Composite Supercapacitor Electrodes by Electrodeposition of MnO2 on MWCNT Felt Directly Grown on Aluminum
Bibliographic record
Abstract
Manganese oxide \ carbon nanotube (CNT) thin film electrodes were fabricated by direct growth of a carbon nanotube layer on aluminum substrate (i.e. a commercially viable material for use as current collector) by chemical vapor deposition, in the presence of an electrochemically deposited thin film nickel catalyst, followed by anodic electrodeposition of MnO2. A proof of concept of this approach is demonstrated showing that the fabrication process, even in its simplest and unsophisticated implementation –notably without any deliberate effort to control the CNT growth arrangement and consequently the composite microstructure– allows the preparation of MnO2/CNT/Al prototype electrodes having almost a three-fold increase in capacitance compared to MnO2/Ni electrodes and, more significantly, comparing favorably with composite electrodes of similar design and fabrication. MnO2/CNT/Al electrodes ensured also improved cyclic stability compared to the reference case of MnO2/Ni electrodes. The proposed scheme is an effective procedure for the fabrication of thin film composite MnO2/CNT/Al electrodes, which may be amenable to significant improvements by tailoring thickness and microstructure of the CNT scaffold and manganese oxide film. Furthermore, a similar process scheme, may be proposed for the fabrication of active electrodes of different scopes with a proper choice of the substrate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".