Results: 61
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
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
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
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
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
Sílvia Escayola, Nathalie Proos Vedin, Albert Poater, Henrik Ottosson, Miquel Solà
In the quest of Hückel‐Hückel and Hückel‐Baird double aromatic tropylium (tri)cation and anion derivatives
J. Phys. Chem., 2023, 36, e4447
DOI: 10.1002/poc.4447Keywords: Aromaticity, Chemical bonding, Excited states