Towards Unlocking/Tuning the Mott Transition Temperature in Alkaline-Doped Vanadium Oxide Thermochromic Coatings and Potential Green Air-Conditioning via Room Temperature VxOy-V-VxOy Layered Coatings
Bibliographic record
Abstract
In this contribution, we validate for the first time that the near infrared-infrared (NIR-IR) modulation of the optical transmission (DTTRANS = T(T<TMIT) - T(T>TMIT)) of vanadium oxide-based nanomaterials can be controlled or tuned via a genuine approach with a simultaneous drastic reduction of its Mott transition temperature TMIT. More accurately, we report a significant thermochromism in multilayered V2O5/V/V2O5 stacks equivalent to that of pure VO2 thin films but with a far lower transition temperature TMIT. Such a multilayered V2O5/V/V2O5 thermochromic system exhibited a net control or tunability of the optical transmission modulation in the NIR-IR (DTTRANS) via the nano-scaled thickness of the intermediate vanadium layer. In addition, the control of DTTRANS is accompanied by a noteworthy diminution of the Mott transition temperature TMIT from the bulk value of 68.8 °C to the range of 27.5–37.5 °C. The observed peculiar thermochromism in the multilayered V2O5/V/V2O5 is likely to be ascribed to a significant interfacial diffusion or an excessive interfacial stress/strain, and/or to an effective halide (Na, K, Ca) doping. This doping is driven by a significant diffusion from the borosilicate substrate surface towards the V2O5/V/V2O5 stacks. If the upscaling of this approach is validated, the current findings would contribute to advancing thermochromic nanomaterials and their applications in smart windows for managing solar heat and green air-conditioning technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".