Enhancing Voltage Tolerance of CsFA Perovskite‐Based Rectifying Diodes Through Ionic Liquid Incorporation
Bibliographic record
Abstract
Abstract Metal halide perovskites have gained significant attention owing to their remarkable semiconductor properties and superior optoelectronic characteristics. In this study, low‐voltage‐driven rectifying diodes are developed based on CsFAPbI 3 and their voltage tolerance is enhanced by incorporating ionic liquids. The fabricated FTO/TiO 2 /CsFAPbI 3 /Ag diode exhibits a low turn‐on voltage of 181 mV and a high rectifier ratio of 2.8 × 10 4 under 400 mV voltage application, which are superior or comparable to those of reported solution processable diodes. However, its voltage tolerance is limited; the hysteresis and the leakage current increase during voltage sweep cycling. By incorporating an ionic liquid, 1‐hexyl‐3‐methylimidazolium chloride, into CsFAPbI 3 , the diodes voltage tolerance improves, maintaining the excellent performances. Alternating current (AC) impedance measurements suggeste that this improvement is attributable to reduced ion migration. AC to direct current (DC) conversion simulation studies indicated that the CsFAPbI 3 ‐based diodes achieve an output voltage of 227 mV under a 400 mV, 125 kHz AC input and 84 mV under a 400 mV, 13.56 MHz input, highlighting their potential for AC–DC conversion in low‐power applications. In addition, the improved voltage tolerance of the CsFAPbI 3 also shows photodetector devices, underlining the vast potential of ionic liquid‐incorporated metal halide perovskite‐based optoelectronic devices.
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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".