Self-Trapped Charge Carriers in Defected Amorphous TiO<sub>2</sub>
Bibliographic record
Abstract
Self-trapped polarons and excitons associated with defects can localize energy in ways that can modify the material properties. The doped amorphous titanium dioxide (aTiO 2 ) that possesses self-trapped polarons and excitons due to its inherited disorder and extrinsic doping has recently drawn increased attention as potential cheap visible light photocatalyst. However, the synergetic role that intrinsic and extrinsic defects play in enhancing the photoactivity of doped aTiO 2 is still a mystery. To gain insights into the photocatalytic behavior of defected aTiO 2, in this study, we analyzed three Fe-doped aTiO 2 models having Fe in Fe(II), Fe(III), and Fe(IV) oxidation states. The density functional theory with Hubbard energy correction (DFT+U) calculations conducted in this study clearly indicate that the visible light absorption of aTiO 2 will be improved by doping it with Fe. Furthermore, our investigation reveals that even though all the doped aTiO 2 models showed highly localized states at mid gap and band edges, doping with Fe(II) led to maximum visible light absorption. This distinct behavior of Fe(II)-doped aTiO 2 is attributed to the unique position of its mid gap states, high self-trap energy, low mobility, and weak chemical bonds.
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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".