Mixed Molybdenum-Tungsten Oxide as Dual-Band, VIS-NIR Selective Electrochromic Material
Bibliographic record
Abstract
Energy efficiency of smart windows can be greatly improved by integrating dual-band electrochromic materials based on nanostructured doped metal oxides, as these will allow for a dynamic and independent control of light and heat supplies in buildings respectively related to transmitted visible (VIS) and near-infrared (NIR) solar radiations. Mixed molybdenum – tungsten oxides MoyW1-yO3-δ “MoWOx” are considered as innovative compounds in this context: in comparison with parent WO3-δ formulations, a remarkable increase of unpaired electrons can be obtained from the formation of a larger amount of both reduced species and oxygen vacancies during the synthetic process of MoWOx materials, with a consequently boosted intensity of light absorption by 850-900 nm wavelengths. Consecutively, spin-coated films obtained from MoWOx structures solvothermally synthesized for 1h from 2/1 Mo/W atomic ratios are shown to be electrochromically commutable through a noticeable VIS-darkened and NIR-transparent warm mode, while WO3-δ benchmarks classically evolve between bright (VIS & NIR bleached), cool (VIS-bleached, NIR-opaque) and dark (VIS & NIR opaque) states. All in all, such advanced optical functionalities are of high interest for fine-tuning the selectivity and improving the efficiency of electrochromic fenestration solutions, further improving their capacity to adapt to different climates, seasons, and users preferences.
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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".