Magnetoelectric (ME)-based magnetometers have garnered much attention as they boast ultra-low-power systems with a small form factor and limit of detection in the tens of picotesla. The highly sensitive and low-power electric readout from the ME sensor makes them attractive for near DC and low-frequency AC magnetic fields as platforms for continuous magnetic signature monitoring. Among multiple configurations of the current ME magnetic sensors, most rely on exploiting the mechanically resonant characteristics of a released ME microelectromechanical system (MEMS) in a heterostructure device. Through optimizing the resonant device configuration, we design and fabricate a fixed-fixed resonant beam structure with high isolation compared to previous designs operating at ~800 nW of power comprised of piezoelectric aluminum nitride (AlN) and magnetostrictive (CoFe)-based thin films that are less susceptible to vibration while providing similar characteristics to ME-MEMS cantilever devices. In this new design of double-clamped magnetoelectric MEMS resonators, we have also utilized thin films of a new iron-cobalt-hafnium alloy (FeCo)Hf that provides a low-stress, high magnetostrictive material with an amorphous crystalline structure and ultra-low magnetocrystalline anisotropy. Together, the improvements of this sensor design yield a magnetic field sensitivity of 125 Hz/mT when released in a compressive state. The overall detection limit of these sensors using an electric field drive and readout are presented, and noise sources are discussed. Based on these results, design parameters for future ME MEMS field sensors are discussed.
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http://dx.doi.org/10.3390/s23208626 | DOI Listing |
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Area of Biochemistry and Molecular Biology, OneHealth-UR Research Group, University of La Rioja, 26006, Logroño, Spain.
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Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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State Key Laboratory of Developmental Biology of Freshwater Fish, Engineering Research Center of Polyploidy Fish Reproduction and Breeding of the State Education Ministry, College of Life Science, Hunan Normal University, Changsha, 410081, People's Republic of China.
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Yangzhou University, College of Food Science and Engineering, Huayang west road, 225127, Yangzhou, CHINA.
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Department of Morphology and Genetics, Federal University of São Paulo, São Paulo-SP, Brazil.
We identified seven distinct coronaviruses (CoVs) in bats from Brazil, classified into 229E-related (Alpha-CoV), Nobecovirus, Sarbecovirus, and Merbecovirus (Beta-CoV), including one closely related to MERS-like CoV with 82.8% genome coverage. To accomplish this, we screened 423 oral and rectal swabs from 16 different bat species using molecular assays, RNA sequencing, and evolutionary analysis.
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