Transparent Zinc‐Mesh Electrodes for Solar‐Charging Electrochromic Windows
Bibliographic record
Abstract
Abstract Newly born zinc‐anode‐based electrochromic devices (ZECDs), incorporating electrochromic and energy storage functions in a single transparent platform, represent the most promising technology for next‐generation transparent electronics. As the existing ZECDs are limited by opaque zinc anodes, the key focus should be on the development of transparent zinc anodes. Here, the first demonstration of a flexible transparent zinc‐mesh electrode is reported for a ZECD window that yields a remarkable electrochromic performance in an 80 cm2 device, including rapid switching times (3.6 and 2.5 s for the coloration and bleaching processes, respectively), a high optical contrast (67.2%), and an excellent coloration efficiency (131.5 cm2 C−1). It is also demonstrated that such ZECDs are perfectly suited for solar‐charging smart windows as they inherently address the solar intermittency issue. These windows can be colored via solar charging during the day, and they can be bleached during the night by supplying electrical energy to electronic devices. The ZECD smart window platform can be scaled to a large area while retaining its excellent electrochromic characteristics. These findings represent a new technology for solar‐charging windows and open new opportunities for the development of next‐generation transparent batteries.
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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".