Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production.

Kudapa VK, Mohd S, Sivasundar V, Mishra A, Sahu SK, Metwally DS, Aman M

DOI: 10.3389/fchem.2026.1894425
Published: 2026
Container: Frontiers in chemistry
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fchem.2026.1894425,
  title = {Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production.},
  author = {Kudapa VK and Mohd S and Sivasundar V and Mishra A and Sahu SK and Metwally DS and Aman M},
  year = {2026},
  journal = {Frontiers in chemistry},
  doi = {10.3389/fchem.2026.1894425},
  url = {https://doi.org/10.3389/fchem.2026.1894425}
}

RIS

TY  - JOUR
TI  - Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production.
AU  - Kudapa VK
AU  - Mohd S
AU  - Sivasundar V
AU  - Mishra A
AU  - Sahu SK
AU  - Metwally DS
AU  - Aman M
PY  - 2026
JO  - Frontiers in chemistry
DO  - 10.3389/fchem.2026.1894425
UR  - https://doi.org/10.3389/fchem.2026.1894425
ER  -

APA

VK, K., S, M., V, S., A, M., SK, S., DS, M., & M, A. (2026). Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production.. Frontiers in chemistry. https://doi.org/10.3389/fchem.2026.1894425

Source records

pubmed · retrieved 2026-09-25T23:47:25.322Z