MIL-101(Cr) supported Pt and Au-Pt composites as active catalysts for the selective hydrogenation of nitrobenzene under mild reaction conditions
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Bibliographic record
Abstract
In this study, we report the successful synthesis of monometallic Pt(2 wt.%)/MIL-101(Cr) and bimetallic Au(1 wt.%)-Pt(1 wt.%)/MIL-101(Cr) catalysts with low dimension MeNPs by the double-solvent (DS) method. The catalysts were characterized by powder X-ray diffraction (PXRD), N2 sorption analysis (BET), thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), temperature-programmed reduction (TPR), and transmission electron microscopy (TEM). The characterization results demonstrated the presence of well-dispersed Pt and Au-Pt nanoparticles (2.9 and 2.7 nm, respectively), located mainly inside the pores of MIL-101(Cr). The stronger interaction of Au-Pt NPs with the support compared to Pt NPs was demonstrated by H2-TPR and XPS, which proved the existence of charge exchange between Pt NPs and Cr from MIL-101 in the case of Au(1 wt%)-Pt(1 wt%)/MIL-101(Cr), but not in the case of Pt(2 wt%)/MIL-101(Cr). The composite materials were tested in the catalytic selective hydrogenation of nitrobenzene to aniline in liquid phase under mild conditions (low temperature, low hydrogen pressure), and in the presence of a biomass-derived non-toxic solvent (ethanol). The bimetallic Au(1 wt%)-Pt(1 wt%)/MIL-101(Cr) catalyst showed superior catalytic activity as compared to the monometallic Pt(2 wt%)/MIL-101(Cr) catalyst. This is due to the synergetic effect between the two metals as demonstrated by the projected density of states studies.
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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 it