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Chimia|May 9, 2026
General Reaction Conditions <i>via</i> Data-driven OptimisationStefan P Schmid, Kjell JornerChimia|October 29, 2025
Educating Future Chemists in the Age of AI: A Digital Chemistry CourseLauriane Jacot-Descombes, Stefan P Schmid, Kjell JornerBeilstein Journal of Organic Chemistry|September 18, 2024
Catalysing (organo-)catalysis: Trends in the application of machine learning to enantioselective organocatalysisStefan P Schmid, Leon Schlosser, Frank Glorius, et al.Journal of Chemical Information and Modeling|February 12, 2026
Rapid Generation of Transition-State Conformer Ensembles via Constrained Distance GeometryStefan P Schmid, Henrik Seng, Thibault Kläy, et al.Chimia|December 4, 2023
Putting Chemical Knowledge to Work in Machine Learning for ReactivityKjell JornerScientific Data|February 1, 2023
Reaction profiles for quantum chemistry-computed [3 + 2] cycloaddition reactionsThijs Stuyver, Kjell Jorner, Connor W ColeyThe Journal of Physical Chemistry. A|March 14, 2024
Ultrafast Computational Screening of Molecules with Inverted Singlet-Triplet Energy Gaps Using the Pariser-Parr-Pople Semiempirical Quantum Chemistry MethodKjell Jorner, Robert Pollice, Cyrille Lavigne, et al.Chemical Science|May 8, 2018
Triplet state homoaromaticity: concept, computational validation and experimental relevanceKjell Jorner, Burkhard O Jahn, Patrick Bultinck, et al.Chemical Science|October 27, 2022
Machine learning meets mechanistic modelling for accurate prediction of experimental activation energiesKjell Jorner, Tore Brinck, Per-Ola Norrby, et al.Chemistry (Weinheim an Der Bergstrasse, Germany)|July 7, 2017
Cyclopropyl Group: An Excited-State Aromaticity Indicator?Rabia Ayub, Raffaello Papadakis, Kjell Jorner, et al.Pageof 5