Layered conductive polymer on nylon membrane templates for high performance, thin-film supercapacitor electrodes
Bibliographic record
Abstract
Flexible Thin-film Electrochemical Capacitors (ECs) are emerging technology that plays an important role as energy supply for various electronics system for both present era and the future. Intrinsically conductive polymers (ICPs) are promising pseudo-capacitive materials as they feature both good electrical conductivity and high specific capacitance. This study focuses on the construction and characterization of ultra-high surface area porous electrodes based on coating of nano-sized conductive polymer materials on nylon membrane templates. Herein, a novel nano-engineered electrode material based on nylon membranes was presented, which allows the creation of super-capacitor devices that is capable of delivering competitive performance, while maintaining desirable mechanical characteristics. With the formation of a highly conductive network with the polyaniline nano-layer, the electrical conductivity was also increased dramatically to facilitate the charge transfer process. Cyclic voltammetry and specific capacitance results showed promising application of this type of composite materials for future smart textile applications.
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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 | 0.000 |
| 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 | 0.001 |
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".