The utilization of sensors has become indispensable in the advent of an intelligent era characterized by artificial intelligence, 5G communication, big data, and other cutting-edge technologies. Traditional sensors require external power sources or batteries, resulting in a complex sensing system that does not promote the development of sustainable and environmentally friendly applications for health monitoring. In recent years, the electrical output and stability of piezoelectric, triboelectric, thermoelectric, and hybrid nanogenerators have been significantly improved, enabling their widespread role in the development of self-powered sensors. The sensors are capable of performing sensing tasks by converting their own energy, thereby obviating the need for an external power supply. In this paper, we initially explore the operating mechanisms, device materials, and structures of diverse nanogenerators and evaluate their output efficacy. Subsequently, we showcase the latest advancements in self-powered sensor systems, spanning various fields such as biomedical and healthcare, wearable devices, sound monitoring, smart vehicles, environmental monitoring, and smart cities. The paper also explores the future potential of self-powered sensor systems, in addition to discussing their practical applications.
Wearable plant sensors (WPSs) can effectively monitor plant growth conditions in the presence of microenvironmental parameter fluctuations, which underlines their immense potential in the field of smart agriculture. Currently, the influence of ambient temperature on plant growth is a research focus in intelligent agriculture. However, it is considerably challenging to achieve real-time and precise monitoring of both physical plant growth and the corresponding ambient temperature using simple and efficient methodologies. In this paper, we introduce a dual-mode (tensile and temperature) WPS, comprising a laser-induced graphene (LIG) sensing layer and a polydimethylsiloxane (PDMS) substrate fabricated through laser inducing and gel-transfer processes. Experimental results demonstrate that the WPS exhibits impressive strain sensitivity (1749.8) and a positive temperature coefficient (0.29 × 10 -2 °C -1 ) within a wide range of strain (0-50%) and temperature (20-100 °C) values. It even maintains stability under low strains (< 0.1%) or small temperature changes (0.5 °C). Furthermore, it has fast response times (87 ms/3.47 s for strain/temperature response) and good stability (4000/25 cycles for strain/temperature). The high-performance WPS served as the foundation for the development of a wireless intelligent plant growth monitoring system, which employs the Long Short-Term Memory (LSTM) network to effectively monitor and decouple the physical plant growth and the corresponding ambient temperature. Our innovative plant monitoring approach introduces a new paradigm in intelligent vegetation surveillance, with promising implications for applications in smart agriculture.
Few-layer SnSe2 was successfully fabricated by liquid phase exfoliation method. A passive Q-switched Tm:YAP laser at the wavelength of 1940 nm was demonstrated by using SnSe2 saturable absorber (SA). Under absorbed pump power of 4.9 W, 400 mW Q-switched was achieved with the pulse width of 1.29 μs and the repetition rate of 109.77 kHz. The results indicate the promising potential of SnSe2 nanosheets as SA to achieve efficient pulsed lasers at around 2 μm.
Motivated by artificial intelligence, we present a novel electronic skin (e-skin) system capable of dual-sensing pressure and temperature signals. Our approach utilizes laser-induced graphene and polydimethylsiloxane, offering a simple yet efficient method for e-skin preparation. Experimental results reveal exceptional performance with good pressure sensitivity (0.037 kPa−1 at 0–50 kPa), a wide detection range (0–220 kPa), a fast response time of 56 ms, an ultra-low detection limit (30 Pa), and excellent stability (8000 cycles). Additionally, the e-skin exhibits positive temperature coefficients (0.0025 ℃-1) within 20–100 ℃, a rapid response time of 2.57 s, an extremely low detection limit (1 ℃), and stability after 50 cycles. Crucially, our intelligent e-skin system, employing a Long Short-Term Memory algorithm, enables real-time multi-modal tactile perception, accurately separating mixed pressure and temperature signals. This versatile technology holds immense potential for applications in intelligent robotics and human health monitoring.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)