journal article·2020-03

Development of mesoporous SiO2/CeO2 core/shell nanoparticles with tunable structures for non-damage and efficient polishing

Yang Chen, Zhaoyu Mu, Wanying Wang, Ailian Chen

Ceramics International· Volume 46· Issue 4
Publisher page

Abstract

Abstract For abrasive particles, the type, morphology, structure, size and distribution, physio-chemical properties are usually considered as key influential factors which determine the ultra-precision polishing performance. It is commonly recognized that the structure design, surface modification, and doping treatment of abrasives contribute to achieving high-quality and high-efficiency polishing. Herein, we report the fabrication of sub-100 nm monodispersed dendritic-like mesoporous silica (D-mSiO2) with tunable structures via an oil-water biphase stratification approach. A CeO2 thin shell was subsequently coated on the D-mSiO2 nanospheres forming core/shell structured D-mSiO2/CeO2 composites. The samples were examined via XRD, SEM, TEM, SAED, DLS, FTIR, and nitrogen adsorption-desorption measurements. The polishing characteristics of the D-mSiO2/CeO2 nano-abrasives over silica films were tracked by atomic force microscopy and noncontact interferometric microscopy. Compared with commercial ceria particles, the obtained D-mSiO2/CeO2 nano-abrasives were favorable for mechanical scratch elimination and removal rate enhancement. Furthermore, an enlarged pore volume or porosity of D-mSiO2 cores achieved an atomic-scale surface with relatively low roughness, less variation, and enhanced removal rate. The mechanism of high-efficiency and defect-free polishing for the CeO2-based composites was discussed. These results may provide promising guidance in the design and optimization of novel particle abrasives.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Diamond and Carbon-based Materials Research · Advanced Surface Polishing Techniques · Electronic and Structural Properties of Oxides

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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