Formation of uniform magnetic C@CoNi alloy hollow hybrid composites with excellent performance for catalysis and protein adsorption
Bibliographic record
Abstract
Metallic nickel- or cobalt-based composites with hollow nanostructures such as nanocages can serve as both advanced catalysts and protein adsorbents owing to their high surface area and increased active sites; hence, they have aroused great interest. Herein, we report a facile route to synthesize hollow carbon spheres (HCS) embedded with bimetallic NiCo nanoparticles (NPs) with hollow structures by using NiCo hydroxide layered nanosheet functionalized carboxyl polystyrene spheres (CPS) as a template and polydopamine (PDA) as both the carbon precursor and reductant. This unique hierarchical architecture, including meso- and macro-pores, provides a large specific surface area (244 m2 g-1) and efficient channels for the diffusion of small molecules and biomacromolecules (protein). These features greatly facilitate the excellent performances of C@CoNi for the reduction of 4-nitrophenol and His-rich protein adsorption. Moreover, the size of the surficial CoNi NPs can be facilely modulated by changing the calcination temperature, which can effectively control the catalytic and adsorption performances of the as-prepared nanocomposites. The as-prepared C@CoNi is employed as a catalyst to investigate its catalytic performance in the reduction of 4-nitrophenol (4-NP). Furthermore, the nickel nanoparticles decorated on the hollow microspheres display a strong affinity to His-rich proteins (BHb and BSA) via specific metal affinity forces between the polyhistidine groups and nickel nanoparticles.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".