Mediated Approach for the Electrochemical Reduction of Chlorobenzenes in Nonaqueous Media
Bibliographic record
Abstract
The use of a range of mediators for the partial or complete dechlorination of a series of polychlorinated benzenes has been investigated. The dechlorinations were carried out in acetonitrile, and the products were analyzed by gas chromatography‐mass spectroscopy (GC‐MS). The partial dechlorination using organic mediators was successful and good control of the reaction ( i.e. , monodechlorination) and good efficiency could be achieved. Some mediators showed poor current efficiencies due to the lower stability of their anion radical in the presence of protons. The monodechlorination of trichlorobenzene with four different mediators showed that the product distribution in terms of initial chlorine removed was little affected by the mediator used. This product distribution has also been investigated for the whole series of polychlorobenzenes. Polydechlorination using a single mediator was tried using biphenyl, anthracene, and dibenzofuran. After passing enough charge to completely dechlorinate trichlorobenzene, few chlorinated benzenes remained in solution and less than the expected amount of benzene was detected. The was explained by nonvolatile products undetected by GC‐MS. It is suggested that when higher overpotential mediators are used, the reaction shifts to produce higher molecular weight products by radical‐radical coupling reactions. Biphenyl might be a convenient mediator for the dechlorination of polychlorobenzene or even polychlorobiphenyl. © 2000 The Electrochemical Society. All rights reserved.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".