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Herein, we provide a "systems architecture"-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (Methodology Optimization for UltrafineStructure Exploration). The MOUSE project provides scattering information on a wide variety of samples, with traceable dimensions for both the scattering vector (q) and the absolute scattering cross-section (I). The measurable scattering vector-range of 0.012≤ q (nm-1) ≤ 92, allows information across a hierarchy of structures with dimensions ranging from ca. 0.1 to 400 nm. In addition to details that comprise the MOUSE project, such as the organisation and traceable aspects, several representative examples are provided to demonstrate its flexibility. These include measurements on alumina membranes, the tobacco mosaic virus, and dual-source information that overcomes fluorescence limitations on ZIF-8 and iron-oxide-containing carbon catalyst materials.
This chapter provides an introduction in secondary ion mass spectrometry as one of the leading surface chemical analysis and imaging techniques with molecular specificity in the field of material sciences. The physical basics of the technique are explained along with a description of the typical instrumental setups and their modes of operation. The application paragraph specifically focuses on nanoparticle analysis by SIMS in terms of surface spectrometry, imaging, analysis in organic and complex media, and depth profiling.
A review of the existing literature is provided, and selected studies are showcased. Limitations and pitfalls as well as current technical developments of SIMS application in nanoparticle surface chemical analysis are equally discussed.
Fluorescent particles like nm- and m-sized polymeric beads doped or labeled with different types of fluorophores and nanocrystalline systems like quantum dots and upconversion phosphors emitting in the visible (vis), near-infrared (NIR), and IR (infrared) region are of increasing importance as fluorescent reporters for bioanalysis and medical diagnostics. The assessment and comparison of material performance and the development of rational design strategies for improved systems requires suitable spectroscopic tools for the determination of signal-relevant optical properties and analytical tools for the determination of the number of surface groups, ligands, biomolecules and /or fluorophores per bead. In this respect, suitable spectroscopic tools for the characterization of the optical properties of such materials like photoluminescence quantum yields and brightness values and the determination of their surface chemistry are introduced. This includes integrating sphere setups for absolute measurements of fluorescence quantum yields of liquid and solid, transparent and scattering materials in the wavelength region of 350 nm to 1600 nm at varying excitation power densities for the study of multi-photon processes and simple optical assays, validated by comparison with established analytical techniques relying on different detection principles. Here, different examples for the optical and analytical characterization of different types of nanoscale reporters are presented.
There is an increasing interest in optical reporters like semiconductor quantum dots and upconversion nanocrystals with emission > 800 nm for bioanalysis, medical diagnostics, and safety barcodes. Prerequisites for the comparison of material performance, the mechanistic understanding of nonradiative decay channels, and the rational design of new nanomaterials with improved properties are reliable fluorescence measurements and validated methods for the assessment of their surface chemistry. The latter is of special relevance for nanocrystalline emitters, where surface states and the accessibility of emissive states by quenchers largely control accomplishable photoluminescence quantum yields and hence, signal sizes and detection sensitivities from the reporter side. Here, we present the design of integrating sphere setups for the excitation power density-dependent absolute measurement of emission spectra and photoluminescence quantum yields in the wavelength region of 350 to 1600 nm and results from spectroscopic studies of semiconductor quantum dots and upconversion nanocrystals of different size and surface chemistries in various environments. Subsequently, examples for simple approaches to surface group and ligand analysis are presented.
Nanoforms with at least one dimension below 100 nm have an important part to play in more and more areas of our daily life. Therefore, risk assessment of these materials is becoming increasingly important. In this context, the European Chemical Agency (ECHA) considered eleven physico-chemical properties as relevant, of which the following six are essential for the registration: chemical composition, crystallinity, particle size, particle shape, surface chemistry and specific surface area. Four of these priority properties can be obtained with electron microscopy and surface analytics like XPS and ToF-SIMS. The reliability of this data must be ensured, especially for their use for grouping and read across approaches. On the other hand, the “reproducibility” crisis has revealed major shortcomings in the reliability of published data.
In a case study, we show how the quality of the data can be ensured by using existing standards and protocols of each step in the workflow of sample characterization. As exemplary samples, two Al-coated TiO2 samples as nanopowders were selected from the JRC repository, capped either with a hydrophilic or a hydrophobic organic ultrathin shell. SEM results provided the size and shape of the nanoparticles, a first overview about the composition was obtained with EDS. XPS and ToF-SIMS supplied the surface chemistry, especially information about the shell and the coating of the particles. Standards and protocols of all steps of the analytical workflow including preparation and data reduction are discussed regarding reliable and reproducible data. Additionally, uncertainties for the different steps are specified.
Only such a detailed description of all these factors allows a comprehensive physico-chemical characterization of the nanoparticles with understanding of their potential risk assessment.
The European legislation has responded to the wide use of nanomaterials in our daily life and defined the term “nanoform” in the Annexes to the REACH (Registration, Evaluation, Authorization of Chemicals) Regulation. Now specific information of the nanomaterials is required from the companies when registering the appropriate materials in a dossier.
In the context of REACH eleven physicochemical properties were considered as relevant, of which the following six are essential for registration of nanoforms (priority properties): chemical composition, crystallinity, particle size, particle shape, chemical nature of the surface (“surface chemistry”), and specific surface area (SSA). A key role is the reliable, reproduceable and traceable character of the data of these priority properties.
In this context, we want to discuss which ‘analytical’ information is exactly required to fulfill these conditions. Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) and X-ray Photoelectron Spectroscopy (XPS) were chosen as the most popular surface analytical methods. Both methods allow a detailed understanding of the surface chemistry with an information depth below ten nanometers. As a rather bulk method for the analysis of nanoforms, Electron Probe Microanalysis (EPMA) in the version with energy dispersive X-ray spectroscopy (EDS) is considered for the quick identification of the main chemical elements present in the sample. Furthermore, Scanning Electron Microscopy (SEM) results are discussed which provide results on particle size and shape. Thus, four of the six priority properties can be obtained with these methods.
ACEnano is an EU-funded project which aims at developing, optimising and validating methods for the detection and characterisation of nanomaterials (NMs) in increasingly complex matrices to improve confidence in the results and support their use in regulation. Within this project, several interlaboratory comparisons (ILCs) for the determination of particle size and concentration have been organised to benchmark existing analytical methods. In this paper the results of a number of these ILCs for the characterisation of NMs are presented and discussed. The results of the analyses of pristine well-defined particles such as 60 nm Au NMs in a simple aqueous suspension showed that laboratories are well capable of determining the sizes of these particles. The analysis of particles in complex matrices or formulations such as consumer products resulted in larger variations in particle sizes within technologies and clear differences in capability between techniques. Sunscreen lotion sample analysis by laboratories using spICP-MS and TEM/SEM identified and confirmed the TiO2 particles as being nanoscale and compliant with the EU definition of an NM for regulatory purposes. In a toothpaste sample orthogonal results by PTA, spICP-MS and TEM/SEM agreed and stated the TiO2 particles as not fitting the EU definition of an NM. In general, from the results of these ILCs we conclude that laboratories are well capable of determining particle sizes of NM, even in fairly complex formulations.
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.