High-Throughput Screening of Lead-Free Perovskite-like Materials for Optoelectronic Applications
Bibliographic record
Abstract
We use high-throughput density functional theory calculations to screen lead-free perovskite-like materials with compositions A 2 BB′X 6, ABX 4, and A 3 B 2 X 9 for optoelectronic performance. We screen monovalent A and B′ cations from Na, K, Rb, Cs Cu, and Ag, trivalent B cations from Ga, In, and Sb, and monovalent anions from Cl, Br, and I. Our screening procedure is based on formation energy and hybrid HSE06 functional predicted bandgaps. We screened more than 480 compounds and found 10 compounds that have bandgaps in the 1.5–2.5 eV range. Of these 10 compounds, seven are new, not having been reported before. We further characterize effective masses, density of states, and absorption coefficients of these selected compounds for their suitability in optoelectronic applications. All 10 of these selected compounds are lead-free and are solution processable. These compounds pave a path forward for lead-free photovoltaics and light emission devices.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".