Article, 2024

Machine learned environment-dependent corrections for a spds∗ empirical tight-binding basis

MACHINE LEARNING-SCIENCE AND TECHNOLOGY, Volume 5, 2, 10.1088/2632-2153/ad4510

Contributors

Soccodato, Daniele (Corresponding author) [1] Penazzi, Gabriele [2] Pecchia, Alessandro [3] [4] Phan, Anh-Luan [1] Maur, Matthias Auf Der [1]

Affiliations

  1. [1] Univ Roma Tor Vergata, Dept Elect Engn, Via Politecn 1, I-00133 Rome, Italy
    2. [NORA names: Italy; Europe, EU; OECD];
  2. [2] Synopsys Denmark, Fruebjergvej 3,PostBox 4, DK-2100 Copenhagen, Denmark
    3. [NORA names: Other Companies; Private Research; Denmark; Europe, EU; Nordic; OECD];
  3. [3] CNR, ISMN, Via Salaria 29,300, I-00017 Rome, Italy
    4. [NORA names: Italy; Europe, EU; OECD];
  4. [4] CNR, ISMN, Via Salaria 29,300, I-00017 Rome, Italy
    5. [NORA names: Italy; Europe, EU; OECD]

Abstract

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Keywords

Delta-learning, III-V materials, antimonides, atomistic simulations, electronic band structure, empirical tight-binding

Data Provider: Clarivate

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