Interdigital <scp>MnO<sub>2</sub></scp>/<scp>PEDOT</scp> Alternating Stacked Microelectrodes for <scp>High‐Performance On‐Chip</scp> Microsupercapacitor and Humidity Sensing
Bibliographic record
Abstract
For microelectronic devices, the on‐chip microsupercapacitors with facile construction and high performance, are attracting researchers' prior consideration due to their high compatibility with modern microsystems. Herein, we proposed interchanging interdigital Au‐/MnO2/polyethylene dioxythiophene stacked microsupercapacitor based on a microfabrication process followed by successive electrochemical deposition. The stacked configuration of two pseudocapacitive active microelectrodes meritoriously leads to an enhanced contact area between MnO2 and the conductive and electroactive layer of polyethylene dioxythiophene, hence providing excellent electron transport and diffusion pathways of electrolyte ions, resulting in increased pseudocapacitance of MnO2 and polyethylene dioxythiophene. The stacked quasi‐solid‐state microsupercapacitors delivered the maximum specific capacitance of 43 mF cm−2 (211.9 F cm−3), an energy density of 3.8 μWh cm−2 (at a voltage window of 0.8 V) and 5.1 μWh cm−2 (at a voltage window of 1.0 V) with excellent rate capability (96.6% at 2 mA cm−2) and cycling performance of 85.3% retention of initial capacitance after 10 000 consecutive cycles at a current density of 5 mA cm−2, higher than those of ever reported polyethylene dioxythiophene and MnO2‐based planar microsupercapacitors. Benefiting from the favorable morphology, bilayer microsupercapacitor is utilized as a flexible humidity sensor with a response/relaxation time superior to those of some commercially available integrated microsensors. This strategy will be of significance in developing high‐performance on‐chip integrated microsupercapacitors/microsensors at low cost and environment‐friendly routes.
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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".