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2025

Data‐Driven Analysis of Ni‐Catalyzed Semihydrogenations of Alkynes

Authors: Miguel Martinez‐Fernandez, Md Bin Yeamin, David Dalmau, Jorge J. Carbó, Albert Poater, Juan V. Alegre‐Requena

Advanced Synthesis & Catalysis, 2025, 367, 9

DOI: 10.1002/adsc.202401444

Keywords: Computational chemistry, Homogeneous catalysis, Machine learning, Predictive Chemistry, Reaction mechanisms

Atomic Neural Network for Calculation of Solvation Free Energies in Organic Solvents

Authors: Sergei F. Vyboishchikov

Journal of Computational Chemistry, 2025, 46, 11

DOI: 10.1002/jcc.70104

Keywords: Machine learning, Method development

The Amsterdam Modeling Suite

Authors: 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, Tomáš Trnka, Lucas Visscher, Alexei Yakovlev, Stan van Gisbergen

The Journal of Chemical Physics, 2025, 162, 16

DOI: 10.1063/5.0258496

Keywords: Computational chemistry, Machine learning, Method development, Spectroscopy

Machine Learning in Predicting Activation Barrier Energy of C=N Bond Rotation in Amides

Authors: Michele Tomasini, Michal Szostak, Albert Poater

Asian Journal of Organic Chemistry, 2025, 14, 4

DOI: 10.1002/ajoc.202400749

Keywords: Computational chemistry, Machine learning, Organometallics, Predictive Chemistry, Reaction mechanisms

COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets

Authors: Zhen Cao, Laura Falivene, Albert Poater, Bholanath Maity, Ziyung Zhang, Gentoku Takasao, Sadeed Bin Sayed, Andrea Petta, Giovanni Talarico, Romina Oliva, Luigi Cavallo

Cell Reports Physical Science, 2025, 6, 1, 102348

DOI: 10.1016/j.xcrp.2024.102348

Keywords: Chemical bonding, Computational chemistry, Joint Exp-Comp, Machine learning, Predictive Chemistry