Issue 12, 2025
From the journal:

Digital Discovery

Correction: Beyond training data: how elemental features enhance ML-based formation energy predictions

Hamed Mahdavi,*a   Vasant Honavara  and  Dane Morganb  

* Corresponding authors

a Department of Computer Science and Engineering, Pennsylvania State University, State College, PA 16801, USA
E-mail: hmm5834@psu.edu, vuh14@psu.edu

b Department of Material Science and Engineering, University of Wisconsin Madison, Wisconsin, USA
E-mail: ddmorgan@wisc.edu

Abstract

Correction for “Beyond training data: how elemental features enhance ML-based formation energy predictions” by Hamed Mahdavi et al., Digital Discovery, 2025, 4, 2972–2982, https://doi.org/10.1039/D5DD00182J.

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Article information

DOI
https://doi.org/10.1039/D5DD90047F
Article type
Correction
Submitted
06 Oct 2025
Accepted
06 Oct 2025
First published
31 Oct 2025
This article is Open Access
Creative Commons BY license

Digital Discovery, 2025,4, 3828-3828

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Correction: Beyond training data: how elemental features enhance ML-based formation energy predictions

H. Mahdavi, V. Honavar and D. Morgan, Digital Discovery, 2025, 4, 3828 DOI: 10.1039/D5DD90047F

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