Electrochemical Oxidation Induced Multi-Level Memory in Carbon-Based Resistive Switching Devices
Bibliographic record
Abstract
Abstract In this work, we report for the first time the electrochemical oxidation as a technique to improve the electrical performances of carbon-based resistive switching devices. The devices obtained through the anodic oxidation of carbon-structures possess superior electrical performances i.e. a 3-level memory behavior and an ON/OFF ratio two order of magnitude higher than the non-oxidized carbon-based devices. It is demonstrated that the chemical composition of the carbon structures (i.e. percentage of oxygen groups, sp2 and sp3 carbon atoms) plays a key role in the improvement of the carbon-based devices. The electrochemical oxidation allows the possibility to control the oxidation degree, and therefore, to tailor the devices electrical performances. We demonstrated that the resistive switching behavior in the electrochemically oxidized devices is originated from the formation of conductive filament paths, which are built from the oxygen vacancies and structural defects of the anodic oxidized carbon materials. The novelty of this work relies on the anodic oxidation as a time- and cost-effective technique that can be employed for the engineering and improvement of the electrical performances of next generation carbon-based resistive switching devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".