Study on the Mechanism of Solid-Phase Oxidant Action in Tribochemical Mechanical Polishing of SiC Single Crystal Substrate

Na2CO3—1.5 H2O2, KClO3, KMnO4, KIO3, and NaOH were selected for dry polishing tests with a 6H-SiC single crystal substrate on a polyurethane polishing pad. The research results showed that all the solid-phase oxidants, except NaOH, could decompose to produce oxygen under the frictional action. After polishing with the five solid-phase oxidants, oxygen was found on the surface of SiC, indicating that all five solid-phase oxidants can have complex tribochemical reactions with SiC. Their reaction products are mainly SiO2 and (SiO2)x. Under the action of friction, due to the high flash point temperature of the polishing interface, the oxygen generated by the decomposition of the solid-phase oxidant could oxidize the surface of SiC and generate a SiO2 oxide layer on the surface of SiC. On the other hand, SiC reacted with H2O and generated a SiO2 oxide layer on the surface of SiC. After polishing with NaOH, the SiO2 oxide layer and soluble Na2SiO3 could be generated on the SiC surface; therefore, the surface material removal rate (MRR) was the highest, and the surface roughness was the largest, after polishing. The lowest MRR was achieved after the dry polishing of SiC with KClO3.

Framework for the Machine Learning Based Wireless Sensing of the Electromagnetic Properties of Indoor Materials

Available digital maps of indoor environments are limited to a description of the geometrical environment, despite there being an urgent need for more accurate information, particularly data about the electromagnetic (EM) properties of the materials used for walls. Such data would enable new possibilities in the design and optimization of wireless networks and the development of new radio services. In this paper, we introduce, formalize, and evaluate a framework for machine learning (ML) based wireless sensing of indoor surface materials in the form of EM properties. We apply the radio-environment (RE) signatures of the wireless link, which inherently contains environmental information due to the interaction of the radio waves with the environment. We specify the content of the RE signature suitable for surface-material classification as a set of multipath components given by the received power, delay, phase shift, and angle of arrival. The proposed framework applies an ML approach to construct a classification model using RE signatures labeled with the environmental information. The ML method exploits the data obtained from measurements or simulations. The performance of the framework in different scenarios is evaluated based on standard ML performance metrics, such as classification accuracy and F-score. The results of the elementary case prove that the proposed approach can be applied for the classification of the surface material for a plain environment, and can be further extended for the classification of wall materials in more complex indoor environments.

ENSURING TIGHTNESS IN PRESSURE COUPLING PARTS

Work objective is to solve the urgent problem of increasing the tightness and reliability of pressure couplings during their operation under dynamic loads. Theoretical and experimental studies assessing the impact on the tightness due to roughness nature of mating surfaces and three types of coatings: soft, double-layer and hard have been undertaken. The joints were tested under the influence of axial cyclic load and torque on a bench for accelerated testing. It is established that tightness of pressure couplings during operation under dynamic loads significantly depends on the parameters of microgeometry and physical and mechanical properties of the mating surface material that determine their actual contact area. Recommendations for preparing the surfaces of parts before pressure coupling assembling have been developed. It is proved that the use of regular microrelief and soft galvanic coatings of mating surfaces have a significant effect on the tightness of pressure couplings.

Influence of surface material and reprocessing on the durability of antimicrobial surfaces

The risk of infection from contaminated surfaces has already been shown in several publications. Due to the increased demand for optimized infection control measures during the Corona pandemic, antimicrobial surface technologies have gained more an interest. Apart from many proofs of efficacy, there are only a few studies dealing with the durability of these surface coatings with regard to the material and the reprocessing measures. This work did therefore examine the impact of different materials and surface textures, as well as different detergents and disinfectants, on the durability of antimicrobial surface technologies. Differently structured materials (glass, wood, plastics, metal) and wallpaper bonded to plasterboard were coated with an TiO2Ag based antimicrobial coating (HECOSOL GmbH, Bamberg). These test samples are then used to perform abrasion tests with various cleaning and disinfecting agents and cloth systems (microfiber cloth, cotton cloth, foam cloth). The majority of the test samples in our experimental setup showed at least significant activity. According to our results, both the selection of cleaning and disinfection methods including wiping systems and the surface material have a major impact on the durability of antimicrobial coatings. In order to be able to come to conclusions about the long-term activity of these surface technologies, the effectiveness should be tested not only during the development phase, but also in the finished product and again after several reprocessing cycles in use.

Water Film Depth Prediction Model for Highly Textured Pavement Surface Drainage

Water film depth (WFD) is an important factor for road traffic safety because of its direct connection with skid resistance, hydroplaning speed, and the tendency of splash and spray. Increasing the pavement macrotexture reduces WFD. However, existing models for WFD prediction have not been developed on highly textured surfaces such as chip seal. Furthermore, the rainfall intensities used for developing most of these models were relatively low, leaving no or low WFD on chip seal surfaces. To propose a WFD prediction model suitable for highly textured surfaces and to consider the effect of surface material type, an experimental study was conducted with 154 different combinations of mean texture depth (MTD), surface material type, surface slope, drainage length, and rainfall intensity. The tests were carried out on chip seal specimens using a full-scale rainfall simulator. Test results from 1,784 WFD readings indicated that the Gallaway and PAVDRN models were not accurate for highly textured surfaces used in this study with MTD ranging from 0.05 to 0.20 in. Two experimental models were, therefore, proposed to predict the WFD; both models displayed a significantly higher correlation between the measured and predicted WFD compared with the existing models. Furthermore, the eco-friendly rubberized chip seal showed an enhanced drainage capability compared with conventional chip seal, especially in low slopes, because of the hydrophobic nature of crumb rubber versus the hydrophilic character of mineral aggregates. Accordingly, the proposed model incorporated a term to consider the effect of surface material type.

Design of bidirectional frictional behaviour for tactile contact using ellipsoidal asperity micro-textures

Tactile perception and friction can be modified by producing a deterministic surface topography. Change of surface feature arrangement and texture symmetry can produce an anisotropic frictional behaviour. It is generally achieved through skin hysteresis by promoting its deformation. This work investigates whether a bidirectional friction can be created with microscale ellipsoidal asperity textures, thus relying on the adhesive component of friction. For this purpose, four textured samples with various asperity dimensions were moulded with a silicone rubber having an elastic modulus comparable to that of the skin. Coefficient of friction measurements were conducted in-vivo in two sliding directions with a range of normal loads up to 4 N. Finite element method (FEM) was used to study elastic deformation effects, explain the observed friction difference, and predict surface material influence. Measurements performed perpendicular to the asperity major radii showed consistently higher friction coefficients than that during parallel sliding. For the larger asperity dimensions, a change of the sliding direction increased friction up to a factor of 2. The numerical analysis showed that this effect is mostly related to elastic asperity deflection. Bidirectional friction differences can be further controlled by asperity dimensions, spacing, and material properties.

Influence of the Surface Material and Illumination upon the Performance of a Microelectrode/Electrolyte Interface in Optogenetics

Integrated optrodes for optogenetics have been becoming a significant tool in neuroscience through the combination of offering accurate stimulation to target cells and recording biological signals simultaneously. This makes it not just be widely used in neuroscience researches, but also have a great potential to be employed in future treatments in clinical neurological diseases. To optimize the integrated optrodes, this paper aimed to investigate the influence of surface material and illumination upon the performance of the microelectrode/electrolyte interface and build a corresponding evaluation system. In this work, an integrated planar optrode with a blue LED and microelectrodes was designed and fabricated. The charge transfer mechanism on the interface was theoretically modeled and experimentally verified. An evaluation system for assessing microelectrodes was also built up. Using this system, the proposed model of various biocompatible surface materials on microelectrodes was further investigated under different illumination conditions. The influence of illumination on the microelectrode/electrolyte interface was the cause of optical artifacts, which interfere the biological signal recording. It was found that surface materials had a great effect on the charge transfer capacity, electrical stability and recoverability, photostability, and especially optical artifacts. The metal with better charge transfer capacity and electrical stability is highly possible to have a better performance on the optical artifacts, regardless of its electrical recoverability and photostability under the illumination conditions of optogenetics. Among the five metals used in our investigation, iridium served as the best surface material for the proposed integrated optrodes . Thus, optimizing the surface material for optrodes could reduce optical interference, enhance the quality of the neural signal recording for optogenetics, and thus help to advance the research in neuroscience.