How machine learning can accelerate electrocatalysis discovery and optimization

Stephan N. Steinmann, Qing Wang, Zhi Wei Seh

Open source

DOI: 10.1039/d2mh01279k
Published: 2023
Container: Materials Horizons
Publisher: Royal Society of Chemistry (RSC)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1039/d2mh01279k,
  title = {How machine learning can accelerate electrocatalysis discovery and optimization},
  author = {Stephan N. Steinmann and Qing Wang and Zhi Wei Seh},
  year = {2023},
  journal = {Materials Horizons},
  doi = {10.1039/d2mh01279k},
  url = {https://doi.org/10.1039/d2mh01279k}
}

RIS

TY  - JOUR
TI  - How machine learning can accelerate electrocatalysis discovery and optimization
AU  - Stephan N. Steinmann
AU  - Qing Wang
AU  - Zhi Wei Seh
PY  - 2023
JO  - Materials Horizons
DO  - 10.1039/d2mh01279k
UR  - https://doi.org/10.1039/d2mh01279k
ER  -

APA

Steinmann, S. N., Wang, Q., & Seh, Z. W. (2023). How machine learning can accelerate electrocatalysis discovery and optimization. Materials Horizons. https://doi.org/10.1039/d2mh01279k

Source records

crossref · retrieved 2026-09-25T16:40:15.209Z