The granulometric characterization of synthetic amorphous silica (SAS) nanomaterials (NMs) still demands harmonized standard operation procedures. SAS is produced as either precipitated, fumed (pyrogenic), gel and colloidal SAS and these qualities differ, among others, with respect to their state of aggregation and aggregate strength. The reproducible production of suspensions from SAS, e.g., for biological testing purposes, demands a reasonable amount of dispersing energy. Using materials representative for each of the types of SAS, we employed ultrasonic dispersing (USD) at energy densities of 8–1440 J/mL and measured resulting particle sizes by dynamic light scattering and laser diffraction. In this energy range, USD had no significant impact on particle size distributions of colloidal and gel SAS, but clearly decreased the particle size of precipitated and fumed SAS. For high energy densities, we observed a considerable contamination of SAS suspensions with metal particles caused by abrasion of the sonotrode’s tip. To avoid this problem, the energy density was limited to 270 J/mL and remaining coarse particles were removed with size-selective filtration. The ultrasonic dispersion of SAS at medium levels of energy density is suggested as a reasonable compromise to produce SAS suspensions for toxicological in vitro testing.

Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring.

Synthetic amorphous silica (SAS) constitute a large group of industrial nanomaterials (NM). Based on their different production processes, SAS can be distinguished as precipitated, fumed, gel and colloidal. The biological activity of SAS, e.g., cytotoxicity or inflammatory potential in the lungs is low but has been shown to depend on the particle size, at least for colloidal silica. Therefore, the preparation of suspensions from highly aggregated or agglomerated SAS powder materials is critical. Here we analyzed the influence of ultrasonic dispersion energy on the biologic activity of SAS using NR8383 alveolar macrophage (AM) assay. Fully characterized SAS (7 precipitated, 3 fumed, 3 gel, and 1 colloidal) were dispersed in H₂O by stirring and filtering through a 5 µm filter. Aqueous suspensions were sonicated with low or high ultrasonic dispersion (USD) energy of 18 or 270 kJ/mL, respectively. A dose range of 11.25–90 µg/mL was administered to the AM under protein-free conditions to detect particle-cell interactions without the attenuating effect of proteins that typically occur in vivo. The release of lactate dehydrogenase (LDH), glucuronidase (GLU), and tumor necrosis factor α (TNF) were measured after 16 h. Hydrogen peroxide (H₂O₂) production was assayed after 90 min. The overall pattern of the in vitro response to SAS (12/14) was clearly dose-dependent, except for two SAS which showed very low bioactivity. High USD energy gradually decreased the particle size of precipitated, fumed, and gel SAS whereas the low adverse effect concentrations (LOECs) remained unchanged. Nevertheless, the comparison of dose-response curves revealed slight, but uniform shifts in EC₅₀ values (LDH, and partially GLU) for precipitated SAS (6/7), gel SAS (2/3), and fumed SAS (3/3). Release of TNF changed inconsistently with higher ultrasonic dispersion (USD) energy whereas the induction of H₂O₂ was diminished in all cases. Electron microscopy and energy dispersive X-ray analysis showed an uptake of SAS into endosomes, lysosomes, endoplasmic reticulum, and different types of phagosomes. The possible effects of different uptake routes are discussed. The study shows that the effect of increased USD energy on the in vitro bioactivity of SAS is surprisingly small. As the in vitro response of AM to different SAS is highly uniform, the production process per se is of minor relevance for toxicity.

Understanding the world of nanoparticles, especially their interactions with the environment, begins with their correct detection and successive quantification. To achieve this purpose, one needs to perform correctly developed standard operating procedures (SOPs). Furthermore, the study of nanoparticles frequently requires their characterisation in complex media (e.g. in cosmetic formulations). In this study, a set of sample preparation procedures for the detection and extraction of NMs in emulsion-based formulations is proposed and their performance for model and real-life products is discussed. A separation or extraction of lipid phases is achieved by means of organic solvents. The polarity of the lipid phases is decisive for selecting an optimum solvent. The use of the Hansen Solubility Parameters (HSP) may clearly support this decision.