Perovskite Photovoltaics: Pick FAPbI <sub>3</sub> and Stick to It
Bibliographic record
Abstract
The choice of the perovskite composition is pivotal for solar cells. In this Perspective, we argue that, among known perovskite compositions, formamidinium lead iodide (FAPbI 3 ) stands out due to its optimal bandgap, absence of halide segregation observed in mixed-halide alloys, and immunity against oxidation unlike in tin-based perovskites. However, stabilizing the photoactive α-FAPbI 3 remains a major challenge, as it readily transforms into the thermodynamically stable δ-FAPbI 3 at room temperature. In this Perspective, we briefly review the challenges in stabilizing α-FAPbI 3, summarize strategies to address this instability with minimal and no bandgap penalty, and offer our outlook on future directions: (i) stabilization of α-FAPbI 3 without bandgap compromise; (ii) understanding the mechanisms of additive-less stabilized α-FAPbI 3 single-crystal perovskite solar cells (PSCs); (iii) development of all-ambient air fabricated tandem solar cells using α-FAPbI 3 as a narrow-bandgap subcell; and (iv) adoption of only green solvents to enable scalable, sustainable, and widespread manufacturing of perovskite solar modules.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".