Low resistivity WxV1−xO2-based multilayer structure with high temperature coefficient of resistance for microbolometer applications
Bibliographic record
Abstract
Materials that exhibit semiconductor-to-metal phase transition (SMT) are commonly used as sensing layers for the fabrication of uncooled microbolometers. The development of highly responsive microbolometers would benefit from using a sensing material that possesses a large thermal coefficient of resistance (TCR) close to room temperature and a resistivity low enough to compromise between noise reduction and high TCR, while it should also satisfies the requirements of current CMOS technology. Moreover, a TCR that remains constant when the IR camera surrounding temperature varies would contribute to achieve reliable temperature measurements without additional corrections steps for TCR temperature dependence. In this paper, the characteristics of the SMT occurring in undoped and tungsten-doped vanadium dioxide thin films deposited on LaAlO3 (100) substrates are investigated. They are further exploited to fabricate a WxV1−xO2 (0 ≤ x ≤ 2.5) multilayer structure exhibiting a bottom-up gradient of tungsten content. This MLS displays a combination of properties that is promising for application to uncooled microbolometer, such as a large TCR of −10.4%/ °C and low resistivity values ranging from 0.012 to 0.10 Ω-cm over the temperature range 22 °C–42 °C.
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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".