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Bioinspired Stretchable MXene Deformation-Insensitive Hydrogel Temperature Sensors for Plant and Skin Electronics

Research 2024年第1期2023卷 389-401页

作者： Jun Wu Yinghui Li Shengshun Duan Zhehan Wang Xu Jing Yucheng Lin Di Zhu Wei Lei qiongfeng shi Li Tao Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and EngineeringSoutheast UniversityNanjingJiangsu 210096China School of Materials Science and Engineering Southeast UniversityNanjingJiangsu 210096China Center of 2D Materials and Devices Southeast UniversityNanjingJiangsu 210096China

Temperature sensing is of high value in the wearable healthcare,robotics/prosthesis,and noncontact physiological monitoring.However,the common mechanic deformation,including pressing,bending,and stretching,usually causes undesirable feature size changes to the inner conductive network distribution of temperature sensors,which seriously influences the accuracy.Here,inspired by the transient receptor potential mechanism of biological thermoreceptors that could work precisely under various skin contortions,we propose an MXene/Clay/poly(N-isopropylacrylamide)(PNIPAM)(MCP)hydrogel with high stretchability,spike response,and deformation insensitivity.The dynamic spike response is triggered by the inner conductive network transformation from the 3-dimensional structure to the 2-dimensional surface after water being discharged at the threshold temperature.The water discharge is solely determined by the thermosensitivity of PNIPAM,which is free from mechanical deformation,so the MCP hydrogels can perform precise threshold temperature(32℃)sensing under various deformation conditions,i.e.,pressing and 15%stretching.As a proof of concept,we demonstrated the applications in plant electronics for the real-time surface temperature monitoring and skin electronics for communicating between human and machines.Our research opens venues for the accurate temperature-threshold sensation on the complicated surface and mechanical conditions.

关键词： stretching proof precise

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Triboelectric Nanogenerators and Hybridized Systems for Enabling Next-Generation IoT Applications

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Research 2021年第1期2021卷 392-421页

作者： qiongfeng shi Zhongda Sun Zixuan Zhang Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3SingaporeSingapore 117583 Center for Intelligent Sensors and MEMS National University of Singapore4 Engineering Drive 3SingaporeSingapore 117583 Smart Systems Institute National University of Singapore3 Research LinkSingaporeSingapore 117602 NUS Graduate School for Integrative Science and Engineering National University of SingaporeSingaporeSingapore 117456

In the past few years,triboelectric nanogenerator-based(TENG-based)hybrid generators and systems have experienced a widespread and flourishing development,ranging among almost every aspect of our lives,e.g.,from industry to consumer,outdoor to indoor,and wearable to implantable applications.Although TENG technology has been extensively investigated for mechanical energy harvesting,most developed TENGs still have limitations of small output current,unstable power generation,and low energy utilization rate of multisource energies.To harvest the ubiquitous/coexisted energy forms including mechanical,thermal,and solar energy simultaneously,a promising direction is to integrate TENG with other transducing mechanisms,e.g.,electromagnetic generator,piezoelectric nanogenerator,pyroelectric nanogenerator,thermoelectric generator,and solar cell,forming the hybrid generator for synergetic single-source and multisource energy harvesting.The resultant TENG-based hybrid generators utilizing integrated transducing mechanisms are able to compensate for the shortcomings of each mechanism and overcome the above limitations,toward achieving a maximum,reliable,and stable output generation.Hence,in this review,we systematically introduce the key technologies of the TENG-based hybrid generators and hybridized systems,in the aspects of operation principles,structure designs,optimization strategies,power management,and system integration.The recent progress of TENG-based hybrid generators and hybridized systems for the outdoor,indoor,wearable,and implantable applications is also provided.Lastly,we discuss our perspectives on the future development trend of hybrid generators and hybridized systems in environmental monitoring,human activity sensation,human-machine interaction,smart home,healthcare,wearables,implants,robotics,Internet of things(IoT),and many other fields.

关键词： IoT generator harvesting

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A hybridized electromagnetic-triboelectric nanogenerator designed for scavenging biomechanical energy in human balance control

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Nano Research 2021年第11期14卷 4227-4235页

作者： Long Liu qiongfeng shi Chengkuo Lee Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore117576Singapore Center for Intelligent Sensors and MEMS National University of SingaporeBlock E6#05-115 Engineering Drive 1Singapore117608Singapore NUS Suzhou Research Institute(NUSRI) Suzhou Industrial ParkSuzhou215123China NUS Graduate School-Integrative Sciences and Engineering Programme(ISEP) National University of SingaporeSingapore119077Singapore

For human beings of different ages and physical abilities, the inherent balance control system is ubiquitous and active to prevent falling, especially in motion states. A hybridized electromagnetic-triboelectric nanogenerator (HETNG) is prepared to harvest biomechanical energy during human balance control processes and achieve significant monitoring functions. The HETNG is composed of a symmetrical pendulum structure and a cylinder magnet rolling inside. Four coils are divided into two groups which form into two electromagnetic generators (EMGs). Besides, two spatial electrodes attached to the inner wall constitute a freestanding mode triboelectric nanogenerator (TENG). With a rectification circuit, the HETNG presents a high output power with a peak value of 0.55 W at a load of 160 Ω. Along with human balance control processes during walking, the HETNG can harvest biomechanical energy at different positions on the trunk. Moreover, the HETNG applied in artificial limb has been preliminarily simulated with the positions on thigh and foot, for monitoring the actions of squat and stand up, and lifting the leg up and down. For the elder that walks slowly with a walking aid, the HETNG equipped on the walking aid can help to record the motions of forwarding and unexpected falling, which is useful for calling for help. This work shows the potential of biomechanical energy-driven HETNG for powering portable electronics and monitoring human motions, also shows significant concerns to people lacked action capability or disabled.

关键词： hybridized electromagnetic-triboelectric nanogenerator human balance control internet of things artificial limb

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A humidity resistant and high performance triboelectric nanogenerator enabled by vortex-induced vibration for scavenging wind energy

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Nano Research 2022年第4期15卷 3246-3253页

作者： Yan Wang Tianyu Chen Shuowen Sun Xiangyu Liu Zhiyuan Hu Zhenhui Lian Long Liu qiongfeng shi Hao Wang Jianchun Mi Tongming Zhou Chengkuo Lee Minyi Xu Dalian Key Lab of Marine Micro/Nano Energy and Self-powered System Marine Engineering CollegeDalian Maritime UniversityDalian 116026China Center for Intelligent Sensors and MEMS(CISM) National University of Singapore Engineering Drive 3 Singapore 117576Singapore3 College of EngineeringPeking UniversityBeijing 100871China School of Civil Environmental and Mining EngineeringThe University of Western AustraliaWA 6009Australia

Wind energy is a promising renewable energy source for a low-carbon society.This study is to develop a fully packaged vortexinduced vibration triboelectric nanogenerator(VIV-TENG)for scavenging wind energy.The VIV-TENG consists of a wind vane,internal power generation unit,an external frame,four springs,a square cylinder and a circular turntable.The internal power generation unit consists of polytetrafluoroethylene(PTFE)balls,a honeycomb frame and two copper electrodes.Different from most of the previous wind energy harvesting TENGs,the bouncing PTFE balls are fully packaged in the square cylinder.The distinct design separates the process of contact electrification from the external environment,and at the same time avoids the frictional wear of the ordinary wind energy harvesting TENGs.The corresponding VIV parameters are investigated to evaluate their influence on the vibration behaviors and the energy output.Resonant state of the VIV-TENG corresponds to the high output performance from the VIV-TENG.The distinct,robust structure ensures the full-packaged VIV-TENG can harvest wind energy from arbitrary directions and even in undesirable weather conditions.The study proposes a novel TENG configuration for harvesting wind energy and the VIV-TENG proves promising powering micro-electro-mechanical appliances.

关键词： vortex-induced vibration wind energy triboelectric nanogenerator self-powered

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Robust triboelectric information-mat enhanced by multi-modality deep learning for smart home

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InfoMat 2023年第1期5卷 139-160页

作者： Yanqin Yang qiongfeng shi Zixuan Zhang Xuechuan Shan Budiman Salam Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingaporeSingapore National University of Singapore Suzhou Research Institute(NUSRI) SuzhouPeople's Republic of China Singapore Institute of Manufacturing Technology and National University of Singapore(SIMTech-NUS)Joint Lab on Large-area Flexible Hybrid Electronics National University of SingaporeSingaporeSingapore Printed Intelligent Device Group Singapore Institute of Manufacturing TechnologyAgency for ScienceTechnology and Research(A*STAR)SingaporeSingapore NUS Graduate School-Integrative Sciences and Engineering Programme(ISEP) National University of SingaporeSingaporeSingapore

In metaverse,a digital-twin smart home is a vital platform for immersive communication between the physical and virtual world.Triboelectric nanogenerators(TENGs)sensors contribute substantially to providing smart-home monitoring.However,TENG deployment is hindered by its unstable out-put under environment changes.Herein,we develop a digital-twin smart home using a robust all-TENG based information mat(InfoMat),which consists of an in-home mat array and an entry mat.The interdigital electrodes design allows environment-insensitive ratiometric readout from the mat array to can-cel the commonly experienced environmental variations.Arbitrary position sensing is also achieved because of the interval arrangement of the mat pixels.Concurrently,the two-channel entry mat generates multi-modality informa-tion to aid the 10-user identification accuracy to increase from 93% to 99% compared to the one-channel case.Furthermore,a digital-twin smart home is visualized by real-time projecting the information in smart home to virtual reality,including access authorization,position,walking trajectory,dynamic activities/sports,and so on.

关键词： digital twin environment-insensitive multi-modality deep learning scalability smart home triboelectric information-mat

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Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

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InfoMat 2020年第6期2卷 1131-1162页

作者： qiongfeng shi Bowei Dong Tianyiyi He Zhongda Sun Jianxiong Zhu Zixuan Zhang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore117576Singapore Center for Intelligent Sensors and MEMS National University of SingaporeSingapore117608Singapore Hybrid-Integrated Flexible(Stretchable)Electronic Systems Program National University of SingaporeSingapore117608Singapore NUS Suzhou Research Institute(NUSRI) Suzhou215123China NUS Graduate School for Integrative Science and Engineering National University of SingaporeSingapore117456Singapore

The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life,for example,healthcare monitoring and treatment,ambient monitoring,soft robotics,prosthetics,flexible display,communication,human-machine interactions,and so on.According to the development in recent years,the next-generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence(AI)and internet of things(IoT),to achieve a higher level of comfort,convenience,connection,and intelligence.Herein,this review provides an opportune overview of the recent progress in wearable electronics,photonics,and systems,in terms of emerging materials,transducing mechanisms,structural configurations,applications,and their further integration with other technologies.First,development of general wearable electronics and photonics is summarized for the applications of physical sensing,chemical sensing,humanmachine interaction,display,communication,and so on.Then self-sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage technologies.Next,technology fusion of wearable systems and AI is reviewed,showing the emergence and rapid development of intelligent/smart systems.In the last section of this review,perspectives about the future development trends of the next-generation wearable electronics/photonics are provided,that is,toward multifunctional,self-sustainable,and intelligent wearable systems in the AI/IoT era.

关键词： artificial intelligence energy harvesting human-machine interface internet of things wearable electronics wearable photonics

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Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

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npj Flexible Electronics 2020年第1期4卷 243-254页

作者： Zixuan Zhang Tianyiyi He Minglu Zhu Zhongda Sun qiongfeng shi Jianxiong Zhu Bowei Dong Mehmet Rasit Yuce Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Centre for Intelligent Sensors and MEMS(CISM) National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Hybrid Integrated Flexible Electronic Systems(HIFES) 5 Engineering Drive 1Singapore 117608Singapore Smart Systems Institute National University of Singapore3 Research LinkSingapore 117602Singapore National University of Singapore Suzhou Research Institute(NUSRI) Suzhou Industrial Park215123 SuzhouChina Department of Electrical and Computer Systems Engineering Monash UniversityMelbourneVIC 3800Australia NUS Graduate School for Integrative Science and Engineering(NGS) National University of SingaporeSingapore 119077Singapore

The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable electronics.Gait reveals sensory information in daily life containing personal information,regarding identification and healthcare.Current wearable electronics of gait analysis are mainly limited by high fabrication cost,operation energy consumption,or inferior analysis methods,which barely involve machine learning or implement nonoptimal models that require massive datasets for training.Herein,we developed low-cost triboelectric intelligent socks for harvesting waste energy from low-frequency body motions to transmit wireless sensory data.The sock equipped with self-powered functionality also can be used as wearable sensors to deliver information,regarding the identity,health status,and activity of the users.To further address the issue of ineffective analysis methods,an optimized deep learning model with an end-to-end structure on the socks signals for the gait analysis is proposed,which produces a 93.54%identification accuracy of 13 participants and detects five different human activities with 96.67%accuracy.Toward practical application,we map the physical signals collected through the socks in the virtual space to establish a digital human system for sports monitoring,healthcare,identification,and future smart home applications.

关键词： Deep smart IoT

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人工智能技术在新能源功率预测的应用及展望

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中国电机工程学报 2023年第8期43卷 3027-3047页

作者：朱琼锋李家腾乔骥史梦洁王朝亮中国电力科学研究院有限公司北京市海淀区100192 国网浙江省电力有限公司营销服务中心浙江省杭州市310000

构建新型电力系统是实现我国“双碳”战略目标的主要举措之一,风力发电和光伏发电作为两种最具代表性的新能源,其波动性和随机性给电网安全和新能源消纳带来了重大挑战,新能源功率预测是降低其随机性影响的核心关键技术。近年来,随着大... 详细信息

构建新型电力系统是实现我国“双碳”战略目标的主要举措之一,风力发电和光伏发电作为两种最具代表性的新能源,其波动性和随机性给电网安全和新能源消纳带来了重大挑战,新能源功率预测是降低其随机性影响的核心关键技术。近年来,随着大数据技术和以深度学习、强化学习为代表的新一代人工智能(artificial intelligence,AI)技术在诸多领域的成功应用,其在新能源功率预测方面的应用仍有方兴未艾之势。首先该文论述AI技术在新能源功率预测应用的理论基础,并对AI技术在风电和光伏功率预测方面的应用进行系统总结,包括数据增强和特征构建等多种数据处理技术的应用,传统机器学习算法、深度学习算法以及组合算法在模型构建方面的应用,以及进化算法、群智能优化算法、强化学习等多种智能优化算法在模型训练和超参数优化方面的应用。然后,对当前相关文献进行统计分析,并基于新能源预测大赛结果和实际预测系统调研情况,对当前学术界研究热点和趋势、产业界模型应用情况进行对比和分析。最后,对当前新能源功率预测在场景自适应、小样本学习、数值天气预报系统(numerical weather prediction,NWP)数据时空分辨率、分布式新能源预测等方面存在的一些问题进行剖析,并对采用强化学习、元学习、图神经网络(graph neural network,GNN)等多种AI技术解决相关问题的前景进行展望。

关键词：风力发电光伏发电功率预测人工智能技术

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乡村旅游发展中的城乡要素流动过程与机制

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中国生态旅游 2021年第3期11卷 386-397页

作者：宁志中张琦何琼峰师满江中国科学院地理科学与资源研究所北京100101 中国旅游研究院北京100005 西南科技大学土木工程与建筑学院绵阳621010

乡村旅游是促进城乡市场连接的途径之一。厘清乡村旅游发展带来的城乡要素流动过程及其机制,既是乡村旅游衔接乡村振兴战略、推动城乡融合发展的重要议题,也是促进乡村旅游高质量发展的题中之义。本文遵循"过程—特征—机制"的研究思路... 详细信息

乡村旅游是促进城乡市场连接的途径之一。厘清乡村旅游发展带来的城乡要素流动过程及其机制,既是乡村旅游衔接乡村振兴战略、推动城乡融合发展的重要议题,也是促进乡村旅游高质量发展的题中之义。本文遵循"过程—特征—机制"的研究思路,分析乡村旅游发展的城乡流动要素类型,总结要素流动过程中的规律与特征,进而阐释要素流动机制。研究表明:乡村旅游带来的要素流动,既涵盖了人、资金、物资等基础要素,也涵盖了生态、文化等核心要素及技术、信息等创新要素。在乡村旅游的萌芽和启动、设计和建设以及运营和转型等发展阶段中,城乡之间的流动要素类型不断增加,要素流向从单向逐步转变为双向,生态和文化是关键要素类型。"需求牵引—价值耦合—市场推动—政策促进"是乡村旅游发展的要素流动机制,合理的流动能促进城乡要素互动以及乡村要素价值增值、类型增多、数量增长,进而推动乡村振兴和城乡融合发展。

关键词：乡村旅游生产要素城乡流动乡村振兴城乡融合

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