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Record W2091910382 · doi:10.1109/jmems.2012.2194776

A Rapid Hot-Embossing Prototyping Approach Using SU-8 Molds Coated With Metal and Antistick Coatings

2012· article· en· W2091910382 on OpenAlex
Yaxi Fan, Tingjie Li, Woon‐Ming Lau, Jun Yang

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

VenueJournal of Microelectromechanical Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsEmbossingMaterials scienceLithographyLayer (electronics)MoldElectroplatingWaferRapid prototypingNanoimprint lithographyPhotoresistFabricationNanotechnologyComposite materialOptoelectronics

Abstract

fetched live from OpenAlex

In this paper, we have developed a rapid prototyping process using hybrid master molds for hot-embossing lithography. The hybrid master mold developed here typically consists of a structural layer of SU-8, an overlayer of copper, and a top layer of antistick compound. The structure is first formed by the negative photoresist SU-8 layer with conventional photolithography. On the structural SU-8 layer, a nanoscale copper thin film is deposited to enhance the mechanical strength of the mold and improve heat transfer during the hot-embossing process. Finally, an outermost antistick layer is formed by the reaction of trichloro-(1H,1H,2H,2H-perfluoroctyl)-silane with the oxidized copper surface. These three layers cooperatively yield a hybrid mold which can be fabricated on a silicon wafer or any other suitable substrates for subsequent hot-embossing lithography. Our tests have verified that the molds fabricated with this method do not show any degradation of their structural design features and surface smoothness after 30 hot-embossing cycles. In comparison to other methods of making master molds for hot-embossing lithography such as laser machining and electroplating, the present method is simple and fast, with no reliance on any additional replication steps and fabrication procedures. Hence, the present method can remarkably reduce cost and the processing time in hot embossing, which is particularly attractive in prototyping or small volume production.

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)0.001
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 score0.406
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.227
Teacher spread0.210 · 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