6 Materialchemie
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The mechanism of action of zirconium permanent modifiers on graphite surfaces was investigated in order to understand its influence on the analytical signal in atomic and molecular absorption spectrometry (AAS/MAS). For this, the molecule formation of CaF was studied, which is used for the indirect analytical determination of fluorine in high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS). The kinetics of this reaction was established by monitoring its molecular spectrum at different atomisation temperatures. An Arrhenius plot showed a pseudo-first order reaction with respect to fluorine (n = 1). An intermediate state was isolated, and its structure was elucidated by spectroscopic methods: scanning electron microscopy with energy dispersive X-ray spectroscopy (SEMEDX), X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XANES and EXAFS), and Raman microspectroscopy. We propose here a mechanism, where ZrO2 acts as a heterogeneous catalyst: after a pyrolytic step, an intermediate state of ZrO(OCaF) is activated, and at higher temperatures, CaF(g) is released from the zirconium-coated graphite surface. No evidence of the formation of zirconium carbide was found. Consequently, as the CaF formation is catalysed by a heterogeneous catalyst, surface modifications with ZrO2 nanoparticles and ZrO xerogels were investigated in order to increase the surface area. Their influence was evaluated in the molecule formation of CaF, CaCl, CaBr, and CaI. Graphite furnace modification with zirconium oxide nanoparticles proves to be the best choice for fluorine analysis with a signal enhancement of more than eleven times with respect a non-coated graphite furnace. However, the influence of zirconium modifications in the analytical signals of Cl, and I is lower than the F signals or even negative in case of the Br. Understanding zirconium modifiers as heterogeneous catalysts offers a new perspective to AAS and MAS, and reveals the potential of surface analytical methods for development of improved permanent modifiers and graphite furnace coatings.
We discuss the role of the volume specific surface area (VSSA) as determined from the specific surface area measured by the (extended) Brunauer-Emmett-Teller (BET) technique, in the identification process of powdered nano- and non-nanomaterials in line with the EU definition of nanomaterial. Results obtained in the NanoDefine project demonstrate that under appropriate conditions, VSSA can be used as proxy to the number-based particle size distribution. The extent of agreement between nano/non-nano classification by electron microscopy (EM) and classification by VSSA is investigated systematically on a large set of diverse particulate substances, representing most of the cases expected in regulatory practice. Thus, parameters such as particle shape, size polydispersity/multi-modality, and particle (inner or coating) porosity are evaluated. Based on these results, we derive a tiered screening strategy for powders, involving the use of VSSA for the purpose of implementing the definition of nanomaterial, and recommend it for inclusion in a technical guidance for the implementation of the definition.
The progress in activities on Microbeam Analysis under VAMAS/TWA 37 is reviewed. Particularly the liaison with the new projects within the ISO technical committee TC 202 is presented and discussed with respect to the possibility of identifying and launching related VAMAS projects. Need of more promotion for the engagement of more participants from industry and academia at national, European and international level is highlighted. Also, the competition with the other technical working areas (on 'nano' or materials-related) is critically discussed. Further, a short overview of the VAMAS areas of activities is given where Germany is involved.
Following points are presented and discussed: i) nPSize as an EMPIR project on the nanoparticle size and shape distribution of (more) complex particles including sample preparation and machine learning approaches; ii) parallel development of ISO 21363 (PSSD by TEM), ISO 19749 (PSSD by SEM), ISO 22292 (3D TEM), ISO 52408 (NP Prep for AFM and EM), iii) VAMAS and pre-standardisation, TWA 34 „Nanoparticle Populations“ with two nPSize ILC projects P15 & P16 – results to be published and integrated in ISO 21363 (PSSD by TEM); iv) Remaining challenges: platelets, 2D materials (TiO2 and GR2M); v) Reference data sets as part of a complete Characterisation Workflow.
Die Bestimmung der Nanopartikelgrößen- und -formverteilung nach OECD TG 125 mit der Transmission and Scanning Electron Microscopy (SEM/TEM) wird punktuell vorgestellt:
- Generelles Messprinzip
- Beispiele
- Korrelative Mikroskopie
- Welchen Durchmesser misst die Methode?
- Welche Partikel kann diese Methode messen?
- Welche Informationen kann diese Methode liefern?
- Wo stößt die Methode an ihre Grenzen?
- Implementierung und Datenauswertung,
- Reporting.
Anschließend wurde eine Q&A-Session für die Imaging-Methoden organisiert.
Metal nanoparticles have a substantial impact across diferent felds of science, such as photochemistry, energy conversion, and medicine. Among the commonly used nanoparticles, silver nanoparticles are of special interest due to their antibacterial properties and applications in sensing and catalysis. However, many of the methods used to synthesize silver nanoparticles often do not result in well-defned products, the main obstacles being high polydispersity or a lack of particle size tunability. We describe an automated approach to on-demand synthesis of adjustable particles with mean radii of 3 and 5 nm using the polyol route. The polyol process is a promising route for silver nanoparticles e.g., to be used as reference materials. We characterised the as-synthesized nanoparticles using small-angle X-ray scattering, dynamic light scattering and further methods, showing that automated synthesis can yield colloids with reproducible and tuneable properties.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.