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Particle Size Distribution of Bimodal Silica Nanoparticles: A Comparison of Different Measurement Techniques
Silica nanoparticles (SNPs) belong to the most widely produced nanomaterials nowadays. Particle size distribution (PSD) is a key property of SNPs that needs to be accurately determined for a successful application. Many single particle and ensemble characterization methods are available for the dete...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412153/ https://www.ncbi.nlm.nih.gov/pubmed/32664525 http://dx.doi.org/10.3390/ma13143101 |
Sumario: | Silica nanoparticles (SNPs) belong to the most widely produced nanomaterials nowadays. Particle size distribution (PSD) is a key property of SNPs that needs to be accurately determined for a successful application. Many single particle and ensemble characterization methods are available for the determination of the PSD of SNPs, each having different advantages and limitations. Since most preparation protocols for SNPs can yield bimodal or heterogeneous PSDs, the capability of a given method to resolve bimodal PSD is of great importance. In this work, four different methods, namely transmission electron microscopy (TEM), dynamic light scattering (DLS), microfluidic resistive pulse sensing (MRPS) and small-angle X-ray scattering (SAXS) were used to characterize three different, inherently bimodal SNP samples. We found that DLS is unsuitable to resolve bimodal PSDs, while MRPS has proven to be an accurate single-particle size and concentration characterization method, although it is limited to sizes above 50 nm. SAXS was found to be the only method which provided statistically significant description of the bimodal PSDs. However, the analysis of SAXS curves becomes an ill-posed inverse mathematical problem for broad size distributions, therefore the use of orthogonal techniques is required for the reliable description of the PSD of SNPs. |
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