Ultra-Fine Pt Entities on High-Index CeO <sub>2</sub> (112) Facet Significantly Boosting Low Temperature Water–Gas Shift Reaction
Bibliographic record
Abstract
In this study, two tactics were employed to develop a very efficient and durable Pt-based catalyst for low-temperature water gas shift (WGS) reaction. First, through facet engineering of CeO 2, the dominantly exposed (112)/(110) facets of the oxygen-deficient CeO 2 hexagonal prism (CeO 2 –HP) were established. Second, the Pt single atoms (SAs) and Pt fine clusters (FCs) were anchored to CeO 2 –HP(112)/(110) with the Pt δ+ –O v –Ce 3+ and Pt 2+ –O 2– –Ce 4+ interfacial sites, verified by AC-HAADF-STEM and XAFS measurements. The as-obtained 0.10Pt/CeO 2 –HP achieved a CO conversion rate of 12.63 mmol CO g Pt –1 s –1 and a TOF as high as 2.46 s –1 at 250 °C, 2.6-fold that of benchmark Pt/Fe-0.01 SAC at 300 °C (0.93 s –1 ). The exposed CeO 2 {112} facets constitute abundant oxygen vacancies and an enhanced Pt dispersion. In-situ FTIR study demonstrated the synergetic effect between the Pt δ+ –O v –Ce 3+ and Pt 2+ –O 2– –Ce 4+ interfacial sites which modulates the competitive adsorption of CO and H 2 O. The DFT simulations revealed that the high density of oxygen vacancy over CeO 2 –HP(112) boosts H 2 O dissociation, causing a substantial enhancement in catalytic performance and a variation in the reaction route. This work provides in-depth insights into how the well-controllably assembled interfacial structure functions electronically and is structurally efficient for the target reaction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".