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Publications
Results: 125
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
Shiyi Yang, Xiang Yu, Yaxu Liu, Michele Tomasini, Lucia Caporaso, Albert Poater, Luigi Cavallo, CatherineS.J. Cazin, StevenP. Nolan, Michal Szostak
Suzuki–Miyaura Cross-Coupling of Amides by N–C Cleavage Mediated by Air-Stable, Well-Defined [Pd(NHC)(sulfide)Cl] Catalysts: Reaction Development, Scope, and Mechanism
J. Org. Chem., 2023, 88, 10858-10868
DOI: 10.1021/acs.joc.3c00912Keywords: Computational chemistry, Cross-coupling reactions, Homogeneous catalysis, Organometallics, Reaction mechanisms
Roger Monreal-Corona, Miquel Solà, Anna Pla-Quintana, Albert Poater
Stereoretentive Formation of Cyclobutanes from Pyrrolidines: Lessons Learned from DFT Studies of the Reaction Mechanism
J. Org. Chem., 2023, 88, 4619–4626
DOI: 10.1021/acs.joc.3c00080Keywords: Computational chemistry, Density Functional Theory, Predictive Chemistry, Reaction mechanisms