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Correction: Catalysis meets machine learning: a guide to data-driven discovery and design
Eleonora Casilloa,
Thomas Scattolin*b and
Steven P. Nolan*a
aDepartment of Chemistry and Center for Sustainable Chemistry, Ghent University, Krijgslaan 281 (S-3), 9000 Ghent, Belgium. E-mail: steven.nolan@ugent.be
bDipartimento di Scienze Chimiche, Università degli Studi di Padova, via Marzolo 1, 35131 Padova, Italy. E-mail: thomas.scattolin@unipd.it
First published on 27th April 2026
Abstract
Correction for ‘Catalysis meets machine learning: a guide to data-driven discovery and design’ by Eleonora Casillo et al., Chem. Commun., 2025, 61, 18247–18272, https://doi.org/10.1039/D5CC05274B.
The authors regret that there were some minor errors with the referencing in the original article.
In the sentence in the final paragraph of page 18265, ref. 64 should be deleted and ref. 48 changed to ref. 68. The corrected sentence should therefore read as follows: “In a separate application to Ziegler–Natta-catalysed propylene polymerization, the method modelled two polymerization cycles and a termination step, simulating monomer insertions and chain termination via β-hydride elimination (Fig. 15(B)).68”
Ref. 48 should instead be cited in the final paragraph before section 6.1 on page 18254. The corrected sentence should therefore read as follows: “In this context, Marcou et al. developed an expert system to predict suitable catalysts and solvents for Michael additions,71 trained on 198 known reactions.47,48”
The Royal Society of Chemistry apologises for these errors and any consequent inconvenience to authors and readers.
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