Chemische Charakterisierung und Spurenanalytik
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Analytical Sciences has developed from Ostwald’s “unentbehrlichen Dienstmagd” to a chemical discipline at the core of many of today’s fundamental and applied scientific problems and innovations. An atomic or molecular understanding of basic processes in chemistry, soft matter physics, materials and life science is enabled only through new analytical methods and instrumentation. Similar observations can be found for pressing sociopolitical conflicts of the future: A rational discussion of global climate change or new energy sources is only possible with reliable analytical results. Progress in Analytical Sciences is only possible if the underlying interdisciplinary character is acknowledged and valued. The talk will illustrate the scope of modern Analytical Science through examples from process analysis relevant to modern process intensification and industry 4.0 to bioanalysis and the use of synchrotron radiation to elucidate fundamental reactions materials.
The common characterization and identification of pollen is a time-consuming task that mainly relies on microscopic determination of the genus-specific pollen morphology. A variety of spectroscopic and spectrometric approaches have been proposed to develop a fast and reliable pollen identification using specific molecular information. Amongst them, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows a high potential for the successful investigation of such complex biological samples. Based on optimized MALDI sample preparation using conductive carbon tape, the application of multivariate statistics (e.g. principal components analysis, PCA) yields an enormous improvement concerning taxonomic classification of pollen species compared to common microscopic techniques.
Since multivariate evaluation of the recorded mass spectra is of vital importance for classification, it’s helpful to implement the applied sequence of standard Matlab functions into a graphical user interface (GUI). In this presentation, a stand-alone application (GUI) is shown, which provides multiple functions to perform fast multivariate analysis on multiple datasets. The use of a GUI enables a first overview on the measured dataset, conducts spectral pretreatment and can give classification information based on HCA and PCA evaluation. Moreover, it can be used to improve fast spectral classification and supports the development of a simple routine method to identify pollen based on mass spectrometry.
Increasing numbers of implant revisions are a current clinical issue. Interactions of the endoprosthesis biomaterial with the body affect implantation time by wear processes, i.e. corrosion and abrasion. Previously, cobalt-chrome implants were shown to cause high levels of cobalt ions being deposited in the bone matrix. To determine a poten- tial functional role of these ions on bone homeostasis, we have developed a non-destructive dual analysis of highly sensitive elemental analysis by synchrotron XRF directly in undecalcified histological bone thin sections (4 μm). In this study, samples from 28 bone samples from hip endoprosthesis carriers (Surface Replacement Arthroplasty, metal-on-metal bearing) with an implant lifetime of 17–1750 days were used. Results were compared to age- matched control specimens. The histological analysis identified areas of bone cell activity and assigned them for XRF measurements. Co-Cr wear particles were identified in the bone marrow. In addition, Co ions were highly enriched in the mineralized bone matrix. The cobalt deposits were not homogeneously distributed, and areas of high signal intensity were identified. Co was distinctly deposited in the newly formed osteoid layer, but also within deeper layers of the bone matrix, whereby the Co concentration increased with higher degrees of bone matrix mineralization. In the current study, we determined cobalt accumulations in the bone matrix and showed for the first time via synchrotron XRF with a high spatial resolution direct on histological slides, that cobalt deposits in the mineralized bone matrix in a mineral-specific way that is dependent upon the implant lifetime.
The structure and composition of ancient gold objects retain information about their long history of manufacture, from the exploitation of the ore to the finishing touches, as well as evidence of their use, deposition, and degradation. By developing an efficient analytical strategy, it is possible to retrieve that information. This chapter sets the necessary foundation 131to explore fully the analytical results presented in the following chapters of this volume. The techniques employed in the analyses of the Egyptian jewellery are described and the analytical parameters provided. For more established techniques, only brief introductions are presented, while more recent developments are presented in greater detail.
Various applications for artificial intelligence in the context of spectroscopy will be presented. in particular, examples from bamline will be featured. After a short introduction to synchrotron radiation, artificial intelligence algorithms for the quantification of X-ray fluorescence measurement are discussed. In the second example, information retrieval by natural language processing is reviewed. As a last example the reconstruction of measurements with the X-ray color camera and coded apertures is presented.
Synchrotron radiation X-ray fluorescence spectroscopy, in conjunction with atomic absorption and Raman spectroscopy, was used to analyze a set of top brand tattoo inks to investigate the presence of toxic elements and hazardous substances. The Cr, Cu, and Pb contents were found to be above the maximum allowed levels established by the Council of Europe through the resolution ResAP(2008)1 on requirements and criteria for the safety of tattoos and permanent makeup. Raman analysis has revealed the presence of a set of prohibited substances mentioned in ResAP(2008)1, among which are the pigments Blue 15, Green 7, and Violet 23. Other pigments that were identified in white, black, red, and yellow inks are the Pigment White 6, Carbon Black, Pigment Red 8, and a diazo yellow, respectively. The present results show the importance of regulating tattoo ink composition.
Ball mass is an important parameter that is known to have an influence on the outcome of a mechanochemical reaction induced by ball-milling. A standard way of modifying the ball mass is to change the size of the ball made of the same material. In this case, however, a change in mass is accompanied by a simulatneous change in the ball size. It is therefore not possible to disentangle the effects of mass and Surface area in these cases. In the present work we report the results of experiments with specially designed and manufactured balls in which (1) milling ball mass is held constant, but their size differs, and (2) the ball mass is altered, with the diameter of the milling ball being held constant. Using the cocrystallisation of theophylline + nicotinamide as a case study it was found that both diameter and ball mass play crucial roles in determining the rate of a mechanochemical reaction. For comparison, we have also used milling balls with the same size (different mass), and others with the same mass (different size) made of different materials, as would be “traditional”. It was found that, despite having the same size, the lightest milling ball (nylon) was the most efficient in initiating the co-crystallisation, presumably due to the sorption of EtOH. Hence, the results of this manuscript also demonstrate how milling ball material can in fact be the most influential parameter, and potentially counterintuitive to classical mechanics.
With increasing demand and environmental concerns, researchers are exploring new materials that can perform as well or better than traditional materials while reducing environmental impact. The BAMline, a real-life sample materials research beamline, provides unique insights into materials’ electronic and chemical structure at different time and length scales. The beamline specializes in x-ray absorption spectroscopy, x-ray fluorescence spectroscopy, and tomography experiments. This enables real-time optimization of material properties and performance for various applications, such as energy transfer, energy storage, catalysis, and corrosion resistance. This paper gives an overview of the analytical methods and sample environments of the BAMline, which cover non-destructive testing experiments in materials science, chemistry, biology, medicine, and cultural heritage. We also present our own synthesis methods, processes, and equipment developed specifically for the BAMline, and we give examples of synthesized materials and their potential applications. Finally, this article discusses the future perspectives of the BAMline and its potential for further advances in sustainable materials research.
A series of new Ba-based coordination polymers (CPs) were mechanochemically synthesized by milling Ba-hydroxide samples with perfluorinated and fluorine-free benzene-dicarboxylic acids, including tetrafluoroisophthalic acid (H2mBDC-F4), tetrafluorophthalic acid (H2oBDC-F4), isophthalic acid (H2mBDC) and phthalic acid (H2oBDC). The new fluorinated CPs: [Ba(mBDC-F4)$0.5H2O] (1) and [Ba(oBDC-F4)·1.5H2O] (2) are compared to their nonfluorinated counterparts: [Ba(mBDC)·2.5H2O] (3), and [Ba(oBDC)·1H2O] (4). These materials are thoroughly characterized using powder X-ray diffraction. The products obtained by milling are all hydrated but vary in their water contents. Compositions and local structures are investigated by elemental analysis, thermal analysis, MAS NMR and attenuated total reflectioninfrared spectroscopy. These materials exhibit high thermal stabilities but small surface areas that remain unchanged even after thermal treatments.
In this talk an overview about artificial intelligence/machine learning applications @BAMline is given. In the first part, the use of neural networks for the quantification of XRF measurements and the decoding of coded-aperture measurements are shown. Then it is shown how Gaussian processes and Bayesian statistics can be used to achieve an optimal alignment of the set-up and in general for optimization of measurements.