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Record W2619068188 · doi:10.1080/15435075.2017.1333434

Experimental evaluation of the catalytic efficiency of calcium based natural and modified catalyst for biodiesel synthesis

2017· article· en· W2619068188 on OpenAlexaff
Jharna Gupta, Madhu Agarwal, Ajay K. Dalai

Bibliographic record

VenueInternational Journal of Green Energy · 2017
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCatalysisBiodieselMethanolLeaching (pedology)TransesterificationCalcinationBiodiesel productionCalcium oxideChemistryYield (engineering)Nuclear chemistryMaterials scienceOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

Transesterification of a mixture of vegetable oils with methanol using metal oxide catalysts derived from snail shell (SS) for biodiesel production was investigated. The metal oxides obtained from calcined snail shells in the temperature range of 650°–950 °C and modified by loading different potassium salts were used as a catalyst in the process. The catalysts were characterized by FT-IR, XRD, SEM-EDS, XPS and TGA. Catalytic activities of developed catalysts were also tested by Hammet indicator method and ion exchange method. The best calcination conditions were observed at 850°C for 4 hours based on biodiesel yield. The KF loaded snail shell gave highest biodiesel yield of 98 ± 1% in a batch reactor with highest basicity (15.9 mmoles/g) and basic strength measured by Hammet method. The optimized reaction conditions were: reaction temperature 65°C, reaction time 3 hours, methanol to oil molar ratio 9:1 and catalyst concentration 3wt%. Leaching and reusability tests confirm the stability of the catalyst as it encounters only 3% of leaching and small changes in catalytic activity up to five runs in terms of biodiesel yield.

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 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 score0.097
Threshold uncertainty score0.196

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 head0.043
GPT teacher head0.303
Teacher spread0.260 · 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 teacher head, 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

Citations16
Published2017
Admission routes1
Has abstractyes

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