Machine learning prediction of multi-step hydrogenation energetics in transition metal-doped phosphorene

Computational and Theoretical Chemistry 2026

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Authors: César Gabriel Vera de la Garza, Wilmer E. Vallejo Narváez, Serguei Fomine

DOI: 10.1016/j.comptc.2026.115767

Cited by: 2

References: 20

Fields of Study & Subjects

Machine Learning in Materials Science 2D Materials and Applications Inorganic Chemistry and Materials

References 20