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Record W2082832237 · doi:10.1088/0960-1317/19/9/095017

Identification of constitutive theory parameters using a tensile machine for deposited filaments of microcrystalline ink by the direct-write method

2009· article· en· W2082832237 on OpenAlexafffund
Nicolas Lourdel, Daniel Therriault, Martin Lévesque

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrocrystallineIdentification (biology)Ultimate tensile strengthInkwellMaterials scienceConstitutive equationComposite materialTensile testingEngineering drawingStructural engineeringMechanical engineeringEngineeringChemistryCrystallographyFinite element method

Abstract

fetched live from OpenAlex

ABSTRACT: A custom-designed tensile machine is developped to characterize the 10 mechanical properties of ink micro-filaments deposited by Direct-Write method. The 11 Direct-Write method has been used for the fabrication of a wide variety of micro12 systems such as microvascular networks, chaotic mixers and laboratory on-chips. The 13 tensile machine was used to measure the induced force in ink filaments during tensile 14 and tension-relaxation tests as a function of the applied strain rate, the ink composition 15 and the filament diameter. Experimental data was fitted by a linearly viscoelastic 16 model using a data reduction procedure in order to identify the constitutive theory 17 parameters of the deposited ink filaments. The model predictions based on the defined 18 constitutive theory parameters were closed to the experimental data generated in this 19 study. Such models will be useful in the development and optimization of future 3D 20 complex structures made by direct-write method.

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 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 score0.442
Threshold uncertainty score0.506

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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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 teacher head, 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

Citations1
Published2009
Admission routes2
Has abstractyes

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