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    王中林院士学术讲座通知
    点击量: 录入时间:2018-05-14

     

     

    应龙8国际娱乐pt老虎机网页版航空学院的邀请,中国科学院外籍院士,欧洲科学院院士,佐治亚理工学院终身教授,中国科学院北京纳米能源与系统研究所所长王中林将于515日(周二)下午230在教一楼第三会议室做学术报告,开展学术交流。

    欢迎各位老师及广大研究生同学踊跃参加!

     

    Nanogenerator for self-powered systems, robotics, artificial intelligence and blue energy

     

    Zhong Lin Wang 王中林

     

    Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, China.

    School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia USA

     

    Self-powered system is a system that can sustainably operate without an external power supply for sensing, detection, data processing and data transmission. Nanogenerators (NG) were first developed for self-powered systems based on piezoelectric effect and triboelectrification effect for converting tiny mechanical energy into electricity, which have applications in internet of things, environmental/infrastructural monitoring, medical science, environmental science and security. Here, we first present the fundamental theory of the NGs starting from the Maxwell equations. In the Maxwell’s displacement current, the term  gives the birth of electromagnetic wave, which is the foundation of wireless communication, radar and later the information technology. Our study indicates that, owing to the presence of surface polarization charges present on the surfaces of the dielectric media in NG, an additional term should be added in the Maxwell’s displacement current, which is the output electric current of the NG. Therefore, our NGs are the applications of Maxwell’s displacement current in energy and sensors. NGs have three major application fields: micro/nano-power source, self-powered sensors and blue energy. We will present the applications of the NGs for harvesting all kind mechanical energy that is available but wasted in our daily life, such as human motion, walking, vibration, mechanical triggering, rotating tire, wind, flowing water and more. Then, we will illustrate the networks based on triboelectric NGs for harvesting ocean water wave energy, for exploring its possibility as a sustainable large-scale power supply. Lastly, we will show that NGs as self-powered sensors for actively detecting the static and dynamic processes arising from mechanical agitation using the voltage and current output signals.

     

    [1]    Z.L. Wang, Materials Today, 20 (2017) 74-82.

    [2]    Nanogenerators for Self-Powered Devices and Systems, by Z.L. Wang, published by Georgia Institute of Technology (first book for free online down load): http://smartech.gatech.edu/handle/1853/39262

    [3]    Z.L. Wang, L. Lin, J. Chen. S.M. Niu, Y.L. Zi Triboelectric Nanogenerators, Springer, 2016. http://www.springer.com/us/book/9783319400389

    [4]    Z.L. Wang Triboelectric Nanogenerators as New Energy Technology for Self-Powered Systems and as Active Mechanical and Chemical Sensors, ACS Nano 7 (2013) 9533-9557.

    [5]    Z.L. Wang, J. Chen, L. Lin Progress in triboelectric nanogenertors as new energy technology and self-powered sensors, Energy & Environmental Sci, 8 (2015) 2250-2282.

     

     

     

     

    王中林院士简介

     

      王中林是是佐治亚理工学院终身校董事讲席教授,Hightower终身讲席教授。王中林是首位中组部千人计划顶尖人才与团队入选者,中国科学院北京纳米能源与系统研究所首席科学家和创始所长。王教授是中国科学院大学纳米科学与技术院的院长,也是中科TiSES和中科纳清公司的董事长。王中林是国际公认的纳米科技领域领军人物,在电子显微学,原位物性测量,一维氧化物纳米材料在能源技术、电子技术、光电子技术以及生物技术等应用方面均作出了原创性重大贡献。他发明了压电纳米发电机,摩擦纳米发电机,并首先提出了自驱动系统和蓝色能源的原创大概念,为微纳电子系统的发展,物联网,传感网络和人类未来的能源开辟了新途径。他开创了纳米结构压电电子学和压电光电子学等领域,对纳米机器人、人-电界面、纳米传感器、LED技术的发展具有里程碑意义。

    王教授是中国科学院外籍院士和欧洲科学院院士。王中林是GoogleScholar(谷歌学术)2018年公布的全球纳米技术专家学术引用与影响力排名榜之第一名。

     

    荣获的各类奖励如下:

     

    美国显微镜学会1999年巴顿奖章

    2011年美国材料学会奖章

    2012年美国陶瓷学会埃瓦德奥顿纪念奖奖 2014年美国物理学会詹姆斯马克顾瓦迪新材料奖, 2013中华人民共和国国际科学技术合作奖

    2014年佐治亚理工学院杰出教授终身成就奖

    2014年材料领域世界技术奖

    2015年汤森路透引文桂冠奖

    2016美国东南地区大学联盟杰出科学家奖

    2016欧洲先进材料奖

    2016中国旅美科协美国华人科技创新卓越领袖奖

    2016北京市华侨华人京华奖;北京市首位战略科学家奖

    2017年潘文渊基金会杰出研究奖 2017年全球纳米能源奖

     

    王中林教授是美国物理学会fellow, 美国科学发展协会(AAAS) fellow, 美国材料学会 fellow, 美国显微学会fellow, 美国陶瓷学会fellow

     

     

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