Chemische Charakterisierung und Spurenanalytik
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Eingeladener Vortrag
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Solvent-free sample preparation offers some advantages over solvent-based techniques, such as improved accuracy, reproducibility and sensitivity, for matrix-assisted laser desorption/ionization (MALDI) analysis. However, little or no information is available on the application of solvent-free techniques for the MALDI analysis of polymer blends. Solvent-free sample preparation by ball milling was applied with varying sample-to-matrix ratios for MALDI time-of-flight mass spectrometry analysis of various polymers, including polystyrenes, poly(methyl methacrylate)s and poly(ethylene glycol)s. The peak intensity ratios were compared with those obtained after using the conventional dried droplet sample preparation method. In addition, solvent-assisted milling was also applied to improve sample homogeneities.
Depending on the sample preparation method used, different peak intensity ratios were found, showing varying degrees of suppression of the signal intensities of higher mass polymers. Ball milling for up to 30 min was required to achieve constant intensity ratios indicating homogeneous mixtures. The use of wet-assisted grinding to improve the homogeneity of the blends was found to be disadvantageous as it caused partial degradation and mass-dependent segregation of the polymers in the vials.The results clearly show that solvent-free sample preparation must be carefully considered when applied to synthetic polymer blends, as it may cause additional problems with regard to homogeneity and stability of the blends.
A poly(L-lactide) with a trifluoroethyl ester end group and an average degree of polymerization (DP) of 50 was synthesized by ROP of L-lactide initiated with trifluoroethanol. Small-angle X-ray scattering (SAXS) in combination with differential scanning calorimetry (DSC) measurements revealed an average crystal thickness of 13 nm, corresponding to 45 repeat units. This suggests that most crystallites were formed by extended PLA chains, and both flat surfaces were covered by CF3 groups. The crystalline PLAs were annealed at 140 or 160 °C in the presence of two catalysts: tin(II) 2-ethylhexanoate, (SnOct2) or dibutyltin bis(pentafluorophenoxide) (BuSnPhF). The chemical reactions, such as polycondensation and cyclization, proceeded in the solid state and were monitored by matrix-assisted laser desorption/ionization time-offlight (MALDI TOF) mass spectrometry and gel permeation chromatography (GPC) measurements. Under optimal conditions a large fraction of linear chains was transformed into crystallites composed of extended cycles. Additionally, MALDI TOF MS analysis of GPC fractions from samples annealed for 28 or 42 days detected chain elongation of the linear species up to a factor of 20.
The usefulness of seven different Tin catalysts, Bismuth subsalicylate and Titan tetra(ethoxide) for the polycondensation of ethyl L-lactate (ELA) was examined at 150 °C/6 d. Dibutyltin bis(phenoxides) proved to be particularly effective. Despite the low reactivity of ELA, weight average molecular masses (Mw) up to 12 500 were found along with partial crystallization. Furthermore, polylactides (PLAs) of similar molecular masses were prepared via ELA-initiated ROPs of L-lactide by means of the four most effective polycondensation catalysts. The crystalline linear PLAs were annealed at 140 or 160 °C in the presence of these catalysts. The consequences of the transesterification reactions in the solid PLAs were studied by means of matrix-assisted laser desorption/ionization (MALDI TOF) mass spectrometry, gel permeation chromatography (GPC) and small-angle X-ray scattering (SAXS). The results indicate that polycondensation and formation of cycles proceed in the solid state via formation of loops on the surface of the crystallites. In summary, five different transesterification reactions are required to explain all results.
This contribution provides an overview of the BAMline synchrotron radiation beamline, which specializes in hard X-ray spectroscopy techniques for materials research. The BAMline offers X-ray absorption spectroscopy (XAS), x-ray fluorescence spectroscopy (XRF), and tomography to study materials' electronic structure, chemical composition, and structure. Key capabilities include standard and dispersive XAS for electronic structure, micro-XRF for elemental mapping, coded aperture imaging, and depth-resolved grazing exit XAS. The BAMline enables in situ characterization during materials synthesis and functions for energy, catalysis, corrosion, biology, and cultural heritage applications.
Ongoing developments like the implementation of machine learning techniques for experiment optimization and data analysis will be discussed. For instance, Bayesian optimization is being used to improve beamline alignment and scanning. An outlook to the future, where the BAMline will continue pioneering dynamic and multi-scale characterization, aided by advanced data science methods, to provide unique insights into materials research, will be given.
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.
Enhancing efficiency at bamline: employing data science and machine learning for x-ray research
(2023)
This talk discusses how data science and machine learning techniques are being applied at the BAM Federal Institute for Materials Research and Testing to enhance efficiency and automation at the BAMLine synchrotron facility. The methods presented include Gaussian processes and Bayesian optimization for beamline adjustment and optimization of X-ray measurements. These statistical techniques allow automated alignment of beamline components and active learning scanning to reduce measurement time.
Additional machine learning methods covered are neural networks for quantification of X-ray fluorescence (XRF) data and decoding coded apertures.
Mechanochemistry provides polymorphs that are difficult to obtain by conventional solution-based methods. Based on the nicotinamide and pimelic acid cocrystal, we demonstrated that the ball size, frequency, and temperature are essential parameters. Our results indicate that fine-tuning the energy input during a mechanochemical reaction can provide control over polymorphism.
Quantitative Analysis and 2D/3D Elemental Imaging of Cocoa Beans Using X‑ray Fluorescence Techniques
(2023)
As an important raw material for the confectionery industry, the cocoa bean (Theobroma cacao L.) has to meet certain legal requirements in terms of food safety and maximum contaminant levels in order to enter the cocoa market. Understanding the enrichment and distribution of essential minerals but also toxic metals is of utmost importance for improving the nutritional quality of this economically important raw food material. We present three X-ray fluorescence (XRF) techniques for elemental bio-imaging of intact cocoa beans and one additional XRF technique for quantitative analysis of cocoa pellets. The interrelation of all the methods presented gives a detailed picture of the content and 3D-resolved distribution of elements in complete cocoa beans for the first time.
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.