Results: 77
JesusVicente de Julián-Ortiz, Emili Besalú
Application of SSIR Method for the Design of Fungicides
Applied Sciences, 2023, 13, 1122-
DOI: 10.3390/app13021122OpenAccess: LinkKeywords: Computational chemistry, Method development, Predictive Chemistry
Sethuraman Muthuramalingam, Marappan Velusamy, Swati Singh Rajput, Mehboob Alam, Ramasamy Mayilmurugan
Nickel(II) Complexes of Tripodal Ligands as Catalysts for Fixation of Atmospheric CO2 as Organic Carbonates
Chemistry, An Asian Journal, 2023, 18, e202201204
DOI: 10.1002/asia.202201204OpenAccess: –Keywords: Catalysis, Method development, Reaction mechanisms, Spectroscopy, Sustainable Catalysis
Sergei F. Vyboishchikov
A quick solvation energy estimator based on electronegativity equalization
J Comput Chem, 2023, 44, 307-318
DOI: 10.1002/jcc.26894OpenAccess: –Keywords: 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.3c00922OpenAccess: –Keywords: 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: 10.1063/5.0142778OpenAccess: LinkKeywords: 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: 10.1063/5.0148941OpenAccess: –Keywords: 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.2c01285OpenAccess: LinkKeywords: 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.3c00143OpenAccess: LinkKeywords: 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.3c00674OpenAccess: –Keywords: 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.3c00858OpenAccess: –Keywords: Machine learning, Method development