Epitaxial Bi<sub>2</sub>FeCrO<sub>6</sub> Multiferroic Thin Film as a New Visible Light Absorbing Photocathode Material
Bibliographic record
Abstract
Ferroelectric materials have been studied increasingly for solar energy conversion technologies due to the efficient charge separation driven by the polarization induced internal electric field. However, their insufficient conversion efficiency is still a major challenge. Here, a photocathode material of epitaxial double perovskite Bi(2) FeCrO(6) multiferroic thin film is reported with a suitable conduction band position and small bandgap (1.9-2.1 eV), for visible-light-driven reduction of water to hydrogen. Photoelectrochemical measurements show that the highest photocurrent density up to -1.02 mA cm(-2) at a potential of -0.97 V versus reversible hydrogen electrode is obtained in p-type Bi(2) FeCrO(6) thin film photocathode grown on SrTiO(3) substrate under AM 1.5G simulated sunlight. In addition, a twofold enhancement of photocurrent density is obtained after negatively poling the Bi(2) FeCrO(6) thin film, as a result of modulation of the band structure by suitable control of the internal electric field gradient originating from the ferroelectric polarization in the Bi(2) FeCrO(6) films. The findings validate the use of multiferroic Bi(2) FeCrO(6) thin films as photocathode materials, and also prove that the manipulation of internal fields through polarization in ferroelectric materials is a promising strategy for the design of improved photoelectrodes and smart devices for solar energy conversion.
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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".