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Record W2951526797 · doi:10.1021/acs.accounts.5b00035

Maximizing the Reactivity of Phenolic and Aminic Radical-Trapping Antioxidants: Just Add Nitrogen!

2015· article· en· W2951526797 on OpenAlexafffund
Luca Valgimigli, Derek A. Pratt

Bibliographic record

VenueAccounts of Chemical Research · 2015
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsReactivity (psychology)ChemistryRadicalAutoxidationRing (chemistry)Reaction rate constantOrganic chemistryMedicinal chemistryKinetics

Abstract

fetched live from OpenAlex

Hydrocarbon autoxidation, the archetype free radical chain reaction, challenges the longevity of both living organisms and petroleum-derived products. The most important strategy in slowing this process is via the intervention of radical-trapping antioxidants (RTAs), which are abundant in nature and included as additives to almost every petroleum-derived product as well as several other commercial products. Accordingly, a longstanding objective of many academic and industrial scientists has been the design and development of novel RTAs that can outperform natural and industrial standards, such as α-tocopherol, the most biologically active form of vitamin E, and dialkylated diphenylamines, respectively. Some time ago we recognized that attempts to maximize the reactivity of phenolic RTAs had largely failed because substitution of the phenolic ring with electron-donating groups to weaken the O-H bond and accelerate the rate of H atom transfer to radicals leads to compounds that are unstable in air. We surmised that incorporating nitrogen into the phenolic ring would render them more stable to one-electron oxidation, enabling their substitution with strong electron-donating groups. Guided by computational chemistry, we demonstrated that replacing the phenyl ring in very electron-rich phenols with either 3-pyridyl or 5-pyrimidyl rings leads to phenolic-like RTAs with good air stability and great reactivity. In fact, rate constants determined for the reactions of some compounds with peroxyl radicals were almost 2 orders of magnitude greater than those for α-tocopherol and implied that the reactions proceeded without an enthalpic barrier. Following extensive thermochemical and kinetic characterization, we took our studies of these compounds to more physiologically relevant media, such as lipid bilayers and human low density lipoproteins, where the heterocyclic analogues of vitamin E shone, displaying unparalleled abilities to inhibit lipid peroxidation and prompting their current investigation in animal models of degenerative disease. Moreover, we carried out studies of these compounds in several industrially relevant contexts and in particular demonstrated that they could be used synergistically with less reactive, less expensive, phenolic RTAs. More recently, our attention has turned to the application of these ideas to maximizing the reactivity of diarylamine RTAs that are common in additives to petroleum-derived products, such as lubricating oils, transmission and hydraulic fluids, and rubber. In doing so, we have developed the most reactive diarylamines ever reported. The 3-pyridyl- and 5-pyrimidyl-containing diarylamines are easily accessed using Pd- and/or Cu-catalyzed cross-coupling reactions, and display an ideal compromise between reactivity and stability. The most reactive compounds are characterized by rate constants for reactions with peroxyl radicals that are independent of temperature, implying that-as for the most reactive heterocyclic phenols-these reactions proceed without an enthalpic barrier. Unprecedented reactivity was also observed when hydrocarbon autoxidations were carried out at elevated temperatures, real-world conditions where diarylamines are uniquely effective because of a catalytic RTA activity that makes use of the hydrocarbon substrate as a sacrificial reductant. Our studies to date suggest that heterocyclic diarylamines have real potential to increase the longevity of petroleum-derived products in a variety of applications where diphenylamines are currently 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.145
GPT teacher head0.368
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations79
Published2015
Admission routes2
Has abstractyes

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