A Non-Resonant Piezoelectric-Electromagnetic-Triboelectric Hybrid Energy Harvester for Low-Frequency Human Motions

Enhanced Selective Ion Transport in Highly Charged Bacterial Cellulose/Boron Nitride Composite Membranes for Thermo-Osmotic Energy Harvesting

Significant untapped energy exists within low-grade heat sources and salinity gradients. Traditional nanofluidic membranes exhibit inherent limitations, including low ion selectivity, high internal resistance, reliance on nonrenewable resources, and instability in aqueous solutions, invariably constraining their practical application. Here, an innovative composite membrane-based nanofluidic system is reported, involving the strategy of integrating tailor-modified bacterial nanofibers with boron nitride nanosheets, enabling high surface charge densities while maintaining a delicate balance between ion selectivity and permeability, ultimately facilitating effective thermo-osmotic energy harvesting. The device exhibits an impressive output power density of 10 W m-2 with artificial seawater and river water at a 50 K temperature gradient. Furthermore, it demonstrates robust power density stability under prolonged exposure to salinity gradients or even at elevated temperatures. This work opens new avenues for the development of nanofluidic systems utilizing composite materials and presents promising solutions for low-grade heat recovery and osmotic energy harvesting.

Harvesting Inertial Energy and Powering Wearable Devices: A Review

Amidst the swift progression of microelectronics and Internet of Things technology, wearable devices are gradually gaining ground in the domains of human health monitoring. Recently, human bioenergy harvesting has emerged as a plausible alternative to batteries. This paper delves into harvesting human inertial energy that stimulates inertial masses through human motion and then transmutes the motion of the inertial masses into electrical energy. The inertial energy harvester is better suited for low-frequency and irregular human motion. This review first identifies the sources of human motion excitation that are compatible with inertial energy harvesters and then provides a summary of the operating principles and the comparisons of the commonly used energy conversion mechanisms, including electromagnetic, piezoelectric, and triboelectric transducers. The review thoroughly summarizes the latest advancements in human inertial energy-harvesting technology that are categorized and grouped based on their excitation sources and mechanical modulation methods. In addition, the review outlines the applications of inertial energy harvesters in powering wearable devices, medical health monitoring, and as mobile power sources. Finally, the challenges faced by inertial energy-harvesting technologies are discussed, and the review provides a perspective on the potential developments in the field.

Intelligent soft robotic fingers with multi-modality perception ability

In the context of industry 4.0, automatic sorting is becoming prevalent in production lines. Herein, we developed a bionic sensing system to achieve real-time object recognition. The system consists of 9 single-layer triboelectric nanogenerators (SL-TENGs) as touch sensors and 3 comb-shaped TENGs (CS-TENGs) as bending sensors, with a sensitivity of 110 V/kPa and stable output after 20,000 press cycles. These sensors were attached to a manipulator composed of three soft actuators, serving as soft robotic fingers. An enhanced electrical output of these sensors was achieved successfully, demonstrating their feasibility in detecting grasping location, contact pressure, and bending curvature. A one-dimensional convolutional neural network (1D-CNN) with 98.96% accuracy extracted information from the sensors, enabling the manipulator to serve as an intelligent sensing system with multi-modality perception ability. This robotic manipulator successfully integrated TENG-based self-powered sensors, soft actuators, and artificial intelligence, demonstrating the potential for future digital twin applications, particularly in automatic component sorting.

Special Issue: Advance in Energy Harvesters/Nanogenerators and Self-Powered Sensors

Internet of things (IoT) technologies are greatly promoted by the rapidly developed 5G-and-beyond networks, which have spawned diversified applications in the new era including smart homes, digital health, sports training, robotics, human-machine interaction, metaverse, smart manufacturing and industry 4 [...].

Recent Progress of Nanogenerators for Green Energy Harvesting: Performance, Applications, and Challenges

Natural sources of green energy include sunshine, water, biomass, geothermal heat, and wind. These energies are alternate forms of electrical energy that do not rely on fossil fuels. Green energy is environmentally benign, as it avoids the generation of greenhouse gases and pollutants. Various systems and equipment have been utilized to gather natural energy. However, most technologies need a huge amount of infrastructure and expensive equipment in order to power electronic gadgets, smart sensors, and wearable devices. Nanogenerators have recently emerged as an alternative technique for collecting energy from both natural and artificial sources, with significant benefits such as light weight, low-cost production, simple operation, easy signal processing, and low-cost materials. These nanogenerators might power electronic components and wearable devices used in a variety of applications such as telecommunications, the medical sector, the military and automotive industries, and internet of things (IoT) devices. We describe new research on the performance of nanogenerators employing several green energy acquisition processes such as piezoelectric, electromagnetic, thermoelectric, and triboelectric. Furthermore, the materials, applications, challenges, and future prospects of several nanogenerators are discussed.