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Record W4400249961 · doi:10.1016/j.clet.2024.100773

Review on utilization of rubber seed oil for biodiesel production: Oil extraction, biodiesel conversion, merits, and challenges

2024· article· en· W4400249961 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCleaner Engineering and Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of New Brunswick
FundersUniversiti Tenaga NasionalTenaga Nasional Berhad
KeywordsBiodieselRaw materialBiodiesel productionNatural rubberFossil fuelBiofuelEnvironmental scienceWaste managementPulp and paper industryRenewable energyVegetable oilEngineeringMaterials scienceChemistryFood science

Abstract

fetched live from OpenAlex

The greater demand for energy has led to a surge in the utilization of fossil fuels, resulting in the rapid depletion of crude oil sources. Regrettably, this trend has engendered a significant negative environmental impact, primarily due to the release of unwanted carbon emissions into the atmosphere. Biodiesel has been considered a suitable substitute for fossil fuels owing to its availability from renewable feedstock, less polluting, sustainable and high biodegradability. However, the production of biodiesel from edible oils is very expensive due to the food versus fuel competition of the oil feedstock. Therefore, non-edible oils such as rubber seed oils have been considered suitable biodiesel feedstock due to their wide availability and abundance in different parts of the world. Rubber plantations are widely cultivated for their latex and the discarded seeds from rubber plantations could be considered as a potential source for biodiesel production. Hence, this review considers the extraction of oil from rubber seeds, the free fatty acid compositions, and physicochemical properties. It investigates biodiesel production from rubber seed oil and explores the variations in its physicochemical properties. The various kinds of catalysts that have been developed for biodiesel production from rubber seed oil were examined; the techno-economic analysis was discussed; the merits and challenges associated with the use of rubber seed oil as a suitable feedstock for biodiesel production were analyzed.

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.

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 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 score0.947
Threshold uncertainty score0.638

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 head0.033
GPT teacher head0.251
Teacher spread0.217 · 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