Orbital-free density functional theory calculation applying semi-local machine-learned kinetic energy density functional and kinetic potential

研究成果: Article

抜粋

This letter proposes a scheme of orbital-free density functional theory (OF-DFT) calculation for optimizing electron density based on a semi-local machine-learned (ML) kinetic energy density functional (KEDF). The electron density, which is represented by the square of the linear combination of Gaussian functions, is optimized using derivatives of electronic energy including ML kinetic potential (KP). The numerical assessments confirmed the accuracy of optimized density and total energy for atoms and small molecules obtained by the present scheme based on ML-KEDF and ML-KP.

元の言語English
記事番号137358
ジャーナルChemical Physics Letters
748
DOI
出版物ステータスPublished - 2020 6

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

フィンガープリント Orbital-free density functional theory calculation applying semi-local machine-learned kinetic energy density functional and kinetic potential' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用