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The fluorolytic sol–gel synthesis is applied with the intention to obtain two different types of core–shell nanoparticles, namely, SrF2–CaF2 and CaF2–SrF2. In two separate fluorination steps for core and shell formation, the corresponding metal lactates are reacted with anhydrous HF in ethylene glycol. Scanning transmission electron microscopy (STEM) and dynamic light scattering (DLS) confirm the formation of particles with mean dimensions between 6.4 and 11.5 nm. The overall chemical composition of the particles during the different reaction steps is monitored by quantitative Al Kα excitation X-ray photoelectron spectroscopy (XPS). Here, the formation of stoichiometric metal fluorides (MF2) is confirmed, both for the core and the final core–shell particles. Furthermore, an in-depth analysis by synchrotron radiation XPS (SR-XPS) with tunable excitation energy is performed to confirm the core–Shell character of the nanoparticles. Additionally, Ca2p/Sr3d XPS intensity ratio in-Depth profiles are simulated using the software Simulation of Electron Spectra for Surface Analysis (SESSA). In principle, core–shell like particle morphologies are formed but without a sharp interface between calcium and strontium containing phases.
Surprisingly, the in-depth chemical distribution of the two types of nanoparticles is equal within the error of the experiment. Both comprise a SrF2-rich core domain and CaF2-rich shell domain with an intermixing zone between them. Consequently, the internal morphology of the final nanoparticles seems to be independent from the synthesis chronology.
Nanoparticles have gained increasing attention in recent years due to their potential and application in different fields including medicine, cosmetics, chemistry, and their potential to enable advanced materials. To effectively understand and regulate the physico-chemical properties and potential adverse effects of nanoparticles, validated measurement procedures for the various properties of nanoparticles need to be developed. While procedures for measuring nanoparticle size and size Distribution are already established, standardized methods for analysis of their surface chemistry are not yet in place, although the influence of the surface chemistry on nanoparticle properties is undisputed. In particular, storage and preparation of nanoparticles for surface analysis strongly influences the analytical results from various methods, and in order to obtain consistent results, sample preparation must be both optimized and standardized. In this contribution, we present, in detail, some standard procedures for preparing nanoparticles for surface analytics. In principle, nanoparticles can be deposited on a suitable substrate from suspension or as a powder. Silicon (Si) Wafers are commonly used as substrate, however, their cleaning is critical to the process. For sample preparation from suspension, we will discuss drop-casting and spin-coating, where not only the cleanliness of the substrate and purity of the suspension but also its concentration play important roles for the success of the preparation methodology.
For nanoparticles with sensitive ligand shells or coatings, deposition as powders is more suitable, although this method requires particular care in fixing the sample.
Most real core-shell nanoparticle (CSNP) samples deviate from an ideal core-shell structure potentially having significant impact on the particle properties. An ideal structure displays a spherical core fully encapsulated by a shell of homogeneous thickness, and all particles in the sample exhibit the same shell thickness. Therefore,
analytical techniques are required that can identify and characterize such deviations.
This study demonstrates that by analysis of the inelastic background in X-ray photoelectron spectroscopy (XPS) survey spectra, the following types of deviations can be identified and quantified: the nonuniformity of the shell thickness within a nanoparticle sample and the incomplete encapsulation of the cores by the shell material. Furthermore, CSNP shell thicknesses and relative coverages can be obtained. These results allow for a quick and straightforward comparison between several batches of a specific CSNP, different coating approaches, and so forth. The presented XPS methodology requires a submonolayer distribution of CSNPs on a substrate.
Poly(tetrafluoroethylene)-poly(methyl methacrylate) and poly(tetrafluoroethylene)-polystyrene polymer CSNPs serve as model systems to demonstrate the applicability of the approach.
A variety of methods used to prepare nano-objects for surface analysis are described along with information about when they might be best applied. Intrinsic properties of NPs which complicate their characterization and need to be considered when planning for surface or other analyses of NPs are identified, including challenges associated with reproducible synthesis and functionalization of the particles as well as their dynamic nature. The relevant information about the sample preparation processes, along with analysis details and data that need to be added to the collection of material provenance information is identified. Examples of protocols that have been successfully used for preparation of nano-objects for surface analysis are included in an annex.