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The shape-memory Nitinol as a nickel-titanium alloy is widely used in actuator and medical applications. However, the connection of a flange to the rod is a critical point. Therefore, laser rod end melting enables material accumulations to generate a preform at the end of a rod, followed by die forming, so that the flange can be generated. This process has been successfully applied on 1.4301 steel. This study is aimed to investigate laser rod end melting of shape-memory Nitinol regarding the resultant surface quality of the preforms. The results showed that spherical preforms could be generated without visible surface discoloration due to oxidation. By using different scan rates, different solidification conditions occurred which led to significantly different surface structures. These findings show that laser rod end melting can principally be applied on Nitinol to generate preforms for flanges whereby the surface quality depends on the solidification conditions.
Beam shaping and splitting with diffractive optics for high performance laser scanning systems
(2021)
Diffractive optical elements (DOEs) enable novel high performance and process-tailored scanning strategies for galvanometer-based scan heads. Here we present several such concepts integrating DOEs with laser scanners and the respective application use cases. Beam shaping DOEs providing a homogeneous fluence over a custom defined profile, such as a rectangular Top-Hat, enable increased process quality in Laser-Induced Forward Transfer (LIFT) compared to the Gaussian beam of the laser source. We show that aberrations which occur over the necessary large wafer-sized image field can be eliminated through the use of a synchronous XY-stage motion. Another application that benefits from the use of DOEs is laser drilling. Drilling in display and electronics manufacturing demands high throughput that can only be achieved through the use of beam splitting DOEs for parallel processing. To this end, the joint MULTISCAN project is developing a variable multi-beam tool capable of scanning and switching each individual beamlet for increased control.
Increasing speed in laser processing is driven by the development of high-power lasers into ranges of more than 1 kW. Additionally, a proper distribution of these laser power is required to achieve high quality processing results. In the case of high pulse repletion rates, a proper distribution of the pulses can be obtained from ultrafast beam deflection in the range of several 100 m/s. A two-dimensional polygon mirror scanner has been used to distribute a nanosecond pulsed laser with up to 1 kW average power at a wavelength of 1064 nm for multi pass laser engraving. The pulse duration of this laser can be varied between 30 ns and 240 ns and the pulse repetition rate is set between 1 and 4 MHz. The depth information is included in greyscale bitmaps, which were used to modulate the laser during the scanning accordingly to the lateral position and the depth. The process allows high processing rates and thus high throughput.
Pulsed laser processing of vacuum component surfaces is a promising method for electron cloud mitigation in particle accelerators. By generating a hierarchically structured surface, the escape probability of secondary electrons is reduced. The choice of laser treatment parameters – such as laser power, scanning speed and line distance – has an influence on the resulting surface morphology as well as on its performance. The impact of processing parameters on the surface properties of copper is investigated by Secondary Electron Yield (SEY) measurements, Scanning Electron Microscopy (SEM), ablation depth measurements in an optical microscope and particle release analysis. Independent of the laser wavelength (532nm and 1064nm), it was found that the surface morphology changes when varying the processing parameters. The ablation depth increases and the SEY reduces with increasing laser fluence. The final application requires the capability to treat tens of meters of vacuum pipes. The limiting factors of this type of surface treatment for the applicability in particle accelerators are discussed.
We demonstrate a thulium-based fiber amplifier delivering pulses tunable between <120fs and 2ps duration at up to 228 μJ of pulse energy at a center wavelength of 1940 nm and 500-kHz repetition rate. Due to the excellent long-term stability, this system proves the ability of this technology to be integrated into ultra-fast material processing machines.
The wind energy sector is undergoing digitalization processes that span multi-tier supply chains of turbine components and wind farm maintenance, amongst others. In an industrial use case that includes Siemens Gamesa Renewable Energy, Vestas and APQP4Wind, the processes of producing, fastening, and servicing bolts in turbines are mapped to a digital model. The model follows the lifetime of turbine bolts from the manufacturing phase, to fastening in turbines and maintenance, until their replacement and recycling. The development of the digital model is iteratively addressed in a design science research approach, as the authors actively contribute to the project. Distributed ledgers (DLs) support the notary documentation of the bolts and turbines, from their registration phase to the assembly-, technical service verification- and recycling phases. The immutable and decentralized nature of DLs secures the data against tampering and prevents any changes taken unilaterally by engaging the service stakeholders and component providers in a blockchain consortium.
There are multiple ways to gain information about an individual and its health status, but an increasingly popular field in medicine has become the analysis of human breath, which carries a lot of information about metabolic processes within the individuals body. The information in exhaled breath consists of volatile (organic) compounds (VOCs). These VOCs are products of metabolic processes within the individuals body, thus might be an indicator for diseases disturbing those processes. The compounds are to be detected by mass-spectrometric (MS) or ion-mobility spectrometric (IMS) techniques, making the analysis of these compounds not only bounded to exhaled breath. The resulting data is spectral data, capturing concentrations of the VOCs indirectly through intensities. However, a number of about 3000 VOCs [1] could already be determined in human exhaled breath. The number of research paper about VOC-analysis and detection had risen nearly constantly over the last decade 1. Furthermore, the technique to identify VOCs could also be used to capture biomarker from alien species within the individuals body. Extracting VOCs from an individual can be done by non- or minimal invasive techniques. However, the manual identification of VOCs and biomarkers related to a certain disease or infection is not feasible due to the complexity of the sample and often unknown metabolic products, thus automized techniques are needed. [1–4] To establish breath analysis as a diagnosis tool, machine learning methodes could be used. Machine learning has become a popular and common technique when dealing with medical data, due to the rapid analysis. Taking this advantage, breath analysis using machine learning could become the model of choice for diagnosis, keeping in mind that conventional methodes are laboratory based and thus when trying detect bacterial infection need sometimes several days to identify the organism. [5]
The objective of this Bachelor Project is the creation of a tool that should support forensic investigators during IT forensic interventions. It uses Kismet as the base program and adds functionalities to it via the plugin interface. The installation of the plugin shall be explained, how the plugin works, and a recommendation on how to use it. To understand the underlying basics, an introduction about WLAN and Bluetooth is given. The tests that were performed with the new plugin are described as well as their results. It is therefore briefly discussed why the tool is applicable for locating Wi-Fi devices, especially access points, but not Bluetooth devices. Using all this a few ideas on how to improve the tool and what can be researched in this area are provided.
In this work, a protocol for portable nanopore sequencing of DNA from pollen collected from honey bees, bumble bees, and wild bees was developed. DNA metabarcoding is applied to identify genera within the mixed DNA samples. The DNA extraction and ITS and ITS2 PCR parameters tested for this purpose were applied to the collected pollen sample and the amplicons were then decoded using the Flongle sequencer adapter from Oxford Nanopore Technologies. It is shown that the main pollinator resources at the different sites can be identified in percentage proportions. The protocol generated in this study can be used for further ecological questions.
We propose a method for edge detection in images with multiplicative noise based on Ant Colony System (ACS). To adapt the Ant Colony System algorithm to multiplicative noise, global pheromone matrix is computed by the Coefficient of Variation. We carried out a performance comparison of the edge detection Ant Colony System algorithm among several techniques, the best results were found in the gradient and the coefficient of variation.