Effect of relative humidity on crystal growth, device performance and hysteresis in planar heterojunction perovskite solar cells
Bibliographic record
Abstract
Due to the hygroscopic nature of organolead halide perovskites, humidity is one of the most important factors affecting the efficiency and longevity of perovskite solar cells. Although humidity has a long term detrimental effect on device performance, it also plays a key role during the initial growth of perovskite crystals. Here we demonstrate that atmospheric relative humidity (RH) plays a key role during the formation of perovskite thin films via the sequential deposition technique. Our results indicate that the RH has a substantial impact on the crystallization process, and hence on device performance. SEM and pXRD analysis show an increase in crystallite size with increasing humidity. At low RH, the formation of small cubic crystallites with large gaps between them is observed. The presence of these voids adversely affects device performance and leads to substantial hysteresis in the device. At higher RH, the perovskite crystals are larger in size, with better connectivity between the crystallites. This produced efficient planar heterojunction solar cells with low hysteresis. By careful control of the RH during the cell fabrication process, efficiencies of up to 12.2% are reached using P3HT as the hole-transport material.
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 | 0.001 |
| 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".