Developing real-time IoT-enabled next-generation fire alarm systems using SrBi4Ti4O15/PDMS flexible triboelectric
Gokana Mohana Rani1, S V N Pammi2, Hanseung Kim1
1Department of Biological Sciences and Bioengineering, NanoBio High-Tech Materials Research Center, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea. umapathi4u@gmail.com.
None:
Sustainable, autonomous, adaptive, and next generation flexible electronic systems inside Internet of Things (IoT) and wearable devices have resulted in innovative advancements in energy harvesting technologies. Despite the existence of numerous energy harvesting technologies, triboelectric nanogenerators (TENGs) have emerged as a potential option for powering smart and compact electronic devices. This study focuses on the fabrication of high-performance TENGs composed of a composite layer with SrBi4Ti4O15 (SBTO) embedded in polydimethylsiloxane (PDMS) and a biocompatible, natural pectin polymer layer. Utilizing the synergistic dielectric enhancement of SBTO, a lead-free Aurivillius-type perovskite, and the charge-accumulative characteristics of pectin, the TENG achieved exceptional electrical performance, with an output voltage reaching 375.7 V, an output current of 20.8 μA and a power density of 12.5 W m-2 under optimal conditions. An optimal filler concentration of 7 wt% and an operating frequency of 5 Hz produced maximum charge transfer efficiency. The engineered devices exhibited exceptional mechanical durability (>10 000 cycles), environmental stability (>30 days), and humidity resistance (45-90% R.H) when encapsulated. Moreover, incorporating TENGs into autonomous fire alarm systems substantiates their real-time sensing and notification capabilities via the integration of Wi-Fi and Bluetooth modules that function without batteries. The developed system delivers prompt, location-specific alerts via human-initiated activation, even during emergencies. This work demonstrates the scalable design of flexible TENGs, offering a unique alternative for autonomous fire detection in off-grid or high-risk environments.
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