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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 

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.

 

Thermal energy harvesting from natural resources and waste heat is becoming critical due to ever-increasing environmental concerns. However, so far, available thermal energy harvesting technologies have only been able to generate electricity from large temperature gradients. Here, we report a fundamental breakthrough in low-grade thermal energy harvesting and demonstrate a device based on the thermomagnetic effect that uses ambient conditions as the heat sink and operates from a heat source at temperatures as low as 24 °C. This concept can convert temperature gradients as low as 2 °C into electricity while operating near room temperature. The device is found to exhibit a power density (power per unit volume of active material) of 105 μW cm −3 at a temperature difference of 2 °C, which increases to 465 μW cm −3 at a temperature difference of 10 °C. The power density increases by 2.5 times in the presence of wind with a speed of 2.0 m s −1 . This advancement in thermal energy harvesting technology will have a transformative effect on renewable energy generation and in reducing global warming. 

Energy harvesting from extremely low frequency magnetic fields using magneto‐mechano‐electric (MME) harvesters enables wireless power transfer for operating Internet of Things (IoT) devices. The MME harvesters are designed to resonate at a fixed frequency by absorbing AC magnetic fields through a composite cantilever comprising of piezoelectric and magnetostrictive materials, and a permanent magnetic tip mass. However, this harvester architecture limits power generation because volume of the magnetic end mass is closely coupled with the resonance frequency of the device structure. Here, a method is demonstrated for maintaining the resonance frequency of the MME harvesters under all operating conditions (e.g., 60 Hz, standard frequency of electricity in many countries) while simultaneously enhancing the output power generation. By distributing the magnetic mass over the beam, the output power of the harvester is significantly enhanced at a constant resonance frequency. The MME harvester with distributed forcing shows 280% improvement in the power generation compared with a traditional architecture. The generated power is shown to be sufficient to power eight different onboard sensors with wireless data transmission integrated on a drone. These results demonstrate the promise of MME energy harvesters for powering wireless communication and IoT sensors.

 

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.