Activated Carbon-Coated Carbon Nanotubes for Energy Storage in Supercapacitors and Capacitive Water Purification
Bibliographic record
Abstract
Polypyrrole-coated multiwalled carbon nanotubes (PPy-MWCNT) were used for the fabrication of activated carbon-coated MWCNT doped with nitrogen (N-AC-MWCNT). The conceptually new method for the fabrication of non-agglomerated PPy-MWCNT with good coating uniformity allowed the fabrication of uniform and well-dispersed N-AC-MWCNT with high surface area. The use of N-AC-MWCNT allowed the fabrication of supercapacitor electrodes with high mass loading in the range of 15–35 mg cm –2 and with a high active material to current collector mass ratio of 0.21–0.50. The N-AC-MWCNT electrodes showed excellent electrochemical performance in aqueous 0.5 M Na 2 SO 4 electrolyte. The maximum specific capacitance of 3.6 F cm –2 (103.1 F g –1 ) was achieved for mass loading of 35 mg cm –2 at a scan rate of 2 mV s –1 . The aqueous supercapacitor cells, based on N-AC-MWCNT electrodes, exhibited excellent performance with energy density of 16.1 mWh g –1, power density of 14.4 W g –1, and enlarged voltage window of 1.8 V. The individual electrodes and cells showed good capacitance retention at high charge–discharge rates and good cycling stability. Moreover, the N-AC-MWCNT electrodes showed promising performance for capacitive deionization of water. The feasibility of capacitive removal of organic dyes from aqueous solutions has been demonstrated. A quartz crystal microbalance method was used as a tool for the analysis of electrosorption and electrodesorption of ions and charged dyes during charge and discharge.
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".