Effect of Molecular Structure of Quinones and Carbon Electrode Surfaces on the Interfacial Electron Transfer Process
Bibliographic record
Abstract
Quinones can undergo thermodynamically reversible proton-coupled electron transfer reactions and are being applied as electroactive compounds in aqueous organic batteries. However, the electrochemical reversibility of these compounds is affected not only by their molecular structure but also by the properties of a carbon-based electrode surface. This study combines experimental and theoretical approaches to understand this dependence. We study the electron transfer kinetics of two synthesized quinone derivatives and two commercially available ones with a glassy carbon, a highly ordered pyrolytic graphite, and a high-edge-density graphite electrode (HEDGE). The electrochemical reversibility is notably improved on the HEDGE, which shows a higher density of defects and presents oxygenated functional groups at its surface. The electron transfer kinetics are controlled by adsorbed species onto the HEDGE. Molecular dynamics simulation and quantum mechanics calculations suggest defects with oxygen-containing functional groups, such as C–O and C═O, on HEDGE surfaces drive the interaction with the functional groups of the molecules, during physisorption from van der Waals forces. The presence of sulfonic acid side groups and a greater number of aromatic rings in the molecular structure may contribute to a higher stabilization of quinone derivatives on HEDGEs. We propose that high-performance carbon-based electrodes can be obtained without catalysts for organic batteries, by the engineering of carbon-based surfaces with edge-like defects and oxygenated functional groups.
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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) | 0.000 | 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) | 0.002 | 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".