learned Interatomic Potentials: Case Studies of Local Charge in Bond Dissociation CurvesEricka Roy Miller, Vignesh Sathyaseelan, Dylan M Gilley, et al.
JACS Au|October 31, 2025
Fast and Accurate Ring Strain Energy Predictions with Machine Learning and Application in Strain-Promoted ReactionsZhen Liu, Jessica Vinskus, Yue Fu, et al.
Physical Chemistry Chemical Physics : PCCP|January 22, 2011
Novel view on the mechanism of water-assisted proton transfer in the DNA bases: bulk water hydrationAl'ona Furmanchuk, Olexandr Isayev, Leonid Gorb, et al.
Bioinformatics (Oxford, England)|February 21, 2019
Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptidesSherif Farag, Rachel M Bleich, Elizabeth A Shank, et al.
Nature Chemistry|June 1, 2021
Best practices in machine learning for chemistryNongnuch Artrith, Keith T Butler, François-Xavier Coudert, et al.
Angewandte Chemie (International Ed. in English)|December 16, 2025
AIMNet2-NSE: A Transferable Reactive Neural Network Potential for Open-Shell ChemistryBhupalee Kalita, Roman Zubatyuk, Dylan M Anstine, et al.
Journal of Chemical Theory and Computation|June 17, 2020
Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and HalogensChristian Devereux, Justin S Smith, Kate K Huddleston, et al.
Pageof 10

Showing results (51-60 of 93) with videos related to

Sort By:
Pageof 10
Journal of Molecular Modeling|July 8, 2011
Evaluation of natural and nitramine binding energies to 3-D models of the S1S2 domains in the N-methyl-D-aspartate receptorJason Ford-Green, Olexandr Isayev, Leonid Gorb, et al.
Scientific Reports|March 20, 2026
Interpretable machine learning for thermoelectric materials design with Kolmogorov-Arnold networksMarco Fronzi, Michael J Ford, Kamal Singh Nayal, et al.
Journal of Computational Chemistry|March 5, 2015
Are the reduction and oxidation properties of nitrocompounds dissolved in water different from those produced when adsorbed on a silica surface? A DFT M05-2X computational studyLiudmyla K Sviatenko, Olexandr Isayev, Leonid Gorb, et al.
Journal of Chemical Theory and Computation|July 8, 2026
Electron Alchemy with Machine-Learned Interatomic Potentials: Case Studies of Local Charge in Bond Dissociation CurvesEricka Roy Miller, Vignesh Sathyaseelan, Dylan M Gilley, et al.
JACS Au|October 31, 2025
Fast and Accurate Ring Strain Energy Predictions with Machine Learning and Application in Strain-Promoted ReactionsZhen Liu, Jessica Vinskus, Yue Fu, et al.
Physical Chemistry Chemical Physics : PCCP|January 22, 2011
Novel view on the mechanism of water-assisted proton transfer in the DNA bases: bulk water hydrationAl'ona Furmanchuk, Olexandr Isayev, Leonid Gorb, et al.
Bioinformatics (Oxford, England)|February 21, 2019
Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptidesSherif Farag, Rachel M Bleich, Elizabeth A Shank, et al.
Nature Chemistry|June 1, 2021
Best practices in machine learning for chemistryNongnuch Artrith, Keith T Butler, François-Xavier Coudert, et al.
Angewandte Chemie (International Ed. in English)|December 16, 2025
AIMNet2-NSE: A Transferable Reactive Neural Network Potential for Open-Shell ChemistryBhupalee Kalita, Roman Zubatyuk, Dylan M Anstine, et al.
Journal of Chemical Theory and Computation|June 17, 2020
Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and HalogensChristian Devereux, Justin S Smith, Kate K Huddleston, et al.
Pageof 10