Novel catalytically active Pd/Ru bimetallic nanoparticles synthesized by Bacillus benzeovorans
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Bibliographic record
Abstract
Abstract Bacillus benzeovorans assisted and supported growth of ruthenium (bio-Ru) and palladium/ruthenium (bio-Pd@Ru) core@shell nanoparticles (NPs) as bio-derived catalysts. Characterization of the bio-NPs using various electron microscopy techniques and high-angle annular dark field (HAADF) analysis confirmed two NP populations (1–2 nm and 5–8 nm), with core@shells in the latter. The Pd/Ru NP lattice fringes, 0.231 nm, corresponded to the (110) plane of RuO 2. While surface characterization using X-ray photoelectron spectroscopy (XPS) showed the presence of Pd(0), Pd(II), Ru(III) and Ru(VI), X-ray absorption (XAS) studies of the bulk material confirmed the Pd speciation (Pd(0) and Pd(II)- corresponding to PdO), and identified Ru as Ru(III) and Ru(IV). The absence of Ru–Ru or Ru–Pd peaks indicated Ru only exists in oxide forms (RuO 2 and RuOH), which are surface-localized. X ray diffraction (XRD) patterns did not identify Pd-Ru alloying. Preliminary catalytic studies explored the conversion of 5-hydroxymethyl furfural (5-HMF) to the fuel precursor 2,5-dimethyl furan (2,5-DMF). Both high-loading (9.7 wt.% Pd, 6 wt.% Ru) and low-loading (2.4 wt.% Pd, 2 wt.% Ru) bio-derived catalysts demonstrated high conversion efficiencies (~95%) and selectivity of ~63% (~20% better than bio-Ru NPs) and 58%, respectively. These materials show promising future scope as efficient low-cost biofuel catalysts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 it