Supplementary Material

Further details on the used features and binding energy models as well as a comparison to results obtained using the foundational pre-trained models CHGNet and MACE-MP-0a.

Publication Details

Journal
Figshare
Published
2025-07-30
DOI
https://doi.org/10.60893/figshare.jcp.29441537.v1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

Supplementary Material

Figshare
Machine Learning in Materials Science
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Supplementary Material

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Abstract

Further details on the used features and binding energy models as well as a comparison to results obtained using the foundational pre-trained models CHGNet and MACE-MP-0a.

Figshare
Affordable and clean energy
Openalex Percentile: Top 65%
Machine Learning in Materials Science
DOISourceOpenAlex
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Supplementary Material · Figshare (2025) | TGRS Research Map | TGRS