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Record W1977684457 · doi:10.3390/s130607021

Improved Adhesion of Gold Thin Films Evaporated on Polymer Resin: Applications for Sensing Surfaces and MEMS

2013· article· en· W1977684457 on OpenAlexafffund
Behrang Moazzez, Stacey O’Brien, E. S.

Bibliographic record

VenueSensors · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMicrofabricationPhotoresistSubstrate (aquarium)AdhesionThin filmLayer (electronics)NanotechnologyDeposition (geology)ShrinkagePolymerSurface finishAdhesivePolymer substrateComposite materialMicroelectromechanical systemsFabrication

Abstract

fetched live from OpenAlex

We present and analyze a method to improve the morphology and mechanical properties of gold thin films for use in optical sensors or other settings where good adhesion of gold to a substrate is of importance and where controlled topography/roughness is key. To improve the adhesion of thermally evaporated gold thin films, we introduce a gold deposition step on SU-8 photoresist prior to UV exposure but after the pre-bake step of SU-8 processing. Shrinkage and distribution of residual stresses, which occur during cross-linking of the SU-8 polymer layer in the post-exposure baking step, are responsible for the higher adhesion of the top gold film to the post-deposition cured SU-8 sublayer. The SU-8 underlayer can also be used to tune the resulting gold film morphology. Our promoter-free protocol is easily integrated with existing sensor microfabrication processes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.261
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations41
Published2013
Admission routes2
Has abstractyes

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