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A Comparative Study of Ultrasound Biodiesel Production Using Different Homogeneous Catalysts

2019· article· en· W2913577054 on OpenAlexaff
K. P. Shinde, Serge Kaliaguine

Bibliographic record

VenueChemEngineering · 2019
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTransesterificationBiodieselBiodiesel productionMethanolCatalysisAmmonium hydroxideOrganic chemistryCanolaChemistryHomogeneousMaterials sciencePulp and paper industryFood scienceEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Biodiesel (BD) is a liquid fuel that consists of mono alkyl esters of long chain fatty acids derived from vegetable oil or fat. Recently, biodiesel has received additional attention and intense research has been performed in this field due to its favorable atmospheric CO2 balance compared with conventional fossil fuels (net energy balance of 3.0–4.0 MJ/MJ). In this work, a comparison of transesterification of Canola oil with methanol under ultrasound and under mechanical stirring is reported. The general aspects of the ultrasound transesterification process and a comparative study of different types of homogeneous catalysts (NaOH, KOH, CH3ONa, tetramethyl ammonium hydroxide and four guanidines) are described. Special attention is given to ultrasound transesterification reaction using guanidines as catalysts.

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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.246
Teacher spread0.220 · 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

Citations30
Published2019
Admission routes1
Has abstractyes

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