6.5 Synthese und Streuverfahren nanostrukturierter Materialien
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Small-angle scattering (SAS) offers a reliable route to characterize the nanostructure of large amounts of material with a minimum of tedium, for example, easily extracting size distributions and volume fractions. There are a variety of analysis programs available while the evaluation of SAS measurements has been dominated by the classical curve fitting approach. SASfit represents such a classical curve fitting toolbox: it is one of the mature programs for SAS data analysis and has been available and used for many years. The latest developments will be presented and a scattering function of a mass fractal model of branched polymers in solution is provided as an example for implementing a plug-in.
Alternatively to classical curve fitting, part two presents the latest developments of the user-friendly open-source Monte Carlo regression package McSAS. The form-free Monte Carlo nature of McSAS means, it is not necessary to provide further restrictions on the mathematical form of the parameter distribution: without prior knowledge, McSAS is able to extract complex multimodal or odd- shaped parameter distributions from SAS data. The headless mode is presented by an example of operation within interactive programming environments such as a Jupyter notebook.
The formation and alignment of gel fibres in alkanes (solvents) was investigated. The gel fibres consist of small amphiphilic molecules containing a C60 molecule and a small ligand chain. Under the right conditions, these self-assemble in core-shell micelles, which themselves pack into micron-sized fibre-like structures. These can be aligned using a strong magnetic field, as investigated using SANS with a 17T superconducting magnet at a range of field strengths.
This poster deals with improvements and characteriztion of small-angle scattering limitations, by looking at the trifecta of Data collection and uncertainty propagation, data analysis methodologies, and real-world tests. It is found that - with appropriate care and instrumentation - accuracies of 1% on mean nanomaterial sizes, and 10% on the size distribution width as well as the volume fraction can be achieved.