Bibliographic record
Abstract
Electrocatalytic transformations giving rise to new C-C bond formation and new products is of value. We have recently discovered that phenolic compounds undergo selective electrochemical oxidation giving rise to reactive phenoxyl radicals which combine to produce a product with new C-C bond formed [1]. Five phenolic compounds including butylated hydroxytoluene (BHT), 4-tert-butylphenol (4TBP), 2-tert-butylphenol (2TBP), 2,4,6-tri-tert-butylphenol (TTBP), and 2,6,-di-tert-butylphenol (DTBP) were systematically evaluated by electrochemical methods to determine their oxidation/reduction potentials as a function of concentration. At identical experimental conditions, only DTBP exhibited electrochromic behavior which was dependent on concentration and electrochemical cycling. The electrocatalytic oxidation of DTBP resulted in a formation of a new compounds due to C-C coupling. The reaction was monitored by electrochemical methods, UV-vis spectroscopy and final product characterized by X-ray diffraction. Recently, we expanded the electrocatalysis to include diverse phenolics such as dihydroxybiphenol (DHBP) which also formed a yellow-coloured solution, indicating a product formation. The electrochemical and spectroscopic characterization of DHBP reaction will be described. 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".