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Record W4210735481 · doi:10.1149/1945-7111/ac50e1

Additive Manufacturing of Microcantilevers of Varying Stiffnesses for Sensing Applications

2022· article· en· W4210735481 on OpenAlexafffund
Shervin Foroughi, Mohsen Habibi, Muthukumaran Packirisamy

Bibliographic record

VenueJournal of The Electrochemical Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsConcordia University
FundersFonds de recherche du Québec – Nature et technologies
KeywordsFabricationCantileverMaterials scienceElastomer3D printingNanotechnologySoft materialsInkwellComposite material

Abstract

fetched live from OpenAlex

Fabrication of the microcantilevers using the traditional methods is time-consuming and costly. With the advancement of additive manufacturing methods, the fabrication of functional microcantilevers is possible. This work presents the fabrication of elastomeric microcantilevers using the SLA 3D printing technology. Different microcantilevers are fabricated. The mechanical characteristics of the fabricated cantilevers are identified by performing micromechanical tests. Results show that the cantilevers’ measured stiffnesses are comparable with those reported in the literature. The method explained in this work reveals the possibility of employing SLA 3D printing and soft elastomeric printing materials to fabricate microcantilevers.

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 score0.410
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

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