Role of Metal–Support Interactions, Particle Size, and Metal–Metal Synergy in CuNi Nanocatalysts for H<sub>2</sub> Generation
Why this work is in the frame
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Bibliographic record
Abstract
Efficient bimetallic nanocatalysts based on non-noble metals are highly desired for the development of new energy storage materials. In this work, we report a simple method for the synthesis of highly dispersed CuNi catalysts supported on mesoporous carbon or silica nanospheres using low-cost metal nitrate precursors. The mesoporous carbon-supported Cu 0.5 Ni 0.5 nanocatalysts exhibit excellent catalytic performance for the hydrolysis of ammonia borane and decomposition of hydrous hydrazine with 100% hydrogen selectivity in aqueous alkaline solution at 60 °C. The chemical composition and size of the metal particles, which have a significant influence on the catalytic properties of the supported bimetallic CuNi materials, can readily be controlled by adjusting the metal loading and ratio of metal precursors. An exceedingly high turnover frequency of 3288 (mol H 2 mol metal –1 h –1 ) and complete reaction within 1 min in dehydrogenation of ammonia-borane were achieved over a tailored-made catalyst obtained through precise monitoring of metal particle size, composition, and support properties.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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