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Record W2899611134 · doi:10.6000/1929-5030.2018.07.04

Ionic Liquids as Efficient Extractants for Quercetin from Red Onion (Allium cepa L.)

2018· article· en· W2899611134 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsAlliumQuercetinChemistryIonic bondingBotanyOrganic chemistryIonBiology

Abstract

fetched live from OpenAlex

The solubility of Quercetin in alcohols, esters and in 1-ethyl-3-methylimidazolium trifluoroacetate, [EMIM][TFA] ionic liquid (IL) using the dynamic method was measured at constant pH in a range of temperature 233-373 K and compare to the literature data. The experimental solubility data have been correlated by means of commonly known GE models,UNIQUAC and NRTL with the assumption that the systems studied here present simple eutectic behaviour. The basic thermal properties of Quercetin, i.e., fusion temperature and the enthalpy of fusion have been measured with differential scanning microcalorimetry technique (DSC).The application of alcohols, esters and ionic liquids (ILs) as alternatives to conventional organic solvents in the liquid-liquid extraction of Quercetin from different medicinal plants, flowers and frozen red onion (Allium cepa L.) was investigated. The parameters affecting the extraction yield using ILs such as chemical structures of the IL cation and anion, the phase volume ratio of extracting solvent, time of extraction and the Quercetin form of sample and concentration were evaluated. Specific Quercetin composition was performed through HPLC measurements. Using the most effective ILs in extraction, the 14.3±0.1g.kg-1 and 5.9±0.1g.kg-1of Quercetin from frozen pure red onion was obtained with N,N-diethyl-N-methyl-N-(2-methoxyethyl)ammonium tetrafluoroborate, [N2,2,1,2OCH3][BF4] and 1-ethyl-3-methylimidazolium trifluoroacetate, [EMIM][TFA], respectively.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.628

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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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