Composition-based machine learning for screening superconducting ternary hydrides from a curated dataset

Kazuaki Tokuyama, Souta Miyamoto, Taichi Masuda, Katsuaki Tanabe

Open source

DOI: 10.1063/5.0319573
Published: 5
Container: APL Machine Learning
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1063/5.0319573,
  title = {Composition-based machine learning for screening superconducting ternary hydrides from a curated dataset},
  author = {Kazuaki Tokuyama and Souta Miyamoto and Taichi Masuda and Katsuaki Tanabe},
  year = {2026},
  journal = {APL Machine Learning},
  doi = {10.1063/5.0319573},
  url = {https://doi.org/10.1063/5.0319573}
}

RIS

TY  - JOUR
TI  - Composition-based machine learning for screening superconducting ternary hydrides from a curated dataset
AU  - Kazuaki Tokuyama
AU  - Souta Miyamoto
AU  - Taichi Masuda
AU  - Katsuaki Tanabe
PY  - 2026
JO  - APL Machine Learning
DO  - 10.1063/5.0319573
UR  - https://doi.org/10.1063/5.0319573
ER  -

APA

Tokuyama, K., Miyamoto, S., Masuda, T., & Tanabe, K. (2026). Composition-based machine learning for screening superconducting ternary hydrides from a curated dataset. APL Machine Learning. https://doi.org/10.1063/5.0319573

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doaj · retrieved 2026-11-10T11:53:50.520Z