| Téléchargement | - Voir la version finale : Inverse design of a graphene-based quantum transducer via neuroevolution (PDF, 14.1 Mio)
- Voir les données supplémentaires : Inverse design of a graphene-based quantum transducer via neuroevolution (PDF, 465 Kio)
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| DOI | Trouver le DOI : https://doi.org/10.1021/acs.jpcc.0c06903 |
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| Auteur | Rechercher : Ryczko, KevinIdentifiant ORCID : https://orcid.org/0000-0001-6933-3856; Rechercher : Darancet, PierreIdentifiant ORCID : https://orcid.org/0000-0002-5846-1673; Rechercher : Tamblyn, Isaac1Identifiant ORCID : https://orcid.org/0000-0002-8146-6667 |
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| Affiliation | - Conseil national de recherches du Canada. Technologies de sécurité et de rupture
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| Format | Texte, Article |
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| Sujet | chemical structure; optimization; Hamiltonians; lattices; doping |
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| Résumé | We introduce an inverse design framework based on artificial neural networks, genetic algorithms, and tight-binding calculations, capable to optimize the very large configuration space of nanoelectronic devices. Our non-linear optimization procedure operates on trial Hamiltonians through superoperators controlling growth policies of regions of distinct doping. We demonstrate that our algorithm optimizes the doping of graphene-based three-terminal devices for valleytronics applications, monotonously converging to synthesizable devices with high merit functions in a few thousand evaluations (out of ≃2³⁸⁰⁰ possible configurations). The best-performing device allowed for a terminal-specific separation of valley currents with ≃96% (≃94%) K(K′) valley purity. Importantly, the devices found through our non-linear optimization procedure have both a higher merit function and higher robustness to defects than the ones obtained through geometry optimization. |
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| Date de publication | 2020-11-18 |
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| Maison d’édition | American Chemical Society |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | a3425708-5b39-4cc4-a8f5-c01b3d2cd0d6 |
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| Enregistrement créé | 2021-06-15 |
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| Enregistrement modifié | 2021-09-21 |
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