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Record W2029291712 · doi:10.1016/j.crci.2012.03.006

Synthesis of colloidal silver nanoparticles for printed electronics

2012· article· en· W2029291712 on OpenAlex
Sarute Ummartyotin, Natthaphon Bunnak, J. Juntaro, Mohini Sain, Hathaikarn Manuspiya

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComptes Rendus Chimie · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsSilver nanoparticleMaterials scienceScanning electron microscopeTransmission electron microscopyOLEDNanoparticleCathodeParticle sizeNanotechnologyChemical engineeringParticle (ecology)ColloidDiodeLayer (electronics)Analytical Chemistry (journal)OptoelectronicsChemistryComposite materialChromatography

Abstract

fetched live from OpenAlex

Colloidal silver particles were successfully prepared by wet chemical synthesis. The pure single phase of silver was confirmed by X-ray diffraction. Transmission electron microscope categorized that the diameters of particles were 100 and 20 nm, depending on the molecular weight of the PVP stabilizer. A schematic drawing model was used to predict the packing efficiency of 1:1 wt% of two mixtures. The mixture of silver solution was deposited as a thin solid film by a desktop inkjet printer. Scanning electron microscope showed that two different sizes of silver particles give higher densely packed structure than the film of single particle size. When a 0–20 V voltage was applied, the current density reached was 0.10 J/cm 2 , suggesting that the silver film has potential to be applied as a cathode layer in organic light emitting diode (OLED) 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.

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 score0.009
Threshold uncertainty score0.605

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)0.0010.000

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 head0.024
GPT teacher head0.256
Teacher spread0.232 · 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