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Record W2275741495 · doi:10.1021/acssuschemeng.5b01080

Recycling Indium Tin Oxide (ITO) Electrodes Used in Thin-Film Devices with Adjacent Hole-Transport Layers of Metal Oxides

2015· article· en· W2275741495 on OpenAlexafffund
Minh Trung Dang, Josianne Lefebvre, James D. Wuest

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsPolytechnique MontréalUniversité de Montréal
FundersUniversité de MontréalNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsPEDOT:PSSIndium tin oxideMaterials scienceElectrodeIndiumSonicationDissolutionOxideThin filmNanotechnologyOptoelectronicsChemical engineeringLayer (electronics)MetallurgyChemistry

Abstract

fetched live from OpenAlex

Many thin-film optoelectronic devices use electrodes made of tin-doped indium oxide (ITO), which is acceptably conductive, as well as virtually transparent and colorless. Regrettably, indium is an uncommon element and its price continues to rise, so it is increasingly important to recover ITO electrodes from devices that are no longer needed. Previous work has shown that simple sonication in neutral water can separate intact ITO electrodes from other components in typical devices, in which the active components and ITO are separated by an ionic buffer layer of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). Sonication in water appears to be effective because it favors selective penetration and dissolution of PEDOT:PSS, thereby freeing the underlying ITO electrode. However, PEDOT:PSS is being replaced in emerging devices by the use of various metal oxides as hole-transport materials. We have now found that ITO electrodes in these new devices can be recycled by sonication in dilute aqueous base. The layers of ITO undergo only minor changes in composition and morphology, and the recovered electrodes can be reused many times to fabricate new devices without loss of performance.

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 score0.402
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.186
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; 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

Citations74
Published2015
Admission routes2
Has abstractyes

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