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We investigate the influence of the geometry and doping level on the performance of n-type silicon nanowire field emitters on silicon pillar structures. Therefore, multiple cathodes with 50 by 50 pillar arrays (diameter: 5 μm, height: 30 μm, spacing: 50 μm) were fabricated and measured in diode configuration. In the first experiment, we compared two geometry types using the same material. Geometry 1 is black silicon, which is a highly dense surface covering a forest of tightly spaced silicon needles resulting from self-masking during a plasma etching process of single crystal silicon. Geometry 2 are silicon nanowires, which are individual spaced-out nanowires in a crownlike shape resulting from a plasma etching process of single crystal silicon. In the second experiment, we compared two different silicon doping levels [n-type (P), 1–10 and <0.005 Ω cm] for the same geometry. The best performance was achieved with lower doped silicon nanowire samples, emitting 2 mA at an extraction voltage of 1 kV. The geometry/material combination with the best performance was used to assemble an integrated electron source. These electron sources were measured in a triode configuration and reached onset voltages of about 125 V and emission currents of 2.5 mA at extraction voltages of 400 V, while achieving electron transmission rates as high as 85.0%.
AbstractRegularized static friction models have been used successfully for many years. However, they are unable to maintain static friction in detail. For this reason, dynamic friction models have been developed and published in the literature. However, commercial multibody simulation packages such as Adams, RecurDyn, and Simpack have developed their own specific stick-slip models instead of adopting one of the public domain approaches. This article introduces the fundamentals of these commercial models and their behavior from a practical point of view. The stick-slip models were applied to a simple test model and a more sophisticated model of a festoon cable system using their standard parameters.
The human nose serves as the primary gateway for air entering the respiratory system and plays a vital role in breathing. Nasal breathing difficulties are a significant health concern, leading to substantial healthcare costs for patients. Understanding nasal airflow dynamics is crucial for comprehending respiratory mechanisms. This article presents a detailed study using tomo-Particle Image Velocimetry (PIV) to investigate nasal airflow dynamics while addressing its accuracy. Embedded in the OpenNose project, the work described aims to provide a validation basis for different numerical approaches to upper airway flow. The study includes the manufacturing of a transparent silicone model based on a clinical CT scan, refractive index matching to minimize optical distortions, and precise flow rate adjustments based on physiological breathing cycles. This method allows for spatial high-resolution investigations in different regions of interest within the nasopharynx during various phases of the breathing cycle. The results demonstrate the accuracy of the investigations, enabling detailed analysis of flow structures and gradients. This spatial high-resolution tomo-PIV approach provides valuable insights into the complex flow phenomena occurring during the physiological breathing cycle in the nasopharynx. The study's findings contribute to advancements in non-free-of-sight experimental flow investigation of complex cavities under nearly realistic conditions. Furthermore, reliable and accurate experimental data is crucial for properly validating numerical approaches that compute this patient-specific flow for clinical purposes.
Increasingly stringent emission limits have made particulate filters necessary for gasoline engines. Similar to diesel applications, gasoline particulate filters (GPFs) can be monitored by differential pressure measurement or by the radio-frequency-based filter diagnosis (RF sensor). In addition to measuring the soot loading, ash detection is critical for monitoring the GPF over the entire vehicle lifetime. Because the RF sensor detects the filter loading through a change in the dielectric properties of the GPF, it can detect not only soot but also ash. In diesel applications, the RF sensor has already demonstrated its potential for ash detection. To verify the feasibility of simultaneous ash and soot monitoring for GPFs, filters were loaded with ash on an engine test bench and measured on a lab test bench under defined synthetic exhaust gas conditions. By evaluating resonant modes, soot and ash could be clearly distinguished, as ash mainly affects the resonant frequency, while soot also changes the quality factor due to its high dielectric losses. However, higher soot loadings could not be detected by the resonant parameters, but instead by a frequency-averaged transmission signal. While the presence of ash caused an offset in this signal, its sensitivity to soot was not affected. Thus, the influence of ash can be corrected if the signal in the soot-free filter state is known, e.g., from the behavior of the resonant parameters. Therefore, even with a continuously increasing ash loading over the lifetime of a vehicle, an accurate soot detection is possible with the RF sensor.
In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position and type of instruments is of great interest. Current work involves both spatial and temporal information, with the idea that predicting the movement of surgical tools over time may improve the quality of the final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify and characterize datasets used for method development and evaluation and quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images and videos. The paper focuses on methods that work purely visually, without markers of any kind attached to the instruments, considering both single-frame semantic and instance segmentation approaches, as well as those that incorporate temporal information. The publications analyzed were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were “instrument segmentation”, “instrument tracking”, “surgical tool segmentation”, and “surgical tool tracking”, resulting in a total of 741 articles published between 01/2015 and 07/2023, of which 123 were included using systematic selection criteria. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing the available potential for future developments.
In fatigue strength assessment, the methods based on ideal elastic stresses according to Basquin and the less established method based on elastic-plastic stress quantities according to Manson, Coffin and Morrow are applied. The former calculates loads using linear-elastic stresses, the latter requires elasticplastic evaluation parameters, such as stresses and strains. These can be determined by finite element analysis (FEA) with a linear-elastic constitutive law, and subsequent conversion to elastic-plastic loads, using the macro support formula by Neuber. In this contribution, an alternative approach to approximate elastic-plastic parameters proposed by Glinka is compared to the the strain-life method using Neuber's formula, as well as the stress-life method of Basquin. Several component tests on 42CrMoS4-QT specimens are investigated. To determine the input data for the fatigue strength evaluations, the entire test setup is computed by FEA. The nodal displacements from these validated full-model simulations are used as boundary conditions for a submodel simulation of a notch, whose results serve as input for the fatigue strength assessments. It is shown that all approaches provide a reliable assessment of components. Our key result is that the strain-life method using the concept by Glinka for notch stress computation, yields improved results in fatigue strength assessments.
Although magnesium and its alloys are promising candidates as biodegradable implant materials, the tendency for localized corrosion mechanism in physiological environment limit their biomedical application. Electropolishing is an attractive strategy for improving the corrosion behaviour of metals, but it is still largely unexplored in magnesium materials. In this study, the characterization of electropolished surfaces of AM50 and pure magnesium was performed, focussing on their in vitro degradation behaviour in cell medium. Corrosion rates were evaluated using potentiodynamic polarisation. The surface morphology before and after the onset of corrosion was investigated by scanning electron microscopy and confocal laser scanning microscopy. The presented electropolishing process led to improved surface performances, observable by significantly lower corrosion rates (0.08 mm·year-1 in Dulbecco's modified Eagle's medium), lower arithmetical mean height (0.05 µm), lower water contact angle (25-35°) and lower micro hardness (35-50 HV 0.1) compared to mechanically and chemically treated surfaces. MgO/Mg(OH)2 could be detected on electropolished surfaces. The localized corrosion mode could be reduced, but not entirely prevented. Electropolishing shows great potential as post-treatment of magnesium-based components, but detailed tests of the long-term corrosion behaviour are an important area of future research.
Commercially available contact angle (CA) measuring devices usually do not allow for the application of magnetic fields to the sample under test. A setup for measuring the CA of liquids on magnetosensitive surfaces has been developed specifically for investigating the surfaces of magnetoactive elastomers (MAEs). The addition of a programmable linear stage, which moves a permanent magnet, allows for fine control of the magnetic field applied to the MAE without the need for large and power-consuming electromagnets. Paired with a custom control and evaluation software, this measurement setup operates semiautomatically, limiting operator error and increasing precision, speed, as well as repeatability of static and dynamic CA measurements for different magnetoactive materials. The software is equipped with robust droplet fitting algorithms to avoid experimental challenges arising with soft magnetoactive materials, such as the curling of sample edges or diffuse non-reflective surfaces. Several application examples on MAE surfaces, both processed and unprocessed, are presented.
Eine Herausforderung performancebasierter Prüfverfahren zur Bewertung der Dauerhaftigkeit ist die Beschleunigung natürlicher Mechanismen. Dies ist notwendig, um innerhalb kurzer Zeit die Langzeit-Leistungsfähigkeit ermitteln zu können. Die Bestimmung der Frost-Tausalzbeständigkeit von Beton kann durch den CDF-Test erfolgen, welcher für Betone mit ausreichendem Frost-Tausalz-Widerstand sehr gut funktioniert. Bei Proben mit einer unzureichenden bzw. unbekannten Performance können erhöhte Randabwitterungen auftreten, welche durch das Ablösen des seitlichen Abdichtbands entstehen. Der zunehmende Randeinfluss führt so zu einer Verfälschung der Ergebnisse und zu einer Unterschätzung der tatsächlichen Performance des Bauteils. In diesem Beitrag werden Mörtel- und Betonprobekörper mit unterschiedlichen Abwitterungsraten in Anlehnung an das CDF-Verfahren untersucht. Zusätzlich wird die Oberflächenschädigung der Proben anhand einer neuartigen Messmethode mittels hochauflösendem 3D-Laserscanning ausgewertet. Die Ergebnisse zeigen, dass die Randeffekte mit der Laserscan-Methode umgangen und vergleichbare Ergebnisse zu den CDF-Untersuchungen erzielt werden können. Somit können Betone ohne Randeinflüsse charakterisiert und eine präzise Prognose der Langzeitbeständigkeit getroffen werden.
Die Carbonatisierung von Beton kann einerseits zu Schäden bei Stahlbetonbauwerken führen, andererseits kann der Beton so CO2 speichern und damit seinen CO2-Fußabdruck verringern. In diesem Beitrag wird dargestellt, wie eine effiziente Beschleunigung der Carbonatisierung durch Anlegen eines geringen äußeren Drucks erreicht werden kann. Damit wird neben der Diffusion der wesentlich schneller ablaufende Transportmechanismus der Permeation ausgenutzt, der das CO2 tiefer in das Probeninnere transportiert und damit in kurzer Zeit die Bestimmung des Carbonatisierungswiderstand zementgebundener Materialien ermöglicht. Hierzu wurde eine Prüfeinrichtung entwickelt, die es ermöglicht, die CO2-Konzentration und in gewissen Grenzen auch relative Luftfeuchte sowie die Temperatur gezielt einzustellen und zu steuern, um so Mörtel- und Betonproben schnell und präzise zu carbonatisieren. Der Einfluss verschiedener Druckstufen und Wechselzyklen wird dargelegt und die resultierenden chemischen und physikalischen Veränderungen der Proben bestimmt. Als besonders effizient und gleichzeitig realitätsnah erwies sich die konstante CO2-Beaufschlagung mit 3 Vol.-% CO2 mit zusätzlichem, moderatem Gasdruck. Das hier entwickelte Verfahren kann daher genutzt werden, um Betone schnell und effizient in zeitraffenden Materialtests hinsichtlich Carbonatisierungswiderstand zu charakterisieren.