Quantitative Studies of the Coverage Effects on Microkinetic Simulations for NO Oxidation on Pt(111)
Bibliographic record
Abstract
To advance a reliable microkinetic modeling approach using density functional theory (DFT) energies is of great importance to bridging between experimental results and theoretical calculations, and the current major issue is the coverage effect. In this work, a full microkinetic modeling for NO oxidation using DFT energetics is developed. We show that the calculated turnover frequency (TOF) (0.22 s–1) agrees with the experimental one (∼0.2 s–1) very well, if the coverage effects are properly incorporated. It is found that to include the interactions of adsorbates, namely, (i) O and O, NO and NO (self-interaction), and (ii) O and NO (cross-interaction), is important to obtain accurate kinetic results. Equally important, the interactions between the adsorbates and the transition states of O–O bond breaking and O–NO coupling are also crucial for achieving precise kinetics. We demonstrate that a two-line model can be used to describe accurately both the self and cross adsorbate–adsorbate interactions as well as the coverage effects on the transition states of O2 dissociation and O–NO coupling. The various approximations including Brønsted–Evans–Polanyi (BEP) relations are carefully examined, and the errors involved are quantified. Moreover, a one-line model is tested, which is a simplified approach but gives rise to a good agreement with experimental results.
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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 | 0.001 |
| 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".