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Publications
Results: 1784
Jordi Poater, Sílvia Escayola, Albert Poater, Francesc Teixidor, Henrik Ottosson, Clara Viñas, Miquel Solà
Single─Not Double─3D-Aromaticity in an OxidizedCloso Icosahedral Dodecaiodo-Dodecaborate Cluster
J. Am. Chem. Soc., 2023, [], ASAP-
DOI: 10.1021/jacs.3c07335Keywords: Aromaticity, Chemical bonding, Excited states, Nanomaterials
Folorunsho Bright Omage, Andrea Madabeni, Amanda Resende Tucci, Pablo Andrei Nogara, Marco Bortoli, Alicedos Santos Rosa, Vivian Neuza dos Santos Ferreira, João Batista Teixeira Rocha, Milene Dias Miranda, Laura Orian
Diphenyl Diselenide and SARS-CoV-2:in silico Exploration of the Mechanisms of Inhibition of Main Protease (Mpro ) and Papain-like Protease (PLpro )
J. Chem. Inf. Model., 2023, 63, 2226-2239
DOI: 10.1021/acs.jcim.3c00168Keywords: Computational chemistry
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
Martí Gimferrer, Pedro Salvador
Exact decompositions of the total KS-DFT exchange–correlation energy into one- and two-center terms
J. Chem. Phys, 2023, 158, 234105
DOI: 10.1063/5.0142778Keywords: Chemical bonding, Method development, Real-space analysis
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
Carmelo Naim, Pau Besalú-Sala, Robert Zaleśny, Josep M. Luis, Frédéric Castet, Eduard Matito
Are Accelerated and Enhanced Wave Function Methods Accurate to Compute Static Linear and Nonlinear Optical Properties?
J. Chem. Theory Comput., 2023, 19, 1753-1764
DOI: 10.1021/acs.jctc.2c01212Keywords: Computational chemistry, Nonlinear optical properties, Spectroscopy
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
Martí Gimferrer, Sergi Danés, Diego M. Andrada, Pedro Salvador
Merging the Energy Decomposition Analysis with the Interacting Quantum Atoms Approach
J. Chem. Theory Comput., 2023, 19, 3469–3485
DOI: 10.1021/acs.jctc.3c00143Keywords: Chemical bonding, Method development, Real-space analysis
Pau Besalú-Sala, Fabien Bruneval, ÁngelJosé Pérez-Jiménez, JuanCarlos Sancho-García, Mauricio Rodríguez-Mayorga
RPA, an Accurate and Fast Method for the Computation of Static Nonlinear Optical Properties
J. Chem. Theory Comput., 2023, 19, 6062-6069
DOI: 10.1021/acs.jctc.3c00674Keywords: Computational chemistry, Method development, Nonlinear optical properties
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