SÍNTESE E CARACTERIZAÇÃO DE HETEROJUNÇÕES DE TITANATOS DE FE E CU CRESCIDOS SOBRE TIO2 PARA FOTÓLISE DA ÁGUA
Bibliographic record
Abstract
In recent years many efforts have been made to obtain materials capable of efficiently exploiting the potential of solar energy conversion.In particular, the generation of fuels by photocatalysis retains great interest due to its intrinsic properties of promoting "up-hill" reactions, with a positive free energy variation, allowing its storage in chemical compounds.The efficiency of these processes, however, is usually limited by the photoactivation of main photocatalysts in UV spectrum, wasting much of the solar energy present in visible spectrum.This work investigates the influence on photoactivation performance of heterojunctions with Fe and Cu titanate grown on TiO 2 for H2 gas production under Visible light by water-splitting.The samples were prepared according route by wet impregnation followed by post-heating treatment, where metal oxides were formed on TiO 2 particles surface with subsequent interdiffusion and formation of ternary phases of Fe 2 TiO 5 e Cu 3 TiO 4 .The materials were characterized by DRX, DSC, TGA, MEV / EDS, DRS, PLS and N 2 Physisorption techniques.The results confirmed the materials sucessful preparation, suggesting the formation of PN-type heterostructures for Fe-containing samples and a rutile-Cu doped phase for Cu-containing samples.The photocatalytic activity was evaluated in a performance test using a photoreactor system built in as part of this work.The tests allowed to identify promising preliminary results for Fe-containing samples, which demonstrated a significant photocatalytic activity in the Visible spectrum.
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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".