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Machine learning-guided development of trialkylphosphine Ni(I) dimers and applications in site-selective catalysis

Machine learning-guided development of trialkylphosphine Ni(I) dimers and applications in site-selective catalysis
Machine learning-guided development of trialkylphosphine Ni(I) dimers and applications in site-selective catalysis

Owing to the unknown correlation of a metal’s ligand and its resulting preferred speciation in terms of oxidation state, geometry, and nuclearity, a rational design of multinuclear catalysts remains challenging. With the goal to accelerate the identification of suitable ligands that form trialkylphosphine-derived dihalogen-bridged Ni(I) dimers, we herein employed an assumption-based machine learning approach. The workflow offers guidance in ligand space for a desired speciation without (or only minimal) prior experimental data points. We experimentally verified the predictions and synthesized numerous novel Ni(I) dimers as well as explored their potential in catalysis. We demonstrate C-I selective arylations of polyhalogenated arenes bearing competing C-Br and C-Cl sites in under 5 min at room temperature using 0.2 mol % of the newly developed dimer, [Ni(I)(μ-Br)PAd2(n-Bu)]2, which is so far unmet with alternative dinuclear or mononuclear Ni or Pd catalysts

0002-7863
15414-15424
Karl, Teresa M.
410e5e27-0d10-455c-b2aa-1481be7125e3
Bouayad-Gervais, Samir
a95f2ba2-2498-4299-9c27-c991df111b5e
Hueffel, Julian A.
45b34cfa-1503-4af0-b53e-dd7e8f320f09
Sperger, Theresa
84d263cd-37df-4f08-958f-d5602f9e0216
Wellig, Sebastian
507dbd62-cb45-4bf2-a021-5bbe8c107b9e
Kaldas, Sherif J.
920d8788-800e-4898-8b13-10183a5940ef
Dabranskaya, Uladzislava
fcdb391c-83b3-45b5-80f6-7ef920e6d284
Ward, Jas S.
263fc49a-cdee-4489-84c9-0971bd4c99da
Rissanen, Kari
440e07e6-fd8f-49e4-aca3-f9d22b2818ee
Tizzard, Graham J.
8474c0fa-40df-43a6-a662-7f3c4722dbf2
Schoenebeck, Franziska
9a0896fb-1f0b-45e7-8236-76bd56932456
Karl, Teresa M.
410e5e27-0d10-455c-b2aa-1481be7125e3
Bouayad-Gervais, Samir
a95f2ba2-2498-4299-9c27-c991df111b5e
Hueffel, Julian A.
45b34cfa-1503-4af0-b53e-dd7e8f320f09
Sperger, Theresa
84d263cd-37df-4f08-958f-d5602f9e0216
Wellig, Sebastian
507dbd62-cb45-4bf2-a021-5bbe8c107b9e
Kaldas, Sherif J.
920d8788-800e-4898-8b13-10183a5940ef
Dabranskaya, Uladzislava
fcdb391c-83b3-45b5-80f6-7ef920e6d284
Ward, Jas S.
263fc49a-cdee-4489-84c9-0971bd4c99da
Rissanen, Kari
440e07e6-fd8f-49e4-aca3-f9d22b2818ee
Tizzard, Graham J.
8474c0fa-40df-43a6-a662-7f3c4722dbf2
Schoenebeck, Franziska
9a0896fb-1f0b-45e7-8236-76bd56932456

Karl, Teresa M., Bouayad-Gervais, Samir, Hueffel, Julian A., Sperger, Theresa, Wellig, Sebastian, Kaldas, Sherif J., Dabranskaya, Uladzislava, Ward, Jas S., Rissanen, Kari, Tizzard, Graham J. and Schoenebeck, Franziska (2023) Machine learning-guided development of trialkylphosphine Ni(I) dimers and applications in site-selective catalysis. Journal of the American Chemical Society, 145 (28), 15414-15424. (doi:10.1021/jacs.3c03403).

Record type: Article

Abstract

Owing to the unknown correlation of a metal’s ligand and its resulting preferred speciation in terms of oxidation state, geometry, and nuclearity, a rational design of multinuclear catalysts remains challenging. With the goal to accelerate the identification of suitable ligands that form trialkylphosphine-derived dihalogen-bridged Ni(I) dimers, we herein employed an assumption-based machine learning approach. The workflow offers guidance in ligand space for a desired speciation without (or only minimal) prior experimental data points. We experimentally verified the predictions and synthesized numerous novel Ni(I) dimers as well as explored their potential in catalysis. We demonstrate C-I selective arylations of polyhalogenated arenes bearing competing C-Br and C-Cl sites in under 5 min at room temperature using 0.2 mol % of the newly developed dimer, [Ni(I)(μ-Br)PAd2(n-Bu)]2, which is so far unmet with alternative dinuclear or mononuclear Ni or Pd catalysts

Text
Machine Learning-Guided Development of Trialkylphosphine Ni(I) Dimers and Applications in Site-Selective Catalysis - Accepted Manuscript
Restricted to Repository staff only until 19 January 2025.
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More information

e-pub ahead of print date: 6 July 2023
Published date: 19 July 2023
Additional Information: Funding Information: We thank RWTH Aachen University, the European Research Council (ERC-637993), the Volkswagen Foundation (Momentum Program), the DFG (German Research Foundation) Cluster of Excellence 2186 (“The Fuel Science Center”─ID: 390919832), and the Fonds der Chemischen Industrie (Kekulé scholarship to T.M.K.) for funding. Calculations were performed with computing resources granted by JARA-HPC from RWTH Aachen University under the project “jara0091”. We thank Prof. Abby Doyle for helpful discussions.

Identifiers

Local EPrints ID: 486678
URI: http://eprints.soton.ac.uk/id/eprint/486678
ISSN: 0002-7863
PURE UUID: 09aa9dca-0121-4ba0-b399-12c73382f1f7
ORCID for Graham J. Tizzard: ORCID iD orcid.org/0000-0002-1577-5779

Catalogue record

Date deposited: 01 Feb 2024 17:39
Last modified: 06 Jun 2024 01:40

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Contributors

Author: Teresa M. Karl
Author: Samir Bouayad-Gervais
Author: Julian A. Hueffel
Author: Theresa Sperger
Author: Sebastian Wellig
Author: Sherif J. Kaldas
Author: Uladzislava Dabranskaya
Author: Jas S. Ward
Author: Kari Rissanen
Author: Franziska Schoenebeck

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