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In this paper, the results of Thermally Stimulated Depolarization Currents (TSDC)-measurements of a complex system of stacked dielectric layers, like typically appearing in semiconductor packages, is presented. Characteristics of the individual isolation layers are presented solely and the results are compared to the stack. The investigated layers are comprising polyimide film, alkali-free glass, polyolefin film and epoxy based mold compound. Measurements have been carried out in the temperature range from 19 - 195°C at varying polarization fields for every material. Various relaxation peaks, originated by different polarization mechanisms within the materials could be observed. A comparison between the TSDC-peaks of the layer stack and the individual materials is shown. Our results demonstrate, that the super positioned spectrum is getting dominated by a single portion, the mold compound.
Anhand zweier Beispiele wird ein interaktives System vorgestellt, mit welchem Live-Messungen an elektronischen Bauteilen und Schaltungen im Hörsaal durchgeführt werden können. Das System basiert auf dem USB-Messgerät „Analog Discovery 2“ der Firma Digilent, erweitert um eine Adapterplatine mit Steckbrett und eine Webcam.
Zunächst werden drei Aspekte erläutert, in welchen ein solches System positive Auswirkungen auf den Kompetenzerwerb haben kann: Praxisbezug, Aktivierung und Vernetzung. Anschließend werden die zwei Beispiele ausgeführt. In Beispiel 1 wird die persönliche Alltagserfahrung mit Akkus über interaktive Clicker-Fragen und begleitende Messungen mit dem Modell der linearen Quelle verknüpft. Die Studierenden lernen, oberflächliche Lösungen wie die Messung der Leerlaufspannung zu hinterfragen und das Verhalten realer Quellen anhand der gemessenen I-U-Kennlinien zu verstehen. Beispiel 2 zeigt kurz die Möglichkeiten auf, den abstrakten Formalismus der komplexen Wechselstromrechnung am Beispiel des Serienschwingkreises im Zeit- und Frequenzbereich
messtechnisch erlebbar zu machen.
Smart materials change their properties with external energy supply. Besides the known ferro-fluids and Magneto Rheological Fluid (MRF) also the Electro Active Polymer (EAP) and Magneto Rheological Elastomer (MRE) belong to these intelligent materials. The latest generation of magnetic elastomers represents a new class of composite materials. This consists of small magnetized particles which are sized in the micron or even nanometer range that in turn is bounded in a highly elastic rubber matrix. These materials are very often called MRE. Only recently, it has managed to develop these materials even further, so that very soft composite materials with a young?s modulus up to 10 kPa are possible. These soft polymers could be named magneto-active polymers. The combination of polymers with magnetic materials show novel and often enhanced properties. A precisely controllable young?s modulus and hardness, giant and non-homogeneous deformation behavior and rapid response to the magnetic field opens up new possibilities for various applications. Since MAP represent a very new technology, the behavior of these materials as a function of their composition and external conditions so far are not yet sufficiently understood. Therefore, some fundamental studies are necessary. In this paper, the mechanical surface properties are studied using a micro hardness meter. This work shows the possibility to control mechanical properties at the surface of MAP with new developed magnetic systems.
Der Roboter als Hilfsmittel in der Chirurgie // International Mechatronik Forum, Linz, October 2006
(2006)
PPG signal acquisition and analysis on in vitro tooth model for dental pulp vitality assessmen
(2012)
Application of Magnetic Garnet Films for Magnetooptical Imaging of Magnetic Field Distributions
(2004)
Rare-earth iron garnet films of high quality can be grown by liquid phase epitaxy on paramagnetic substrates of gadolinium galliumgarnet. Such films are currently used for imaging of the spatial distribution of magnetic fields. This application is based on the Faraday rotation which can strongly be enhanced by bismuth incorporation.
The physical properties of the films can be controlled by the chemical composition, the growth conditions and the crystallographic orientation. The sensor properties like sensitivity, dynamic range, signal linearity and unambiguity must be optimized according to the application desired. These properties, however, are not independent of each other. In addition, they strongly depend on the optical wavelength. Thus, it is necessary to find compromises.
The influence of Faraday rotation, Faraday ellipticity, optical absorption, magnetic anisotropies and film thickness on the performance of a magnetooptical indicator film is investigated. Based on the swing of the photoresponse, a new optimization process is introduced. The process is experimentally verified and application examples are demonstrated.
Furthermore, two methods are presented to enhance the sensitivity of magnetooptical sensors. Using specific crystallographic orientations, an easy plane of magnetization can be induced which is inclined with respect to the film plane. If the magnetization lies in this plane a very high sensitivity is achieved. The dependence of the geometrical orientation of the easy plane on the growth direction is calculated and the sensitivity and dynamic range are derived. Experimental results of a [112] oriented garnet film are in good agreement with calculations.
Garnet films which are magnetized along the film normal due to a strong induced uniaxial anisotropy support magnetic domains. If the collapse field perpendicular to the film plane is small, such films can be used as very sensitive indicator films. Such films are easier to prepare than sensitive in-plane films. However, the spatial resolution is limited by the size of the domains. This disadvantage can be avoided by applying a bias field in the film plane. Directly at the in-plane collapse field the sensor film is in-plane magnetized yielding high spatial resolution at still high sensitivity. The variation of magnetooptical images with in-plane induction is demonstrated. Experimental results are in agreement with calculations.
Adaptive surface microstructures are used extensively in nature to control various surface properties such as wettability, adhesion, self-cleaning, drag reduction, etc. Regulation of these properties can be achieved with the appropriate employment of a multitude of smart materials, whose characteristics/response can be controlled by noncontact stimuli, e.g., light, heat, or magnetic field. One of the very promising magneto-regulable smart materials are magnetoactive elastomers (MAEs). They are comprised of a compliant polymer matrix with embedded micrometer-sized ferromagnetic particles. The particles interact with each other and a magnetic field. This results in remarkable tunability of the physical properties of MAEs. This paper reports a fast, resilient, and tailored method for direct surface micromachining of MAEs that enables micro-structuring without mechanical contact between the tool and the material, bypassing the usual constraints of conventional fabrication methods. It is shown that it is possible to fabricate a large variety of different microstructure geometries whose precision is limited predominantly by the size of magnetic particles. Lamellar structures with a high aspect ratio (up to 6:1) oriented either perpendicularly to the surface, can be strongly bent by applying magnetic fields in the range of 0–250 mT.
Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated over a wide spectral range, from visible to terahertz (THz) light. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.
The Trilopede
(2012)
Mechanical properties of biological tissue represent important diagnostic information and are of histological and pathological relevance. Malignant tumors are significantly stiffer and more immobile than surrounding healthy tissue. Hard calcifications in vessels occur due to arteriosclerosis. The problem is, that such information is usually not available or can only be obtained by manual palpation, which is subjective and limited in sensitivity. It requires intuitive assessment and does not allow quantitative documentation. Unfortunately, none of the established medical imaging equipment such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT) can provide direct measure of tissue elasticity. On the one hand a suitable sensor is required for quantitative measurement of mechanical tissue properties. On the other hand there is also some need for a realistic haptic display of such tissue properties. Suitable actuator arrays with high spatial resolution acting in real time are required. A haptic sensor actuator system is presented in this paper including a sensitive sensor part and an actuator array for different applications. The mechanical consistency of an object is to be locally specified using a sensor system and represented perceptibly in a remote position on an actuator system for the user. The sensor system uses ultrasound (US) elastography, whereas the actuator array is based on electrorheological (ER) fluids.
A detailed experimental study of the magnetoelectric response of planar bi- and symmetric trilayer composite structures to magnetic field pulses is reported. The structures consist of layers of commercially available piezoelectric (lead zirconate titanate) and magnetostrictive (permendur or nickel) materials. The magnetic-field pulses have the form of a half-wave sine function with duration of 450 μs and amplitude from 500 Oe up to 38 kOe. The measurement method is explained and the measured time dependence of the resulting voltage is presented. The most interesting case, when pulse amplitudes are sufficiently large (~ 1-10 kOe) and various types of acoustic oscillation with frequencies much larger than the reciprocal pulse length are excited in the structures, is considered. The dependencies of the magnetoelectric voltage coefficient on the excitation frequency and the applied magnetic field are calculated. By digital signal processing the results are compared with those obtained by the method of harmonic field modulation (HFM). The findings are of interest for developing magnetoelectric sensors for pulsed magnetic fields as well as for rapid characterization of magnetoelectric composite structures.
Magneto-active Polymers (MAP) are closely related to magneto-rheological fluids in that they contain magnetic micro-particles. However, instead of being freely suspended in a carrier fluid they are physically bound within a highly elastic polymer-matrix. The application of an external magnetic field allows changes in the mechanical properties, such as elastic and shear moduli, of the composite material to be achieved. The colossal magneto-rheological effect has been shown to demonstrate changes in Young's modulus by over 1E6 %. Current research concentrates on controllable compliance and the resulting shape memory properties of MAP. This paper deals with recent advancements in this respect, including tubular magneto-active devices with potential applications in medical and other technology.
By using more powerful LEDs a good thermal management is becoming more and more important. Here usually the thermal interconnects have to be in focus. Therefore a simple and rapid measurement method for the thermal check of the solder joint in a high volume production is necessary. A standard thermal resistance measurement is very time consuming due to the calibration of each device. By using thermal characterized reference devices it is possible to skip the time consuming part. Furthermore, a simple methodology for evaluating the thermal performance of the various metal core PCB (MCPCB) materials and construction is required during development. In this paper we will present how we successfully demonstrated that this new method offers an opportunity to determine the thermal performance of a high power QFN LED on different types of isolated metal substrate (IMS) and with a standard SMU [1] (source measurement units).
Most of the mechanical simulations for industrial usage are done by finite element (FE-) analysis. Milling machines are mechatronic systems, combining electrical, mechanical and control components for machining certain materials. Modelica provides a powerful and strong tool to simulate different physical ares in one model. For this usage a mechanical model of a 5-Axis-Milling Machine is implemented with rigid and flexible bodies. Specific attention will be paid to which components can be modelled rigid without significant deviation in accordance to the real behaviour of the machine. Two classes of implementing flexible bodies in multi body systems are given by the flexible bodies Library, advantages and disadvantages of both classes will be evaluated. At the end a comparision of the static and dynamic behaviour of the passive structure of the model in contrast to a FE-analysis is given.
The ability to synchronize expectations among human-robot teams and understand discrepancies between expectations and reality is essential for human-robot collaboration scenarios. To ensure this, human activities and intentions must be interpreted quickly and reliably by the robot using various modalities. In this paper we propose a multimodal recognition system designed to detect physical interactions as well as nonverbal gestures. Existing approaches feature high post-transfer recognition rates which, however, can only be achieved based on well-prepared and large datasets. Unfortunately, the acquisition and preparation of domain-specific samples especially in industrial context is time consuming and expensive. To reduce this effort we introduce a weakly-supervised classification approach. Therefore, we learn a latent representation of the human activities with a variational autoencoder network. Additional modalities and unlabeled samples are incorporated by a scalable product-of-expert sampling approach. The applicability in industrial context is evaluated by two domain-specific collaborative robot datasets. Our results demonstrate, that we can keep the number of labeled samples constant while increasing the network performance by providing additional unprocessed information.
The concept of Industrial Revolution 4.0 (IR4.0) has sparked the urgency of many manufacturers to revisit their manufacturing processes and search for opportunities to further improved their production output. Unfortunately, it is difficult to improve a process with inadequate data. Many of the SMEs in developing countries are still using manufacturing machines from the yesteryears which do not have computational and connectivity capabilities. Therefore, we developed an end-to-end Internet-of-Things (IoT) solution, which reliably tracks the production performance of manufacturing machines. This paper elaborates on the designs and the rationale behind it. As of the writing of this paper, our IoT system has been deployed in real manufacturing environment and has been running for approximately 90 days on a 24/7 basis without data lost.
Collaboration between robots and humans requires communicative skills on both sides. The robot has to understand the conscious and unconscious activities of human workers. Many state-of-the-art activity recognition algorithms with high performance rates on existing benchmark datasets are available for this task. This paper re-evaluates appropriate architectures in light of human work activity recognition for working cells in industrial production contexts. The specific constraints of such a domain is elaborated and used as prior knowledge. We utilize state-of-the-art algorithms as spatiotemporal feature encoders and search for appropriate classification and fusion strategies. Furthermore, we combine keypoint-based with appearance-based approaches to a multi-stream recognition system. Due to data protection rules and the high effort of data annotation within industrial domains only small datasets are available that reflect production aspects. Therefore, we use transfer learning approaches to reduce the dependency on data volume and variance in the target domain. The resulting recognition system achieves high performance for both singular person action and human-object interaction.
The mixed-signal event-driven (MixED) method developed to simulate small portions of analog circuitry within a digital environment is demonstrated in a mixed signal application. The MixED models using concurrent iteration to account for analog nodes were coded and run in standard VHDL’93. Networks containing linear components such as sources, resistors, capacitors, inductors and operational amplifiers are presented. The possibility to manipulate resistors during runtime is used to simulate switches.
A method to model high-gain feedback-loop analog amplifiers on an event driven timeaxis is presented. The demonstrator is coded in digital VHDL’93. In the event-driven scheme any node in the network must converge „on its own“ based on the information delivered from its neighbors, as no overall matrix is set up. For this reason signalloops with a loop gain larger than one are typically unstable. This communication presents a numerically stable generic model for high gain amplifiers with a userdefined feedback network. Non-ideal effects like offset or finite gain can be taken into account.
The mixed-signal event-driven (MixED) simulationalgorithm using standard VHDL is capable of modelinga number of analog and mixed-signal problems in digital circuits, e.g. RCL networks representing pads or wires, charge pumps, dynamic logic, voltage-controlledoscillators, phase-locked loops, etc. Important featuresare single-kernel simulation as well as rapid A/D andD/A interfacing.
This paper demonstrates the simulation of a phase-locked loop (PLL), which is one of the most interesting applications of the MixED method. Many digital designs contain a PLL as only mixed-signal building block. The MixED method allows to simulate such designs with standard VHDL.
A method for solving networks containing generic analog components such as resistors, capacitors and inductors onan event driven time axis using digital VHDL is presented. The components are modeled as complex state machines communicating with their neighbors using INOUT type ports. The method takes advantage of simulation deltas to iterate without simulation-time consumption. A limited range of implicit equations can be solved this way.
A family of CMOS low- to high-voltage output interface circuits based on a standard, unmodified low-voltage CMOS technology is described. Using only thin-oxide high-voltage (HV) devices with reduced V/sub GS/ (gate-to-source voltage) swing, it makes use of level-shift techniques to meet the constraints on the gate control signals. These static circuits permit the full output voltage swing of V/sub DDH/, while keeping the V/sub GS/ swing of the output devices within the safety limits, including during HV supply transients. Using a standard 2- mu m n-well CMOS technology, reliable, reproducible V/sub DS/ breakdown voltages as high as 120 V and 80 V have been obtained for HV-nMOS and HV-pMOS devices, respectively.< >
Design and Optimization of High-Voltage CMOS Devices Compatible wih a Standard 5V CMOS Technology
(1993)
High-voltage n- and p-MOSFETs fully compatible with a standard 5 V CMOS technology have been designed, optimized, and fabricated. No process changes are required. By modifying the logical equations generating one of the physical masks from the design masks, a p-type buffer region for the high-voltage p-MOS was easily implemented. This modification does not affect the low-voltage part of the circuits. These high-voltage devices have been used successfully as output drivers in semicustom arrays, and as building blocks for custom low- to high-voltage output interfaces. Aspects of reliability, device protection, and circuit design techniques are addressed.
An analytical model for dual-gate-controlled SOI MOSFETs is presented, assuming uniformly doped p-silicon films. It is restricted to electron inversion layers and depletion regions, neglecting hole densities. It allows to account for the spatial description of electronic quantities in the silicon film. Due to the non-linearities of the semiconductor equations the model parameters must be extracted iteratively. Some applications are presented to demonstrate the usefulness of the model.