Piezoelectric Sensors Operating at Very High Temperatures and in Extreme Environments Made of Flexible Ultrawide-Bandgap Single-Crystalline AlN Thin Films

Extreme environments are often faced in energy, transportation, aerospace, and defense applications and pose a technical challenge in sensing. Piezoelectric sensor based on single-crystalline AlN transducers is developed to address this challenge. The pressure sensor shows high sensitivities of 0.4–0.5 mV per psi up to 900 °C and output voltages from 73.3 to 143.2 mV for input gas pressure range of 50 to 200 psi at 800 °C. The sensitivity and output voltage also exhibit the dependence on temperature due to two origins. A decrease in elastic modulus (Young's modulus) of the diaphragm slightly enhances the sensitivity and the generation of free carriers degrades the voltage output beyond 800 °C, which also matches with theoretical estimation. The performance characteristics of the sensor are also compared with polycrystalline AlN and single-crystalline GaN thin films to investigate the importance of single crystallinity on the piezoelectric effect and bandgap energy-related free carrier generation in piezoelectric devices for high-temperature operation. The operation of the sensor at 900 °C is amongst the highest for pressure sensors and the inherent properties of AlN including chemical and thermal stability and radiation resistance indicate this approach offers a new solution for sensing in extreme environments.     

A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems

The metaheuristic optimization algorithms are relatively new optimization algorithms introduced to solve optimization problems in recent years. For example, the firefly algorithm (FA) is one of the metaheuristic algorithms inspired by the fireflies' flashing behavior. However, its weakness in terms of exploration and early convergence has been pointed out. In this paper, two approaches were proposed to improve the FA. In the first proposed approach, a new improved opposition-based learning FA (IOFA) method was presented to accelerate the convergence and improve the FA's exploration capability. In the second proposed approach, a symbiotic organisms search (SOS) algorithm improved the exploration and exploitation of the first approach; two new parameters set these two goals, and the second approach was named IOFASOS. The purpose of the second method is that in the process of the SOS algorithm, the whole population is effective in the IOFA method to find solutions in the early stages of implementation, and with each iteration, fewer solutions are affected in the population. The experiments on 24 standard benchmark functions were conducted, and the first proposed approach showed a better performance in the small and medium dimensions and exhibited a relatively moderate performance in the higher dimensions. In contrast, the second proposed approach was better in increasing dimensions. In general, the empirical results showed that the two new approaches outperform other algorithms in most mathematical benchmarking functions. Thus, The IOFASOS model has more efficient solutions.

     

Evidential reasoning using extended fuzzy Dempster–Shafer theory for handling various facets of information deficiency

This work investigates the problem of combining deficient evidence for the purpose of quality assessment. The main focus of the work is modeling vagueness, ambiguity, and local nonspecificity in information within a unified approach. We introduce an extended fuzzy Dempster–Shafer scheme based on the simultaneous use of fuzzy interval‐grade and interval‐valued belief degree (IGIB). The latter facilitates modeling of uncertainties in terms of local ignorance associated with expert knowledge, whereas the former allows for handling the lack of information on belief degree assignments. Also, generalized fuzzy sets can be readily transformed into the proposed fuzzy IGIB structure. The reasoning for quality assessment is performed by solving nonlinear optimization problems on fuzzy Dempster–Shafer paradigm for the fuzzy IGIB structure. The application of the proposed inference method is investigated by designing a reasoning scheme for water quality monitoring and validated through the experimental data available for different sampling points in a water distribution network. © 2011 Wiley Periodicals, Inc.     

Fabrication of circular microfluidic channels through grayscale dual-projection lithography

Circular microfluidic channels are in great demand since they are more realistic in mimicking physiological flow systems, generating axis-symmetrical flow, and achieving uniform shear stress. A typical microchannel with rectangular cross section can induce non-physiological gradients of shear rate, pressure, and velocity. This paper presents a novel method of fabricating microfluidic channels with circular and elliptical cross sections through grayscale dual-projection lithography. Our method utilizes two projecting systems to expose grayscale image face-to-face and simultaneously polymerize the photocurable material. The cross-sectional profiles of the fabricated microchannels are consistent with mathematical predictions and, therefore, demonstrate the capability of controlling the channel shapes precisely. Customized circular microchannels can be generated with complex features such as junctions, bifurcations, hierarchies, and gradually changed diameters. This method is capable of fabricating circular channels with a wide range of diameters (39 μm–2 mm) as well as elliptical channels with a major-to-minor axis ratio up to 600%. Microfluidic devices with circular cross sections suitable for particle analysis were made as a demonstrative application in nanoparticle binding and distribution within a mimetic blood vessel. A ready-to-use microfluidic device with customized circular channels can be fabricated within 1 h without the need of clean room or expensive photolithography devices.     

A General Framework for Trajectory Triangulation

The multiple view geometry of static scenes is now well understood. Recently attention was turned to dynamic scenes where scene points may move while the cameras move. The triangulation of linear trajectories is now well handled. The case of quadratic trajectories also received some attention. We present a complete generalization and address the problem of general trajectory triangulation of moving points from non-synchronized cameras. Two cases are considered: (i) the motion is captured in the images by tracking the moving point itself, (ii) the tangents of the motion only are extracted from the images. The first case is based on a new representation (to computer vision) of curves (trajectories) where a curve is represented by a family of hypersurfaces in the projective space ?⁵. The second case is handled by considering the dual curve of the curve generated by the trajectory. In both cases these representations of curves allow: (i) the triangulation of the trajectory of a moving point from non-synchronized sequences, (ii) the recovery of more standard representation of the whole trajectory, (iii) the computations of the set of positions of the moving point at each time instant an image was made. Furthermore, theoretical considerations lead to a general theorem stipulating how many independent constraints a camera provides on the motion of the point. This number of constraint is a function of the camera motion. On the computation front, in both cases the triangulation leads to equations where the unknowns appear linearly. Therefore the problem reduces to estimate a high-dimensional parameter in presence of heteroscedastic noise. Several method are tested.     

Pore-network modeling of liquid water flow in gas diffusion layers of proton exchange membrane fuel cells

Fluid flow through the gas diffusion layer (GDL) of fuel cells is numerically studied using a pore network modeling approach. The model is developed based on an experimental visualization technique (fluorescence microscopy). The images obtained from this technique are analyzed to find patterns of flow inside the GDL samples with different hydrophobicity. Three different flow patterns are observed: initial invasion, progression, and pore-filling. The observation shows that liquid water flows into the majority of available pores on the boundary of the untreated GDL and several branches are segregated from the initial pathways. For the treated GDL, however, a handful of boundary pores are invaded and the original pathways extend toward the other side of the medium with minimum branching. The numerical model, developed based on an invasion percolation algorithm, is used to study the effects of GDL hydrophobicity and thickness on the flow configuration and breakthrough time as well as to determine the flow rate and saturation in different GDL samples. During the injection of water into the samples, it is numerically shown that the flow rates are monotonically decreasing for both treated and untreated samples. For the treated sample, however, the injection flow rate is constantly lower than that of the untreated sample, resulting in a lower overall water saturation at breakthrough. The numerical results also suggest that hydrophobic treatment of thick samples has minor effects on water management and overall performance. The developed model can be used to optimize the GDL properties for designing porous medium with effective transport characteristics.     

Thermodiffusion‐Assisted Pyroelectrics—Enabling Rapid and Stable Heat and Radiation Sensing

Sensors for monitoring temperature, heat flux, and thermal radiation are essential for applications such as electronic skin. While pyroelectric and thermoelectric effects are suitable candidates as functional elements in such devices, both concepts show individual drawbacks in terms of zero equilibrium signals for pyroelectric materials and small or slow response of thermoelectric materials. Here, these drawbacks are overcome by introducing the concept of thermodiffusion‐assisted pyroelectrics, which combines and enhances the performance of pyroelectric and ionic thermoelectric materials. The presented integrated concept provides both rapid initial response upon heating and stable synergistically enhanced signals upon prolonged exposure to heat stimuli. Likewise, incorporation of plasmonic metasurfaces enables the concept to provide both rapid and stable signals for radiation‐induced heating. The performance of the concept and its working mechanism can be explained by ion–electron interactions at the interface between the pyroelectric and ionic thermoelectric materials.     

The ETH‐MAV Team in the MBZ International Robotics Challenge

This study describes the hardware and software systems of the Micro Aerial Vehicle (MAV) platforms used by the ETH Zurich team in the 2017 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The aim was to develop robust outdoor platforms with the autonomous capabilities required for the competition, by applying and integrating knowledge from various fields, including computer vision, sensor fusion, optimal control, and probabilistic robotics. This paper presents the major components and structures of the system architectures and reports on experimental findings for the MAV‐based challenges in the competition. Main highlights include securing the second place both in the individual search, pick, and place the task of Challenge 3 and the Grand Challenge, with autonomous landing executed in less than 1 min and a visual servoing success rate of over for object pickups.