Publication | Closed Access
3D Printed Piezoelectric‐Regulable Cells with Customized Electromechanical Response Distribution for Intelligent Sensing
65
Citations
47
References
2022
Year
Materials ScienceEnergy HarvestingEngineeringElectronic MaterialsPiezoelectric PerformanceMechanical EngineeringMaterials CharacterizationPiezoelectric Conversion EfficiencyPrinted ElectronicsPiezoelectric Materials3D PrintingBiomedical EngineeringPrinted Piezoelectric‐regulable CellsPiezoelectric OutputPiezoelectric MaterialPiezoelectricitySelf-powered NanodevicesSensor Technology
Abstract Piezoelectric energy harvesters (PEHs) have attracted great attention owing to the capability of converting various forms of mechanical energy into electricity. Traditional approaches for improving piezoelectric conversion efficiency usually involve either complicated composite preparation or significant compromise in the device's mechanical strength and measure, which obviously cannot fulfill the stringent requirements for power supplies within miniaturized footprint and on mechanical compliance of modern electronics. Herein, an innovative strategy coupling 3D printing with a rational structural design is proposed to address the substantial difficulty to architect 3D PEHs featuring boosting piezoelectric performance without alteration either in material (high β‐phase content (97.4%) self‐poled poly(vinylidene fluoride) (PVDF) used in this case) or in device measure. The 3D‐printed piezoelectric latticed cells tailoring in density distribution geometries not only demonstrate the appealing advantages of fast response time, high sensitivity, and excellent linearity within a wide pressure range outperforming many 2D film sensors, but are more sensitive to structure variation for easier regulation of piezoelectric output saving the hassle of changing material, which is beyond the practicability to the traditional 2D sensors. 3D printing highlights a powerful tool in modeling and manipulating complex 3D piezoelectric‐regulable energy harvesters for intelligent sensing applications otherwise inaccessible to traditional techniques.
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