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Record W2470563699 · doi:10.1021/acs.joc.6b01032

Determination of Key Hydrocarbon Autoxidation Products by Fluorescence

2016· article· en· W2470563699 on OpenAlexafffund
Ron Shah, Derek A. Pratt

Bibliographic record

VenueThe Journal of Organic Chemistry · 2016
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationUniversity of Ottawa
KeywordsChemistryAutoxidationConjugated systemTitrationOrganic chemistryHydrocarbonProtonationCarboxylic acidIodometrySolventPhotochemistryFluorescencePolymer

Abstract

fetched live from OpenAlex

Hydroperoxides and carboxylic acids are key primary products that arise in the autoxidation of hydrocarbons. We have developed a simple approach to rapidly and simultaneously determine both types of products using hydroperoxide- and acid-sensitive moieties conjugated to nonpolar coumarin- and BODIPY-based fluorophores. The coumarin- and BODIPY-conjugated amine probes described here undergo 38- and 8-fold enhancement, respectively, upon protonation in a solvent system compatible with heavy hydrocarbons. The latter can be used directly with our previously described hydroperoxide-sensitive coumarin-conjugated phosphine probe to enable rapid quantification of both carboxylic acids and hydroperoxides in hydrocarbon samples. The utility of the approach is illustrated by the ready determination of the differing relative rates of hydroperoxide and acid formation with changes in hydrocarbon structure (e.g., n-hexadecane vs 1-hexadecene vs a lubricant base stock). The method offers significant versatility and automation compared with common but laborious titration approaches, and greatly improves screening efficiency and accuracy for the identification of novel radical-trapping antioxidants for high temperature applications. This application was demonstrated by the automated analysis of hydroperoxides and carboxylic acids (by microplate reader) in samples from 24 inhibited autoxidations of a lubricating oil, which were carried out on a parallel synthesizer at 160 °C in triplicate in a single day.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

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)0.0010.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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.

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

Citations17
Published2016
Admission routes2
Has abstractyes

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