621 Angewandte Physik
Refine
Document Type
- Article (47)
- Conference Proceeding (40)
- Article in a Periodical of the TH Wildau (15)
- Book (3)
- Preprint (2)
- Part of a Book (1)
- Doctoral Thesis (1)
Year of publication
Institute
Has Fulltext
- yes (109)
Keywords
- nanoindentation (5)
- carbon (3)
- hardness (3)
- photonic integrated circuit (3)
- renewable energy (3)
- water adsorption (3)
- Fabry-Perot sensor (2)
- Simulation (2)
- renewable energy source (2)
- surface plasmon resonance (2)
The two main features of the memristive devices which makes them the promising candidates for neuromorphic applications are low power consumption and CMOS compatibility. The monolithic integration of memristive devices with CMOS circuitry paves the way for in-memory computing. This chapter focuses on the factors governing the CMOS integration process. Firstly, the influence of CMOS baseline technology selection on the memristor module is briefly discussed. Secondly, the selection of metal level interconnects and their effect on the memristive device performance is explained. Further, the widely used deposition technique for the CMOS compatible memristive switching layers is presented. Finally, the implementation of the optimized process for the fabrication of the memristive module and its influence on the device performance is presented in terms of electrical characterization results.
Fabry-Pèrot (FP) interferometer sensors enable highly sensitive backward mode acoustic detection in Photoacoustic (PA) imaging. They are transparent to the excitation wavelength, can be placed directly next to the PA source, and offer a broadband frequency response and high acoustic sensitivity. PA tomography using parallelized detection requires high spatial uniformity of the optical and acoustic properties, which can be hampered by contaminations during fabrication that lead to the formation of inhomogeneities and artefacts. The quality and homogeneity of the dielectric and polymer layers have a direct effect on the maximum optical phase sensitivity, and hence acoustic sensitivity. In this study, cross-sectional images of FP sensors were obtained using focused ion beam milling and ultramicrotomy followed by Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) to evaluate different fabrication methods.
Fabry-Perot (FP) sensors are typically read out using a raster scan to acquire tomographic Photoacoustic (PA) images. To speed up the recording time, wide-field illumination of the sensor in combination with a camera as detector can be used. In this study, an sCMOS camera and wavelengths around 517 nm are used to interrogate a FP sensor with a homogeneous optical thickness over a 4 cm2 aperture. The recorded time series show PA signals are acquired over the entire area of the interrogation beam. The performance of the system, such as the noise equivalent pressure, is evaluated.
Biomedical photoacoustics is usually used to image absorption-based contrast in soft tissues up to depths of several centimeters and with sub-millimeter resolution. By contrast, measuring Photoacoustic (PA) signals through hard bone tissue shows severe signal degradation due to aberration and high attenuation of high frequency acoustic signal components. This is particularly noticeable when measuring through thicker, human, skull bone. Which is the main reason why transcranial PA imaging in humans has so far proved challenging to implement. To tackle this challenge, we developed an optical resonator sensor based on a previous planar-concave design. This sensor was found to be highly suitable for measuring the low-pressure amplitude and low acoustic frequency signals that are transmitted through human cranial bone. A plano-concave optical resonator sensor was fabricated to provide high sensitivity in the acoustic frequency range of DC to around 2 MHz, a low noise equivalent pressure and a small active element size enabling it to significantly outperform conventional piezoelectric transducers when measuring PA waves transmitted through ex vivo human cranial bones.
We study the dynamics of avalanche ionization of pure helium nanodroplets activated by a weak extreme-ultraviolet (XUV) pulse and driven by an intense near-infrared (NIR) pulse. In addition to a transient enhancement of ignition of a nanoplasma at short delay times ${\sim}200$ fs, long-term activation of the nanodroplets lasting up to a few nanoseconds is observed. Molecular dynamics simulations suggest that the short-term activation is caused by the injection of seed electrons into the droplets by XUV photoemission. Long-term activation appears due to electrons remaining loosely bound to photoions which form stable 'snowball' structures in the droplets. Thus, we show that XUV irradiation can induce long-lasting changes of the strong-field optical properties of nanoparticles, potentially opening new routes to controlling avalanche-ionization phenomena in nanostructures and condensed-phase systems.
Thin polytetrafluoroethylene (PTFE) films are produced by deposition from a gas phase by two methods: electron-enhanced vacuum deposition (EVD) and EVD + low-temperature plasma (LTP). Structure, morphology, and composition of the films are studied by IR spectroscopy, atomic force microscopy, and X-ray photoelectron spectroscopy. They are close to the structure of bulk PTFE. The roughness of the films’ surface is changed with gas pressure and LTP power variations. Films are transparent from UV to near-infrared regions. Refractive and extinction indices and their anisotropy are measured by spectral ellipsometry. They are tuned by variations of deposition conditions. Hardness and Young modulus of the films are increased if EVD + low power LTP is used for film deposition. Use of EVD + LTP also increases thermal stability of the films. Contact angle of the films corresponds to the bulk PTFE. The PTFE molecules oriented are preferentially in perpendicular direction to the substrate surface.
We have investigated the possibility to track and control correlation dynamics of valence electrons in krypton (Kr) initiated by the absorption of one extreme ultraviolet (XUV) photon. In this investigation, pump-probe experiments have been performed where monochromatized single high-harmonics at photon energies 29.6, 32.8, and 35.9 eV have been used as pump to populate different intermediate excited states. A temporally delayed near-infrared (NIR) pulse probes the population of various decay channels via the detection of Kr²⁺ ion yields and its transient profiles. We observe that by varying the NIR pulse intensity within a range from 0.3 x 10¹³ to 2.6 x 10¹³ W cm⁻², the shape of the Kr²+ transient profile changes significantly. We show that by varying the intensity of the NIR pulse, it is possible—(i) to control the ratio between sequential and non-sequential double ionization of Kr; (ii) to selectively probe quantum beating oscillations between Kr+* satellite states that are coherently excited within the bandwidth of the XUV pulse; and (iii) to specifically probe the relaxation dynamics of doubly excited (Kr**) decay channels. Our studies show that the contribution of different ionization and decay channels (i)–(iii) can be altered by the NIR pulse intensity, thus demonstrating an efficient way to control the ionization dynamics in rare gas atoms.
Silicon photonic micro-ring resonators (MRR) developed on the silicon-on-insulator (SOI) platform, owing to their high sensitivity and small footprint, show great potential for many chemical and biological sensing applications such as label-free detection in environmental monitoring, biomedical engineering, and food analysis. In this tutorial, we provide the theoretical background and give design guidelines for SOI-based MRR as well as examples of surface functionalization procedures for label-free detection of molecules.
After introducing the advantages and perspectives of MRR, fundamentals of MRR are described in detail, followed by an introduction to the fabrication methods, which are based on a complementary metal-oxide semiconductor (CMOS) technology. Optimization of MRR for chemical and biological sensing is provided, with special emphasis on the optimization of waveguide geometry. At this point, the difference between chemical bulk sensing and label-free surface sensing is explained, and definitions like waveguide sensitivity, ring sensitivity, overall sensitivity as well as the limit of detection (LoD) of MRR are introduced. Further, we show and explain chemical bulk sensing of sodium chloride (NaCl) in water and provide a recipe for label-free surface sensing.
From Lab-on-chip to Lab-in-App: Challenges towards silicon photonic biosensors product developments
(2022)
This work presents and evaluates different approaches of integrated optical sensors based on photonic integrated circuit (PIC) technologies for refractive index sensing. Bottlenecks in the fabrication flow towards an applicable system are discussed that hinder a cost-effective mass-production for disposable sensor chips. As sensor device, a waveguide coupled micro-ring based approach is chosen which is manufactured in an 8” wafer level process. We will show that the co-integration with a reproducible, scalable and low-cost microfluidic interface is the main challenge which needs to be overcome for future application of silicon technology based PIC sensor chips.
3D printed rotor blades for a research wind turbine: Aerodynamic and structural design and testing
(2022)
This study combines the design, the 3D printing and the testing of a small 3-bladed wind turbine rotor for research and teaching purposes. The objective is the additive manufacturing of a rotor with a radius of one meter, as an alternative to subtractive methods, such as computerized milling. The blade design is developed using freely available software packages. The aerodynamic considerations include the airfoil selection, the calculation of the blade geometry and the simulation of the ultimate load cases. The structural considerations are focussed on the printable materials, the infill structures and the retrofit of a load-carrying spar. The rotor blades are 3D printed with the BigRep One at the maker space of the TH Wildau. The structural integrity of the prototype blade is tested in terms of the ultimate root bending moments and the centrifugal forces at the HTW Berlin. The aerodynamic run-up tests are performed at the large wind tunnel of the TU Berlin measuring the power curves. The successful prototype paves the way for follow-up projects, such as open field tests and the 3D printing of larger rotor blades.
Laboratory plasmas inherently exhibit temperature and density gradients leading to complex investigations. We show that plasmas generated by laser ablation can constitute a robust exception to this. Supported by emission features not observed with other sources, we achieve plasmas of various compositions which are both uniform and in local thermodynamic equilibrium. These properties characterize an ideal radiation source opening multiple perspectives in plasma spectroscopy. The finding also constitutes a breakthrough in the analytical field as fast analyses of complex materials become possible.
Label-free direct-optical biosensors such as surface-plasmon resonance (SPR) spectroscopy has become a gold standard in biochemical analytics in centralized laboratories. Biosensors based on photonic integrated circuits (PIC) are based on the same physical sensing mechanism: evanescent field sensing. PIC-based biosensors can play an important role in healthcare, especially for point-of-care diagnostics, if challenges for a transfer from research laboratory to industrial applications can be overcome. Research is at this threshold, which presents a great opportunity for innovative on-site analyses in the health and environmental sectors. A deeper understanding of the innovative PIC technology is possible by comparing it with the well-established SPR spectroscopy. In this work, we shortly introduce both technologies and reveal similarities and differences. Further, we review some latest advances and compare both technologies in terms of surface functionalization and sensor performance.
Direct optical detection methods such as surface plasmon resonance imaging (SPRi) and photonic-integrated-circuits (PIC)-based biosensors provide a fast label-free detection of COVID-19 antibodies in real-time. Each technology, i.e., SPRi and PIC, has advantages and disadvantages in terms of throughput, miniaturization, multiplexing, system integration, and cost-effective mass production. However, both technologies share similarities in terms of sensing mechanism and both can be used as high-content diagnostics at or near to point of care, where the analyte is not just quantified but comprehensively characterized. This is significant because recent results suggest that not only the antibody concentration of the three isotypes IgM, IgG, and IgA but also the strength of binding (affinity) gives an indication of potential COVID-19 severity. COVID-19 patients with high titers of low affinity antibodies are associated with disease severity. In this perspective, we provide some insights into how SPR and PIC technologies can be effectively combined and complementarily used for a comprehensive COVID-19 severity monitoring. This opens a route toward an immediate therapy decision to provide patients a treatment in an early stage of the infection, which could drastically lowers the risk of a severe disease course.
Summary In the course of classical optics manufacturing glass components are in permanent direct contact with aqueous operating materials. Such contact leads to a certain absorption of water and hydrogenous compounds that may induce severe glass defects. In this contribution, absorption of hydrogen and other contaminants during grinding of glass was observed and qualitatively detected via laser-induced breakdown spectroscopy. It is shown that hydrogen, calcium, magnesium, and carbon are implanted into the glass surface where the contaminant concentration increases over grinding time or contact time of the glass surface with water and the grinding tool, respectively. The contaminants hydrogen, calcium, and magnesium can be attributed to the water used as lubricant. In contrast, carbon most likely originates from wear debris of the used silicon carbide grinding pads. Several possible mechanisms that lead to such surface contamination of glasses during grinding – diffusion, accumulation in micro cracks as well as the formation of hydrated silica – are finally introduced.
Electro-optical properties of doped polymers with high transparency in the visible wavelength range
(2021)
The electro-optical (EO) properties of poly(methyl methacrylate) and the photopolymer poly(vinyl cinnamate) doped with varying concentrations of the EO chromophore 2-Methyl-4-nitroaniline were measured. The EO polymers were embedded in Fabry-Pérot etalons for the simultaneous determination of the Pockels and Kerr coefficients from measurements of the fringe shift induced by an external electric field. It was found that the host polymer has a significant impact on the EO performance and that the undoped host polymers exhibit a significant Pockels effect. Moreover, the Kerr effect provides a substantial contribution of 27% to the total change of the refractive index at relatively high electric field strengths of E = 91.2 MV m−1.
Polycrystalline infrared (PIR) fibers are used for numerous applications, one of those being power delivery for CO2 lasers. However, the fiber tip surface's transmittance cannot be increased with conventional antireflection coatings due to the surface unevenness. Antireflection microstructures (ARMs) offer an alternative way of increasing transmittance. In this work, ARMs were fabricated on the fiber tip surface of an AgClBr fiber by single-pulse femtosecond laser ablation. A single-surface transmittance of 92.8% at 10.6 μm, a CO2 laser operation wavelength, was achieved. The proposed method can help significantly improve the systems' efficiency, where power delivery for CO2 lasers or sources operating in the wide wavelength range is required.
Small and medium-sized companies increasingly turning their attention towards the fourth industrial revolution. In order to increase their own long-term competitiveness, there is a growing desire to make production smarter, more efficient, safer and more sustainable through new technologies. Often, however, existing plants cannot be easily replaced by modern equipment. The reasons for this can be high investment costs, excessive downtimes or the unavailability of an equivalent machine. An alternative solution to the purchase of new equipment is the modernisation or expansion of existing systems, also called retrofitting. Thus, this paper deals with the retrofit process of a machine tool, whereby the software architecture of the control unit is the primary concern of this work.
During the last decade production innovation was mainly focused on connectivity aspects. The vision of smart factories running on software, that uses collected machine data, has become true but foremost for leading industrial companies in highly developed countries. Apart from these, production can also be found in non-industrialized craft professions as well as in less developed countries. As digitalization does not necessarily require an industrial or developed setting the latter could possibly benefit from it as well. Socio-cyber-physical production systems have been used to describe the interdependencies of linked production systems but usually focus on highly developed regions as well as for industrial applications. This paper lines out similarities and differences for each case, introduces the concept of cyber-physical production systems (CPPS) and its extension to socio-CPPS (SCPPS), which emphasizes the role of human workers in the production environment. The relation between industrial, non-industrial production and innovations is examined. Furthermore, the widening of SCCPS concepts for non-industrial production is discussed.
Dermatological in vivo measurements are used for various purposes, e.g. health care, development and testing of skin care products or claim support in marketing. Especially for the last two purposes, in vivo measurements are extensive due to the quantity and repeatability of the measurement series. Furthermore, they are performed manually and therefore represent a nonnegligible time and cost factor. A solution to this is the implementation of collaborative robotics for the measurement execution. Due to various body shapes and surface conditions, common static control procedures are not applicable. To solve this problem, spatial information obtained from a stereoscopic camera can be integrated into the robot control process. However, the designated measurement area has to be detected and the spatial information processed. Therefore the authors propose a concept towards segmenting arm areas through a CNN-based object detector and their further processing to perform robot-based in vivo measurements. The paper gives an overview of the utilization of RGB-D images in 2D object detectors and describes the selection of a suitable model for the application. Furthermore the creation, annotation and augmentation of a custom dataset is presented.
Faults in industrial chiller systems can lead to higher energy consumption, increasing wear of system components and shorten equipment life. While they gradually cause anomalous system operating conditions, modern automatic fault detection models aim to detect them at low severity by using real-time sensor data. Many scientific contributions addressed this topic in the past and presented data-driven approaches to detect faulty system states. Although many promising results were presented to date, there is lack of suitable comparison studies that show the effectiveness of the proposed models by use of data stemming from different chiller systems. Therefore this study aims at detecting a suitable data-driven approach to detect faults reliable in different domains of industrial chillers. Thus, a unified procedure is developed, to train all algorithms in an identical way with same data-basis. Since most of the reviewed papers used only one dataset for training and testing, the selected approaches are trained and validated on two different datasets from real refrigeration systems. The data-driven approaches are evaluated based on their accuracy and true negative rate, from which the most suitable approach is derived as a conclusion.