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Record W2041806583 · doi:10.2202/1542-6580.2027

Biodiesel Production from Jatropha curcas Oil Using Potassium Carbonate as an Unsupported Catalyst

2009· article· en· W2041806583 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

VenueInternational Journal of Chemical Reactor Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsJatropha curcasTransesterificationBiodieselBiodiesel productionPotassium carbonateMethanolChemistryCarbonatePotassium hydroxidePulp and paper industryCatalysisDimethyl carbonateDiesel fuelRaw materialPotassiumWaste managementNuclear chemistryOrganic chemistryBiotechnology

Abstract

fetched live from OpenAlex

Jatropha curcas (JTC) oil, an inedible vegetable oil, can be a substitute feedstock for traditional food crops in the production of environment friendly and renewable fuel (biodiesel). In the present study, unsupported potassium carbonate was used as a catalyst to provide an understanding of the catalytic activity in the transesterification reaction. Researching the potential and the behavior of potassium carbonate is very important because every biomass ash contains this compound in a significant amount. It can be extracted by using classical extraction or leaching technologies. During the biodiesel production reaction, the formation of soap as a byproduct was also monitored using the FTIR-ATR method. From this study it was observed that the transesterification of JTC oil to JTC biodiesel appeared to be complete within 15 minutes when a 5 wt% (based on the wt. of the oil) potassium carbonate, 6:1 methanol to oil molar ratio, 60°C or a 4 wt% potassium carbonate, 9:1 methanol to oil molar ratio and 60°C reaction temperature were used.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.811

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 head0.013
GPT teacher head0.249
Teacher spread0.236 · 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