Correction: A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential

Chen Qu; Qi Yu; Riccardo Conte; Paul L. Houston; Apurba Nandi; Joel M. Bowman

doi:10.1039/D2DD90021A

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Correction: A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential

Chen Qu,*^a Qi Yu,^b Riccardo Conte,^c Paul L. Houston,^de Apurba Nandi^f and Joel M. Bowman*^f

Author affiliations

* Corresponding authors

^a Independent Researcher, Toronto, Ontario M9B 0E3, Canada
E-mail: szquchen@gmail.com

^b Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA

^c Dipartimento di Chimica, Università degli Studi di Milano, via Golgi 19, 20133 Milano, Italy

^d Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA

^e Department of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, USA

^f Department of Chemistry, Cherry L. Emerson Center for Scientific Computation, Emory University, Georgia 30322, Atlanta, USA
E-mail: jmbowma@emory.edu

Abstract

Correction for ‘A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential’ by Chen Qu et al., Digital Discovery, 2022, 1, 658–664, https://doi.org/10.1039/D2DD00057A.

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A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body …

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DOI: https://doi.org/10.1039/D2DD90021A
Article type: Correction
Submitted: 19 Oct 2022
Accepted: 19 Oct 2022
First published: 25 Oct 2022
This article is Open Access

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Digital Discovery, 2022,1, 941-941

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Correction: A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential

C. Qu, Q. Yu, R. Conte, P. L. Houston, A. Nandi and J. M. Bowman, Digital Discovery, 2022, 1, 941 DOI: 10.1039/D2DD90021A

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Correction: A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential

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