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Results: 19

Sergei F. Vyboishchikov
Atomic Charges via Gradient Boosting: Development and Application for Solvation Energies in Organic Solvents
J Comput Chem, 2026, 47, ASAP-
DOI: 10.1002/jcc.70310
OpenAccess: –
Keywords: Chemical bonding, Machine learning, Method development

Raquel Parrondo-Pizarro, Jessica Lanini, Raquel Rodríguez-Pérez
Uncertainty Quantification in Molecular Machine Learning for Property Predictions under Data Shifts
J. Chem. Inf. Model., 2026, 66, 923-935
DOI: 10.1021/acs.jcim.5c02381
OpenAccess: Link
Keywords: Chemoinformatics, Machine learning

Huda Alsaud, Ramon Carbó-Dorca
Fermat Polynomials and Extended Fermat’s Theorem
JAMP, 2026, 14, 1699-1713
DOI: 10.4236/jamp.2026.144080
OpenAccess: Link
Keywords: Computational chemistry, Machine learning

Miguel Martinez‐Fernandez, MdBin Yeamin, David Dalmau, Jorge J. Carbó, Albert Poater, Juan V. Alegre‐Requena
Data‐Driven Analysis of Ni‐Catalyzed Semihydrogenations of Alkynes
Adv Synth Catal, 2025, 5, 656-658
DOI: 10.1002/adsc.202401444
OpenAccess: –
Keywords: Computational chemistry, Homogeneous catalysis, Machine learning, Predictive Chemistry, Reaction mechanisms

Michele Tomasini, Michal Szostak, Albert Poater
Machine Learning in Predicting Activation Barrier Energy of C=N Bond Rotation in Amides
Asian J Org Chem, 2025, 14, e202400749
DOI: 10.1002/ajoc.202400749
OpenAccess: Link
Keywords: Computational chemistry, Machine learning, Organometallics, Predictive Chemistry, Reaction mechanisms

Zhen Cao, Laura Falivene, Albert Poater, Bholanath Maity, Ziyung Zhang, Gentoku Takasao, SadeedBin Sayed, Andrea Petta, Giovanni Talarico, Romina Oliva, Luigi Cavallo
COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets
Cell Reports Physical Science, 2025, 6, 102348-
DOI: 10.1016/j.xcrp.2024.102348
OpenAccess: –
Keywords: Chemical bonding, Computational chemistry, Joint Exp-Comp, Machine learning, Predictive Chemistry

Thalía Ortiz-García, Sergio Posada-Pérez, Layla El-Khchin, David Dalmau, JuanV. Alegre-Requena, Miquel Solà, Valerio D’Elia, Albert Poater
Systematic investigation of the role of the epoxides as substrates for CO₂ capture in the cycloaddition reaction catalysed by ascorbic acid
Ind. Chem. Mater., 2025, 3, 452-463
DOI: 10.1039/D5IM00037H
OpenAccess: Link
Keywords: Cycloaddition, Machine learning, Predictive Chemistry, Reaction mechanisms, Sustainable Catalysis

Raquel Parrondo-Pizarro, Luca Menestrina, Ricard Garcia-Serna, Adrià Fernández-Torras, Jordi Mestres
Enhancing molecular property prediction through data integration and consistency assessment
J Cheminform, 2025, 17, ASAP-
DOI: 10.1186/s13321-025-01103-3
OpenAccess: Link
Keywords: Chemoinformatics, Machine learning

Sergei F. Vyboishchikov
Atomic Neural Network for Calculation of Solvation Free Energies in Organic Solvents
J Comput Chem, 2025, 46, e70104
DOI: 10.1002/jcc.70104
OpenAccess: –
Keywords: Machine learning, Method development

Evert Jan Baerends, Nestor F. Aguirre, Nick D. Austin, Jochen Autschbach, F. Matthias Bickelhaupt, Rosa Bulo, Chiara Cappelli, Adri C. T. van Duin, Franco Egidi, Célia Fonseca Guerra, Arno Förster, Mirko Franchini, Theodorus P. M. Goumans, Thomas Heine, Matti Hellström, Christoph R. Jacob, Lasse Jensen, Mykhaylo Krykunov, Erik van Lenthe, Artur Michalak, Mariusz M. Mitoraj, Johannes Neugebauer, Valentin Paul Nicu, Pier Philipsen, Harry Ramanantoanina, Robert Rüger, Georg Schreckenbach, Mauro Stener, Marcel Swart, Jos M. Thijssen, Tomás Trnka, Lucas Visscher, Alexei Yakovlev, Stan van Gisbergen
The Amsterdam Modeling Suite
J. Chem. Phys., 2025, 162, 162501
DOI: 10.1063/5.0258496
OpenAccess: Link
Keywords: Computational chemistry, Machine learning, Method development, Spectroscopy