Constructing Synergistic Interactions Between Multi‐Hydroxyl Molecules and Perovskite to Alleviate Mechanical‐Thermal Mismatch for Achieving High‐Performance Flexible Solar Cells
Bibliographic record
Abstract
Abstract Due to the presence of residual tensile strain, as well as the inherent brittleness and film quality of the perovskite, flexible perovskite solar cells (f‐PSCs) face ongoing challenges in stability. To address these issues, this study introduces a multi‐hydroxyl regulated stress management strategy for f‐PSCs. Three hydroxyl‐substituted phenylacetic acids (p‐hydroxyphenylacetic acid, 3,4‐dihydroxyphenylacetic acid, and 2‐(3,4,5‐trihydroxyphenyl)acetic acid) are incorporated into the perovskite films to investigate the significance of their interaction modes with perovskite in regulating f‐PSC performance. These multi‐hydroxyl molecules, through their progressively enhanced synergistic interactions with the perovskite, effectively promote greater energy dissipation during stress deformation, reducing the Young's modulus of the perovskite by 11.1% and decreasing the thermal expansion coefficient of perovskite film by 38.5%, thereby improving the mechanical strength of the f‐PSCs. Additionally, the multi‐hydroxyl molecules regulate the excess PbI2 during the fabrication process of perovskite, enhancing the film quality and optimizing the energy level alignment. As a result, the inverted f‐PSCs achieved a champion power conversion efficiency (PCE) of 25.01%. These devices demonstrated excellent mechanical and thermal stability, retaining 90% of their original PCE after 3000 bending cycles, and maintaining 83% of their initial PCE after continuous heating at 85 °C for 1000 h.
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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".