Influence of hydrogen, oxygen, nitrogen, and water vapor on the formation of pores at welding of copper using laser light at 515 nm wavelength. - In: Journal of laser applications, ISSN 1938-1387, Bd. 32 (2020), 2, 022020, S. 022020-1-022020-7
https://doi.org/10.2351/7.0000063
Line edge roughness metrology software. - In: Journal of vacuum science & technology, ISSN 2166-2754, Bd. 38 (2020), 1, S. 012602-1-012602-8
https://doi.org/10.1116/1.5122675
Tip- and laser-based nanofabrication up to 100 mm with sub-nanometre precision. - In: Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020, (2020), S. 113240A-1-113240A-17
Although the field of optical lithography is highly investigated and numerous improvements are made, structure sizes smaller than 20 nm can only be achieved by considerable effort when using conventional technology. To cover the upcoming tasks in future lithography, enormous exertion is put into the development of alternative fabrication technologies in particular for micro- and nanotechnologies that are capable of measuring and patterning at the atomic scale in growing operating areas of several hundred square millimetres. Many new technologies resulted in this process, and are promising to overcome the current limitations^1, 2, but most of them are demonstrated in small areas of several square micrometers only, using state-of-the-art piezo stages or the like. At the Technische Universitat Ilmenau, the NanoFabrication Machine 100 (NFM-100) was developed, which serves as an important experimental platform for basic research in the field of scale-spanning AFM tip-based and laser-based nanomeasuring and nanofabrication for simultaneous subnanometre measuring and structuring on surfaces up to Ø100 mm. This machine can be equipped with several probing systems like AFM, laser focus probes and 3D-micro probes as well as tools for different nanofabrication technologies like tip-based technologies, optical technologies and mechanical two-dimensional technologies in a large working range with subnanometre reproducibility and uncertainty. In this paper, the specifics and advantages of the NFM-100 will be described as well as nanofabrication technologies that are currently worked on e.g. advanced scanning proximal probe lithography based on Fowler-Nordheim-electron-field emission, direct laser writing and UV-nanoimprint lithography.
https://doi.org/10.1117/12.2551044
On the use of a cascaded convolutional neural network for three-dimensional flow measurements using astigmatic PTV. - In: Measurement science and technology, ISSN 1361-6501, Volume 31 (2020), number 7, 074015, 14 Seiten
Many applications in chemistry, biology and medicine use microfluidic devices to separate, detect and analyze samples on a miniaturized size-level. Fluid flows evolving in channels of only several tens to hundreds of micrometers in size are often of a 3D nature, affecting the tailored transport of cells and particles. To analyze flow phenomena and local distributions of particles within those channels, astigmatic particle tracking velocimetry (APTV) has become a valuable tool, on condition that basic requirements like low optical aberrations and particles with a very narrow size distribution are fulfilled. Making use of the progress made in the field of machine vision, deep neural networks may help to overcome these limiting requirements, opening new fields of applications for APTV and allowing them to be used by nonexpert users. To qualify the use of a cascaded deep convolutional neural network (CNN) for particle detection and position regression, a detailed investigation was carried out starting from artificial particle images with known ground truth to real flow measurements inside a microchannel, using particles with uni- and bimodal size distributions. In the case of monodisperse particles, the mean absolute error and standard deviation of particle depth-position of less than and about 1 [my]m were determined, employing the deep neural network and the classical evaluation method based on the minimum Euclidean distance approach. While these values apply to all particle size distributions using the neural network, they continuously increase towards the margins of the measurement volume of about one order of magnitude for the classical method, if nonmonodisperse particles are used. Nevertheless, limiting the depth of measurement volume in between the two focal points of APTV, reliable flow measurements with low uncertainty are also possible with the classical evaluation method and polydisperse tracer particles. The results of the flow measurements presented herein confirm this finding. The source code of the deep neural network used here is available on https://github.com/SECSY-Group/DNN-APTV.
https://doi.org/10.1088/1361-6501/ab7bfd
In-situ monitoring of hybrid friction diffusion bonded EN AW 1050/EN CW 004A lap joints using artificial neural nets. - In: Proceedings of the Institution of Mechanical Engineers, ISSN 2041-3076, Bd. 234 (2020), 5, S. 766-785
In this work, a dissimilar copper/aluminum lap joint was generated by force-controlled hybrid friction diffusion bonding setup (HFDB). During the welding process, the appearing torque, the welding force as well as the plunge depth are recorded over time. Due to the force-controlled process, tool wear and the use of different materials, the resulting data series varies significantly, which makes quality assurance according to classical methods very difficult. Therefore, a Convolutional Neural Network was developed which allows the evaluation of the recorded process data. In this study, data from sound welds as well as data from samples with weld defects were considered. In addition to the different welding qualities, deviations from the ideal conditions due to tool wear and the use of different alloys were also considered. The validity of the developed approach is determined by cross validation during the training process and different amounts of training data. With an accuracy of 88.5%, the approach of using Convolutional Neural Network has proven to be a suitable tool for monitoring the processes.
https://doi.org/10.1177/1464420720912773
Reduction of friction stir welding setup loadability, process forces and weld seam width by tool scaling. - In: Proceedings of the Institution of Mechanical Engineers, ISSN 2041-3076, Bd. 234 (2020), 5, S. 786-795
Friction stir welding is an increasingly used method to join similar and dissimilar materials with excellent mechanical weld seam properties. However, in certain cases, friction stir welding is restricted by high mechanical loads as a result of high forces and torques during the welding process. This relates in particular stiffness-reduced machine concepts which may cause path deviations, massive vibrations and insufficient tool plunging. Against this background, this investigation demonstrates a method to reduce forces and torques by tool scaling. Due to the stepwise diameter reduction of shoulder and probe and a simultaneous adjustment of the process parameters, a significant force and spindle torque reduction was achieved. Furthermore, it could be shown that tool scaling does not affect the mechanical strength properties. The experimental investigations were carried out with EN AW 5754 H11 with a sheet thickness of 8 mm. The weld seams were performed on a robotized friction stir welding setup (KUKA KR500) with a maximum axial force of 10 kN. Based on a 26-mm shoulder and a 10-mm pin diameter, it could be demonstrated that the general weldability of 8 mm EN AW 5754 H11 is restricted (incomplete tool plunge) by the maximum axial force of the robotized friction stir welding setup (10 kN). Due to the stepwise reduction of the shoulder and probe diameter from 26 mm to 20.8 mm and 10 mm to 8 mm, respectively, a general weldability and weld seams without irregularities could be achieved by the equal robotized friction stir welding setup. Furthermore, it could be shown that an axial force and spindle torque reduction from 10 kN to 4 kN and 29 Nm to 10 Nm, respectively, was obtained due to further reduction of the tool diameters.
https://doi.org/10.1177/1464420720903331
Cancer drugs affect the interaction of nanoparticles with an in vitro placenta barrier. - In: Oncology research and treatment, ISSN 2296-5262, Bd. 43 (2020), S. 209
Meeting abstract: 809
https://doi.org/10.1159/000506491
Comparison of different methods for experimental determining the inhomogeneity of thermocouples :
Vergleich verschiedener Methoden zur experimentellen Bestimmung der Inhomogenität von Thermoelementen. - In: Technisches Messen, ISSN 2196-7113, Bd. 87 (2020), 3, S. 146-152
https://doi.org/10.1515/teme-2019-0138
Feasibility of new stimulator setup for temporal interference TES and its application in a homogeneous volume conductor. - In: Clinical neurophysiology, ISSN 1872-8952, Bd. 131 (2020), 4, S. e152
https://doi.org/10.1016/j.clinph.2019.12.348
A group-level sensitivity analysis to assess the influence of white matter lesions on the electrical field in simulations of transcranial electric stimulation. - In: Clinical neurophysiology, ISSN 1872-8952, Bd. 131 (2020), 4, S. e124
https://doi.org/10.1016/j.clinph.2019.12.304