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Record W4225370072 · doi:10.1021/acs.chemmater.1c04438

Inhibition of Amine–Water Proton Exchange Stabilizes Perovskite Ink for Scalable Solar Cell Fabrication

2022· article· en· W4225370072 on OpenAlexafffund
Erin G. Moloney, Deepak Thrithamarassery Gangadharan, Vishal Yeddu, Dongyang Zhang, Shahram Moradi, Abdelrahman M. Askar, Michael M. Adachi, David C. Leitch, Makhsud I. Saidaminov

Bibliographic record

VenueChemistry of Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsFormamidiniumFabricationSolar cellPerovskite (structure)Perovskite solar cellChemical engineeringMaterials scienceDimethylformamideChemistryInorganic chemistryOrganic chemistryOptoelectronicsSolvent

Abstract

fetched live from OpenAlex

Ambient air processing is desirable for the industrial fabrication of perovskite solar cells. Here, we show that perovskite ink containing methylammonium and formamidinium in N-methyl-2-pyrrolidone and N,N-dimethylformamide, a cosolvent composition that satisfies prerequisites for upscaling solar cell fabrication, degrades within a day in ambient air. From 1H NMR spectroscopic analysis, we find that water proton exchange with methylammonium and formamidinium facilitates the aminolysis of formamidinium by methylamine. The addition of elemental sulfur inhibits this proton exchange process via sulfur–amine reactions, resulting in a stable perovskite ink with an extrapolated half-life of 6300 h. The control ink aged for 1 day does not form perovskite films for solar cell fabrication, while the sulfur-stabilized ink is reproducibly used to make devices with efficiencies >15% when aged for over 1 month. The stabilized ink is suitable for upscaling perovskite solar cell fabrication, with efficiencies up to 17% for blade-coated 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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.008
Threshold uncertainty score0.999

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)0.0020.000

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 head0.010
GPT teacher head0.203
Teacher spread0.192 · 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

Citations21
Published2022
Admission routes2
Has abstractyes

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