(Invited) Photovoltaic Proprieties and Photocatalytic Activity of Perovskite Oxide-Based Systems
Bibliographic record
Abstract
Photocatalytic water splitting with semiconductor materials has been investigated as a clean and renewable process for directly converting sunlight into chemical energy. In particular, multiferroics MFs have recently been used for applications in both photocatalysis (PC) and photovoltaics (PV) due to their ferroelectric properties and narrow band gaps, allowing them to harness the majority of solar radiation in the visible range. As typical MFs, BiFeO3 (BFO) and Bi2FeCrO6 (BFCO) have been recognized as potential materials for PV and visible-light PC applications owing to their suitable band gap (1.4-2.8 eV) and good chemical stability. However, the investigations on such materials for photocatalytic water splitting are still limited and efforts have to be undertaken to demonstrate their full potential. An efficient PV system is at the basis on an effective PC process. Thus, the control of PV properties of MFs is a critical issue for achieving highly efficient photocatalytic system. Here we will present, the controlled growth and characterization of BFCO and BFO thin films and nanostructures via pulsed laser and hydrothermal techniques. The PV properties of such systems and their photocatalytic activity will be also discussed
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".