Results: 46
Sebastian P. Sitkiewicz, RubénR. Ferradás, Eloy Ramos-Cordoba, Robert Zaleśny, Eduard Matito, Josep M. Luis
Spurious Oscillations Caused by Density Functional Approximations: Who is to Blame? Exchange or Correlation?
J. Chem. Theory Comput., 2024, 20, 3144-3153
DOI: 10.1021/acs.jctc.3c01339Keywords: Computational chemistry, Method development, Nonlinear optical properties, Spectroscopy
SergeiF. Vyboishchikov
Solvation Enthalpies and Free Energies for Organic Solvents through a Dense Neural Network: A Generalized-Born Approach
Liquids, 2024, 4, 525-538
DOI: 10.3390/liquids4030030Keywords: Machine learning, Method development
Sergei F. Vyboishchikov
A quick solvation energy estimator based on electronegativity equalization
J Comput Chem, 2023, 44, 307-318
DOI: 10.1002/jcc.26894Keywords: Computational chemistry, Method development
Sergei F. Vyboishchikov
Dense Neural Network for Calculating Solvation Free Energies from Electronegativity-Equalization Atomic Charges
J. Chem. Inf. Model., 2023, 63, 6283-6292
DOI: 10.1021/acs.jcim.3c00922Keywords: Machine learning, Method development
Pau Besalú-Sala, Alexander A. Voityuk, Josep M. Luis, Miquel Solà
Effect of external electric fields in the charge transfer rates of donor–acceptor dyads: A straightforward computational evaluation
J. Chem. Phys, 2023, 158, 244111
DOI: 10.1063/5.0148941Keywords: Chemical bonding, Electron and energy transfer, Excited states, Method development, Photovoltaic materials
Elizaveta F. Petrusevich, Manon H. E. Bousquet, Borys Ośmiałowski, Denis Jacquemin, Josep M. Luis, Robert Zaleśny
Cost-Effective Simulations of Vibrationally-Resolved Absorption Spectra of Fluorophores with Machine-Learning-Based Inhomogeneous Broadening
J. Chem. Theory Comput., 2023, 19, 2304-2315
DOI: 10.1021/acs.jctc.2c01285Keywords: Computational chemistry, Excited states, Machine learning, Method development, Spectroscopy
Sergei F. Vyboishchikov
Predicting Solvation Free Energies Using Electronegativity-Equalization Atomic Charges and a Dense Neural Network: A Generalized-Born Approach
J. Chem. Theory Comput., 2023, 19, 8340-8350
DOI: 10.1021/acs.jctc.3c00858Keywords: Machine learning, Method development
Alex Iglesias-Reguant, Heribert Reis, Miroslav Medveď, Josep M. Luis, Robert Zaleśny
A new computational tool for interpreting the infrared spectra of molecular complexes
Phys. Chem. Chem. Phys., 2023, 25, 11658-11664
DOI: 10.1039/D2CP03562FKeywords: Chemical bonding, Computational chemistry, Method development, Non-covalent interactions, Spectroscopy
Alex Iglesias-Reguant, Heribert Reis, Miroslav Medved’, Borys Ośmiałowski, Robert Zaleśny, Josep M. Luis
Decoding the infrared spectra changes upon formation of molecular complexes: the case of halogen bonding in pyridine⋯perfluorohaloarene complexes
Phys. Chem. Chem. Phys., 2023, 25, 20173-20177
DOI: 10.1039/D3CP02412AKeywords: Chemical bonding, Computational chemistry, Method development, Spectroscopy
Sebastian P. Sitkiewicz, Eduard Matito, Josep M. Luis, Robert Zaleśny
Pitfall in simulations of vibronic TD-DFT spectra: diagnosis and assessment
Phys. Chem. Chem. Phys., 2023, 25, 30193-30197
DOI: 10.1039/D3CP04276FKeywords: Computational chemistry, Excited states, Method development, Spectroscopy