Considerations about phenol electrohydrogenation on electrodes made with reticulated vitreous carbon cathode
Bibliographic record
Abstract
The electrocatalytic hydrogenation (ECH) of phenol was carried out in aqueous media with catalytic powders. The catalytic powders were composed of palladium nanoaggregates deposited on various substrates such as Al2O3, BaSO4, and BaCO3. Composite powders are trapped (upon stirring) into a reticulated vitreous carbon (RVC) matrix, allowing a rapid in situ build-up of the electrode and alleviating the use of a binder, since the latter may have a detrimental effect on the ECH. For a given amount of noble metal (5% palladium by weight), it is observed that the ECH of phenol to cyclohexanol increases in the following order: Pd/BaCO3 < Pd/BaSO4 < Pd/Al2O3. It is deduced that the ECH rate is largely dependent on the adsorption of organic molecules on the nonmetallic substrate, and a model is considered to explain such a behavior. The ECH of phenol is also feasible at a reasonable rate with composite Pd/Al2O3 (0.25% Pd by weight) powders fabricated by physical vapor deposition because the peripheral distribution of Pd nanoaggregates is favorable towards the ECH.Key words: electrocatalytic hydrogenation (ECH) of phenol, reticulated vitreous carbon (RVC), alumina-based catalyst, agglomeration process, adlineation point, adsorption.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".