Binder-Less Molybdenum Doped CoO Based Integrated Electrodes Fabricated by Electric Discharge Corrosion for High-Efficiency Supercapacitors
Bibliographic record
Abstract
Due to its low cost, natural abundance, non-toxicity, and high theoretical capacitance, cobalt oxide (CoO) stands as a promising candidate electrode material for supercapacitors. In this study, binder-less molybdenum doped CoO (Mo@CoO) integrated electrodes were one-step fabricated using a simple electric discharge corrosion (EDC) method. This EDC method enables the direct synthesis of Mo@CoO active materials with oxygen vacancy on cobalt substrates, without any pre-made templates, conductive additives, or chemicals. Most importantly, the EDC method enables precise control over the discharge processing parameter of pulse width, which facilitates tailoring the surface morphologies of the as-prepared Mo@CoO active materials. It was found that the fabricated Mo@CoO based symmetric supercapacitor prepared by a pulse width of 24 μs (Mo@CoO-SCs24) achieved a maximum areal capacitance 36.0 mF cm−2 (0.15 mA cm−2), which is 1.83 and 1.97 times higher than that of Mo@CoO-SCs12 and Mo@CoO-SCs36. Moreover, the Mo@CoO-SCs24 devices could be worked at 10 V s−1, which demonstrates their fast charge/discharge characteristic. These results demonstrated the significant potential of the EDC strategy for efficiency fabricating various metal oxide binder-less integrated electrodes for various applications, like supercapacitors, batteries and sensors.
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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 | 0.001 |
| 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".