Quantification of branching in fumed silica. (July 2017)

• Record Type: Journal Article
• Authors: Mulderig, Andrew; Beaucage, Gregory; Vogtt, Karsten; Jiang, Hanqiu; Kuppa, Vikram
• Is Part Of: Journal of aerosol science. Volume 109(2017)
• Page Start: 28
• Page End: 37
• Publication Date: 2017-07
• Subjects: Fumed silica -- Fractal -- Aerosol -- Small-angle x-ray scattering -- Colloid -- Aggregate; Aerosols -- Periodicals; Aerosols -- Periodicals; Aérosols -- Périodiques; 541.34515
• DOI: 10.1016/j.jaerosci.2017.04.001
• Languages: English
• ISSNs: 0021-8502

Abstract

Abstract: The fractal structure of ceramic aggregates has been widely studied in terms of the mass fractal dimension and primary particle size. However, there has not yet been a quantitative description of the branched topology in these structures. In this work, the highly ramified aggregate structure in six commercial grades of hydrophilic fumed silica is investigated. Ultra-small angle X-ray scattering was coupled to a hierarchical scattering model, the unified scattering function, to obtain topological parameters. These generic topological parameters were used to quantify branching and were then compared with simple aggregation simulations. Surprisingly, a single parameter, the sticking probability, can empirically account for complex topological differences in the materials studied. It is found that samples of higher specific surface area display a higher branch fraction. For grades of highest specific surface area, a hyper-branched structure is observed with extensive branch on branch aggregation. This approach can be used to quantify complex morphological differences in ceramic oxide and carbon black aggregates. Highlights: Branching in fractal aggregates may be characterized via small-angle scattering. Aggregates of smaller nanoparticles tend to form more highly branched fractal structures with a higher degree of aggregation. Fractal aggregates are simulated, and heuristically selected by comparison with measured branched aggregate parameterization. These heuristic, simulated aggregates compare favorably with TEM images.