Crossmark

Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

Crossref DOI link: https://doi.org/10.1039/d1sc00482d

Published Online: 2021

Update policy: https://doi.org/10.1039/rsc_crossmark_policy

Authors

Gallarati, Simone https://orcid.org/0000-0002-2349-1944
Fabregat, Raimon https://orcid.org/0000-0002-7946-817X
Laplaza, Rubén https://orcid.org/0000-0001-6315-4398
Bhattacharjee, Sinjini https://orcid.org/0000-0001-5830-7425
Wodrich, Matthew D. https://orcid.org/0000-0002-6006-671X
Corminboeuf, Clemence https://orcid.org/0000-0001-7993-2879
Funding

Funding for this research was provided by:

H2020 European Research Council (817977)

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (NCCR Catalysis)

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (NCCR MARVEL)

National Center of Competence in Research Materials’ Revolution: Computational Design and Discovery of Novel Materials

École Polytechnique Fédérale de Lausanne
License Information

Version of Record valid from 2021-04-03
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SIMILARITY CHECK

: This document is Similarity Check deposited

RELATED DATA

: Supplementary Information

IDENTIFIERS

: Simone Gallarati (ORCID)

: Raimon Fabregat (ORCID)

: Rubén Laplaza (ORCID)

: Sinjini Bhattacharjee (ORCID)

: Matthew D. Wodrich (ORCID)

: Matthew D. Wodrich (ResearcherID)

: Clemence Corminboeuf (ORCID)

: Clemence Corminboeuf (ResearcherID)

PEER REVIEW METHOD

: Single-blind

PUBLICATION HISTORY

: Received 26 January 2021; Accepted 1 April 2021; Accepted Manuscript published 3 April 2021; Advance Article published 13 April 2021; Version of Record published 26 May 2021