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Record W2585837785 · doi:10.1002/cjce.22801

One pot peroxidation of oleic acid rich <i>Azadirachta indica</i> oil over bio‐waste derived heterogeneous catalyst

2017· article· en· W2585837785 on OpenAlexvenueno aff
Himadri Sahu, Kaustubha Mohanty

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAzadirachtaCatalysisIodine valueOleic acidNuclear chemistryNeem oilChemistryFormic acidOrganic chemistryBiochemistryBotany

Abstract

fetched live from OpenAlex

Abstract In this work, a heterogeneous catalyst was developed from waste fish bone. ZnO was deposited onto the waste fish bone to enhance the surface properties along with ion exchangeability. After characterization, the developed catalyst was found to have a much higher surface area (217 m 2 · g −1 ) than that of raw fish bone (10 m 2 · g −1 ). This catalyst was used during peroxidation of oleic acid rich Azadirachta indica oil (neem oil) to observe its suitability and efficiency. A quadratic model was developed with five input variables (temperature ( T ), time ( t ), g/g of catalyst ( H Zn ), H 2 O 2 :oil ratio ( γ H:FA ), formic acid:oil ratio ( γ F:FA )) and 2 output variables (Iodine value, Oxirane Oxygen Conversion). The optimized parametric values for T , t , H Zn , γ H:FA , and γ F:FA were found to be 60 °C, 3.88 h, 20 g/g, 19.05:1, and 19.85:1 respectively. The final epoxidized oil was characterized using FTIR and 1 HNMR. The reusability of the catalyst was studied both quantitatively and qualitatively.

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 score0.052
Threshold uncertainty score0.580

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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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