Kjell Jorner
Affiliations: | Eidgenössische Technische Hochschule Zürich, Zürich, ZH, Switzerland |
Area:
Digital chemistry, computational chemistry, machine learningGoogle:
"Kjell Jorner"Parents
Sign in to add mentor| Rolandh Lindh | grad student | 2013-2018 | Uppsala | |
| (Co-supervisor) | ||||
| Henrik Ottosson | grad student | 2013-2018 | Uppsala | |
| Per-Ola Norrby | post-doc | 2018-2020 | AstraZeneca | |
| Alán Aspuru-Guzik | post-doc | 2021-2022 | University of Toronto | |
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Publications
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| Valverde D, Ser CT, Ricci G, et al. (2024) Computational Investigations of the Detailed Mechanism of Reverse Intersystem Crossing in Inverted Singlet-Triplet Gap Molecules. Acs Applied Materials & Interfaces |
| Jorner K, Pollice R, Lavigne C, et al. (2024) Ultrafast Computational Screening of Molecules with Inverted Singlet-Triplet Energy Gaps Using the Pariser-Parr-Pople Semiempirical Quantum Chemistry Method. The Journal of Physical Chemistry. A. 128: 2445-2456 |
| Pablo-García S, Morandi S, Vargas-Hernández RA, et al. (2023) Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks. Nature Computational Science. 3: 433-442 |
| Jorner K, Tomberg A, Bauer C, et al. (2023) Publisher Correction: Organic reactivity from mechanism to machine learning. Nature Reviews. Chemistry. 5: 295 |
| Vargas-Hernández RA, Jorner K, Pollice R, et al. (2023) Inverse molecular design and parameter optimization with Hückel theory using automatic differentiation. The Journal of Chemical Physics. 158: 104801 |
| El Bakouri O, Szczepanik DW, Jorner K, et al. (2022) Three-Dimensional Fully π-Conjugated Macrocycles: When 3D-Aromatic and When 2D-Aromatic-in-3D? Journal of the American Chemical Society. 144: 8560-8575 |
| Gensch T, Dos Passos Gomes G, Friederich P, et al. (2022) A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis. Journal of the American Chemical Society |
| Jorner K, Tomberg A, Bauer C, et al. (2021) Organic reactivity from mechanism to machine learning. Nature Reviews. Chemistry. 5: 240-255 |
| Ayub R, El Bakouri O, Smith JR, et al. (2021) Triplet State Baird Aromaticity in Macrocycles: Scope, Limitations, and Complications. The Journal of Physical Chemistry. A. 125: 570-584 |
| Jorner K, Brinck T, Norrby PO, et al. (2020) Machine learning meets mechanistic modelling for accurate prediction of experimental activation energies. Chemical Science. 12: 1163-1175 |