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Ab initio Modeling of MoS2/Oxide Device Interfaces with Machine Learned Electronic Structures — arXiv:2608.27533

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.27533
License (as archived): CC0-1.0
Archived: 2026-10-17T11:06:41.452Z
SHA-256 of the archived text: d924f455d28e33069a3a25256c26442530edacc3d11dff08bb47e3cbe4546fa5
Stable URL of this page: https://metraipolis.com/documento/dc_313bbbbd44f6

How to cite

Ab initio Modeling of MoS2/Oxide Device Interfaces with Machine Learned Electronic Structures — arXiv:2608.27533 — arXiv (en), https://arxiv.org/abs/2608.27533 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_313bbbbd44f6 (Metraipolis archive dc_313bbbbd44f6, sha256 d924f455d28e33069a3a25256c26442530edacc3d11dff08bb47e3cbe4546fa5)

BibTeX

@misc{dc313bbbbd44f6,
  title = {Ab initio Modeling of MoS2/Oxide Device Interfaces with Machine Learned Electronic Structures — arXiv:2608.27533},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.27533},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_313bbbbd44f6; sha256 d924f455d28e33069a3a25256c26442530edacc3d11dff08bb47e3cbe4546fa5},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.27533. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

We introduce a new ab initio approach to simulate semiconductor devices that integrates scalable machine-learned (ML) electronic structure models with an advanced quantum transport (QT) solver. The developed framework enables 10,000X speedups over density functional theory to produce the Hamiltonian matrix of devices made of >20,000 atoms, while offering high prediction accuracy. We use its unique features to investigate MoS2/oxide samples and single-layer MoS2 field-effect transistors, where the surrounding oxide layers, here, HfO2 or Al2O3, are explicitly included into the QT domain. In particular, we reveal that the presence of undercoordinated metal atoms (Hf or Al) close to the semiconductor-oxide interface significantly affects the magnitude of the electronic current and its propagation through MoS2.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-31 in cs.LG).
Categorie arXiv: Materials Science (cond-mat.mtrl-sci) ; Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2608.27533 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T10:50:25.828Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-08-31?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).