Preparation and electrochemical characterization of PANI/MnCo<sub>2</sub>O<sub>4</sub> nanocomposite as supercapacitor electrode material
Bibliographic record
Abstract
In this work, PANI/MnCo2O4 nanocomposite was prepared via in-situ chemical polymerization method. Materials synthesized were characterized by FTIR spectroscopy, X-ray diffraction, and scanning electron spectroscopy. In addition, surface characterization of samples such as specific surface area, pore volume, and pore size distribution was studied. Supercapacitor capability of materials was investigated in 1 mol L–1 Na2SO4 solution using cyclic voltammetry in different potential scan rates and electrochemical impedance spectroscopy (EIS). The specific capacitance of materials was calculated, and it was observed that the specific capacitance of PANI/MnCo2O4 nanocomposite was 185 F g−1, much larger than PANI. Moreover, the prepared nanocomposite exhibited better rate capability in scan rate of 100 mV s−1 with respect to PANI. The EIS experiments revealed that the nanocomposite has lower charge transfer resistance compared with pure PANI. Subsequently, it was shown that the nanocomposite cycling performance was superior to the PANI cycling performance.
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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".