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Record W4377226157 · doi:10.1002/cjoc.202300128

Advances to Stabilize Photoactive Phase of <scp>FAPbI<sub>3</sub></scp> Perovskite<sup>†</sup>

2023· article· en· W4377226157 on OpenAlex
Kailin Li, Huanping Zhou

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

VenueChinese Journal of Chemistry · 2023
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsPerovskite (structure)FormamidiniumChemistryCrystallizationNucleationPhotoactive layerPhase (matter)Energy conversion efficiencyTrihalideChemical engineeringCrystal (programming language)IodideNanotechnologyMaterials scienceHalideOrganic solar cellCrystallographyInorganic chemistryOptoelectronicsOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Comprehensive Summary Recently, hybrid organic–inorganic perovskite materials have drawn widespread attention because of their outstanding optoelectrical properties ( i.e ., high absorption coefficient, long carrier diffusion distance), hence they are suitable light‐absorbing materials for photovoltaic application. Among all perovskite materials, formamidinium lead iodide (FAPbI 3 ) based solar cells exhibit impressive power conversion efficiency (PCE) at laboratory stage, showing great potential to compete with silicon‐based solar cell. However, FAPbI 3 still suffers from poor phase stability which is the prior problem that needs to be addressed before its further commercialization. To be precise, the photoactive phase (α phase) is thermodynamically metastable at room temperature, which not only makes α phase tend to transform into photoinactive phase (δ phase), but also causes competitive crystallization between two phases during the film preparation process, making it hard to fabricate pure α‐FAPbI 3 films. In our review, we summarized key factors that are vital for obtaining high‐quality FAPbI 3 perovskite thin films and enhancing the stability of FAPbI 3 photoactive phase. First of all, precursor solution stability is of great importance since the conditions of precursor solution determine the nucleation and crystal growth process of perovskite. By introducing coordinating additives, using FAPbI 3 single crystal as raw material or applying co‐solution strategy, the impurities formed by side reaction during precursor solution aging can be effectively suppressed, thus the stability of FAPbI 3 solution can be greatly prolonged. Second, the crystallization kinetics of FAPbI 3 have been systematically manipulated to obtain dense and large grain size perovskite films. Through introducing intermediate phase, regulating the surface energy, and retarding the crystal growth of FAPbI 3 in crystallization process, not only films without pinholes and fewer grain boundaries can be obtained, the pre‐formed δ phase at room temperature can also be well‐suppressed, thus high‐quality α‐FAPbI 3 films can be obtained. Third, how to thermodynamically enhance the phase stability of acquired FAPbI 3 film has been extensively studied. The Gibbs free energy of FAPbI 3 photoactive phase can be reduced through composition engineering, dimension engineering and external additives engineering, hence the phase transition barrier from α phase to δ phase has been significantly improved, which further enhance the phase stability of α‐FAPbI 3 . Lastly, we pointed out challenges of each method and proposed potential applications of mentioned strategies on improving the stability of all kinds of perovskite materials, thus further boost the commercialization of perovskite solar cell devices.

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 score0.018
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.256
Teacher spread0.248 · 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