Synthesis of Ni–Ru Alloy Nanoparticles and Their High Catalytic Activity in Dehydrogenation of Ammonia Borane
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Bibliographic record
Abstract
We report the synthesis and characterization of new Ni(x)Ru(1-x) (x = 0.56-0.74) alloy nanoparticles (NPs) and their catalytic activity for hydrogen release in the ammonia borane hydrolysis process. The alloy NPs were obtained by wet-chemistry method using a rapid lithium triethylborohydride reduction of Ni(2+) and Ru(3+) precursors in oleylamine. The nature of each alloy sample was fully characterized by TEM, XRD, energy dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS). We found that the as-prepared Ni-Ru alloy NPs exhibited exceptional catalytic activity for the ammonia borane hydrolysis reaction for hydrogen release. All Ni-Ru alloy NPs, and in particular the Ni(0.74)Ru(0.26) sample, outperform the activity of similar size monometallic Ni and Ru NPs, and even of Ni@Ru core-shell NPs. The hydrolysis activation energy for the Ni(0.74)Ru(0.26) alloy catalyst was measured to be approximately 37 kJ mol(-1). This value is considerably lower than the values measured for monometallic Ni (≈70 kJ mol(-1)) and Ru NPs (≈49 kJ mol(-1)), and for Ni@Ru (≈44 kJ mol(-1)), and is also lower than the values of most noble-metal-containing bimetallic NPs reported in the literature. Thus, a remarkable improvement of catalytic activity of Ru in the dehydrogenation of ammonia borane was obtained by alloying Ru with a Ni, which is a relatively cheap metal.
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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 | 0.002 | 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