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Record W823249794 · doi:10.14447/jnmes.v12i4.199

Preparation of a New Proton Conducting Silicon Membrane for Miniature Fuel Cells

2008· article· en· W823249794 on OpenAlexvenueno aff
Yi-Tang Chen, Sean S.-Y. Lin, Sung‐O Kim, Su Ha

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
Fundersnot available
KeywordsSiliconMembraneMaterials scienceSurface micromachiningSubstrate (aquarium)Plasma-enhanced chemical vapor depositionEtching (microfabrication)FabricationProton exchange membrane fuel cellChemical vapor depositionBulk micromachiningNanotechnologyProtonOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

The membranes based on silicon substrate filled with Nafionr have been fabricated as a proton exchange membrane for miniature fuel cells. This fabrication utilizes the micromachining procedures including photo-lithography, plasma-enhanced chemical vapor deposition (PECVD), and dry and wet etching processes. The device size of the silicon membrane filled with Nafionr was 1 cm t 1 cm. The pores were smaller than 500 nm. The cross-sectional shape of the silicon membrane was an inverse pyramid structure to improve its mechanical strength and to enhance its surface treatment process. This technique combines the advantages of Nafionr with a good proton conductivity and silicon membrane, such as easy serial and parallel integration, respectively.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.024
GPT teacher head0.260
Teacher spread0.236 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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