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Record W2001724882 · doi:10.1115/icnmm2011-58056

Microfabrication Technologies Based on Electro-Dispensing

2011· article· en· W2001724882 on OpenAlexaff
Jacqueline Nichols, Brandon Born, Emily L. Landry, Jonathan F. Holzman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMicrofabricationMaterials scienceMicrofluidicsPolymerNanotechnologyChipVoltageOptoelectronicsLab-on-a-chipPhotoresistOpticsFabricationElectrical engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

A microfabrication technology with real-time polymer processing control is introduced in this work. The technique is titled electro-dispensing, as it employs a metal micro-dispensing tip that is biased with a user-defined voltage. The in-situ voltage directs an electric field through the underlying dispensed polymer structure. Polymer droplets are dispensed directly onto a chip with precise (pL) volumes, and the in-situ micro-dispensing tip voltage is varied to adjust the polymer droplet morphology during the microfabrication process. The technique is carried out within a glycerol ambient filler solution, to create an initial high contact angle (160°) on the polymer microdroplets, and voltage tunability is applied to control the microdroplet shapes. Ultraviolet curing is subsequently employed to solidify the micro-spheroid structures on the desired locations across the chip. The electro-dispensing process is demonstrated in this work for numerous microdroplets, with a variety of polymer morphologies and diameters down to 150 μm. The capabilities of the electro-dispensing process are also demonstrated in this work for a specific application relating to integrated photonic circuitry. Polymer microdroplets in the past have been limited to use as lenses for vertical beam focusing (through the plane of the chip), because of their exceedingly low contact angles on solid surfaces. In this work, polymer micro-droplets are introduced for lateral beam focusing and retroreflection (above and parallel to the plane of the chip). These new technologies for on-chip optical beam dispersion management are brought about by the capabilities of electro-dispensing: the use of an ambient filler allows the dispensing process to create high-contact-angle near-spherical microdroplets; the electro-dispensing process then allows this droplet to be tuned for its specific role within the integrated photonic chip (e.g. as a spherical element for in-plane focusing or an elliptical element for in-plane retroreflection). Ray-based analyses and electromagnetic models are used to characterize the optical responses of the micro-spheroid structures, and the results are compared to experimental measurements with on-chip laser beam control.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.183
Teacher spread0.164 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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