ABSTRACT
Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing. In this overview, some solutions for techniques widely used in nano-analytics to overcome this problem are discussed. Two examples of sample preparation optimization by automation are presented, which demonstrate that this approach is leading to increased analytical confidence. Our first example is motivated by the need to exclude human bias and focuses on the development of automation in sample introduction. To this end, a robotic system has been developed, which can prepare stable and homogeneous nanomaterial suspensions amenable to a variety of well-established analytical methods, such as dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), field-flow fractionation (FFF) or single-particle inductively coupled mass spectrometry (sp-ICP-MS). Our second example addresses biological samples, such as cells exposed to nanomaterials, which are still challenging for reliable analysis. An air-liquid interface has been developed for the exposure of biological samples to nanomaterial-containing aerosols. The system exposes transmission electron microscopy (TEM) grids under reproducible conditions, whilst also allowing characterization of aerosol composition with mass spectrometry. Such an approach enables correlative measurements combining biological with physicochemical analysis. These case studies demonstrate that standardization and automation of sample preparation setups, combined with appropriate measurement processes and data reduction are crucial steps towards more reliable and reproducible data.
ABSTRACT
Particle size is arguably the most important physico-chemical parameter associated with the notion of a nanoparticle. Precise knowledge of the size and size distribution of nanoparticles is of utmost importance for various applications. The size range is also important, as it defines the most "active" component of a nanoparticle dose. Asymmetrical Flow Field-Flow Fractionation (AF4) is a powerful technique for sizing of particles in suspension in the size range of approximately 1-1000 nm. There are several ways to derive size information from an AF4 experiment. Besides coupling AF4 online with size-sensitive detectors based on the principles of Multi-Angle Light Scattering or Dynamic Light Scattering, there is also the possibility to correlate the size of a sample with its retention time using a well-established theoretical approach (FFF theory) or by comparing it with the retention times of well-defined particle size standards (external size calibration). We here describe the development and in-house validation of a standard operating procedure (SOP) for sizing of an unknown gold nanoparticle sample by AF4 coupled with UV-vis detection using external size calibration with gold nanoparticle standards in the size range of 20-100 nm. This procedure provides a detailed description of the developed workflow including sample preparation, AF4 instrument setup and qualification, AF4 method development and fractionation of the unknown gold nanoparticle sample, as well as the correlation of the obtained results with the established external size calibration. The SOP described here was eventually successfully validated in the frame of an interlaboratory comparison study highlighting the excellent robustness and reliability of AF4 for sizing of nanoparticulate samples in suspension.
Subject(s)
Fractionation, Field Flow/methods , Gold/chemistry , Metal Nanoparticles/chemistry , Particle Size , Suspensions/chemistry , Calibration , Dynamic Light Scattering , Hydrodynamics , Reference Standards , Reproducibility of Results , Solutions , Static Electricity , Time FactorsABSTRACT
Nanoplastic pollution is an emerging environmental concern, but current analytical approaches are facing limitations in this size range. However, the coupling of nanoparticle separation with chemical characterization bears potential to close this gap. Here, we realize the hyphenation of particle separation/characterization (field-flow fractionation (FFF), UV, and multiangle light scattering) with subsequent chemical identification by online Raman microspectroscopy (RM). The problem of low Raman scattering was overcome by trapping particles with 2D optical tweezers. This setup enabled RM to identify particles of different materials (polymers and inorganic) in the size range from 200 nm to 5 µm, with concentrations in the order of 1 mg/L (109 particles L-1). The hyphenation was realized for asymmetric flow FFF and centrifugal FFF, which separate particles on the basis of different properties. This technique shows potential for application in nanoplastic analysis, as well as many other fields of nanomaterial characterization.
ABSTRACT
The dimensional characterization of insoluble, inorganic particles, such as zinc oxide ZnO, dispersed in cosmetic or pharmaceutical formulations, is of great interest considering the current need of declaring the possible presence of nanomaterials on the label of commercial products. This work compares the separation abilities of Centrifugal- and Asymmetrical Flow Field-Flow Fractionation techniques (CF3 and AF4, respectively), equipped with UV-vis, MALS and DLS detectors, in size sorting ZnO particles, both as pristine powders and after their extraction from cosmetic matrices. ZnO particles, bare and superficially modified with triethoxycaprylyl silane, were used as test materials. To identify the most suitable procedure necessary to isolate the ZnO particles from the cosmetic matrix, two O/W and two W/O emulsions were formulated on purpose. The suspensions, containing the extracted particles ZnO, were separated by both Field-Flow Fractionation (FFF) techniques to establish a common analysis protocol, applicable for the analysis of ZnO particles extracted from three commercial products, sold in Europe for the baby skin care. Key aspects of this study were the selection of an appropriate dispersing agent enabling the particles to stay in stable suspensions (>24h)and the use of multiple detectors (UV-vis, MALS and DLS) coupled on-line with the FFF channels, to determine the particle dimensions without using the retention parameters. Between the two FFF techniques, CF3 revealed to be the most robust one, able to sort all suspensions created in this work.
