Electrochromic Battery Displays with Energy Retrieval Functions Using Solution‐Processable Colloidal Vanadium Oxide Nanoparticles
Bibliographic record
Abstract
Abstract Electrochromic displays have attracted increased attention owing to their reversible switch of multicolors. However, the external voltage requirement for triggering the color switching makes them far from an optimum energy‐efficient technology. The newly developed electrochromic batteries eliminate the energy consumption for coloration while they can retrieve the consumed energy for bleaching. Such features make the electrochromic battery technology the most promising technology for energy‐efficient electrochromic displays. Here, a scalable method to synthesize colloidal V 3 O 7 nanoparticles is presented, which is compatible with solution‐process techniques for aqueous Zn‐V 3 O 7 electrochromic battery displays. The Zn‐V 3 O 7 electrochromic battery display shows an optical transmittance contrast (21%), rapid self‐coloration time (6.6 s), and switching times (10.4/28.6 s for coloration/bleaching processes). Moreover, the electrochromic battery display shows a compelling energy retrieval function. For a proof of concept, a prototype display is constructed, which possesses an open‐circuit potential (OCP) of 1.38 V. The prototype display can reversibly switch between the multicolors (fully yellow, fully grayish‐blue, and half yellow‐half grayish‐blue images) and partially retrieve the consumed energy. This research presents a facile strategy to synthesize colloidal V 3 O 7 nanoparticles, as well as a novel electrochromic battery display having energy retrieval functions, thus facilitating the development of energy‐efficient electrochromic displays.
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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".