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Record W2781211721

Thermally Sprayed Low Cost Current Collectors with Optimized Mass Transport Behavior for PEM Electrolyzers

2017· article· en· W2781211721 on OpenAlexaboutno aff
Svenja Kolb

Bibliographic record

Venueelib (German Aerospace Center) · 2017
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
Fundersnot available
KeywordsStack (abstract data type)Proton exchange membrane fuel cellCurrent (fluid)PorosityElectrolysisMaterials scienceMass transportElectrodeConductivityPolymer electrolyte membrane electrolysisLayer (electronics)Nuclear engineeringComposite materialAnalytical Chemistry (journal)Environmental scienceChemical engineeringChemistryElectrical engineeringComputer scienceEngineeringEngineering physicsElectrolyteChromatographyFuel cells
DOInot available

Abstract

fetched live from OpenAlex

The costs of the Proton Exchange Membrane (PEM) electrolyzer system need to be reduced while maintaining high performance. The stack component costs comprise 60% of the total system costs in which the bipolar plates and the current collectors are the main factors. In this thesis the facts that current collectors are produced by Vacuum Plasma Spraying (VPS) are discussed and described and are characterized physically as well as electrochemically. The developed graded structures exhibit improved properties regarding conductivity and water transport. The optimal structures for the layer contacting the electrode have pore diameters between 6 and 17um and porousness between 17 and 30%. X-Ray scanning tomography (performed at the University of Toronto) enables 3D reconstructions of the samples confirming the porosity and pore distribution. Moreover, a model in OpenPNM was used to predict the movement of the gases through the current collectors.

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 categoriesMeta-epidemiology (narrow)
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 score0.216
Threshold uncertainty score1.000

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 head0.240
Teacher spread0.231 · 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
Published2017
Admission routes1
Has abstractyes

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