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Record W2036797751 · doi:10.1021/cm0611643

Studies of Gold Nanoparticles as Precursors to Printed Conductive Features for Thin-Film Transistors

2006· article· en· W2036797751 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemistry of Materials · 2006
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsXerox (Canada)
Fundersnot available
KeywordsMaterials scienceThin-film transistorElectrodeMicrocontact printingColloidal goldTransistorPrinted electronicsNanoparticleNanotechnologyElectrical conductorAnnealing (glass)OptoelectronicsSemiconductorFlexible electronicsInkwellComposite materialElectrical engineeringChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

Gold nanoparticles stabilized with various alkanethiols were studied as printable precursors for fabricating electrically conductive elements for printed electronics. Gold nanoparticle features were printed using stencil and microcontact techniques and then converted to highly conductive features for thin-film transistors (TFTs) at relatively low annealing temperatures. TFT devices with printed source/drain electrodes of this nature exhibited similar or better field-effect transistor (FET) characteristics than those with vacuum-evaporated gold electrodes. The improved performance was attributable to the presence of alkanethiol stabilizers on the printed electrode surface, which enabled intimate electrode/semiconductor interfacial interactions. Different alkanethiol stabilizers exerted different effects on the decomposition profiles of gold nanoparticles but not on FET 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.

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 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 score0.003
Threshold uncertainty score0.583

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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