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November 14, 2025The Journal of Physical Chemistry AOpen Access

A Comparison of Electronic Structure Methods for Predicting the Hydrogenation Energies of Candidate Molecules for Hydrogen Storage

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Authors

ADAmanda DumiSUShiv UpadhyayHHHassan Harb

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Overview

Computational methods find hydrogen storage challenges in candidate molecules, suggesting AI may optimize selection processes.

Key Points

  • Computational methods identify challenges in finding viable hydrogen storage candidates.
  • Artificial intelligence shows potential in optimizing hydrogen candidate selection for energy uses.
  • Density functional theory and diffusion Monte Carlo serve as key electronic structure methods.
  • Implications point to improved training data for hydrogen storage materials through machine learning approaches.

Cite This Study

Dumi et al. (2025) studied this question.

synapsesocial.com/papers/692519a7c0ce034ddc354013https://doi.org/10.1021/acs.jpca.5c05284
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