Nanostructure Enabled Memristor and Supercapacitor
Notice bibliographique
Résumé
The composition of conventional circuits is based on four basic elements: resistors, capacitors, inductors, and memristors. Among them, resistors and inductors have been widely studied. Memristor has a desirable application prospect in information storage, artificial synapse, neural network, and artificial intelligence. Capacitors, specifically supercapacitors, have shown better performance, higher capacitance, and efficiency than traditional batteries and capacitors. With the development of technology, more and more electronic products have come into people's lives, and the application of the Internet of Things (IoT) has become more and more widespread. Supercapacitors as energy storage devices and memristors as data storage & computing device play crucial roles in the development of IoT. \nThe memristor is usually considered a non-linear resistor with a memory function. The more widely accepted mechanism is the formation of a conductive filament, which transforms the resistor from a linear resistive state to a resistive-capacitive coupled state and then to a pure memory state. However, there is still a lack of theoretical knowledge on the mechanism of memristors. Is it starting as a linear resistance? This is a problem worth exploring in the development of memristive devices. \nIn this thesis, a silver (Ag)/Prussian blue (PB)/In-doped Tin Oxide (ITO) structure shows a unique glucose-controlled transition from a linear resistive state to a capacitance-coupled storage effect and finally to a pure memristive storage effect. Unlike other methods of controlling circuit elements, glucose, as a new factor, is a very effective and direct method of controlling circuit elements. Ion transport recombination and redox reactions under bias in lead layers are controlled by glucose to form conductive filaments in the switching layer PB. This device further explores the mechanism of conduction filament and provides a promising application in complex integrated sensor and artificial intelligence applications. \nSupercapacitors have been extensively studied for their excellent rate performance and cycling stability. The electrode material is the main factor that determines the performance of the capacitor. Studies have shown that electrode materials' structure, surface area, and morphology are essential factors in determining electrochemical performance. However, constructing supercapacitors with high energy density, long cycle life, and high capacitance remains challenging. Therefore, to solve the current problems, it is crucial to research the electrode material with better performance. \nIn this thesis, magnetron sputtering techniques were first introduced to construct MnO2 and V2O5 decorated carbon-based electrodes. First, spin coating the carbon nanofibers on the carbon cloth substrate and then sputter the MnO2 and V2O5 multilayer. The addition of carbon nanofibers increases the electrical conductivity of carbon cloth and improves the electron transfer rate, while the double carbon core-shell structure improves the reaction site for metal oxide deposition. Electrodes with CC/CNFs/MnO2/V2O5/MnO2/V2O5/MnO2/V2O5/MnO2 (MVMVMVM) structure show the best electrochemical performance. At a scan rate of 5 mV/s, the capacitance is increased by a factor of nearly 10 compared to the carbon cloth electrode based on CNFs, with a capacitance of 90 mF/cm3. As for the cell stability, after 2000 cycles of CV loops, the capacitance extension remains stable at 120%. Due to the nanostructured multilayer MnO2/V2O5, the redox ion reaction can pass through the surface to the interlayer, exhibiting partial to full activation. This study constructs the supercapacitor electric double-layer pseudocapacitive electrode interface from the atomic scale, which provides an essential reference and impetus for the development of supercapacitors.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».