Computational Prognosis and Efficiency Augmentation of Lead‐Free and Legacy Piezoelectric Bimorph Cantilevers for Low‐Power Energy Scavenging in IoT and Wearable Systems

This study presents a simulation analysis of bimorph cantilever energy harvesters using both lead‐free and conventional piezoelectric materials, focusing on their efficiency for low‐power electromechanical transduction in IoT and wearable systems. The materials examined include lead‐free zinc oxide (ZnO), aluminum nitride (AlN), barium titanate (BaTiO 3 ), and lithium niobate (LiNbO 3 ), alongside conventional piezoelectric materials such as lead zirconate titanate (PZT5A), Pz21, polyvinylidene fluoride (PVDF), and cadmium sulfide (CdS). Advanced simulations evaluate key performance parameters such as operational resonance frequency, load resistance optimization, and W‐plate configurations, assessing their influence on energy conversion efficiency. Among the lead‐free materials, BaTiO 3 demonstrates the highest performance, achieving 0.18579 V, 1.61 μW mechanical power, and 1.44 μW electrical power at 80 Hz. In comparison, the conventional material PZT5A peaks at 71 Hz with 5.295 V, 1183.11 μW mechanical power, and 1168.21 μW electrical power. Under high acceleration (2 g), Pz21 shows superior output, delivering 9.22066 V and 3542.52 μW electrical power. BaTiO 3 exhibits optimal performance at a load resistance of 100 kΩ, generating 0.91977 V and 4.23 μW electrical power. These findings emphasize the critical role of material selection and design optimization in enhancing power harvesting efficiency, offering sustainable solutions for powering IoT devices and wearable electronics.

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Publication Details

Journal
Energy Technology
Published
2025-03-09
DOI
https://doi.org/10.1002/ente.202402193
Citations
5
Primary Topic
Innovative Energy Harvesting Technologies
Type
article
Field-Weighted Citation Impact
3.57
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article

Computational Prognosis and Efficiency Augmentation of Lead‐Free and Legacy Piezoelectric Bimorph Cantilevers for Low‐Power Energy Scavenging in IoT and Wearable Systems

Deepak Punetha, Ravi Ranjan Kumar
5 citations
Energy Technology
Innovative Energy Harvesting Technologies
3.57
article

Computational Prognosis and Efficiency Augmentation of Lead‐Free and Legacy Piezoelectric Bimorph Cantilevers for Low‐Power Energy Scavenging in IoT and Wearable Systems

Deepak Punetha, Ravi Ranjan Kumar
article en
5 citations

Abstract

This study presents a simulation analysis of bimorph cantilever energy harvesters using both lead‐free and conventional piezoelectric materials, focusing on their efficiency for low‐power electromechanical transduction in IoT and wearable systems. The materials examined include lead‐free zinc oxide (ZnO), aluminum nitride (AlN), barium titanate (BaTiO 3 ), and lithium niobate (LiNbO 3 ), alongside conventional piezoelectric materials such as lead zirconate titanate (PZT5A), Pz21, polyvinylidene fluoride (PVDF), and cadmium sulfide (CdS). Advanced simulations evaluate key performance parameters such as operational resonance frequency, load resistance optimization, and W‐plate configurations, assessing their influence on energy conversion efficiency. Among the lead‐free materials, BaTiO 3 demonstrates the highest performance, achieving 0.18579 V, 1.61 μW mechanical power, and 1.44 μW electrical power at 80 Hz. In comparison, the conventional material PZT5A peaks at 71 Hz with 5.295 V, 1183.11 μW mechanical power, and 1168.21 μW electrical power. Under high acceleration (2 g), Pz21 shows superior output, delivering 9.22066 V and 3542.52 μW electrical power. BaTiO 3 exhibits optimal performance at a load resistance of 100 kΩ, generating 0.91977 V and 4.23 μW electrical power. These findings emphasize the critical role of material selection and design optimization in enhancing power harvesting efficiency, offering sustainable solutions for powering IoT devices and wearable electronics.

Energy TechnologyVol. 13(9)
Motilal Nehru National Institute of Technology (IN)
Openalex Percentile: Top 8%
Innovative Energy Harvesting Technologies
3.57
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