Chemical Mapping and Electrochemical Performance of Manganese Dioxide/Activated Carbon Based Composite Electrode for Asymmetric Electrochemical Capacitor
Bibliographic record
Abstract
A MnO 2 @BP nanocomposite was synthesized by simultaneously reduction of KMnO 4 with Mn(CH 3 COO) 2 .4H 2 O and highly porous Black Pearls 2000 at room temperature. The specific surface area, porosity, crystalline form and conductivity of MnO 2 @BP nanocomposite were characterized by nitrogen gas adsorption measurements, scanning electron microscopy, X-ray diffraction and 4-point probe measurements, respectively. The content of MnO 2 and BP in the composite was determined by thermogravimetric analysis. Chemical mapping using Raman spectroscopy was performed to investigate the distribution of MnO 2 and BP in a composite electrode film prepared with polytetrafluoroethylene (PTFE) as binder. This composite electrode exhibits more homogeneously distributed MnO 2 particles when compared to an electrode made by physical mixing of MnO 2 , BP and PTFE (MnO 2 /BP-PTFE). Also, Raman spectroscopy data of both composite electrodes indicates a loss of electrical conductivity of BP in the case of MnO 2 @BP-PTFE. The electrochemical properties were characterized by cyclic voltammetry in aqueous 0.65 M K 2 SO 4 . The specific capacitance of MnO 2 @BP-PTFE composite electrode was 122 ± 5 F/g, which is statistically equivalent to the capacitance of MnO 2 /BP-PTFE composite electrode (129 ± 6 F/g).
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".