Structural discrimination of nanosilica particles and mixed-structure silica by multivariate analysis applied to SAXS profiles in combination with FT-IR spectroscopy

Abstract

The structural characteristics of silica nanoparticles with functional properties can be investigated using Fourier transform infrared (FT-IR) and small-angle X-ray scattering (SAXS) techniques. Herein, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to analyze the variance and to detect similarities between spectroscopic and scattering data. To analyze its potentiality, nanosilica and mixed-structure silica samples were synthesized by a sol–gel process using several reagents, such as SiCl₄, octadecylamine, Pluronic®L-31, and Tween®80, to modify the surfaces of silica nanoparticles. Additionally, the quantities of these reagents used in synthesis of the different particle types were studied at distinct levels. A total of 168 measurements (IR spectra and X-ray scatterings) were performed using 28 samples. The FT-IR/SAXS/multivariate analysis results suggest that samples can be separated into two major groups associated with the incorporation of organic groups into the silica network and the organizational structures of aggregates in the low-q region, which separated the surface fractals (3.0 < P_L < 3.8, class I) from the mass fractals (1.7 < P_L < 2.8, classes II and III). It was determined that only two principal components carried over 96.5 and 89.7% of variance (FT-IR and SAXS, respectively) within the sample set. The organic groups in the hybrid mixed-structure silicas created more compact and denser silicas, increased the aggregate radii, decreased D_pBJH and S_BET, and shifted the halo toward higher 2θ angles due to the changes in the densities of the silicas. We demonstrate that the FT-IR and SAXS techniques combined with multivariate analysis can simplify the interpretation of changes in the structural properties of mesoporous silica materials.