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Record W2794734691 · doi:10.1007/s13203-018-0199-4

Autoxidation of aromatics

2018· article· en· W2794734691 on OpenAlexafffund
Natalia Montoya Sánchez, Arno de Klerk

Bibliographic record

VenueApplied Petrochemical Research · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersCanadian Centre for Clean Coal/Carbon and Mineral Processing Technologies
KeywordsAutoxidationChemistryOxygenateAromaticityOrganic chemistryAlicyclic compoundPetrochemicalHeteroatomOxygenRing (chemistry)Bond cleavageReactivity (psychology)CatalysisPhotochemistryMolecule

Abstract

fetched live from OpenAlex

Autoxidation is a conversion pathway that has the potential to add value to multinuclear aromatic-rich coal liquids, heavy oils and bitumens, which are typically considered low-value liquids. In particular, autoxidation of these heavy materials could lead to products that may have petrochemical values, e.g., lubricity improvers and emulsifiers. Proper assessment of an oxidative transformation to ring-open the multinuclear aromatics present in heavy feeds relies on the understanding of the fundamentals of aromatic oxidation. This work reviews the selective oxidation chemistry of atoms that form part of an aromatic ring structure using oxygen (O2) as oxidant, i.e., the oxidation of aromatic carbons as well as heteroatoms contained in an aromatic ring. Examples of industrially relevant oxidations of aromatic and heterocyclic aromatic hydrocarbons are provided. The requirements to produce oxygenates involving the selective cleavage of the ring C–C bonds, as well as competing non-selective oxidation reactions are discussed. On the other hand, the Clar formalism, i.e., a rule that describes the stability of polycyclic systems, assists the interpretation of the reactivity of multinuclear aromatics towards oxidation. Two aspects are developed. First, since the interaction of oxygen with aromatic hydrocarbons depends on their structure, oxidation chemistries which are fundamentally different are possible, namely, transannular oxygen addition, oxygen addition to a carbon–carbon double bond, or free radical chemistry. Second, hydrogen abstraction is not necessary for the initiation of the oxidation of aromatics compared to that of aliphatics.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.368
Teacher spread0.316 · 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

Citations43
Published2018
Admission routes2
Has abstractyes

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