Electrophoretic Nanotechnology of Composite Electrodes for Electrochemical Supercapacitors
Bibliographic record
Abstract
The electrophoretic deposition (EPD) method has been developed for the fabrication of MnO(2)-multiwalled carbon nanotube (MWCNT) films for application in electrochemical supercapacitors (ESs). For MWCNT applications, which depend on electrical conductivity, it is challenging to achieve dispersion and EPD of pristine MWCNT and avoid defects due to chemical treatment or functionalization. An important finding was the possibility of efficient dispersion and controlled EPD of MWCNT using calconcarboxylic acid (CCA). Moreover, the use of CCA allowed efficient dispersion of MnO(2) in concentrated suspensions and EPD of MnO(2) films. The comparison of the experimental data for chromotrope FB (CFB) and CCA and chemical structures of the molecules provided insight into the mechanism of CCA adsorption on MnO(2). The fabrication of stable suspensions of MnO(2) nanoparticles containing MWCNT, and controlled codeposition of both materials is a crucial aspect in the EPD of composites. The new approach was based on the use of CCA as a charging and dispersing agent for EPD of MnO(2) nanoparticles and MWCNT. The deposition yield measurements at various experimental conditions and Fourier transform infrared spectroscopy data, coupled with results of electron microscopy, thermogravimetric, and differential thermal analysis provided evidence of the formation of MnO(2)-MWCNT composites. The electrochemical testing results and impedance spectroscopy data showed good capacitive behavior of the composite films and the beneficial effect of MWCNTs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".