Zeitschriftenaufsätze

Aiming at circular economy we must provide strategies for reuse of EoL (end of life) glass products, for maintenance and increase high material recycling quotas and be open for new technologies. The well-established returnable bottle system in Germany is an almost perfect example for product recycling, albeit in a confined market segment for certain beverages. On the other hand, recycling nonpackaging glass is tremendously far from closed cycles. The glass packaging market has grown slowly but successfully in spite of the competition from PET and other plastics. Glass producers struggle with even higher energy prices and will focus more and more on renewable energies. Consumers are aware that glass offers an alternative to increasing packaging waste. Which future tasks result from this situation? Three main topics arise for container glass: less one-way packaging, more returnable packaging, and innovative strategies for collection and sort- ing. Knowledge on the best practice examples is expected to be transferred to non-container glasses. An overview on the current status of demands is being documented with the goal of more ideas being generated to assist in glass recycling.

There is a variety of software packages, toolboxes, or libraries for the analysis and processing of neurophysiological data such as EEG and MEG. Many of these solutions provide algorithms for both, sensor-space analysis and sourcespace analysis. Especially with the solutions that run on Windows machines, it is noticeable that the step of the volume model generation is usually not included, since the state-ofthe- art software for this (FreeSurfer) is a Unix-based software and thus not available forWindows machines. Therefore, our goal was to develop a fully-integrated software solution for Windows machines, accessing all processing steps already implemented in an existing toolbox and using FreeSurfer in the same system. Due to its widespread use, we chose MNE Python as the basis for our fully integrated software solution. We used the Windows Subsystem for Linux to create a virtual Linux kernel for the FreeSurfer installation. To demonstrate the workflow, the libeep, and AutoReject libraries have been added. A 64-channel EEG recording during right-hand movement (ME) and imagination (MI) was used to test the implemented workflow. The developed framework consists of several modules within Python, mainly using existing scripts and functions. The library libeep was integrated to read the EEG data with the ‘.cnt’, eeprope format. AutoReject was used to automatically interpolate detected bad channels or to reject complete epochs. FreeSurfer was successfully integrated and customized Python scripts enabled the communication between MNE Python on a Windows machine and FreeSurfer on a virtual Linux kernel. With the above-mentioned EEG dataset, we performed source reconstruction and were able to show ERD/S patterns for both, ME and MI. Our new, fullyintegrated software framework can be used on Windows machines to perform a complete process of source reconstruction.

The measurement of the transport of scalar quantities within flows is oftentimes laborious, difficult or even unfeasible. On the other hand, velocity measurement techniques are very advanced and give high-resolution, high-fidelity experimental data. Hence, we explore the capabilities of a deep learning model to predict the scalar quantity, in our case temperature, from measured velocity data. Our method is purely data-driven and based on the u-net architecture and, therefore, well-suited for planar experimental data. We demonstrate the applicability of the u-net on experimental temperature and velocity data, measured in large aspect ratio Rayleigh-Bénard convection at Pr = 7.1 and Ra = 2 x 10^5, 4 x 10^5, 7 x 10^5. We conduct a hyper-parameter optimization and ablation study to ensure appropriate training convergence and test different architectural variations for the u-net. We test two application scenarios that are of interest to experimentalists. One, in which the u-net is trained with data of the same experimental run and one in which the u-net is trained on data of different Ra. Our analysis shows that the u-net can predict temperature fields similar to the measurement data and preserves typical spatial structure sizes. Moreover, the analysis of the heat transfer associated with the temperature showed good agreement when the u-net is trained with data of the same experimental run. The relative difference between measured and reconstructed local heat transfer of the system characterized by the Nusselt number Nu is between 0.3 and 14.1% depending on Ra. We conclude that deep learning has the potential to supplement measurements and can partially alleviate the expense of additional measurement of the scalar quantity.

Currently, 5G low-earth orbit satellite communications offer enhanced wireless coverage beyond the reach of 5G terrestrial networks, with important implications, particularly for automated and connected vehicles. Such wireless automotive mass-market applications demand well-designed compact user equipment antenna terminals offering non-terrestrial jointly with terrestrial communications. The antenna should be low-profile, conformal, and meet specific parameter values for gain and operational frequency bandwidth, tailored to the intended applications, in line with the aesthetic design requirements of passenger cars. This work presents an original concept for a dual-band nested circularly polarized automotive user terminal that operates at the S-band frequencies around 3.5 GHz and Ka-band frequencies around 28 GHz, namely within the 5G new-radio bands n78 and n257, respectively. The proposed terminal is designed to be integrated into the plastic components of a passenger vehicle. The arrays consist of 2 × 2 aperture-coupled corner-truncated microstrip slot patch antenna elements for the n78 band and of 4 × 4 single-layer edge-truncated microstrip circular slot patch antenna elements for the n257 band. The embedded arrays offer, across the two bands, respectively, 9.9 and 13.7 dBi measured realized gain and 3-dB axial ratio bandwidths of 100 and 1500 MHz for the n78 and n257 bands along the broadside direction. Detailed link budget calculations anticipate uplink data rates of 21 and 6 Mbit/s, respectively, deeming it suitable for various automotive mobility and Internet-of-Things applications.

The increasing demand for micro- and nanofabrication and in parallel the increasing requirements on feature size and resolution is leading to an enormous growth in the field of multi-photon three-dimensional fabrication. To enable new and diverse investigations in this field and to enable high precision for nanofabrication on large areas, a high precision positioning system is combined with an ultra-short pulse laser system. The aim is a modular setup with constant adherence to the Abbe-comparator principle in order to achieve systematic improvements in the area of Direct Laser Writing. For a high-quality identification of the microstructures a measurement tool based on atomic force microscopy is used. To enable the fabrication of continuous micro- and nanostructures on large area, an extremely high positioning precision is used, where no further stitching methods are necessary. Therefore as base of the Direct Laser Writing system the nanopositioning and nanomeasuring machine (NMM-1) is used, which was developed at Technische Universität Ilmenau together with SIOS Meßtechnik GmbH, with a positioning volume of 25 mm × 25 mm × 5 mm and a positioning resolution in the sub-nanometer range. First investigations already confirmed that microfabrication with a Femtosecond Laser and the NMM-1 could be realized and showed the possibility of further developments in the field of Direct Laser Writing. Now the modular structure as a research platform is designed in such a way that the various extensions and measurement setups for large-scale investigations can always be implemented in a metrologically traceable manner. The presented work shows the development of a modular functional setup of an exposure system and NMM-1, which enables micro- and nanofabrication and an improvement in the structure size over large areas.