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An extrusion printed capacitively interrogated DC electric field sensor

2024· article· en· W4400978989 on OpenAlexafffund
Desmond Lagace, Tao Chen, Cyrus Shafai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsUniversity of Manitoba
FundersMitacsManitoba Hydro
KeywordsExtrusionElectrical engineeringElectric fieldMaterials science3d printedField (mathematics)OptoelectronicsMechanical engineeringComputer scienceEngineeringPhysicsComposite materialManufacturing engineeringMathematics

Abstract

fetched live from OpenAlex

This paper presents a novel high voltage DC electric field sensor constructed upon a polyimide substrate utilizing extrusion printing of silver conductive ink. The sensor consists of an electrostatically deflected printed electrode suspended by meandering polyimide springs. In the presence of a DC electric field, the electrode is displaced and a parallel electrode capacitively interrogates this displacement. The sensor is simple, low cost, and easy to manufacture, requiring virtually zero interaction with a cleanroom. Results showed that the printed sensor is successful in detecting various electric field intensities up to 250 kV/m. The sensor has a resolution of 4.7 kV/m at 5 Hz signal averaging when the interrogating electrode is placed initially ~185 μm away from the suspended electrode.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.999

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)0.0020.000

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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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.

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
Published2024
Admission routes2
Has abstractyes

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