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Record W4360615387 · doi:10.3390/cryst13040549

Effects of Solvent Vapor Atmosphere on Photovoltaic Performance of Perovskite Solar Cells

2023· article· en· W4360615387 on OpenAlexafffund
Miao He, Shuyan Chen, Taoran Wang, Gu Xu, Na Liu, Fan Xu

Bibliographic record

VenueCrystals · 2023
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsMcMaster University
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceShenzhen Municipal Science and Technology Innovation CouncilNatural Sciences and Engineering Research Council of CanadaScience, Technology and Innovation Commission of Shenzhen MunicipalityNational Natural Science Foundation of China
KeywordsChlorobenzeneMaterials scienceFabricationSolventPerovskite (structure)Chemical engineeringAtmosphere (unit)Photovoltaic systemAnnealing (glass)Energy conversion efficiencyPhotovoltaicsPerovskite solar cellDimethylformamideNanotechnologyChemistryOptoelectronicsOrganic chemistryCatalysisComposite material

Abstract

fetched live from OpenAlex

Tremendous efforts have been devoted to facilitating the commercialization of perovskite solar cells (PSCs) in the past decade. However, the influence of solvent vapor atmosphere on PSC device performance during its fabrication still lacks related investigations. Here, by using three commonly employed solvent vapors during the perovskite annealing process, i.e., isopropanol, chlorobenzene and dimethylformamide, we reveal the effects of atmosphere on related perovskite film properties and device performance. The results indicate that perovskite films prepared under these external solvent vapors exhibit distinct crystalline phases, morphologies and optical properties from films under normal conditions (nitrogen gas), resulting in a significant drop in power conversion efficiency from the initial 20.01% to the lowest of only ~15%. Our work highlights the importance of atmospheric effects in preparing efficient PSCs for scalable fabrication and commercialization.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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