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Microfabricated Membranes for Radiative Near Field Measurements

2019· preprint· en· W2969910466 on OpenAlexafffund
Olivier Marconot, Ivan Latella, Alexandre Juneau-Fecteau, Julien Sylvestre, Luc G. Fréchette

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrofabricationMembraneMaterials scienceHeat transferSubstrate (aquarium)SiliconThermal radiationOptoelectronicsNear and far fieldRadiative transferOpticsChemistryFabricationMechanicsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

We present in this paper measurements of near-field heat transfer across sub-micron gaps between suspended membranes and their substrate. A microfabrication process using amorphous silicon as a sacrificial layer is developed to create membranes (50 μm × 50 μm) with nanoscale separation distance (down to 250 nm). In this configuration, evanescent near-field radiation couples between the membrane and the substrate, which is expected to enhance the heat transfer. Experimental measurements using an embedded heater and thermistor on the membrane demonstrate the enhancement of heat transfer at the smaller gaps, reaching radiation levels beyond the ideal black body. This is the first demonstration of near field heat transfer over large areas in a fully microfabricated device including a gap effect study.

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)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.038
GPT teacher head0.254
Teacher spread0.216 · 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".

Quick stats

Citations3
Published2019
Admission routes2
Has abstractyes

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