Materials Processing Routes to Trap-Free Halide Perovskites
Bibliographic record
Abstract
Photovoltaic devices based on lead iodide perovskite films have seen rapid advancements, recently achieving an impressive 17.9% certified solar power conversion efficiency. Reports have consistently emphasized that the specific choice of growth conditions and chemical precursors is central to achieving superior performance from these materials; yet the roles and mechanisms underlying the selection of materials processing route is poorly understood. Here we show that films grown under iodine-rich conditions are prone to a high density of deep electronic traps (recombination centers), while the use of a chloride precursor avoids the formation of key defects (Pb atom substituted by I) responsible for short diffusion lengths and poor photovoltaic performance. Furthermore, the lowest-energy surfaces of perovskite crystals are found to be entirely trap-free, preserving both electron and hole delocalization to a remarkable degree, helping to account for explaining the success of polycrystalline perovskite films. We construct perovskite films from I-poor conditions using a lead acetate precursor, and our measurement of a long (600 ± 40 nm) diffusion length confirms this new picture of the importance of growth conditions.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".