Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory

Sergei Manzhos, Johann Lüder, Pavlo Golub, Manabu Ihara

Open source

DOI
10.1088/2632-2153/ade7ca
Published
2025-07-03
Container
Machine Learning: Science and Technology
Publisher
IOP Publishing
Open access
unknown

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BibTeX

@article{allodium:10.1088/2632-2153/ade7ca,
  title = {Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory},
  author = {Sergei Manzhos and Johann Lüder and Pavlo Golub and Manabu Ihara},
  year = {2025},
  journal = {Machine Learning: Science and Technology},
  doi = {10.1088/2632-2153/ade7ca},
  url = {https://doi.org/10.1088/2632-2153/ade7ca}
}

RIS

TY  - JOUR
TI  - Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory
AU  - Sergei Manzhos
AU  - Johann Lüder
AU  - Pavlo Golub
AU  - Manabu Ihara
PY  - 2025
JO  - Machine Learning: Science and Technology
DO  - 10.1088/2632-2153/ade7ca
UR  - https://doi.org/10.1088/2632-2153/ade7ca
ER  - 

APA

Manzhos, S., Lüder, J., Golub, P., & Ihara, M. (2025). Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory. Machine Learning: Science and Technology. https://doi.org/10.1088/2632-2153/ade7ca

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