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Record W3093609814 · doi:10.1002/solr.202000495

Advances in Phase Stability of Cesium Lead Halide Perovskites

2020· article· en· W3093609814 on OpenAlexaff
Meiqian Tai, Cho Fai Jonathan Lau, Hong Lin, Zhiping Wang

Bibliographic record

VenueSolar RRL · 2020
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsMorgan Solar (Canada)
FundersNational Natural Science Foundation of China
KeywordsHalideCaesiumPerovskite (structure)Phase (matter)Lead (geology)Phase transitionIodideMaterials scienceNanotechnologyChemical physicsChemistryInorganic chemistryPhysicsThermodynamicsGeologyCrystallography

Abstract

fetched live from OpenAlex

Cesium lead halide (CsPbX3) perovskite solar cells have gained considerable attention for their rapid evolution to over 19% power conversion efficiency. Despite high chemical stability, the spontaneous phase transition from desired black phase to nonperovskite yellow phase after long‐time storage or under attack of extrinsic factors significantly hinders their development and application. This review summarizes the current advances in recognizing phase transition behaviors of cesium lead halides, especially cesium lead tri‐iodide, and addressing phase instability issues. Advancing strategies that are used for phase stabilization, including compositional engineering, grain size reduction, modification of surface termination, and strain engineering, are highlighted as well as their present limitations. Also, existing scientific debates on phase transition and stability, origin of these arguments, and possible solutions are presented and discussed. Finally, some potential avenues for further enhancing stability of cesium lead halides are proposed based on current understandings.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.259
Teacher spread0.239 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2020
Admission routes1
Has abstractyes

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