High Capacitance and Cycle‐Life Performance of a Binder‐Free Supercapacitor Nanocomposite Electrode by Direct Growth of Manganese Oxide Nanostructures on Carbon Nanotubes
Bibliographic record
Abstract
Abstract MnOx thin films with various oxidation states (MnO, Mn2O3, MnO2 and mixed MnO/Mn3O4) were directly grown onto carbon nanotubes by pulsed laser deposition under vacuum and at different oxygen partial pressures. The microstructural features of the as‐deposited thin films are characterized by scanning electron microscopy and X‐ray photoelectron spectroscopy. The electrochemical behavior of the CNT/MnOx nanocomposites in 1 M Na2SO4 electrolyte is discussed with regards to specific capacitance, and cycle‐life, by means of cyclic voltammetry and electrochemical impedance measurements. First, at slow potential scan rate of 1 mV s−1, MnOx prepared under vacuum and 10 mTorr of O2 delivered specific capacitance as high as 738 and 653 F g−1, respectively. Second, the rate capability of these two nanocomposites over a wide range of scan rates showed that at 500 mV s−1, the former retained 93 % whereas the later displayed an increase of 1.2 % with regards to their respective initial specific capacitance values at 1 mV s−1. They also maintained 90 % and 95 % of their specific capacitance after 10 000 continuous cycles with a 100 mV s−1 scan rate. The binder‐free nature of the CNT/MnOx nanocomposites and remarkable electrochemical properties suggest that these materials could find application as excellent electrodes for supercapacitors.
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) | 0.000 | 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".