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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/app13021122
Keywords: 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.202201204
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.26894
Keywords: Computational chemistry, Method development

SergeiF. 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.3c00922
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: 10.1063/5.0142778
Keywords: 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: 10.1063/5.0148941
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.2c01285
Keywords: 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.3c00143
Keywords: 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.3c00674
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.3c00858
Keywords: Machine learning, Method development

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