Fabrication of Polypyrrole-Coated Carbon Nanotubes Using Oxidant–Surfactant Nanocrystals for Supercapacitor Electrodes with High Mass Loading and Enhanced Performance
Bibliographic record
Abstract
A conceptually new approach to the fabrication of polypyrrole (PPy)-coated multiwalled carbon nanotubes (MWCNT) for application in electrodes of electrochemical supercapacitors (ES) is proposed. Cetrimonium persulfate (CTA)2S2O8 in the form of nanocrystals is used as an oxidant for the chemical polymerization of PPy. Ponceau S (PS) dye is investigated as a new anionic dopant. Testing results show that PS allows reduced PPy particle size and improved electrochemical performance, whereas (CTA)2S2O8 nanocrystals promote the formation of PPy nanofibers. We demonstrate for the first time that MWCNT can be efficiently dispersed using (CTA)2S2O8 nanocrystals. The analysis of the dispersion mechanism indicates that (CTA)2S2O8 dissociation is catalyzed by MWCNT. This new finding opens a new and promising strategy in MWCNT dispersion for colloidal processing of nanomaterials and electrophoretic nanotechnology. Uniformly coated MWCNT are obtained using (CTA)2S2O8 as a dispersant for MWCNT and oxidant for PPy polymerization and utilizing advantages of PS as an efficient dopant and nanostructure controlling agent. The analysis of the testing results provides an insight into the influence of PS molecular structure on PPy nanostructure and electrochemical properties. The PPy-coated MWCNT show superior electrochemical performance compared to PPy nanoparticles. The proof-of-principle is demonstrated by the fabrication of ES electrodes with excellent electrochemical performance at high active material loadings, good capacitance retention at high charge-discharge rates, and excellent cycling stability.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".