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Microfabrication of a Silicon Turbopump with Embedded Thermal Isolation for a Rankine MEMS Heat Engine

2019· article· en· W2992667382 on OpenAlexaff
Amrid Amnache, Luc G. Fréchette

Bibliographic record

VenueJournal of Physics Conference Series · 2019
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceDeep reactive-ion etchingMechanical engineeringSiliconWaferMicroelectromechanical systemsThermal insulationMicrofabricationComposite materialFabricationEtching (microfabrication)OptoelectronicsEngineeringReactive-ion etchingLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract This paper presents the fabrication of a silicon MEMS microturbopump with embedded thick thermal isolation, covering the key building blocks to incorporate thermally insulated zones in a multiple wafer stack, and the resulting device. Thermal insulation is a roadblock for the implementation of heat engines at the MEMS scale. To implement the Rankine cycle on a chip, insulation is required to prevent boiling of water in the pump while the turbine is exposed to high temperature vapour flows. To prevent heat from conducting through the silicon rotor, thick glass insulation was embedded into the rotor structure using glass molding and planarization. This composite rotor approach allows us to leverage the capabilities of silicon DRIE, while creating over 100 micron thick glass insulation between the turbine and the pump. Also, in-plane thermal insulation is required between the central pump zone and the surrounding fluid film bearings, fed with steam. This was accomplished by etching deep trenches in silicon to form an array of thin walls, followed by a thermal oxidation step that consumes the silicon walls and closes the trenches to form a deep monolithic oxide zone. These techniques were successfully implemented for the fabrication of a complete MEMS turbopump, which consists of a stack of 4 silicon wafers and one glass wafer, and a total of 18 lithography/etch steps.

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 score0.420
Threshold uncertainty score0.350

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 head0.202
Teacher spread0.194 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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