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Im Vortrag werden das Messprinzip einer Photozentrifuge erläutert und die Anforderungen der zugrundeliegenden Normen diskutiert. Die praktische Durchführung der Messung und insbesondere auch die vorbereitenden Arbeiten, sowie die Auswertung der Rohdaten bilden den Schwerpunkt des Vortrags. Gezeigt werden auch die Validierung sowie ein Beispiel zur regelmäßigen Verifizierung des Verfahrens. Nach Anwendungsbeispielen und Vergleichen zu Ergebnissen mit anderen Messverfahren, wird das Verfahren in einer Zusammenfassung bewertet.
Foroutan, F. ; Kyffin, B. A. ; Nikolaou, A. ; Merino-Gutierrez, J. ; Abrahams, I. ; Kanwal, N. ; Knowles, J. C. ; Smith, A. J. ; Smales, Glen Jacob ; Carta, D.
Mesoporous glasses are a promising class of bioresorbable biomaterials characterized by high surface area and extended porosity in the range of 2 to 50 nm. These peculiar properties make them ideal materials for the controlled release of therapeutic ions and molecules. Whilst mesoporous silicate-based glasses (MSG) have been widely investigated, much less work has been done on mesoporous phosphate-based glasses (MPG). In the present study, MPG in the P2O5–CaO–Na2O system, undoped and doped with 1, 3, and 5 mol% of Cu ions were synthesized via a combination of the sol–gel method and supramolecular templating. The non-ionic triblock copolymer Pluronic P123 was used as a templating agent. The porous structure was studied via a combination of Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), and N2 adsorption–desorption analysis at 77 K. The structure of the phosphate network was investigated via solid state 31P Magic Angle Spinning Nuclear Magnetic Resonance (31P MAS-NMR) and Fourier Transform Infrared (FTIR) spectroscopy. Degradation studies, performed in water via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), showed that phosphates, Ca2+, Na+ and Cu ions are released in a controlled manner over a 7 days period. The controlled release of Cu, proportional to the copper loading, imbues antibacterial properties to MPG. A significant statistical reduction of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacterial viability was observed over a 3 days period. E. coli appeared to be more resistant than S. aureus to the antibacterial effect of copper. This study shows that copper doped MPG have great potential as bioresorbable materials for controlled delivery of antibacterial ions.
This talk introduces the expanded view that comes from wide-range X-ray scattering investigations.
Compared to X-ray diffraction studies alone, the additional angular range of this technique provides information on the larger structural dimensions present in your samples. This allows for the extraction of information on the size and size distribution of nanostructural components, such as nanoparticles, nanovoids, and any other structure exhibiting an electron density contrast.
The talk introduces the technique, the MOUSE instrument used for these investigations, and provides several real-world examples of its uses. The audience is invited to choose which examples captures their interest from a range of options, in the latter segment of the talk.
Laser-induced Periodic Surface Structures (LIPSS, ripples) are a universal phenomenon and can be generated in a contactless, single-step process on almost any type of solid upon irradiation with intense laser pulses. They represent a (quasi-)periodic modulation of the surface topography in the form of a linear grating and are typically formed in a “self-ordered” way in the focus of a laser beam. Thus, they are often accompanying laser material processing applications. The structural sizes of LIPSS typically range from several micrometers down to less than 100 nanometers – far beyond the optical diffraction limit – while their orientations exhibit a clear correlation with the local polarization direction of the laser radiation.
From a theoretical point of view, a controversial debate has emerged during the last decades, whether LIPSS originate from electromagnetic effects (seeded already during the laser irradiation) – or whether they emerge from matter-reorganization processes (distinctly after the laser irradiation). From a practical point of view, however, LIPSS represent a simple and robust way for the nanostructuring of solids that allows creating a wide range of different surface functionalities featuring applications in optics, tribology, medicine, energy technologies, etc.
This presentation reviews the currently existent theories of LIPSS. A focus is laid on the historic development of the fundamental ideas behind the LIPSS, their corresponding mathematical descriptions and numerical implementations, along with a comparison and critical assessment of the different approaches.
Fourth generation light sources, namely short wavelength, short pulse free electron lasers (FELs) are offering new and fascinating possibilities to resolve laser-induced structure formation at surfaces on the sub-micrometer to nanometer length scale and in temporal regimes ranging from picoseconds to several nanoseconds with sub-picosecond resolution. This unique spatio-temporal resolution allows to reveal early signatures of coherent/plasmonic electromagnetic scattering effects followed by the excitation of hydrodynamic capillary waves – providing new insights to the above-mentioned debate.
Finally, some unsolved scientific problems related to LIPSS are identified and the pending technological limitations are discussed. While the currently available laser and scanner technology already allows large area surface processing with rates at the m2/min level, industrial applications of LIPSS are sometimes limited by the complex interplay between the nanoscale surface topography and the specific surface chemistry. This typically manifests in difficulties to control the processing of LIPSS and in limitations to ensure the long-term stability of the created surface functions. Strategies for overcoming such limitations are outlined.
McSAS3
(2023)
McSAS3 is a refactored version of the original McSAS (see DOI 10.1107/S1600576715007347). This software fits scattering patterns to obtain size distributions without assumptions on the size distribution form. The refactored version has some neat features:
- Multiprocessing is included, spread out over as many cores as number of repetitions!
- Full state of the optimization is stored in an organized HDF5 state file.
- Histogramming is separate from optimization and a result can be re-histogrammed as many times as desired.
- SasModels allow a wide range of models to be used
- If SasModels does not work (e.g. because of gcc compiler issues on Windows or Mac), an internal sphere model is supplied
- Simulated data of the scattering of a special shape can also be used as a McSAS fitting model. Your models are infinite!
- 2D fitting also works.
Continuing progress in the field of X-ray scattering methods empowers scientists with new possibilities to capture the most important piece of information about the structure of the sample - its 3D electron density.
Although the first methods appeared almost a century ago, recovering the density structure of a sample is still very problematic. Most avail-able imaging techniques transform a 3D electron density of a realspace structure into the 2D Fourier Transform of the intensity of scattered waves in the reciprocal space. This process causes a loss of information.
Firstly, instead of a 3D sample, a 2D image is created, and secondly, the phase information of the scattered waves is lost. The latter is known as the ”phase problem” and poses a serious obstacle on a way to recover a 3D electron density. In this work, we draw attention to the problem of forward and inverse Small Angle X-Ray Scattering. In the first, forward, part, we rethink the existing pipelines to computationally simulate such scattering experiments. Although there are efficient implementations of fast Fourier transformation, they often have some drawbacks. For instance, to calculate a 3D fast Fourier transform it is required to place its density in the RAM. For high-resolution structures of size > 1024 3 , this becomes very problematic, as the whole density structure requires more than 16 GB of memory.
CUDA solution allows for a very fast and parallelizable implementation of high-resolution data on hundreds of last-generation machines.
Such computations are very pricy and inaccessible for most scientists.
To bypass this limitation, we propose a solution for a split-up 3D fast Fourier transform, which is implemented as a sequence of 2D and 1D operations. We compare our implementation on the simulated 3D shapes and show the result of a proof-of-concept on 4096 3 Metallorganic framework density structure. In the second, inverse problem, we train an invertible neural network, that given scattering data can predict the shape and its parameters. The architecture is built such, that the inverse problem is learned together with the forward process - the Fourier Transformation. We achieved very good results with this architecture, nonetheless, further testing is required, as the current training set only encompasses three simple shapes: sphere, hard sphere and cylinder.
All code to reproduce and analyze the results is available at https: //github.com/sofyalaski/SAXS-simulations.
This is a remote presentation I gave at the 2022 Small-angle Scattering conference in Campinas, Brazil. The video has been obtained from the conference organisers with their explicit permission for use on YouTube. I've tried to spruce up the audio from the remote recording the best I could.
The conference abstract for this talk was:
"How much do we, the small-angle scatterers, influence the results of an investigation? What uncertainty do we add by our human diversity in thoughts and approaches, and is this significant compared to the uncertainty from the instrumental measurement factors?
After our previous Round Robin on data collection, we know that many laboratories can collect reasonably consistent small-angle scattering data on easy samples[1]. To investigate the next, human component, we compiled four existing datasets from globular (roughly spherical) scatterers, each exhibiting a common complication, and asked the participants to apply their usual methods and toolset to the quantification of the results (https://lookingatnothing.com/index.ph....
Accompanying the datasets was a modicum of accompanying information to help with the interpretation of the data, similar to what we normally receive from our collaborators. More than 30 participants reported back with volume fractions, mean sizes and size distribution widths of the particle populations in the samples, as well as information on their self-assessed level of experience and years in the field.
While the Round Robin is still underway (until the 25th of April, 2022), the initial results already show significant spread in the results. Some of these are due to the variety in interpretation of the meaning of the requested parameters, as well as simple human errors, both of which are easy to correct for. Nevertheless, even after correcting for these differences in understanding, a significant spread remains. This highlights an urgent challenge to our community: how can we better help ourselves and our colleagues obtain more reliable results, how could we take the human factor out of the equation, so to speak?
In this talk, we will introduce the four datasets, their origins and challenges. Hot off the press, we will summarize the anonymized, quantified results of the Data Analysis Round Robin. (Incidentally, we will also see if a correlation exists between experience and proximity of the result to the median). Lastly, potential avenues for improving our field will be offered based on the findings, ranging from low-effort yet somehow controversial improvements, to high-effort foundational considerations."
Jamro, R. ; Mente, Tobias ; Kardjilov, N. ; Markötter, Henning ; Al-Falahat, Ala'A. M. ; Woracek, R. ; Manke, I. ; Griesche, Axel
This study was carried out to investigate the neutron transmission signal as a function of sample temperature during a welding process. A theoretical description that includes the Debye-Waller factor was used to describe the temperature influence on the neutron crosssections. Neutron imaging using a monochromatic beam helps to observe transmission variations related to the material temperature. In-situ neutron imaging of welding experiments show the distribution of the temperature in bulk steel samples. The performed finite element modelling of expected temperature distributions shows good agreement with the obtained experimental data.