(Invited) Fabrication and Characterization of Carbon-Based Nanoscale Devices: Insights and Applications
Notice bibliographique
Résumé
Nanoscale devices made from carbon-based materials are investigated for a variety of unique properties and features, including their promise to improve performance, decrease production costs, or provide totally new functionality relative to extant electronic devices. Because these devices have active areas composed of materials that are much thinner than those used in conventional devices, the details of the interfaces can often act to control the physics that lead to the operational device characteristics in unexpected ways. This is particularly true in molecular electronics, where design rules based on chemical intuition often fail to account for key physical aspects that dominate device behaviour. Thus, the ability to modify interfaces in a way that leads to control of device properties is a key to enabling next-generation devices based on nanoscale phenomenon. In addition, it is important to achieve an understanding of the processes that occur during carrier transport in nanoscale devices in order to obtain desirable functionality. This presentation will describe several aspects of carbon-based nanoscale devices, including fabrication and operation of molecular electronics and graphene field effect transistors (GFETs). After a discussion of some general physical principles that operate within the interfacial energy level alignment regime in molecular electoronics, a discussion of how light emission from nanoscale devices can be used to characterize them will be provided. In particular, we have used light emission from both large area molecular junctions and GFETs to understand important distance scales (elastic limits) and processes (transport and emission mechanisms). The data indicate that processes that involve hot carrier interactions with plasmonic structures in the devices lead to light emission, and that this phenomenon can be used to measure energy losses of carriers as they traverse a molecular layer. Results indicate that carriers can travel approximately 7 nm through a molecular junction before energy losses become significant, indicating that elastic transport is achieved for thin layers, but a transition in mechanism occurs for thicker films. The characteristics of the energy losses are reported for several different structures, providing insights into the nature of the transport in molecular electronics. Light emission from GFETs, on the other hand, appears to follow a novel mechanism that involves the excitation of plasmons in the graphene by hot carriers followed by decay through photon emission. By controlling the location of defects in the graphene lattice and the nanostructures around these scattering sites, emission could be localized to regions where this coupling is more optimized. In this second case, the devices may be able to be engineered through nanostructuring in order to gain control over the character of light emission. Finally, a few novel and emerging applications of nanoscale devices will be discussed, including using molecular devices in audio circuits, as well as for high frequency harmonic generation.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,020 | 0,019 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».