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  1. BSTRACT:Piezoelectricmaterialsare used to fabricateacoustictransducersforbubblechambersin searchfor particlesof dark matter.It has been shownthat bubblesinitiatedby nuclearrecoilsemit acousticradiationdistinguishablefrom the phasetransitionscausedby alpha-decay�themain backgroundnoisein such searches.However,these piezoelectricmaterialsmust exhibitultralowradioactivityto minimizethe neutronbackgroundfor dark matterdetectionwhilepossessinghigh acousticsensitivity.Here,for the first time, we demonstrateradiopurehigh-performancepiezoelectricceramicsmeetingthe criteriafor acousticsensing.The screeningofradiopureprecursorsis performedto identifythose with low238U,232Th, and210Pbcontents.Usingthe radiopureprecursors,piezoelectricceramicswith varyingcompositionsare synthesized,and their electromechanicalacousticsensingperformanceis evaluated.Multiplesynthesismodificationssuch as dopingand texturingare utilizedtotailor the piezoelectriccoefficientsof the piezoelectricceramics,and the relationshipbetweenthe piezoelectriccoefficientsand acousticsensingperformanceof the ceramicsis investigated.Acoustictransducersfabricatedusing texturedPb(Mg1/3Nb2/3)O3−PbTiO3(PMN−PT)ceramicsare found to exhibitsuperioracousticsensitivitydue totheir high piezoelectrictransductioncoefficient(d33×g33). This study demonstratesa usefulfigure of merit (FOM)for acousticsensingin bubblechambers 
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    Free, publicly-accessible full text available December 26, 2024
  2. Abstract

    The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

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  3. Abstract

    Internet of Things (IoT) is driving the development of new generation of sensors, communication components, and power sources. Ideally, IoT sensors and communication components are expected to be powered by sustainable energy source freely available in the environment. Here, a breakthrough in this direction is provided by demonstrating high output power energy harvesting from very low amplitude stray magnetic fields, which exist everywhere, through magnetoelectric (ME) coupled magneto‐mechano‐electric (MME) energy conversion. ME coupled MME harvester comprised of multiple layers of amorphous magnetostrictive material, piezoelectric macrofiber composite, and magnetic tip mass, interacts with an external magnetic field to generate electrical energy. Comprehensive experimental investigation and a theoretical model reveal that both the magnetic torque generated through magnetic loading and amplification of magneto‐mechanical vibration by ME coupling contributes toward the generation of high electrical power from the stray magnetic field around power cables of common home appliances. The generated electrical power from the harvester is sufficient for operating microsensors (gyro, temperature, and humidity sensing) and wireless data transmission systems. These results will facilitate the deployment of IoT devices in emerging intelligent infrastructures.

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