Identification of a Pt<sub>3</sub>Co Surface Intermetallic Alloy in Pt–Co Propane Dehydrogenation Catalysts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bimetallic Pt–Co nanoparticles (NPs) were prepared and characterized by scanning transmission electron microscopy, in situ X-ray absorption spectroscopy, in situ synchrotron X-ray diffraction, and catalytic conversion for propane dehydrogenation with and without added H2. In addition, the surface extended X-ray absorption fine structure (EXAFS) obtained by fitting the difference spectrum between the fully reduced and room-temperature-oxidized catalysts suggest that the surface structure remains Pt3Co, although the core changes from Pt to Pt3Co and to PtCo. At low Co loading, the bimetallic nanoparticles form a Pt3Co intermetallic surface alloy with Pt-rich core. With increasing Co loading, a full alloy forms where both the surface and NP compositions are Pt3Co. A further increase in Co loading leads to a Co-rich NP core, likely PtCo, with a surface of Pt3Co. Although Pt–Co intermetallic alloys form two different phases and several morphologies, the surface structures are similar in all catalysts. Although both monometallic Pt and Co are active for alkane dehydrogenation, all bimetallic Pt–Co catalysts are significantly more olefin selective than either single metal. The turnover rates of the bimetallic catalysts indicate that Pt is the active atom with little contribution from Co atoms. The high olefin selectivity is suggested to be due to Co acting as a less active structural promoter to break up large Pt ensembles in bimetallic NPs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it