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The size, surface charge and agglomeration state of nanoparticles under physiological conditions are fundamental parameters to be determined prior to their application in toxicological studies. Although silica-based materials are among the most promising candidates for biomedical applications, more systematic studies concerning the characterisation before performing toxicological studies are necessary. This interest is based on the necessity to elucidate the mechanisms affecting its toxicity. We present here TEM, SAXS and SMPS as a combination of methods allowing an accurate determination of single nanoparticle sizes. For the commercial material, Ludox TM50 single particle sizes around 30 nm were found in solution. DLS measurements of single particles are rather affected by polydispersity and particles concentration but this technique is useful to monitor their agglomeration state. Here, the influence of nanoparticle concentration, ionic strength (IS), pH and bath sonication on the agglomeration behaviour of silica particles in solution has been systematically investigated. Moreover, the colloidal stability of silica particles in the presence of BSA has been investigated showing a correlation between silica and protein concentrations and the formation of agglomerates. Finally, the colloidal stability of silica particles in standard cell culture medium has been tested, concluding the necessity of surface modification in order to preserve silica as primary particles in the presence of serum. The results presented here have major implications on toxicity investigations because silica agglomeration will change the probability and uptake mechanisms and thereby may affect toxicity.
Coating, stabilization layers, functionalization of particles or simple contamination are common variants of a core-shell system. For smaller nanoparticles this is of major importance. A particle with 16 nm diameter and a usual surface layer of 2 nm will have the same volume for the core as for the shell. In this case the material of the particle doesn’t have a clear definition. It is a common case that a particle consists of four different layers: Core, shell, stabilization layer and contamination. The properties of the particles differ according to this structure. For example silver particles might have a different dissolution rate for pure particles and for particles which are grown on top of a core.
Different solubility or defined other properties of materials is a common reason for producing core-shell systems. Gold cores are surrounded by silica to stabilize them or to get a defined distance between the cores. Silica might be surrounded by gold and the silica dissolved afterwards. This delivers hollow shells. Another important example for core-shell systems are quantum dots. A small core is surrounded by a different material for increasing the photoluminescence. Furthermore there a stabilization layer is needed. The smallest part of the final particles is the initial core. The photoluminescence is based on this core, but the shells contain much more material. Categorization should address this.
Core-shell systems are not covered by most of the existing decision trees for grouping. They are either regarded as special case or a singular layer. This disqualifies core-shell systems for grouping within the common models. There might be a very easy way to avoid this problem and even to combine some of the different decision trees. Starting the decision tree with the solubility of the outer shell and subsequently addressing the inner layers will be a pragmatic approach to solve the problem. If there is no shell, the categorization can start with a tiered approach or with the proposed “stawman” chemical categorization. If a shell is covering the surface there is a need to check if the shell is stable. If it is stable, the particle can be categorized based on this shell. If it is soluble, the ions need to be addressed as in the classic case. Furthermore the shell might increase the uptake by the cells. If the ions and the uptake are not critical the categorization can continue with the next layer.
With this not perfect but pragmatic approach, the surface layers can be addressed with very limited additional efforts. Most criteria are based on classically tabulated data. Including a rating system like the precautionary matrix approach might even address the fact that some parameters are not always Yes/No, e.g. solubility, ion toxicity and uptake.