Porous RuO<sub><i>x</i></sub>N<sub><i>y</i></sub>S<sub><i>z</i></sub> Electrodes for Microsupercapacitors and Microbatteries with Enhanced Areal Performance
Bibliographic record
Abstract
Three-dimensional (3D) electrodes with improved areal energy have become increasingly important for microscale energy storage at the dawn of the Internet of Things. At its heart are a plethora of microelectronic devices that require embedded energy harvesters and energy storage components to ensure autonomy. In this study, we develop porous metallic microstructures and their conformal coating with a new RuO x N y S z material through a facile optimized electrodeposition process. The microporous structure with a nanodendritic network shows high areal capacitance (14.3 F cm –2 for the electrode and 714 mF cm –2 for an all-solid-state microsupercacitor) and stable performance (>80% retention after 5000 cycles) toward H + storage. Remarkable Li + storage capability with high areal capacity (5 mAh cm –2 ) and rate characteristics (1.5 mAh cm –2 at 3 C ) is also observed. These results coupled with a facile synthetic strategy can thus offer inspiration for large-scale production of 3D porous electrodes for microbatteries and microsupercapacitors.
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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".