From prediction to materials design: machine learning in electrocatalytic water splitting.

Pitchai C, Lo TY, Hsu YT, Chen I, Li HC, Chen CM

DOI: 10.1039/d6cc01937d
Published: 2026 Jun 26
Container: Chemical communications (Cambridge, England)
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1039/d6cc01937d,
  title = {From prediction to materials design: machine learning in electrocatalytic water splitting.},
  author = {Pitchai C and Lo TY and Hsu YT and Chen I and Li HC and Chen CM},
  year = {2026},
  journal = {Chemical communications (Cambridge, England)},
  doi = {10.1039/d6cc01937d},
  url = {https://doi.org/10.1039/d6cc01937d}
}

RIS

TY  - JOUR
TI  - From prediction to materials design: machine learning in electrocatalytic water splitting.
AU  - Pitchai C
AU  - Lo TY
AU  - Hsu YT
AU  - Chen I
AU  - Li HC
AU  - Chen CM
PY  - 2026
JO  - Chemical communications (Cambridge, England)
DO  - 10.1039/d6cc01937d
UR  - https://doi.org/10.1039/d6cc01937d
ER  -

APA

C, P., TY, L., YT, H., I, C., HC, L., & CM, C. (2026). From prediction to materials design: machine learning in electrocatalytic water splitting.. Chemical communications (Cambridge, England). https://doi.org/10.1039/d6cc01937d

Source records

pubmed · retrieved 2026-11-10T15:01:38.582Z