Dark Self-Healing-Mediated Negative Photoconductivity of a Lead-Free Cs<sub>3</sub>Bi<sub>2</sub>Cl<sub>9</sub> Perovskite Single Crystal
Bibliographic record
Abstract
Recently, halide perovskites have emerged as a promising material for device applications. Lead-based perovskites have been widely explored, while investigation of the optical properties of lead-free perovskites remains limited. Lead-halide perovskite single crystals have shown light-induced positive photoconductivity, and as lead-free perovskites are optically active, they are expected to demonstrate similar properties. However, we report here light-induced negative photoconductivity with slow recovery in lead-free Cs 3 Bi 2 Cl 9 perovskite. Femtosecond transient reflectance (fs-TR) spectroscopy studies further reveal that these electronic transport properties are due to the formation of light-activated metastable trap states within the perovskite crystal. The figure of merits were calculated for Cs 3 Bi 2 Cl 9 single-crystal detectors, including responsivity (17 mA/W), detectivity (6.23 × 10 11 Jones), and the ratio of current in dark to light (∼7160). These observations for Cs 3 Bi 2 Cl 9 single crystals, which were optically active but showed retroactive photocurrent on irradiation, remain unique for such materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".