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Record W4413682403 · doi:10.1016/j.cej.2025.167647

Toward cesium halide-gradient stabilized CH3NH3PbI3 perovskite solar cells

2025· article· en· W4413682403 on OpenAlexaff
Yue Feng, Md. Shahiduzzaman, Neng Hani Handayani, Peng Liu, Masahiro Nakano, Makoto Karakawa, Koji Tomita, Md. Akhtaruzzaman, Jean‐Michel Nunzi, Tetsuya Taima

Bibliographic record

VenueChemical Engineering Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsHalideCaesiumPerovskite (structure)ChemistryInorganic chemistryMaterials scienceChemical engineeringCrystallographyEngineering

Abstract

fetched live from OpenAlex

Halide-Gradient intercalation emerges as a promising strategy for enhancing the stability of perovskite solar cells (PSCs). In this study, we systematically investigate the effects of interfacial cesium halide (CsX, X = Cl, Br, I) intercalation on the morphology and crystallinity, charge transport properties, and environmental stability of CH 3 NH 3 I 3 (MAPbI 3 )-based PSCs. A gradient interlayer of CsX was vacuum deposited on both sides of perovskite films. Comprehensive characterization revealed that Br − and Cl − effectively increase crystallinity, passivate defects, and facilitate charge extraction. Among the three halides, Br − intercalated devices achieved the highest power conversion efficiency (PCE) of 18.93 %, along with minimal hysteresis and excellent reproducibility. Long-term stability tests under 30 %–40 % relative humidity and thermal aging at 85 °C revealed that devices with intercalated Br − and Cl − retained over 85 % of their initial PCE after 4000 and 640 h, respectively. These findings highlight that interfacial halide intercalation, particularly with Br − , is a viable approach to improve the operational stability of perovskite photovoltaics, with minimal efficiency compromise.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.228
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.192
Teacher spread0.186 · 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 teacher head, not a consensus.

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

Citations4
Published2025
Admission routes1
Has abstractyes

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