Electrocatalytic Hydrogenation of Guaiacol in Diverse Electrolytes Using a Stirred Slurry Reactor
Bibliographic record
Abstract
Abstract Electrocatalytic hydrogenation (ECH) of guaiacol was performed in a stirred slurry electrochemical reactor (SSER) using 5 wt % Pt/C catalyst in the cathode compartment. Different pairs of acid (H 2 SO 4 ), neutral (NaCl), and alkaline (NaOH) catholyte–anolyte combinations separated by a Nafion ® 117 cation exchange membrane, were investigated by galvanostatic and potentiostatic electrolysis to probe the electrolyte and proton concentration effect on guaiacol conversion, product distribution, and Faradaic efficiency. The acid–acid and neutral–acid pairs were found to be the most effective. In the case of the neutral–acid pair, proton diffusion and migration through the membrane from the anolyte to the catholyte supplies the protons required for ECH. Typically, the two major hydrogenation products were cyclohexanol and 2‐methoxycyclohexanol. However, ECH at constant cathode superficial current density (−182 mA cm −2 ) and higher temperature (i.e., 60 °C) favored a pathway leading mainly to cyclohexanone. The guaiacol conversion routes were affected by temperature‐ and cathode potential‐dependent surface coverage of adsorbed hydrogen radicals generated through electroreduction of protons.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".