Soft Polymer–Organolead Halide Perovskite Films for Highly Stretchable and Durable Photodetectors with Pt–Au Nanochain-Based Electrodes
Bibliographic record
Abstract
The rigid and brittle nature of methylammonium lead iodide (MAPbI 3 ) polycrystalline films limits their application in stretchable devices due to rapid deterioration in performance on cycling. By incorporation of polymer chains in the MAPbI 3 films, a strategy to alter the mechanical modulus and the viscoelastic nature of the films has been developed. Combining this with flexible nanochain electrodes, highly stretchable and stable perovskite devices have been fabricated. The resultant polymer-MAPbI 3 photodetector exhibits ultralow dark currents (∼10 –11 A) and high light switching ratios (∼10 3 ) and maintains 75% of performance after 30 days. The viscoelastic nature and lower modulus of the polymer improve the energy dissipation in the polymer-MAPbI 3 devices; as a result, they maintain 52% of the device performance after 10000 stretching cycles at 50% strain. The difference in the mechanical behavior is clearly observed in the failure mode of the two films. While rapid catastrophic cracking is observed in MAPbI 3 films, the intensity and size of such crack formation are highly limited in polymer-MAPbI 3 films, which prevent their failure.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".