TY - JOUR A1 - Bennet, Francesca A1 - Opitz, R. A1 - Ghoreishi, N. A1 - Plate, K. A1 - Barnes, J.-P. A1 - Bellew, A. A1 - Bellu, A. A1 - Ceccone, G. A1 - de Vito, E. A1 - Delcorte, A. A1 - Franquet, A. A1 - Fumageli, F. A1 - Gilliland, D. A1 - Jungnickel, H. A1 - Lee, T.G. A1 - Poleunis, C. A1 - Rading, D. A1 - Shon, H.K. A1 - Spampinato, V. A1 - Son, J.G. A1 - Wang, F. A1 - Wang, Y.-C. A. A1 - Zhao, Y. A1 - Roloff, A. A1 - Tentschert, J. A1 - Radnik, Jörg T1 - VAMAS TWA2 interlaboratory comparison: Surface analysis of TiO2 nanoparticles using ToF-SIMS N2 - Due to the extremely high specific surface area of nanoparticles and corresponding potential for adsorption, the results of surface analysis can be highly dependent on the history of the particles, particularly regarding sample preparation and storage. The sample preparation method has, therefore, the potential to have a significant influence on the results. This report describes an interlaboratory comparison (ILC) with the aim of assessing which sample preparation methods for ToF-SIMS analysis of nanoparticles provided the most intra- and interlaboratory consistency and the least amount of sample contamination. The BAM reference material BAM-P110 (TiO2 nanoparticles with a mean Feret diameter of 19 nm) was used as a sample representing typical nanoparticles. A total of 11 participants returned ToF-SIMS data,in positive and (optionally) negative polarity, using sample preparation methods of “stick-and-go” as well as optionally “drop-dry” and “spin-coat.” The results showed that the largest sources of variation within the entire data set were caused by adventitious hydrocarbon contamination or insufficient sample coverage, with the spin-coating protocol applied in this ILC showing a tendency toward insufficient sample coverage; the sample preparation method or the participant had a lesser influence on results. KW - Secondary Ion Mass Spectrometry KW - VMAAS KW - Titania KW - Interlaboratory comparison KW - Reproducibility PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-582290 DO - https://doi.org/10.1116/6.0002814 SN - 0734-2101 VL - 41 IS - 5 SP - 053210-1 EP - 053210-13 PB - AIP (American Institute of Physics) AN - OPUS4-58229 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bennet, Francesca A1 - Müller, Anja A1 - Radnik, Jörg A1 - Hachenberger, Y. A1 - Jungnickel, H. A1 - Laue, P. A1 - Luch, A. A1 - Tentschert, J. T1 - Preparation of Nanoparticles for ToF-SIMS and XPS Analysis N2 - 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. KW - Titania nanoparticles KW - X-ray photoelectron spectroscopy KW - Secondary ion mass spectrometry KW - Surface chemisttry PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-520103 UR - https://www.jove.com/video/61758 DO - https://doi.org/10.3791/61758 VL - 163 SP - e61758 AN - OPUS4-52010 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Peters, R. A1 - Elbers, I. A1 - Undas, A. A1 - Sijtsma, E. A1 - Briffa, S. A1 - Carnell-Morris, P. A1 - Siupa, A. A1 - Yoon, T.-H. A1 - Burr, L. A1 - Schmid, D. A1 - Tentschert, J. A1 - Hachenberger, Y. A1 - Jungnickel, H. A1 - Luch, A. A1 - Meier, F. A1 - Kocic, J. A1 - Kim, J. A1 - Park, B. C. A1 - Hardy, B. A1 - Johnston, C. A1 - Jurkschat, K. A1 - Radnik, Jörg A1 - Hodoroaba, Vasile-Dan A1 - Lynch, I. A1 - Valsami-Jones, E. T1 - Benchmarking the ACEnano toolbox for characterisation of nanoparticle size and concentration by interlaboratory comparisons N2 - 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. KW - Nanomaterials KW - Benchmarking KW - Inter-laboratory comparison KW - ACEnano KW - Characterisation KW - Size KW - Concentration PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-531852 DO - https://doi.org/10.3390/molecules26175315 SN - 1420-3049 VL - 26 IS - 17 SP - 1 EP - 23 PB - MDPI CY - Basel AN - OPUS4-53185 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Radnik, Jörg A1 - Hodoroaba, Vasile-Dan A1 - Jungnickel, H. A1 - Tentschert, J. A1 - Luch, A. A1 - Sogne, V. A1 - Maier, F. A1 - Burr, L. A1 - Schmid, D. A1 - Yoon, T.-H. A1 - Petters, R. A1 - Briffa, S.M. A1 - Valsami-Jones, E. T1 - Automation and Standardization—A Coupled Approach Towards Reproducible Sample Preparation Protocols for Nanomaterial Analysis N2 - 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 au-tomation 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 de-veloped, 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. KW - Sample preparation KW - Automation KW - Nanomaterial analysis KW - Standardization PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543988 DO - https://doi.org/10.3390/molecules27030985 VL - 27 IS - 3 SP - 1 EP - 22 PB - MDPI AN - OPUS4-54398 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -