Computational modeling of supported catalyst systems: investigation of free catalyst nanoparticles and support effects
Bibliographic record
Abstract
Improvements in durability and performance of cathode catalyst layers in polymer electrolyte fuel cells require a fundamental understanding of the stability and electrocatalytic reactivity of Pt/support systems. The objective of this Ph.D. work was to investigate the effects of geometrical factors defining the properties of the catalyst as well as the impact of the support material on the thermal stability and catalytic behaviour of free Pt nanoparticles and Pt/support systems. This dissertation consists of three parts, dealing with the following phenomena: i) effects of atomic structure on the energetics and adsorption properties of free Pt nanoparticles, ii) effects of metal oxide support materials within Pt/NbxOy bilayer systems; iii) effects of the spillover of hydrogen from catalyst surface to support on the apparent hydrogen evolution reactivity in the systems of Pd nanoislands on an Au support. The first two parts of this work employed ab initio calculations based on density functional theory. The third part employed a mean field approach based on the Wigner-Seitz cellular method. In the study of free Pt nanoparticles, the calculated cohesive energies agree with the Gibbs-Thomson relation. These results imply that the cohesive energy of Pt nanoparticles is determined primarily by the particle size and not the particle shape. The calculated adsorption energies of atomic oxygen showed high spatial variation on all nanofacets. The adsorption energies depend on the atom arrangement at the reaction site. In the study of Pt/NbxOy bilayer systems, the degree of oxygen incorporation into NbxOy was observed to influence the distribution of electronic charge density and the formation of chemical bonds at the Pt|NbxOy interface. These results imply that the electronic and geometric structure of Pt is changed by interaction between Pt and support. The spillover effect was studied by developing a kinetic model of hydrogen evolution on an array of Au-supported catalyst particles. These results imply that the spillover effect could be a major cause of the enormous enhancement of the current density observed in experimental studies.
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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".