Galvanostatic Rejuvenation of Electrochromic WO<sub>3</sub> Thin Films: Ion Trapping and Detrapping Observed by Optical Measurements and by Time-of-Flight Secondary Ion Mass Spectrometry
Bibliographic record
Abstract
Electrochromic (EC) smart windows are able to decrease our energy footprint while enhancing indoor comfort and convenience. However, the limited durability of these windows, as well as their cost, result in hampered market introduction. Here, we investigate thin films of the most widely studied EC material, WO 3 . Specifically, we combine optical measurements (using spectrophotometry in conjunction with variable-angle spectroscopic ellipsometry) with time-of-flight secondary ion mass spectrometry and atomic force microscopy. Data were taken on films in their as-deposited state, after immersion in a Li-ion-conducting electrolyte, after severe degradation by harsh voltammetric cycling and after galvanostatic rejuvenation to regain the original EC performance. Unambiguous evidence was found for the trapping and detrapping of Li ions in the films, along with a thickness increase or decrease during degradation and rejuvenation, respectively. It was discovered that (i) the trapped ions exhibited a depth gradient; (ii) following the rejuvenation procedure, a small fraction of the Li ions remained trapped in the film and gave rise to a weak short-wavelength residual absorption; and (iii) the surface roughness of the film was larger in the degraded state than in its virgin and rejuvenated states. These data provide important insights into the degradation mechanisms of EC devices and into means of achieving improved durability.
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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) | 0.000 | 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".