Deciphering the Oxygen Reduction Reaction on Platinum: A Theoretical Framework
Bibliographic record
Abstract
The 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 a central role in this reaction, since they necessarily act as intermediates but also as site-blockers. Any attempt to decipher the oxygen reduction reaction must relate the formation of oxygen intermediates to basic electronic and electrostatic properties of the catalyst surface and, on the other hand, link it to effective parameters of the electrode activity. An approach that accomplishes this feat will be of great utility in guiding design and development of catalyst materials and developing predictive models of electrode operation. Here, we present a theoretical framework for the multiple interrelated surface phenomena and processes involved. It correlates the formation of chemisorbed oxygen intermediates, metal surface charging phenomena, ion density and potential distribution in electrolyte, field-dependent ordering of interfacial water molecules, and effective kinetic parameters of the ORR. Parameterized with density functional theory results and rotating disk electrode data, the model sheds light on the double-edged roles of oxygen intermediates; it produces as output the Tafel slope and exchange current density as continuous functions of electrode potential and presents a new perspective on the volcano relation the ORR. The optimal oxide coverage is a result of two oppositely-headed trends upon increasing coverage by oxygen intermediates, viz, the intuitive site-blocking effect and the increasing protophilicity of the surface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".