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Record W2081717135 · doi:10.1088/0960-1317/21/7/075018

Maskless direct micro-structuring of PDMS by femtosecond laser localized rapid curing

2011· article· en· W2081717135 on OpenAlex
Hamsapriya Selvaraj, Bo Tan, Krishnan Venkatakrishnan

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 Micromechanics and Microengineering · 2011
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStereolithographyPolydimethylsiloxaneMaterials scienceCuring (chemistry)FemtosecondLaserMicrosecondRapid prototypingOptoelectronicsComposite materialNanotechnologyOptics

Abstract

fetched live from OpenAlex

Polydimethylsiloxane (PDMS) is widely used to build biomedical microdevices because of its excellent properties. Prototyping 2D and 3D PDMS microdevices normally requires a long curing time and must go through multiple steps. In this paper, we propose femtosecond laser stereolithography for the rapid prototyping of PDMS 2D and 3D microstructures. This work presents a new way of rapid curing of PDMS resin on a microsecond timescale using femtosecond laser pulses of megahertz pulse frequency. The proposed technique permits single-step curing and is capable of fabricating 2D and 3D structures in micro-scale. The rapid localized curing can be explained by the volume-constrained quick temperature rise due to the accumulated heating at repetitive irradiation. The rapid cooling following the curing limits the decomposition and, therefore, the PDMS retains its mechanical strength.

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 score0.028
Threshold uncertainty score0.969

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 head0.006
GPT teacher head0.170
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