Ingenieurwissenschaften und zugeordnete Tätigkeiten
Filtern
Erscheinungsjahr
- 2016 (4) (entfernen)
Dokumenttyp
- Vortrag (3)
- Posterpräsentation (1)
Sprache
- Englisch (4)
Referierte Publikation
- nein (4) (entfernen)
Schlagworte
- Nanoparticles (4) (entfernen)
Eingeladener Vortrag
- nein (3)
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.
Silver nanoparticles (Ag NPs) are widely used in consumer products due to their excellent antibacterial properties. Their broad application has led to a variety of recent regulation on their use and labelling. Thus, a highly specific analytical method for their characterization and quantification is needed.
Due to their large separation range, field-flow fractionation (FFF) techniques are repeatedly applied for the analysis of NP. Limitations of FFF include quantification, sample loss and insufficient recovery rates. Another challenge can be non-ideal elution behavior of particles in complex and unknown matrices.
The possible sources for sample losses of Ag NP have been studied using an asymmetric flow FFF (AF4) in combination with inductively coupled plasma mass spectrometry (ICP-MS). The influence of different parameters, for example the sample concentration, on the recovery rates and sample loss has been investigated. Using laser ablation ICP-MS, the Ag deposition on the membrane was located and quantified. Our results identified ionic silver as the main sources of sample loss. These results can be useful for further method improvement.
However, when a Ag NP sample containing an unknown complex matrix is analyzed, FFF method optimization is challenging as the sample might show a shift in the retention times and lower recovery rates. In this case, ICP-MS experiment in the single particle mode (sp-ICP-MS) can be a useful addition to the FFF measurement. Here, upon assumption of spherical particles, the geometric diameters can be calculated. This fast and easy approach can be helpful in order to interpret the FFF fractograms and advice the FFF method optimization process.
We report on the development of ultra-small core-shell silver nanoparticles synthesized by an up-scaled modification of the polyol process. It is foreseen to use these thoroughly characterized particles as reference material to compare the catalytic and biological properties of functionalized silver nanoparticles. Small-angle X-ray scattering (SAXS) analysis reveal a narrow size distribution of the silver cores with a mean radius of RC = 3.0 nm and a distribution width of 0.6 nm. Dynamic light scattering (DLS) provides a hydrodynamic radius of RH = 10.0 nm and a PDI of 0.09. The particles’ surface is covered with poly(acrylic acid) (PAA) forming a shell with a thickness of 7.0 nm, which provides colloidal stability lasting for more than six months at ambient conditions. The PAA can be easily exchanged by biomolecules to modify the surface functionality. Replacements of PAA with glutathione (GSH) and bovine serum albumin (BSA) have been performed as examples. We demonstrate that the particles effectively catalyze the reduction of 4-nitrophenol to 4-aminophenol with sodium borohydride. The tunable catalytic activity of (436 ± 24) L g-1 s-1 is the highest reported in literature for silver nanoparticles.