The rapid development of the Internet of Things (IoT) has tremendously increased the demands for wind speed sensors in various applications, such as weather forecasting and environmental monitoring. To date, many wind speed sensors are developed based on triboelectric nanogenerators (TENGs). However, the low output current leads to a poor sensing precision, which greatly limits their practical applications. Here, a wind speed sensor is proposed by integrating a wind-driven triboelectrification-induced electroluminescence (TIEL) component with a perovskite-based photodetector (PD) for enlarged electric current output. Compared with mechanoluminescence (ML), TIEL displays significantly higher signal intensity even under gentle breezes. In addition, the emission peak of TIEL matches with the absorption band of perovskite materials. Thus, TIEL materials are promising candidates for generating distinct electrical signals in real-time to facilitate the detection of wind speed. With a comparable detection limit (5 m s) to a conventional TENG-based wind speed sensor, the sensitivity of this hybrid sensor is three magnitudes higher at low bias voltages and, the response time is extremely short (<0.3 s). Moreover, it shows a favorable correlation with a commercial sensor. This research provides important progress toward environmentally-friendly light sources and TIEL-related sensor systems.
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http://dx.doi.org/10.1002/advs.201901980 | DOI Listing |
Sci Rep
January 2025
College of New Energy and Environment, Jilin University, Changchun, 130012, China.
Land use and land cover changes (LULCC) alter local surface attributes, thereby modifying energy balance and material exchanges, ultimately impacting meteorological parameters and air quality. The North China Plain (NCP) has undergone rapid urbanization in recent decades, leading to dramatic changes in land use and land cover. This study utilizes the 2020 land use and land cover data obtained from the MODIS satellite to replace the default 2001 data in the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model.
View Article and Find Full Text PDFCurr Biol
January 2025
Norwegian Institute for Nature Research (NINA), Trondheim 7034, Norway.
Understanding the movements of highly mobile animals is challenging because of the many factors they must consider in their decision-making. Many seabirds, for example, are adapted to use winds to travel long distances at low energetic cost but also potentially benefit from targeting specific foraging hotspots. To investigate how an animal makes foraging decisions, given the inevitable trade-off between these factors, we tracked over 600 foraging trips of breeding Manx shearwaters (Puffinus puffinus; N = 218 individuals) using GPS accelerometers.
View Article and Find Full Text PDFSci Robot
January 2025
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Aerial insects are exceptionally agile and precise owing to their small size and fast neuromotor control. They perform impressive acrobatic maneuvers when evading predators, recovering from wind gust, or landing on moving objects. Flapping-wing propulsion is advantageous for flight agility because it can generate large changes in instantaneous forces and torques.
View Article and Find Full Text PDFOtolaryngol Head Neck Surg
January 2025
Department of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Objective: Facial trauma volume is difficult to predict accurately. We aim to understand the capacity of climate and regional events to predict daily facial trauma volume. This can provide epidemiologic understanding and subsequently tailor workforce distribution and scheduling.
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January 2025
Electrical Power and Machines Department, Egyptian Chinese University, Cairo, Egypt.
This research is dedicated to improving the control system of wind turbines (WT) to ensure optimal efficiency and rapid responsiveness. To achieve this, the fuzzy logic control (FLC) method is implemented to control the converter in the rotor side (RSC) of a doubly fed induction generator (DFIG) and its performance is compared with an optimized proportional integral (PI) controller. The study demonstrated an enhancement in the performance of the DFIG through the utilization of the proposed FLC, effectively overcoming limitations and deficiencies observed in the conventional controllers, this approach significantly improved the performance of the wind turbine.
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