Computational analysis of starch for sustainable power generation towards integrated wearable IoT

Thanjan Shaji Bincy, Asokan Poorani Sathya Prasanna, A. Sakthi Balaji, K. Janani Sivasankar, D. John Thiruvadigal, Monunith Anithkumar and Sang-Jae Kim

Applied Energy, 2024, vol. 370, issue C, No S0306261924009735

Abstract: Green energy has gained immense attention recently due to its low environmental impact. Developing triboelectric nanogenerators (TENG) with polysaccharide-based materials will pave the way for green self-powered sensor and wireless communication systems for different applications. Herein, different edible starch-based TENG was fabricated using arrowroot, corn, potato, and tapioca starch as the active layer. Density functional theory (DFT) provided information on the triboactive sites with the electron difference density (EDD) mapping. The results suggest amylopectin has a low work function and high chemical potential to exhibit high reactivity compared with amylose. The cornstarch-based nanogenerator (CS-TENG) delivered the maximum output performance. The green wearable IoT (Internet of Things) was constructed using a mechano-electric sensor with a wireless physio health monitoring system (WPHM) to track the different exercises. The developed Android application was used to calculate different exercises and calories burnt. Further, this wearable IoT can be used in sports fitness monitoring and sports person analytics.

Keywords: Green energy; Wearable IoTs; Polysaccharides; Tribo-active sites; Physio health monitor (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123590

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