High photothermal conversion efficiency of RF sputtered Ti4O7 Magneli phase thin films and its linear correlation with light absorption capacity
Bibliographic record
Abstract
RF-sputtering is used to deposit Ti 4 O 7 -Magneli-phase films onto various substrates at deposition temperatures ( T s ) ranging from 25 to 650 °C. Not only the structural, but also electrical conductivity, optical absorbance and photothermal properties of the Ti 4 O 7 films are shown to change significantly with T s . A T s of 500 °C is pointed out as the optimal temperature that yields highly-crystalized pure-Ti 4 O 7 -Magneli phase with a densely-packed morphology and a conductivity as high as 740 S/cm. The Ti 4 O 7 films deposited at T s = 450–500 °C also exhibited the highest optical absorption over all the broad (200–1500) nm range. The absorbed sunlight (AM1.5) was efficiently converted into heat by raising the temperature of the Ti 4 O 7 films up to ~ 54 °C. Thus, the external photothermal efficiency (η ext ) of the Ti 4 O 7 films, was found to be as high as ~ 74%. This is the highest η ext reported so far for sputtered-Ti 4 O 7 coatings (just ~ 450 nm-thick), highlighting their significant potential for photothermal applications such as desalination, deicing and/or smart windows. Finally, the η ext of the Ti 4 O 7 coatings is demonstrated, for the first time, to be linearly correlated to their integrated light absorption coefficient. This fundamental relationship paves the way towards the design and optimization of highly efficient solar-thermal conversion 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".