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Record W2042207502 · doi:10.1021/ie0510526

Waste Cooking OilAn Economical Source for Biodiesel:  A Review

2006· review· en· W2042207502 on OpenAlexaff
Mangesh G. Kulkarni, Ajay K. Dalai

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typereview
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBiodieselTransesterificationDiesel fuelRaw materialVegetable oil refiningWaste managementBiodiesel productionEnvironmental sciencePulp and paper industryCooking oilRenewable energyRenewable fuelsBiofuelChemistryMethanolEngineeringOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Biodiesel (fatty acid methyl ester) is a nontoxic and biodegradable alternative fuel that is obtained from renewable sources. A major hurdle in the commercialization of biodiesel from virgin oil, in comparison to petroleum-based diesel fuel, is its cost of manufacturing, primarily the raw material cost. Used cooking oil is one of the economical sources for biodiesel production. However, the products formed during frying, such as free fatty acid and some polymerized triglycerides, can affect the transesterification reaction and the biodiesel properties. Apart from this phenomenon, the biodiesel obtained from waste cooking oil gives better engine performance and less emissions when tested on commercial diesel engines. The present paper attempts to review methods for the transesterification of waste cooking oil and the performance of biodiesel obtained from waste cooking oil in a commercial diesel engine. The paper also examines the basic chemistry involved during frying and the effects of the products formed in the frying process on biodiesel quality.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.241
GPT teacher head0.391
Teacher spread0.150 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1,179
Published2006
Admission routes1
Has abstractyes

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