Thermochromic La1−xSrxMnO3 (x=0.1, 0.175, and 0.3) smart coatings grown by reactive pulsed laser deposition
Bibliographic record
Abstract
Thermochromic La1−xSrxMnO3 (x=0.1, 0.175, and 0.3) (LSMO) smart coatings were synthesized on (100) silicon and (0001) sapphire substrates by means of reactive pulsed laser deposition process at relatively low substrate temperature (500°C) and without postannealing. X-ray diffraction patterns indicated that all deposited LSMO films have polycrystalline structures. The energy dispersive x-ray spectroscopy analysis indicated approximately the same La∕Sr ratio in the formed LSMO coatings as in their corresponding targets. While, the x-ray photoelectron spectroscopy analysis of the LSMO/sapphire revealed that the strontium segregate at the film surface. The thermochromism of LSMO coatings was investigated by measuring their infrared reflectance as a function of temperature (up to 160°C). It was observed that the reflectance decreased as the temperature increased. Reflectance switching of about 25% was achieved in La0.7Sr0.3MnO3∕Si at a wavelength of 5μm. The sheet electrical resistivity as a function of temperature (up to 130°C) of LSMO/sapphire was investigated by means of the standard four-point probe technique. The resistivity decreased with increasing the temperature and no metallic-to-insulator transition was observed. However, it is found that the resistivity is very sensitive to the concentration level of Sr dopant: the resistivity decreased as the concentration of Sr increased. In addition, at room temperature, a higher temperature coefficient of resistance of −2.30%∕°C was achieved in La0.9Sr0.1MnO3 thin films. Finally, these LSMO smart coatings are promising materials for optical switching and IR uncooled bolometer devices.
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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".