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A Hybrid Optoelectronic Sensor Platform with an Integrated Solution‐Processed Organic Photodiode
(2021)
Hybrid systems, unifying printed electronics with silicon‐based technology, can be seen as a driving force for future sensor development. Especially interesting are sensing elements based on printed devices in combination with silicon‐based high‐performance electronics for data acquisition and communication. In this work, a hybrid system integrating a solution‐processed organic photodiode in a silicon‐based system environment, which enables flexible device measurement and application‐driven development, is presented. For performance evaluation of the integrated organic photodiode, the measurements are compared to a silicon‐based counterpart. Therefore, the steady state response of the hybrid system is presented. Promising application scenarios are described, where a solution‐processed organic photodiode is fully integrated in a silicon system.
Quantifying the midsole material characteristics of athletic footwear is a standard task in footwear research and development. Current material testing protocols primarily focus on the determination of cushioning properties of the heel region or the quantification of the midsole properties as one assembly. However, midsoles possess different spatial material properties that have not been quantified from previous methodologies. Therefore, new material testing methods are required to quantify the local material response of athletic footwear. We developed a cyclical force-controlled material testing protocol for the determination of non-homogeneously distributed material stiffness with a high spatial resolution. In five prototype shoes varying in their stiffness distribution, we found that the material properties can be reliably measured across the midsole. Furthermore, we observed a characteristic non-linear material response regardless of the midsole location. We found that the material stiffness increased with an increase of the applied force and that this effect is further intensified by higher testing cycles. Additionally, the obtained midsole stiffness depends on the geometry of the midsole. We explored different approaches to reduce the measurement time of the testing protocol and found that the number of measurements can be reduced by 70% using 2 D-interpolation procedures. Determining the spatial material properties of midsoles needs to be considered to understand foot-shoe interactions. Furthermore, this measurement protocol can be used for quality control within the footwear and can be adapted for considering the effects of different running styles or speeds on ground force application characteristics.
Pure orbital blowout fractures occur within the confines of the internal orbital wall. Restoration of orbital form and volume is paramount to prevent functional and esthetic impairment. The anatomical peculiarity of the orbit has encouraged surgeons to develop implants with customized features to restore its architecture. This has resulted in worldwide clinical demand for patient-specific implants (PSIs) designed to fit precisely in the patient’s unique anatomy. Material extrusion or Fused filament fabrication (FFF) three-dimensional (3D) printing technology has enabled the fabrication of implant-grade polymers such as Polyetheretherketone (PEEK), paving the way for a more sophisticated generation of biomaterials. This study evaluates the FFF 3D printed PEEK orbital mesh customized implants with a metric considering the relevant design, biomechanical, and morphological parameters. The performance of the implants is studied as a function of varying thicknesses and porous design constructs through a finite element (FE) based computational model and a decision matrix based statistical approach. The maximum stress values achieved in our results predict the high durability of the implants, and the maximum deformation values were under one-tenth of a millimeter (mm) domain in all the implant profile configurations. The circular patterned implant (0.9 mm) had the best performance score. The study demonstrates that compounding multi-design computational analysis with 3D printing can be beneficial for the optimal restoration of the orbital floor.
Treadmills are essential to the study of human and animal locomotion as well as for applied diagnostics in both sports and medicine. The quantification of relevant biomechanical and physiological variables requires a precise regulation of treadmill belt velocity (TBV). Here, we present a novel method for time-efficient tracking of TBV using standard 3D motion capture technology. Further, we analyzed TBV fluctuations of four different treadmills as seven participants walked and ran at target speeds ranging from 1.0 to 4.5 m/s. Using the novel method, we show that TBV regulation differs between treadmill types, and that certain features of TBV regulation are affected by the subjects’ body mass and their locomotion speed. With higher body mass, the TBV reductions in the braking phase of stance became higher, even though this relationship differed between locomotion speeds and treadmill type (significant body mass × speed × treadmill type interaction). Average belt speeds varied between about 98 and 103% of the target speed. For three of the four treadmills, TBV reduction during the stance phase of running was more intense (> 5% target speed) and occurred earlier (before 50% of stance phase) unlike the typical overground center of mass velocity patterns reported in the literature. Overall, the results of this study emphasize the importance of monitoring TBV during locomotor research and applied diagnostics. We provide a novel method that is freely accessible on Matlab’s file exchange server (“getBeltVelocity.m”) allowing TBV tracking to become standard practice in locomotion research.
In recent years, physically unclonable functions (PUFs) have gained significant attraction in IoT security applications, such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of different devices to generate unique fingerprints for security applications. When generating PUF-based secret keys, the reliability and entropy of the keys are vital factors. This study proposes a novel method for generating PUF-based keys from a set of measurements. Firstly, it formulates the group-based key generation problem as an optimization problem and solves it using integer linear programming (ILP), which guarantees finding the optimum solution. Then, a novel scheme for the extraction of keys from groups is proposed, which we call positioning syndrome coding (PSC). The use of ILP as well as the introduction of PSC facilitates the generation of high-entropy keys with low error correction costs. These new methods have been tested by applying them on the output of a capacitor network PUF. The results confirm the application of ILP and PSC in generating high-quality keys.
Governments have restricted public life during the COVID-19 pandemic, inter alia closing sports facilities and gyms. As regular exercise is essential for health, this study examined the effect of pandemic-related confinements on physical activity (PA) levels. A multinational survey was performed in 14 countries. Times spent in moderate-to-vigorous physical activity (MVPA) as well as in vigorous physical activity only (VPA) were assessed using the Nordic Physical Activity Questionnaire (short form). Data were obtained for leisure and occupational PA pre- and during restrictions. Compliance with PA guidelines was calculated based on the recommendations of the World Health Organization (WHO). In total, n = 13,503 respondents (39 ± 15 years, 59% females) were surveyed. Compared to pre-restrictions, overall self-reported PA declined by 41% (MVPA) and 42.2% (VPA). Reductions were higher for occupational vs. leisure time, young and old vs. middle-aged persons, previously more active vs. less active individuals, but similar between men and women. Compared to pre-pandemic, compliance with WHO guidelines decreased from 80.9% (95% CI: 80.3–81.7) to 62.5% (95% CI: 61.6–63.3). Results suggest PA levels have substantially decreased globally during the COVID-19 pandemic. Key stakeholders should consider strategies to mitigate loss in PA in order to preserve health during the pandemic.
Time-Sensitive Networking (TSN) is the most promising time-deterministic wired communication approach for industrial applications. To extend TSN to "IEEE 802.11" wireless networks two challenging problems must be solved: synchronization and scheduling. This paper is focused on the first one. Even though a few solutions already meet the required synchronization accuracies, they are built on expensive hardware that is not suited for mass market products. While next Wi-Fi generation might support the required functionalities, this paper proposes a novel method that makes possible high-precision wireless synchronization using commercial low-cost components. With the proposed solution, a standard deviation of synchronization error of less than 500 ns can be achieved for many use cases and system loads on both CPU and network. This performance is comparable to modern wired real-time field busses, which makes the developed method a significant contribution for the extension of the TSN protocol to the wireless domain.
A Review on Kinetic Energy Harvesting with Focus on 3D Printed Electromagnetic Vibration Harvesters
(2021)
The increasing amount of Internet of Things (IoT) devices and wearables require a reliable energy source. Energy harvesting can power these devices without changing batteries. Three-dimensional printing allows us to manufacture tailored harvesting devices in an easy and fast way. This paper presents the development of hybrid and non-hybrid 3D printed electromagnetic vibration energy harvesters. Various harvesting approaches, their utilised geometry, functional principle, power output and the applied printing processes are shown. The gathered harvesters are analysed, challenges examined and research gaps in the field identified. The advantages and challenges of 3D printing harvesters are discussed. Reported applications and strategies to improve the performance of printed harvesting devices are presented.
It is important to minimize the unscheduled downtime of machines caused by outages of machine components in highly automated production lines. Considering machine tools such as, grinding machines, the bearing inside of spindles is one of the most critical components. In the last decade, research has increasingly focused on fault detection of bearings. In addition, the rise of machine learning concepts has also intensified interest in this area. However, up to date, there is no single one-fits-all solution for predictive maintenance of bearings. Most research so far has only looked at individual bearing types at a time.
This paper gives an overview of the most important approaches for bearing-fault analysis in grinding machines. There are two main parts of the analysis presented in this paper. The first part presents the classification of bearing faults, which includes the detection of unhealthy conditions, the position of the error (e.g. at the inner or at the outer ring of the bearing) and the severity, which detects the size of the fault. The second part presents the prediction of remaining useful life, which is important for estimating the productive use of a component before a potential failure, optimizing the replacement costs and minimizing downtime.
We present a densitometric quantification method for triclosan in toothpaste, separated by high-performance thin-layer chromatography (HPTLC) and using a 48-bit flatbed scanner as the detection system. The sample was band-wise applied to HPTLC plates (10 × 20 cm), with fluorescent dye, Merck, Germany (1.05554). The plates were developed in a vertical developing chamber with 20 min of chamber saturation over 70 mm, using n-heptane–methyl tert-butyl ether–acetic acid (92:8:0.1, V/V) as solvent. The RF value of triclosan is hRF = 22.4, and quantification is based on direct measurements using an inexpensive 48-bit flatbed scanner for color measurements (in red, green, and blue) after plate staining with 2,6-dichloroquinone-4-chloroimide (Gibbs' reagent). Evaluation of the red channel makes the measurements of triclosan very specific. For linearization, an extended Kubelka–Munk expression was used for data transformation. The range of linearity covers more than two orders of magnitude and is between 91 and 1000 ng. The separation method is inexpensive, fast and reliable.
We present a video-densitometric high-performance thin-layer chromatography (HPTLC) quantification method for patulin in apple juice, developed in a vertical chamber from the starting point to a distance of 50 mm, using MTBE, n-pentane (9 + 5, v/v) as mobile phase. After separation the plate is sprayed with methyl-benzothiazolinone hydrazone hydrochloride monohydrate (MBTH) solution (40 mg in 20 mL methanol) and heated at 105 °C for 15 min. Patulin zones are transformed into yellow spots. The quantification is based on direct measurements using an inexpensive 48-bit flatbed scanner for color measurements (in red, green, and blue). Evaluation of the blue channel makes the measurements very specific. Quantification in fluorescence was also done by use of a 16-bit CCD-camera and UV-366 nm illumination as well as using a HPTLC DAD-scanner. For linearization the extended Kubelka–Munk expression for data transformation was used. The range of linearity covers more than two magnitudes and lies between 5 and 800 ng patulin. The extraction of 20 g apple juice and an extract application on plate up to 50 µL allows statistically defined checking the limit of detection (LOD) of 50 ng patulin per track, which is equivalent to 50 µg patulin per kg apple juice.
Surface acoustic waves are propagated toward the edge of an anisotropic elastic medium (a silicon crystal), which supports leaky waves with a high degree of localization at the tip of the edge. At an angle of incidence corresponding to phase matching with this leaky wedge wave, a sharp peak in the reflection coefficient of the surface wave was found. This anomalous reflection is associated with efficient excitation of the leaky wedge wave. In laser ultrasound experiments, surface acoustic wave pulses were excited and their reflection from the edge of the sample and their partial conversion into leaky wedge wave pulses was observed by optical probe-beam deflection. The reflection scenario and the pulse shapes of the surface and wedge-localized guided waves, including the evolution of the acoustic pulse traveling along the edge, have been confirmed in detail by numerical simulations.
IoT-Plattformen stellen ein zentrales Element für die Vernetzung von physischen Objekten und die Bereitstellung deren Daten für digitale Zwillinge dar. Der Markt für solche Plattformen ist in den vergangenen Jahren stark gewachsen. Bei inzwischen über 600 Anbietern ist die Wahl der „richtigen“ Plattform für das eigene Unternehmen keine triviale Aufgabe mehr. Dieser Beitrag soll Unternehmen im Auswahlprozess unterstützen, indem gängige Funktionen von IoT-Plattformen und Kriterien für die Auswahl von IoT-Plattformen aufgezeigt werden.
Cyclic micro-bending tests on fcc single crystal Ni-base Alloy 718 cantilevers with different crystal orientations were performed to analyze the influence of activated slip systems on dislocation plasticity, latent hardening and the Bauschinger effect. The investigations indicate that plasticity in single crystal micro-cantilevers is significantly influenced by two phenomena - dislocation interaction and dislocation pile-up at the neutral plane. Both phenomena occur at the same time. Their ratio seems to be determined by the activated slip systems. Slip trace analysis indicates that the activation of only one slip system leads to a strong localization of plasticity to a limited number of parallel slip bands. This results in low dislocation interaction and consequently pronounced pile-ups at the neutral plane. In multi slip orientation, the second slip system leads to activation of significantly more dislocation sources, causing a much earlier and more homogeneous elastic-plastic transition zone. In stress-strain hysteresis loops during bending, pronounced dislocation interaction in multi slip orientation leads to a more pronounced latent hardening. The results suggest that on a microstructural length scale, plasticity behavior is strongly affected by activated slip systems, which determine local dislocation phenomena. Based on the results presented in this paper, a finite element analysis of latent hardening and the Bauschinger effect using a single crystal plasticity model with latent kinematic hardening is presented in Part II.
In the last decade, deep learning models for condition monitoring of mechanical systems increasingly gained importance. Most of the previous works use data of the same domain (e.g., bearing type) or of a large amount of (labeled) samples. This approach is not valid for many real-world scenarios from industrial use-cases where only a small amount of data, often unlabeled, is available.
In this paper, we propose, evaluate, and compare a novel technique based on an intermediate domain, which creates a new representation of the features in the data and abstracts the defects of rotating elements such as bearings. The results based on an intermediate domain related to characteristic frequencies show an improved accuracy of up to 32 % on small labeled datasets compared to the current state-of-the-art in the time-frequency domain.
Furthermore, a Convolutional Neural Network (CNN) architecture is proposed for transfer learning. We also propose and evaluate a new approach for transfer learning, which we call Layered Maximum Mean Discrepancy (LMMD). This approach is based on the Maximum Mean Discrepancy (MMD) but extends it by considering the special characteristics of the proposed intermediate domain. The presented approach outperforms the traditional combination of Hilbert–Huang Transform (HHT) and S-Transform with MMD on all datasets for unsupervised as well as for semi-supervised learning. In most of our test cases, it also outperforms other state-of-the-art techniques.
This approach is capable of using different types of bearings in the source and target domain under a wide variation of the rotation speed.
There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.
Objective: To quantify the effect of inhaled 5% carbon-dioxide/95% oxygen on EEG recordings from patients in non-convulsive status epilepticus (NCSE).
Methods: Five children of mixed aetiology in NCSE were given high flow of inhaled carbogen (5% carbon dioxide/95% oxygen) using a face mask for maximum 120s. EEG was recorded concurrently in all patients. The effects of inhaled carbogen on patient EEG recordings were investigated using band-power, functional connectivity and graph theory measures. Carbogen effect was quantified by measuring effect size (Cohen's d) between "before", "during" and "after" carbogen delivery states.
Results: Carbogen's apparent effect on EEG band-power and network metrics across all patients for "before-during" and "before-after" inhalation comparisons was inconsistent across the five patients.
Conclusion: The changes in different measures suggest a potentially non-homogeneous effect of carbogen on the patients' EEG. Different aetiology and duration of the inhalation may underlie these non-homogeneous effects. Tuning the carbogen parameters (such as ratio between CO2 and O2, duration of inhalation) on a personalised basis may improve seizure suppression in future.