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The Analysis and Design of Microchannel Reactors

2006· article· en· W2129315105 on OpenAlexaff
C.A. Bellemare-Davis, Kunal Karan, Jon G. Pharoah, G. Zak

Bibliographic record

VenueAdvanced materials research · 2006
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsQueen's University
Fundersnot available
KeywordsMicrochannelFabricationMaterials scienceAluminiumEtching (microfabrication)Surface finishSurface roughnessGaussianMicrochannel plate detectorOptoelectronicsOpticsNanotechnologyComposite materialLayer (electronics)ChemistryPhysics

Abstract

fetched live from OpenAlex

This investigation considers the development of microchannel reactors with catalystcoated walls for fuel-processing applications. In particular, the focus is to study the possibility of direct etching of microchannels into aluminum and alumina using a solid-state UV laser. Microchannels of a scale between 10μm-200μm across and 10μm-100μm have been ablated into aluminum and alumina bases. It was found that single scans resulted in narrow channels (20μm- 30μm in width) with shapes described by a Gaussian-like distribution. Multiple scans allowed fabrication of channels with a larger width, but of a similar depth. The surface quality was observed to be quite uneven, with roughness on the order of 1μm-2μm.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.053
GPT teacher head0.369
Teacher spread0.316 · 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
Published2006
Admission routes1
Has abstractyes

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