Method for studying high temperature aqueous electrochemical systems: Methanol and glycerol oxidation
Bibliographic record
Abstract
A method for high purity aqueous electrochemical experiments at temperatures above the normal boiling point of water and at temperatures up to 140 °C is described. A three-electrode cell in a self-pressurized glass autoclave is heated in an oil bath. Slow ramping of the temperature allows efficient acquisition of kinetic parameters such as activation energies, oxidation onset potentials and Tafel slopes by using cyclic voltammetry. The oxidation of two organic alcohols with different volatilities, methanol (high volatility) and glycerol (low volatility), are studied to demonstrate the capabilities of the method. Methanol oxidation on platinum is found to have a similar mechanism at all temperatures, with either dissociative adsorption of water or dissociative adsorption of methanol as the rate-determining step. In the case of glycerol oxidation on platinum, the mechanism changes at 110 °C. At low temperatures dissociative adsorption of water or dissociative adsorption of glycerol is suggested to be the rate-determining step. At higher temperatures, a significant decrease in onset potential was observed and the glycerol is suggested to selectively oxidize to glyceraldehyde or dihydroxyacetone, with dissociative glycerol adsorption as the rate-determining step.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".