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Record W2015452550 · doi:10.1149/1.3308569

Advancing Direct Liquid Redox Fuel Cells: Mixed-Reactant and In Situ Regeneration Opportunities

2010· article· en· W2015452550 on OpenAlexafffund
Alan B. Ilicic, David P. Wilkinson, Khalid Fatih

Bibliographic record

VenueJournal of The Electrochemical Society · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsBC Innovation CouncilUniversity of British Columbia
FundersLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsRedoxAnodeGravimetric analysisRegeneration (biology)Chemical engineeringMethanol fuelElectrolyteCathodeMethanolChemistryIn situMaterials scienceInorganic chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Two approaches pertaining to the direct liquid redox fuel cell (DLRFC) have been investigated and demonstrated: mixed-reactant operation and in situ regeneration of the redox couple. The former involves supplying a mixed methanol redox electrolyte to the selective carbon cathode of the DLRFC and supplying the fuel to the anode via methanol crossover. This approach has the potential to significantly improve the cost, compactness, and volumetric and gravimetric power densities of the cell. The latter in situ regeneration approach involves substituting the fuel supply with air to spontaneously reverse the direction of electron flow in a DLRFC, which eliminates the need for an auxiliary regeneration unit and reduces the overall cost and complexity of a DLRFC system. Both modes of DLRFC operation, discharge, and regeneration, produce power that is unique compared to conventional systems.

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 score0.002
Threshold uncertainty score0.007

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 communication0.0010.002
Open science0.0010.001
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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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

Citations15
Published2010
Admission routes2
Has abstractyes

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