Unifying theoretical framework for deciphering the oxygen reduction reaction on platinum
Bibliographic record
Abstract
Rapid conversion of oxygen into water is crucial to the operation of polymer electrolyte fuel cells and other emerging electrochemical energy technologies. Chemisorbed oxygen species play double-edged roles in this reaction, acting as vital intermediates on one hand and site-blockers on the other. Any attempt to decipher the oxygen reduction reaction (ORR) must first relate the formation of oxygen intermediates to basic electronic and electrostatic properties of the catalytic surface, and then link it to parameters of catalyst activity. An approach that accomplishes this feat will be of great utility for catalyst materials development and predictive model formulation of electrode operation. Here, we present a theoretical framework for the multiple interrelated surface phenomena and processes involved, particularly, by incorporating the double-layer effects. It sheds light on the roles of oxygen intermediates and gives out the Tafel slope and exchange current density as continuous functions of electrode potential. Moreover, it develops the concept of a rate determining term, which should replace the concept of a rate determining step for multielectron reactions, and offers a new perspective on the volcano relation of the ORR.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".