Polyaniline@cellulose nanofibers multifunctional composite material for supercapacitors, electromagnetic interference shielding and sensing
Bibliographic record
Abstract
Recently, multifunctional materials have received widespread attention from researchers. Cellulose nanofibers (CNF) is one of biomass materials with abundant hydroxyl groups, which shows great potential in manufacturing multifunctional composite material. In this paper, a kind of polyaniline@CNF/polyvinyl alcohol-H2SO4 multifunctional composite material (PANI@CNF/PVA-H2SO4) was successfully designed by in-situ chemical polymerization of conductive polyaniline (PANI) onto CNF aerogel with high aspect ratio, and then coated with PVA-H2SO4 gel. The composite material has a specific capacitance of 502.2 F/g at a scan rate of 5 mV/s as supercapacitor electrode. Furthermore, when the composite was assembled into a symmetrical supercapacitor, it can still provide an energy density of 11.49 W h/kg at a high power density of 413.55 W/kg. Besides, the as-obtained PANI@CNF/PVA-H2SO4 composite has an excellent electromagnetic shielding performance of 34.75 dB in X-band. In addition, due to the excellent flexibility of CNF and PVA, the PANI@CNF/PVA-H2SO4 composites can be further applied to stress sensors to detect pressure and human motion signals.
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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 | 0.000 |
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".