Enhanced stability of ITO/In<inf>2</inf>O<inf>3</inf> thin film thermocouples by coating Al<inf>2</inf>O<inf>3</inf> layer
Bibliographic record
Abstract
Ceramic thin film thermocouples as a kind of promising candidate thermal sensor have been used to replace noble-metal thin film thermocouples to measure the hot section of turbine energies. ITO (In2O:SnO2=90wt.%:10wt.%) and In2O3thin films with spinning Al2O3coating layer were investigated systematically and ITO/In2O3thin film thermocouples were evaluated at 1230°C for a long time. Uncoated ITO and In2O3thin film annealed at different temperatures exhibited polycrystalline phases and the degree of crystallization become more obvious along with the increase of annealing temperatures. From SEM morphologies, the grain sizes of In2O3and ITO exhibited increasing trend obviously. When ITO and In2O3thin films coated with Al2O3were annealed at 1250°C for different time, the change of thicknesses shown that alumina coating layer could effectively slow down the volatilization of ITO and In2O3films, especially ITO films. The ITO/In2O3thin film thermocouple coated with Al2O3could endure 1230°C for a long time than that of uncoated thermocouple, and the sensitivity could reach to 151.7 pV/°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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".