Room Temperature Synthesis and Thermal Evolution of Porous Nanocrystalline TiO<sub>2</sub> Anatase
Bibliographic record
Abstract
TiO 2 nanoparticles are a major component in many areas, and especially for dye-sensitized solar cells (DSSC) as a result of their electronic structure that allows them to collect the electrons transferred from the dye molecules after sunlight irradiation, as well as of their semiconducting properties, which provide the surface transport of these electrons up to the collecting electrode. However, for this application or others, the optimization of both structural and electronic properties of titanium oxide is still a challenge because it depends on both crystalline structure and material nano/mesostructure. We report how small (<6 nm) titanium oxide nanoparticles were synthesized by a single step method, with the anatase crystalline phase obtained at room temperature, and an opened nanostructure. A mixture design method was required to identify the precise composition that led to the suitable material. Mesoporous materials made of pure anatase nanocrystals were obtained with the suitable porosity (5 nm pore diameter, 190 m 2 /g, 0.3 mL/g porous volume) without any surfactant agent. Both the evolution of the crystal size and nature of the phases were studied as a function of heating temperatures ranging from 20 to 800 °C. These materials display a good thermal stability up to 400 °C, in term of crystal size, and up to 700 °C, regarding the crystalline phase. Finally, the study of their semiconducting properties as a function of the crystal size allowed us to confirm the previous theoretical models regarding the crystal size-dependence of band gap and to set the limit of the size quantum confinement effect around 7 nm.
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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) | 0.000 | 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".