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Record W7114916796 · doi:10.1021/acsenergylett.5c03275

Perovskite Photovoltaics: Pick FAPbI <sub>3</sub> and Stick to It

2025· article· en· W7114916796 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Energy Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFormamidiniumPerovskite (structure)HalideTandemBand gapIodidePhotovoltaics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.188
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it