MétaCan
Menu
Back to cohort
Record W4411459449 · doi:10.1021/acsaem.5c01035

Engineered Vacuum-Incorporated Rubidium Iodide for CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> Perovskite Solar Cell Stability

2025· article· en· W4411459449 on OpenAlexaff
Neng Hani Handayani, Md. Shahiduzzaman, Munkhtuul Gantumur, Yue Feng, Y Higashi, Masahiro Nakano, Makoto Karakawa, Koji Tomita, Jean‐Michel Nunzi, Tetsuya Taima

Bibliographic record

VenueACS Applied Energy Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsQueen's University
FundersJapan Society for the Promotion of Science
KeywordsRubidiumPerovskite (structure)IodideMaterials sciencePerovskite solar cellSolar cellInorganic chemistryChemical engineeringChemistryOptoelectronicsCrystallographyMetallurgyPotassiumEngineering

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide A cation engineering strategy is crucial for optimizing CH 3 NH 3 PbI 3 (MAPbI 3 )-based perovskite solar cells (PSCs) and for controlling their interfacial properties to achieve high stability. In this study, we used vacuum-deposited rubidium iodide (RbI) and induced incorporation into solution-processed MAPbI 3 to obtain high-quality dense perovskite films for highly stable PSCs. An optimized 10 nm film of RbI was deposited and incorporated on both interfaces of the MAPbI 3 film, at the interfaces with the electron transport layer (ETL) and hole transport layer (HTL), forming the structure RbI–MAPbI 3 –RbI. This significantly enhanced the host MAPbI 3 morphology, grain size, and crystallinity. PSCs with RbI–MAPbI 3 –RbI as perovskite film exhibited power conversion efficiencies (PCEs) as high as 17.50%, whereas the pristine MAPbI 3 devices reached 14.81%. The RbI–MAPbI 3 –RbI-based devices (non-encapsulated) retained over 95% of their initial PCE after 2300 h in ambient air under a relative humidity of 25%–35%. RbI incorporation improves the hydrophobicity of the perovskite film, leading to an improvement in moisture stability. The present work demonstrates the potential for developing highly stable perovskite devices through precise RbI incorporation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.188
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueACS Applied Energy MaterialsSame topicPerovskite Materials and ApplicationsFrench-language works237,207