Self-Powered Piezo-Supercapacitors Based on ZnO@Mo-Fe-MnO2 Nanoarrays
Bibliographic record
Abstract
The development of self-charging supercapacitor power cells (SCSPCs) has profound implications for smart electronic devices used in different fields. Here, we epitaxially electrodeposited Mo- and Fe-codoped MnO2 films on piezoelectric ZnO nanoarrays (NAs) grown on the flexible carbon cloth (denoted ZnO@Mo-Fe-MnO2 NAs). An SCSPC device was assembled with the ZnO@Mo-Fe-MnO2 NA electrode and poly(vinylidenefluoride-co-trifluoroethylene) (PVDF-Trfe) piezoelectric film doped with BaTiO3 (BTO) and carbon nanotubes (CNTs) (denoted PVDF-Trfe/CNTs/BTO). The SCSPC device exhibited an energy density of 30 μWh cm-2 with a high-power density of 40 mW cm-2, and delivered an excellent self-charging performance of 363 mV (10 N) driven by both the piezoelectric ZnO NAs and the PVDF-Trfe/CNTs/BTO films. More intriguingly, the device also could also be self-charged by 184 mV due to residual stress alone, and showed excellent energy conversion efficiency and low self-discharge rate. This work illustrates for the first time the self-charging mechanism involving electrolyte ion migration driven by both electrodes and films. A comprehensive analysis strongly confirmed the important contribution of the piezoelectric ZnO NAs in the self-charging process of the SCSPC device. This work provides novel directions and insights for the development of SCSPCs.
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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".