De‐Intercalation of Iodoplumbate(DMSO)<i><sub>x</sub></i> Complex for Uniaxially Oriented Halide Perovskite Thin‐Film Solar Cells
Bibliographic record
Abstract
Abstract Organic lead halide perovskite solar cells (PSCs) have become a viable alternative for next‐generation photovoltaic systems. The significance of reproducibly processing perovskite with less defects comes from the fact that imperfections have a major impact on the solar cell's performance and long‐term stability. Although it is well known that cautious precursor processing has a significant influence on perovskite defect generation, there haven't been extensive investigations on the serial associations between precursor processing, perovskite orientation, and defect generation in PSCs. Making use of a unique precursor chemistry treatment technique that facilitates uniaxially oriented perovskite growth, it is aimed to mitigate defects of sequentially spin‐coated perovskite. Through the temperature‐dependent configurational entropic effect on coordination between iodoplumbate and dimethylsulfoxide (DMSO), a DMSO de‐intercalation processing method is developed. This method enables the induction of uniaxially‐oriented α‐FA0.9MA0.1PbI3‐xBrx (FA: formamidnium, MA: methylammomnium, x < 0.13) perovskite growth parallel to substrates. As a result, this processing delivered significant advances in power conversion efficiency (24.02%) and ambient operational stability under light. This straightforward technique provides a accesible process for producing efficient and stable perovskite solar cells, enabling uniaxially oriented perovskite fabrication without complicated procedures or additional substances.
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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".