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Record W1968897150 · doi:10.1021/ie060555o

Effect of Membrane Pore Size on the Performance of a Membrane Reactor for Biodiesel Production

2006· article· en· W1968897150 on OpenAlexafffund
Peigang Cao, André Y. Tremblay, Marc A. Dubé, Katie Morse

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMethanolBiodieselMembraneChemistryMembrane reactorVolume (thermodynamics)PermeationBiodiesel productionChromatographyCanolaGlycerolChemical engineeringNuclear chemistryOrganic chemistryCatalysisBiochemistryFood science

Abstract

fetched live from OpenAlex

Biodiesel was produced from canola oil and methanol in a novel membrane reactor. The membrane in the reactor served to separate the unreacted emulsified oil from the product stream, producing high-purity fatty acid methyl ester (FAME). The effects of the pore size of the membrane used in the semicontinuous reactor and the initial methanol/canola oil loading were studied. Four carbon membranes having different pore sizes of 0.05, 0.2, 0.5, and 1.4 μm were tested, with four different initial methanol volume fractions (φ 1 ) of 0.29, 0.38, 0.47, and 0.64. It was found that all four membranes retained canola oil in the reactor. Permeate was observed at the 0.38, 0.47, and 0.64 initial methanol volume fractions, whereas it was not observed at φ 1 = 0.29. The initial oil loadings represent methanol/oil mole ratios of 11:1, 16:1, 23:1, and 46:1. For all runs, no triglycerides were found in the permeate. The permeate dephased upon cooling to room temperature. Glycerol was not detected in the FAME-rich phase. This opens the possibility of reaching methanol/oil mole ratios of 6:1 with a single recycling step.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.044
GPT teacher head0.286
Teacher spread0.242 · 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

Citations124
Published2006
Admission routes2
Has abstractyes

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Same venueIndustrial & Engineering Chemistry ResearchSame topicBiodiesel Production and ApplicationsFrench-language works237,207