Laser Selective Photoactivation of Amorphous TiO<sub>2</sub> Films to Anatase and/or Rutile Crystalline Phases
Bibliographic record
Abstract
Titanium dioxide (TiO 2 ) is a remarkable metal-oxide semiconductor with unique optoelectronic properties ideal for photovoltaics and photocatalytic conversion. The principal crystalline phases for TiO 2 are anatase, rutile, and brookite. The combination of both anatase and rutile crystalline structures can positively impact the optoelectronic properties of TiO 2 films. With standard sol–gel processing, high-temperature conversion generally yields one dominant phase and limits the combined use of anatase and rutile TiO 2 for optoelectronic devices. We report on a singular route to controllably engineer hybrid nanocrystalline films of TiO 2 at room temperature to synergistically exploit both anatase and rutile TiO 2 phases. Relying on sol–gel chemistry, this approach starts from an amorphous film and uses photoinduced activation using a low-power laser to achieve specific spatially controlled pattern consisting of different TiO 2 crystalline phases within the same film. While achieving remarkable precision, reproducibility, and control, we also avoid costly high-temperature, ion-metal-assisted, or specific atmospheric processing that currently prevents the integration of TiO 2 in several optoelectronic platforms. In the future, we believe this unprecedented level of control and the ability to engineer the TiO 2 crystalline structure at the microscopic scale will allow the design and fabrication of novel high-performance TiO 2 hybrids for energy conversion and environmental applications.
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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) | 0.002 | 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".