Interfacial Field-Driven Proton-Coupled Electron Transfer at Graphite-Conjugated Organic Acids
Bibliographic record
Abstract
Interfacial proton-coupled electron transfer (PCET) reactions are central to the operation of a wide array of energy conversion technologies, but molecular-level insights into interfacial PCET are limited. At carbon surfaces, designer sites for interfacial PCET can be incorporated by conjugating organic acid functional groups to graphite edges though aromatic phenazine linkages. At these graphite-conjugated catalysts (GCCs) bearing organic acid moieties, PCET is driven by complex interfacial electrostatic and field gradients that are difficult to probe experimentally. Herein, the spatially inhomogeneous interfacial electrostatic potentials and electric fields of GCC organic acids are computed as functions of applied potential. The calculated proton-coupled redox potentials for the PCET reactions at the GCC phenazine bridges and organic acid sites are in agreement with cyclic voltammetry measurements for a series of GCC acids. The trends in these redox potentials are explained in terms of the acidity of the molecular analogues and continuous conjugation between the acid and the graphite surface. The calculations illustrate that this conjugation is interrupted in a GCC acetic acid system, providing an explanation for the absence of a cyclic voltammetry peak corresponding to PCET at this acid site. This combined theoretical and experimental study demonstrates the critical role of continuous conjugation and strong electronic coupling between the GCC acid site and the graphite to enable interfacial field-driven PCET at the acid site. Understanding the connection between the atomic structure of the surface and the interfacial electrostatic potentials and fields that govern PCET thermochemistry may guide heterogeneous catalyst design.
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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) | 0.001 | 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".