Oxidative Ring-Opening of Aromatics: Decomposition of Biphenyl Carboxylic Acids and Zinc Biphenyl Carboxylates
Bibliographic record
Abstract
Abstract Ring-opening conversion of multinuclear aromatics can be used to upgrade heavy aromatic oils to lighter products, and it is usually performed reductively with H2. Oxidative ring-opening is an alternative strategy that involves three steps: (i) oxidation of multinuclear aromatics to quinonoids, (ii) further oxidation and ring-opening to produce aromatic carboxylic acids, and (iii) decarboxylation of aromatic carboxylic acids. In the last step, decomposition by ketonization is an undesirable side reaction that leads to a ring-closed product. Selectivity control during aromatic carboxylic acid decomposition was investigated using biphenyl-2-carboxylic acid, biphenyl-2,2′-dicarboxylic acid, zinc(II) biphenyl-2-carboxylate, and zinc(II) biphenyl-2,2′-dicarboxylate. The reaction networks of thermal decomposition of the aromatic carboxylic acids were determined. Decomposition of biphenyl-2-carboxylic acid took place mainly by decarboxylation to produce biphenyl, dehydration and ring-closure to produce fluorenone, and the formation of diphenic anhydride as intermediate product leading to fluorenone. Decomposition of biphenyl-2,2′-dicarboxylic acid proceeded through decarboxylation to biphenyl-2-carboxylic acid as intermediate, as well as two seemingly related pathways, leading to the formation of a hydroxy-fluorenone and a cyclic trione. Over the temperature range from 340 °C to 400 °C, thermal decomposition invariably resulted in a higher ketonization than decarboxylation selectivity. Decomposition of the analogous zinc carboxylates demonstrated that ketonization could be suppressed and the most abundant products were biphenyl > fluorenone > fluorene. It was possible to achieve a biphenyl (decarboxylation) to fluorenone (ketonization) selectivity ratio of 17:1 during batch reactor decomposition of zinc(II) biphenyl-2,2′-dicarboxylate at 380 °C. Reaction stoichiometry indicated that water should affect selectivity, which is consistent with observations in the literature, but this aspect was not investigated further.
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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 | 0.000 | 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".