This review describes an in-depth overview and knowledge on the variety of synthetic strategies for forming metal sulfides and their potential use to achieve effective hydrogen generation and beyond.
Abstract Dielectric elastomers are of interest for actuator applications due to their large actuation strain, high bandwidth, high energy density, and their flexible nature. If future dielectric elastomers are to be used reliably in applications that include soft robotics, medical devices, artificial muscles, and electronic skins, there is a need to design devices that are tolerant to electrical and mechanical damage. In this paper, the first report of self‐healing of both electrical breakdown and mechanical damage in dielectric actuators using a thermoplastic methyl thioglycolate–modified styrene–butadiene–styrene (MGSBS) elastomer is provided. The self‐healing functions are examined from the material to device level by detailed examination of the healing process, and characterization of electrical properties and actuator response before and after healing. It is demonstrated that after dielectric breakdown, the initial dielectric strength can be recovered by up to 67%, and after mechanical damage, a 39% recovery can be achieved with no degradation of the strain–voltage response of the actuators. The elastomer can also heal a combination of mechanical and electrical failures. This work provides a route to create robust and damage tolerant dielectric elastomers for soft robotic and other applications related to actuator and energy‐harvesting systems.
A 3 × 3 hydrophone array for low frequency applications was constructed from reticulated PZT ceramic foams. The hydrophone array was tested for receiving sensitivity and compared with single element PZT-air and dense PZT hydrophones. The composite array showed a flat response in the 20 kHz–100 kHz frequency range while the single element hydrophone displayed broadening radial resonance around 50 kHz. The flat, broadband response indicates that the radial resonance is suppressed by both porous nature of the PZT-air composites and the array construction of the hydrophone. The sensitivity of the array hydrophone was –205 dB re 1 Vμ Pa−1.
The coupling of photovoltaic and pyroelectric effects is a common phenomenon in ferroelectric films and often results in coupling enhancements. Although the coupling effects of a variety of ferroelectric films have been examined in terms of improved performance, they have yet to be quantitatively ranked and assessed. Here, by taking the charge coupling factor, the Yang's charge, and output energy as metrics to evaluate the coupling performance, a methodology is developed for evaluating the performance of a range ferroelectric films when the pyroelectric and photovoltaic effects are coupled. By experimentally measuring and quantitatively ranking the evaluation metrics, the influence of coupling effects on the output charge and the energy harvesting capabilities of various ferroelectric films can be readily visualized. In addition, the analysis of the underlying reasons for the coupling enhancement enables optimization of the methods to quantify the charge coupling factor. This work provides a unique reference for the selection of materials, optimization of performance, and energy harvesting for coupled ferroelectric film-based generators.
Objective Neurodegenerative diseases affect millions of families around the world, while various wearable sensors and corresponding data analysis can be of great support for clinical diagnosis and health assessment. This systematic review aims to provide a comprehensive overview of the existing research that uses wearable sensors and features for the diagnosis of neurodegenerative diseases. Methods A systematic review was conducted of studies published between 2015 and 2022 in major scientific databases such as Web of Science, Google Scholar, PubMed, and Scopes. The obtained studies were analyzed and organized into the process of diagnosis: wearable sensors, feature extraction, and feature selection. Results The search led to 171 eligible studies included in this overview. Wearable sensors such as force sensors, inertial sensors, electromyography, electroencephalography, acoustic sensors, optical fiber sensors, and global positioning systems were employed to monitor and diagnose neurodegenerative diseases. Various features including physical features, statistical features, nonlinear features, and features from the network can be extracted from these wearable sensors, and the alteration of features toward neurodegenerative diseases was illustrated. Moreover, different kinds of feature selection methods such as filter, wrapper, and embedded methods help to find the distinctive indicator of the diseases and benefit to a better diagnosis performance. Conclusions This systematic review enables a comprehensive understanding of wearable sensors and features for the diagnosis of neurodegenerative diseases.
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