Hemin Zhang

Bio: Hemin Zhang is an academic researcher from University of Cambridge. The author has contributed to research in topics: Resonator & Nonlinear system. The author has an hindex of 12, co-authored 43 publications receiving 644 citations. Previous affiliations of Hemin Zhang include Northwestern Polytechnical University & ESIEE Paris.

An Acceleration Sensing Method Based on the Mode Localization of Weakly Coupled Resonators

Abstract: This paper reports an acceleration sensing method based on two weakly coupled resonators (WCRs) using the phenomenon of mode localization. When acceleration acts on the proof masses, differential electrostatic stiffness perturbations will be applied to the WCRs, leading to mode localization, and thus, mode shape changes. Therefore, acceleration can be sensed by measuring the amplitude ratio shift. The proposed mode localization with the differential perturbation method leads to a sensitivity enhancement of a factor of 2 than the common single perturbation method. The theoretical model of the sensitivity, bandwidth, and linearity of the accelerometer is established and verified. The measured relative shift in amplitude ratio ( $\sim 312162$ ppm/g) is 302 times higher than the shift in resonance frequency ( $\sim 1035$ ppm/g) within the measurement range of ±1 g. The measured resolution based on the amplitude ratio is 0.619 mg and the nonlinearity is $\sim 3.5$ % in the open-loop measurement operation. [2015-0247]

A Handheld Inertial Pedestrian Navigation System With Accurate Step Modes and Device Poses Recognition

Abstract: In this paper, a handheld inertial pedestrian navigation system (IPNS) based on low-cost microelectromechanical system sensors is presented. Using the machine learning method of support vector machine, a multiple classifier is developed to recognize human step modes and device poses. The accuracy of the selected classifier is >85%. A novel step detection model is created based on the results of the classifier to eliminate the over-counting and under-counting errors. The accuracy of the presented step detector is >98%. Based on the improvements of the step modes recognition and step detection, the IPNS realized precise tracking using the pedestrian dead reckoning algorithm. The largest location error of the IPNS prototype is ~40 m in an urban area with a 2100-m-long distance.

A High-Sensitivity Micromechanical Electrometer Based on Mode Localization of Two Degree-of-Freedom Weakly Coupled Resonators

Abstract: This paper reports a high-sensitivity resonant electrometer based on the mode localization of two degree-of-freedom weakly coupled resonators (WCRs). When charges are applied to the input electrodes, the effective stiffness of a specific resonator of the WCRs will be perturbed, leading to a drastic change in mode shape owing to the mode localization phenomenon. By measuring the shift of the amplitude ratio, the small charge fluctuation can be accurately sensed. The theoretical mode of the electrometer is established based on the transfer functions of the WCRs. In particular, we establish the design rules of the coupling factor according to the −3-dB bandwidth, amplitude ratio measurement errors, and frequency misalignment between the resonators. The experimental results show that the amplitude ratio-based sensitivity is $\sim 2151$ times higher than the frequency-based sensitivity. The amplitude ratio-based resolution of the electrometer is approximately 1.269 fC . [2016-0119]

Triboelectric Nanogenerator: Structure, Mechanism, and Applications.

Abstract: With the rapid development of the Internet of Things (IoT), the number of sensors utilized for the IoT is expected to exceed 200 billion by 2025. Thus, sustainable energy supplies without the recharging and replacement of the charge storage device have become increasingly important. Among various energy harvesters, the triboelectric nanogenerator (TENG) has attracted considerable attention due to its high instantaneous output power, broad selection of available materials, eco-friendly and inexpensive fabrication process, and various working modes customized for target applications. The TENG harvests electrical energy from wasted mechanical energy in the ambient environment. Three types of operational modes based on contact-separation, sliding, and freestanding are reviewed for two different configurations with a double-electrode and a single-electrode structure in the TENGs. Various charge transfer mechanisms to explain the operational principles of TENGs during triboelectrification are also reviewed for electron, ion, and material transfers. Thereafter, diverse methodologies to enhance the output power considering the energy harvesting efficiency and energy transferring efficiency are surveyed. Moreover, approaches involving not only energy harvesting by a TENG but also energy storage by a charge storage device are also reviewed. Finally, a variety of applications with TENGs are introduced. This review can help to advance TENGs for use in self-powered sensors, energy harvesters, and other systems. It can also contribute to assisting with more comprehensive and rational designs of TENGs for various applications.

Material aspects of triboelectric energy generation and sensors

Abstract: The triboelectric nanogenerator (TENG) is a new type of energy generator first demonstrated in 2012. TENGs have shown potential as power sources for electronic devices and as sensors for detecting mechanical and chemical stimuli. To date, studies on TENGs have focused primarily on optimizing the systems and circuit designs or exploring possible applications. Even though triboelectricity is highly related to the material properties, studies on materials and material designs have been relatively less investigated. This review article introduces recent progress in TENGs, by focusing on materials and material designs to improve the electrical output and sensing performance. This article discusses the current technological issues and the future challenges in materials for TENG. The development of materials for a technology that uses the movement of the human body to provide power has been reviewed by scientists in South Korea. A triboelectric nanogenerator converts mechanical energy into electricity by harnessing the fact that two surfaces rubbing against one another can become electrically charged. This is known as the triboelectric effect. One exciting use for these nanogenerators is in wearable electronics, where the motion of the body provides the power. Unyong Jeong and colleagues from Pohang University of Science and Technology have reviewed recent progress in material advances in the four main elements of a triboelectric nanogenerator: the charge-generating layer, the charge-trapping layer, the charge-collecting layer, and the charge-storage layer. These improvements all aim to increase the electrical output of such devices. Over the last decade, triboelectric nanogenerator (TENG) has been verified to be an effective way of converting daily mechanical energy into electric power or detecting various stimuli in the external environment. To promote the material researches in TENG, we introduce recent progresses in materials and material designs to improve the power generation and sensing performance. Also, we discuss on the future challenges and suggest possible approaches to solve the challenges.