High-throughput exploration of halide perovskite compositionally-graded films and degradation mechanisms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The conventional approach to search for new materials is to synthesize a limited number of candidates. However, this approach might delay or prevent the discovery of better-performing materials due to the narrow composition space explored. Here, we fabricate binary alloy films with a composition gradient in a single shot in less than one minute. We apply this approach to study the stability of halide perovskites. We synthesize all possible binary compositions from MAPbI 3 and MAPbBr 3 and then study their optical properties, structure, and environmental stability in a high-throughput manner. We find that perovskite alloys experience three different degradation mechanisms depending on halogen content: bromine-rich perovskites degrade by hydration, iodine-rich perovskites by the loss of the organic component, and all other intermediate alloys by phase segregation. The proposed method offers an avenue for discovering new materials and processing parameters for a wide range of applications that rely on compositional engineering.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it