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Record W2509089058 · doi:10.1109/iscas.2016.7527378

Aerosol Jet Printing for printed electronics rapid prototyping

2016· article· en· W2509089058 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsMaterials sciencePrinted electronics3D printingFabricationScreen printingRapid prototypingSubstrate (aquarium)NozzlePEDOT:PSSOptoelectronicsInkwellLayer (electronics)NanotechnologyComposite materialMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

This work investigates optimization procedures for rapid prototyping with Aerosol Jet Printing by printing high quality structures for the fabrication of multi-layer passive devices on various substrates. The effects of gas flow rate, nozzle diameter, stage speed and substrate temperature are examined in order to optimize printed line width for each material. Inductors, capacitors and resistors are fabricated using silver nano-particle ink, SU-8 dielectric and PEDOT:PSS organic conductor. Further applications are show-cased by printing silver interconnect lines with fine pitch for various applications such as: replacement for die wirebonding, printing a strain gauge on a 3D conformal surface, and for printing on flexible plastic substrates.

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 score0.180
Threshold uncertainty score0.340

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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

Quick stats

Citations79
Published2016
Admission routes2
Has abstractyes

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