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Enregistrement W4386854053 · doi:10.1149/ma2023-01331854mtgabs

(Invited) Potential of Silicon Oxide Films for Low-Cost and High-Performance Resistive Switching Devices

2023· article· en· W4386854053 sur OpenAlex
Yasuhisa Ōmura

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Notice bibliographique

RevueECS Meeting Abstracts · 2023
Typearticle
Langueen
DomaineEngineering
ThématiqueAdvanced Memory and Neural Computing
Établissements canadiensAssociation of Canadian Archivists
Organismes subventionnairesnon disponible
Mots-clésOxideMaterials scienceSiliconSilicon oxideOptoelectronicsSputteringSubstrate (aquarium)NanotechnologyElectric fieldThin filmEngineering physicsMetallurgyPhysics

Résumé

récupéré en direct d'OpenAlex

Although resistance switching in transition-metal oxide (TMO) films has been widely studied [1], the physics and chemistry of resistance switching in non-transition-metal oxide (nTMO) films remains under-studied [2]. This must be corrected because inexpensive and chemically stable device configurations are required for the future Internet-of-Things society. It is easily anticipated that the switching electric field of silicon oxide films is apt to be higher than that of TMO films because the dielectric constant of silicon oxide films is smaller than those of the TMO films. However, the use of two-layer stacks like SiOx/hi- k oxide reduces the switching electric field [3]. Therefore, the study of silicon oxide films is still meaningful. Many scientists have recently investigated resistance switching in sputter-deposited silicon oxide films in detail [4,5] because this structure dispenses with the TMO (Fig. 1). Many papers addressed the role of silicon sub-oxide (SiOx) [6] because it is anticipated that the unstable bonds of non-stoichiometric silicon oxide can create degraded, but reversible, conductive paths inside the film. However, it is not yet clear how the SiOx region can trigger resistance switching, how important the SiOx region is, and whether the SiOx region is the only determiner of resistance switching [7] (Figs. 2, 3). The author demonstrated that hot-electron injection from the Si substrate had great potential in triggering resistance switching and lowering the switching voltage of sputter-deposited Si oxide films [5,8]; it was also mentioned that Si precipitates played an important role in realizing repeatable bipolar switching [9] (Fig. 2). Relating to this study, the author also proposed the physical and chemical structure of conductive filaments and their switching behavior based on an analysis of a possibly equivalent circuit model [10] (Fig. 4). However, it was not definitely elucidated why unipolar switching is not easily observed in sputter-deposited silicon oxide films, even though it is not a TMO. Recently, the author performed various Monte Carlo simulations to elucidate the physical and chemical parameters that rule the unipolar switching process in sputter-deposited silicon oxide films. Generations of simple bond breaking, oxygen vacancies, metallic Si sites, and E’’ centers were implemented in the simulation algorithm [8]. All-positive voltage stress mode for both the electroforming process and the reset process will not yield devices with stable, repeatable switching [11]. On the other hand, the all-negative stress mode results in stable, repeatable switching because the recovery of the internal degradation of the Si oxide film is not completed [11] (Fig. 5). This difference stems from the physical asymmetry of the electrode materials (Fig. 1). Though some may consider that silicon oxide films are not preferable to ReRAM devices from the chemical points of view, the theoretical analysis provided by the author in this paper suggests that silicon oxide films can be applied to the ReRAM device. [1] Y. Tokura, Physics Today , vol. 56, pp. 50-55, 2003. [2] T. Yanagida, et al ., Sci. Rep. , vol. 3, No.1657, pp.1-6, 2013. [3] P. Broqvist and A. Pasquarello, Appl. Phys. Lett., vol. 91, 192905, 2007. [4] J. Yao, et al ., Appl. Phys. Lett , vol. 93, pp. 253101-1-253101-3, 2008. [5] R. Yamaguchi, S. Sato, and Y. Omura, Jpn. J. Appl. Phys. , vol. 56, pp. 041301-1-041301-6, 2017. [6] A. Mehonic, et al. , J. Appl. Phys. , vol. 111, pp. 074507-1-074507-9, 2012. [7] Y. Wang, et al ., Appl. Phys. Lett ., vol.102, pp. 042103-1-042103-5, 2013. [8] Y. Omura, Ind. J. Electrical Eng. & Comput. Sci ., vol. 24, pp. 1367-1378, 2021. [9] Y. Omura, R. Yamaguchi, and S. Sato, IEEE Trans. Device Reliab. and Mat . Vol. 17, pp. 561-567 (2017). [10] Y. Omura, ECS J. Solid State Sci. and Technol ., vol. 10, pp. 124006-1-124006-10, 2021. [11] Y. Omura, Materials Today Proc ., vol. 20, pp. 273-282, 2020; the advanced study will be published in the ECS J. Solid State Sci. and Technol . Figure 1

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,448
Score d'incertitude au seuil0,642

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,234
Écart entre enseignants0,221 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle