Colloidal Processing of Mn3O4-Carbon Nanotube Nanocomposite Electrodes for Supercapacitors
Bibliographic record
Abstract
This investigation addresses the challenges in the development of efficient nanostructured Mn3O4 cathodes for supercapacitors. A high areal capacitance and the ability to avoid a time-consuming activation procedure for electrodes with high active mass loading of 40 mg cm−2 are reported. This facilitates practical applications of Mn3O4 based electrodes. The highest capacitance of 6.11 F cm−2 (153 F g−1) is obtained from cyclic voltammetry at a scan rate of 2 mV s−1 and 6.07 F cm−2 (151.9 F g−1) from the chronopotentiometry at a current density of 3 mA cm−2 in a potential window of 0.9 V in a neutral Na2SO4 electrolyte. The new approach is based on the application of rhamnolipids (RL) as a capping agent for the synthesis of Mn3O4 particles and a co-dispersant for Mn3O4 and carbon nanotubes, which are used as conductive additives. The size and shape of the Mn3O4 particles are influenced by RL. The enhanced performance of the electrodes is linked to the chemical structure and properties of RL molecules, which exert influence on Mn3O4 particle size and shape during synthesis, reduce agglomeration, facilitate RL adsorption on Mn3O4 and carbon nanotubes, and influence their co-dispersion and mixing at the nanometric scale.
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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".