Optimizing Piezoelectric Nanogenerators for Efficient Wearable Health Monitoring Systems

This study investigates the simulation - based optimization of piezoelectric nanogenerators (PENGs) for autonomous health monitoring sensors. PENG enables the continuous and independent functioning of health monitoring equipment by converting mechanical energy from body motions into electrical energy. This work optimizes the energy harvesting efficiency of Ba1 - x - yCaxSryZr1 - x - yTixSnyO3 (x = 0.1 and y = 0.05) based PENG by using density functional theory. Numerous elements are included in the analysis, such as doping impact and piezoelectric material choices. This study enables to determine the high d33 value = 830 pC/N and output voltage 18 V for Ba1 - x - yCaxSryZr1 - x - yTixSnyO3 (x = 0.1 and y = 0.05) based PENG. The enhanced PENG is suitable for wearable health monitoring applications, as evidenced by the results, which show a considerable change in the piezoelectric constant d33. By improving the quality of piezoelectric material, this research helps to design novel health monitoring systems.