Real‐Time Wireless Detection of Heavy Metal Ions Using a Self‐Powered Triboelectric Nanosensor Integrated with an Autonomous Thermoelectric Generator‐Powered Robotic System

The integration of the Internet of Things (IoT) with advanced sensing technologies is transforming environmental monitoring and public health protection. In this study, a fully self-powered and automated chemical sensing system is developed and integrated with a robotic hand for "touch and sense" detection of toxic heavy metal ions (Pb<sup>2</sup>⁺, Cr⁶⁺, As<sup>3</sup>⁺) in aquatic environments. The system combines a self-powered solid-liquid triboelectric nanosensor (SL-TENS) with a thermoelectric generator (TEG), which harnesses ambient heat to power the robotic hand, eliminating the need for external power sources. The robotic hand is controlled wirelessly via an exo-hand, minimizing the risk of exposure during remote monitoring. The sensing component uses copper oxide nanowires (CuO NWs) coated with ion-selective membranes (ISMs) to enhance triboelectric output and enable highly selective ion detection. The system demonstrates effective real-time, on-site detection in lake water and data transmitted wirelessly to the user. This innovative approach provides a highly safe and efficient method for detecting hazardous pollutants in difficult-to-access areas, offering significant potential for wireless and real-time environmental monitoring and hazard prevention, thus contributing to the safeguarding of human health. This study presents a novel advancement in the field of IoT-enabled environmental monitoring systems.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2024-11-08
DOI
https://doi.org/10.1002/advs.202410424
Citations
14
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
2.92

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Real‐Time Wireless Detection of Heavy Metal Ions Using a Self‐Powered Triboelectric Nanosensor Integrated with an Autonomous Thermoelectric Generator‐Powered Robotic System

Yan‐Tsz Huang, Zong‐Hong Lin, Kuldeep Kaswan, Arshad Khan et al.
14 citations
Advanced Science
Gas Sensing Nanomaterials and Sensors
2.92
article

Real‐Time Wireless Detection of Heavy Metal Ions Using a Self‐Powered Triboelectric Nanosensor Integrated with an Autonomous Thermoelectric Generator‐Powered Robotic System

Yan‐Tsz Huang, Zong‐Hong Lin, Kuldeep Kaswan, Arshad Khan, Yuying Cheng, Kuan‐Ming Lee, Anindita Ganguly, S. Suresh, Jui‐Han Yu
article en
14 citations

Abstract

The integration of the Internet of Things (IoT) with advanced sensing technologies is transforming environmental monitoring and public health protection. In this study, a fully self-powered and automated chemical sensing system is developed and integrated with a robotic hand for "touch and sense" detection of toxic heavy metal ions (Pb<sup>2</sup>⁺, Cr⁶⁺, As<sup>3</sup>⁺) in aquatic environments. The system combines a self-powered solid-liquid triboelectric nanosensor (SL-TENS) with a thermoelectric generator (TEG), which harnesses ambient heat to power the robotic hand, eliminating the need for external power sources. The robotic hand is controlled wirelessly via an exo-hand, minimizing the risk of exposure during remote monitoring. The sensing component uses copper oxide nanowires (CuO NWs) coated with ion-selective membranes (ISMs) to enhance triboelectric output and enable highly selective ion detection. The system demonstrates effective real-time, on-site detection in lake water and data transmitted wirelessly to the user. This innovative approach provides a highly safe and efficient method for detecting hazardous pollutants in difficult-to-access areas, offering significant potential for wireless and real-time environmental monitoring and hazard prevention, thus contributing to the safeguarding of human health. This study presents a novel advancement in the field of IoT-enabled environmental monitoring systems.

Advanced ScienceVol. 12(24)
National Taiwan University (TW), National Tsing Hua University (TW)
National Science and Technology Council
Openalex Percentile: Top 8%
Gas Sensing Nanomaterials and Sensors
2.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.