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Record W4285398412 · doi:10.1149/ma2022-01251212mtgabs

(Digital Presentation) Electrocatalytic Transformations of Phenolic Compounds

2022· article· en· W4285398412 on OpenAlexaff
Sanela Martić

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldChemistry
TopicRadical Photochemical Reactions
Canadian institutionsTrent University
Fundersnot available
KeywordsElectrochemistryButylated hydroxytolueneChemistryElectrochromismPhenolsSubstrate (aquarium)RadicalOrganic chemistryCyclic voltammetryCombinatorial chemistryElectrodeAntioxidantPhysical chemistry

Abstract

fetched live from OpenAlex

Electrocatalytic transformations giving rise to new C-C bond formation and new products are of value. We have recently discovered that phenolic compounds undergo selective electrochemical oxidation giving rise to reactive radicals which combine to produce product with new C-C bond formed [1]. A series of phenolic compounds, including butylated hydroxytoluene (BHT), 4- tert -butylphenol (4TBP), 2- tert -butylphenol (2TBP), 2,4,6-tri- tert -butylphenol (TTBP), 2,6,-di- tert -butylphenol (DTBP), diphenylphenol (DPP), and trichlosan were systematically evaluated by electrochemical methods.The selective electrochromic behavior was observed via electrochemical cycling. The electrocatalytic oxidation of substrates resulted in a formation of new compounds due to C-C coupling, or related products. The products were characterized by X-ray diffraction, GC-MS, and NMR, among other methods. The electrochemical synthesis was compared to the traditional chemical synthesis and the reaction yields and products were highly dependent on the synthetic strategy used and a substrate. References Zabik, N., Virca, C. N., McCormick, T., Martic-Milne, S. (2016). Selective electrochemical versus chemical oxidation of bulky phenols. J. Phys. Chem. B. 120: 8914-8924.

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 score0.466
Threshold uncertainty score0.548

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 integrity0.0000.001
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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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