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Featured researches published by Steven L. Zhang.


ACS Nano | 2017

A Highly Stretchable and Washable All-Yarn-Based Self-Charging Knitting Power Textile Composed of Fiber Triboelectric Nanogenerators and Supercapacitors

Kai Dong; Yi-Cheng Wang; Jianan Deng; Yejing Dai; Steven L. Zhang; Haiyang Zou; Bohong Gu; Baozhong Sun; Zhong Lin Wang

Rapid advancements in stretchable and multifunctional wearable electronics impose a challenge on corresponding power devices that they should have comparable portability and stretchability. Here, we report a highly stretchable and washable all-yarn-based self-charging knitting power textile that enables both biomechanical energy harvesting and simultaneously energy storing by hybridizing triboelectrical nanogenerator (TENG) and supercapacitor (SC) into one fabric. With the weft-knitting technique, the power textile is qualified with high elasticity, flexibility, and stretchability, which can adapt to complex mechanical deformations. The knitting TENG fabric is able to generate electric energy with a maximum instantaneous peak power density of ∼85 mW·m-2 and light up at least 124 light-emitting diodes. The all-solid-state symmetrical yarn SC exhibits lightweight, good capacitance, high flexibility, and excellent mechanical and long-term stability, which is suitable for wearable energy storage devices. The assembled knitting power textile is capable of sustainably driving wearable electronics (for example, a calculator or temperature-humidity meter) with energy converted from human motions. Our work provides more opportunities for stretchable multifunctional power sources and potential applications in wearable electronics.


Advanced Materials | 2018

Actively Perceiving and Responsive Soft Robots Enabled by Self‐Powered, Highly Extensible, and Highly Sensitive Triboelectric Proximity‐ and Pressure‐Sensing Skins

Ying-Chih Lai; Jianan Deng; Ruiyuan Liu; Yung-Chi Hsiao; Steven L. Zhang; Wenbo Peng; Hsing-Mei Wu; Xingfu Wang; Zhong Lin Wang

Robots that can move, feel, and respond like organisms will bring revolutionary impact to todays technologies. Soft robots with organism-like adaptive bodies have shown great potential in vast robot-human and robot-environment applications. Developing skin-like sensory devices allows them to naturally sense and interact with environment. Also, it would be better if the capabilities to feel can be active, like real skin. However, challenges in the complicated structures, incompatible moduli, poor stretchability and sensitivity, large driving voltage, and power dissipation hinder applicability of conventional technologies. Here, various actively perceivable and responsive soft robots are enabled by self-powered active triboelectric robotic skins (tribo-skins) that simultaneously possess excellent stretchability and excellent sensitivity in the low-pressure regime. The tribo-skins can actively sense proximity, contact, and pressure to external stimuli via self-generating electricity. The driving energy comes from a natural triboelectrification effect involving the cooperation of contact electrification and electrostatic induction. The perfect integration of the tribo-skins and soft actuators enables soft robots to perform various actively sensing and interactive tasks including actively perceiving their muscle motions, working states, textiles dampness, and even subtle human physiological signals. Moreover, the self-generating signals can drive optoelectronic devices for visual communication and be processed for diverse sophisticated uses.


ACS Applied Materials & Interfaces | 2018

Concurrent Harvesting of Ambient Energy by Hybrid Nanogenerators for Wearable Self-Powered Systems and Active Remote Sensing

Haiwu Zheng; Yunlong Zi; Xu He; Hengyu Guo; Ying-Chih Lai; Jie Wang; Steven L. Zhang; Changsheng Wu; Gang Cheng; Zhong Lin Wang

Harvesting energy available from ambient environment is highly desirable for powering personal electronics and health applications. Due to natural process and human activities, steam can be produced by boilers, human perspiration, and the wind exists ubiquitously. In the outdoor environment, these two phenomena usually exist at the same place, which contain heat and mechanical energies simultaneously. However, previous studies have isolated them as separate sources of energy to harvest and hence failed to utilize them effectively. Herein, we present unique hybrid nanogenerators for individually/simultaneously harvesting thermal energy from water vapors and mechanical energy from intermittent wind blowing from the bottom side, which consist of a wind-driven triboelectric nanogenerator (TENG) and pyroelectric-piezoelectric nanogenerators (PPENGs). The output power of the PPENG and the TENG can be up to about 184.32 μW and 4.74 mW, respectively, indicating the TENG plays the dominant role. Our hybrid nanogenerators could provide different applications such as to power digital watch and enable self-powered sensing with wireless transmission. The device could also be further integrated into a face mask for potentially wearable applications. This work not only provides a promising approach for renewable energy harvesting but also enriches potential applications for self-powered systems and wireless sensors.


Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies archive | 2018

SATURN: A Thin and Flexible Self-powered Microphone Leveraging Triboelectric Nanogenerator

Nivedita Arora; Steven L. Zhang; Fereshteh Shahmiri; Diego Osorio; Yi-Cheng Wang; Mohit Gupta; Zhengjun Wang; Thad Starner; Zhong Lin Wang; Gregory D. Abowd

We demonstrate the design, fabrication, evaluation, and use of a self-powered microphone that is thin, flexible, and easily manufactured. Our technology is referred to as a Self-powered Audio Triboelectric Ultra-thin Rollable Nanogenerator (SATURN) microphone. This acoustic sensor takes advantage of the triboelectric nanogenerator (TENG) to transform vibrations into an electric signal without applying an external power source. The sound quality of the SATURN mic, in terms of acoustic sensitivity, frequency response, and directivity, is affected by a set of design parameters that we explore based on both theoretical simulation and empirical evaluation. The major advantage of this audio material sensor is that it can be manufactured simply and deployed easily to convert every-day objects and physical surfaces into microphones which can sense audio. We explore the space of potential applications for such a material as part of a self-sustainable interactive system.


Advanced Functional Materials | 2017

Single‐Thread‐Based Wearable and Highly Stretchable Triboelectric Nanogenerators and Their Applications in Cloth‐Based Self‐Powered Human‐Interactive and Biomedical Sensing

Ying-Chih Lai; Jianan Deng; Steven L. Zhang; Simiao Niu; Hengyu Guo; Zhong Lin Wang


Nano Energy | 2017

An ultrathin paper-based self-powered system for portable electronics and wireless human-machine interaction

Xu He; Yunlong Zi; Hua Yu; Steven L. Zhang; Jie Wang; Wenbo Ding; Haiyang Zou; Wei Zhang; Canhui Lu; Zhong Lin Wang


Advanced Functional Materials | 2017

Auxetic Foam-Based Contact-Mode Triboelectric Nanogenerator with Highly Sensitive Self-Powered Strain Sensing Capabilities to Monitor Human Body Movement

Steven L. Zhang; Ying-Chih Lai; Xu He; Ruiyuan Liu; Yunlong Zi; Zhong Lin Wang


Extreme Mechanics Letters | 2017

A washable, stretchable, and self-powered human-machine interfacing Triboelectric nanogenerator for wireless communications and soft robotics pressure sensor arrays

Abdelsalam Ahmed; Steven L. Zhang; Islam Hassan; Zia Saadatnia; Yunlong Zi; Jean W. Zu; Zhong Lin Wang


Extreme Mechanics Letters | 2017

An aeroelastic flutter based triboelectric nanogenerator as a self-powered active wind speed sensor in harsh environment

Minyi Xu; Yi-Cheng Wang; Steven L. Zhang; Wenbo Ding; Jia Cheng; Xu He; Peng Zhang; Zhengjun Wang; Xinxiang Pan; Zhong Lin Wang


Advanced Energy Materials | 2018

A Soft and Robust Spring Based Triboelectric Nanogenerator for Harvesting Arbitrary Directional Vibration Energy and Self-Powered Vibration Sensing

Minyi Xu; Peihong Wang; Yi-Cheng Wang; Steven L. Zhang; Aurelia Chi Wang; Chunli Zhang; Zhengjun Wang; Xinxiang Pan; Zhong Lin Wang

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Zhong Lin Wang

Georgia Institute of Technology

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Xu He

Georgia Institute of Technology

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Yi-Cheng Wang

Georgia Institute of Technology

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Yunlong Zi

Georgia Institute of Technology

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Haiyang Zou

Georgia Institute of Technology

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Minyi Xu

Georgia Institute of Technology

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Ying-Chih Lai

Georgia Institute of Technology

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Zhengjun Wang

Georgia Institute of Technology

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Jianan Deng

Georgia Institute of Technology

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Wenbo Ding

Georgia Institute of Technology

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