Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis

Zhu, Jianxiong; Sun, Zhongda; Xu, Jikai; Walczak, Rafał; Dziuban, Jan; Lee, Chengkuo

doi:10.1016/j.scib.2021.03.021

Cited by 60 publications

(42 citation statements)

References 97 publications

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“…On the other hand, self-powered sensors using piezoelectric nanogenerators (PENGs) and/or triboelectric nanogenerators (TENGs) have received growing attention. With self-generated voltage due to mechanical stimuli, they can realize self-powered sensing regarding force, pulse, strain, gas, chemical, etc . − Among them, the TENG stands out for its broad material choices, simple design and fabrication, and low cost. − Moreover, combining multiple self-powered sensors with artificial intelligence (AI) technology has also become a trend in the development of smart wearable devices, to extract complete sensory information on small-volume data instead of analyzing large-volume data in terms of superficial magnitude and frequency. − …”

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confidence: 99%

Artificial Intelligence-Enabled Caregiving Walking Stick Powered by Ultra-Low-Frequency Human Motion

et al. 2021

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The increasing population of the elderly and motion-impaired people brings a huge challenge to our social system. However, the walking stick as their essential tool has rarely been investigated into its potential capabilities beyond basic physical support, such as activity monitoring, tracing, and accident alert. Here, we report a walking stick powered by ultralow-frequency human motion and equipped with deep-learningenabled advanced sensing features to provide a healthcaremonitoring platform for motion-impaired users. A linear-torotary structure is designed to achieve highly efficient energy harvesting from the linear motion of a walking stick with ultralow frequency. Besides, two kinds of self-powered triboelectric sensors are proposed and integrated to extract the motion features of the walking stick. Augmented sensing functionalities with high accuracies have been enabled by deep-learningbased data analysis, including identity recognition, disability evaluation, and motion status distinguishing. Furthermore, a selfsustainable Internet of Things (IoT) system with global positioning system tracing and environmental temperature and humidity amenity sensing functions is obtained. Combined with the aforementioned functionalities, this walking stick is demonstrated in various usage scenarios as a caregiver for real-time well-being status and activity monitoring. The caregiving walking stick shows the potential of being an intelligent aid for motion-impaired users to help them live life with adequate autonomy and safety.

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Artificial Intelligence-Enabled Caregiving Walking Stick Powered by Ultra-Low-Frequency Human Motion

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“…In addition, ML algorithms visualized the relationship between different VOCs in the mixture, demonstrating the feasibility of VOC identification for simulated patients. A machine learning enhanced ion mobility analyzer with a triboelectric-based ion generator is also reported by Zhu et al, which provides good ion mobility selectivity and VOC identification in small devices and non-strict operating environments Zhu et al (2021) . By extracting specific features automatically from ion mobility spectroscopy data with an ML algorithm that significantly improves the detection capability of the TENG VOC-based analyzer.…”

Section: Ai-teng Sensors For Low Abundance Biosensingmentioning

confidence: 92%

What can AI-TENG do for Low Abundance Biosensing?

Jiang

Zheng

Zhu

2022

Front. Bioeng. Biotechnol.

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Biosensing technology helps prevent, diagnose, and treat diseases and has attracted more and more researchers in recent years. Artificial intelligence-based triboelectric nanogenerators (AI-TENG) are promising for applications in biosensors due to their myriad of merits, including high efficiency and precision, low cost, light weight, and self-powered. This article aims to show how artificial intelligence and triboelectric nanogenerators have been combined to develop biosensors. We first focus on the working principle of triboelectric nanogenerators and the method of combining them with artificial intelligence. Secondly, we highlight the representative research work of AI-TENG in biomolecules sensing, organic compounds, and complex mixture of cells. Finally, this paper concludes with a summary and prospect on the existing challenges and possible solutions in the application of AI-TENG to the field of biosensors.

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“…Current rapid advances of the internet of things and wearable devices also demand new self-powered or zero-power gas sensing nodes. Several approaches, including triboelectric nanogenerators [199][200][201], passive photonic platforms [202,203], zero-power 2D material-based photodetectors [204,205], have been extensively explored in the past few decades to enable this battery-free property.…”

Section: Gas Sensingmentioning

confidence: 99%

Recent Progress in the Energy Harvesting Technology—From Self-Powered Sensors to Self-Sustained IoT, and New Applications

et al. 2021

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With the fast development of energy harvesting technology, micro-nano or scale-up energy harvesters have been proposed to allow sensors or internet of things (IoT) applications with self-powered or self-sustained capabilities. Facilitation within smart homes, manipulators in industries and monitoring systems in natural settings are all moving toward intellectually adaptable and energy-saving advances by converting distributed energies across diverse situations. The updated developments of major applications powered by improved energy harvesters are highlighted in this review. To begin, we study the evolution of energy harvesting technologies from fundamentals to various materials. Secondly, self-powered sensors and self-sustained IoT applications are discussed regarding current strategies for energy harvesting and sensing. Third, subdivided classifications investigate typical and new applications for smart homes, gas sensing, human monitoring, robotics, transportation, blue energy, aircraft, and aerospace. Lastly, the prospects of smart cities in the 5G era are discussed and summarized, along with research and application directions that have emerged.

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Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis

Cited by 60 publications

References 97 publications

Artificial Intelligence-Enabled Caregiving Walking Stick Powered by Ultra-Low-Frequency Human Motion

Artificial Intelligence-Enabled Caregiving Walking Stick Powered by Ultra-Low-Frequency Human Motion

What can AI-TENG do for Low Abundance Biosensing?

Recent Progress in the Energy Harvesting Technology—From Self-Powered Sensors to Self-Sustained IoT, and New Applications

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