上海交通大学姚振鹏 - - Powered by Discuz!

标题: 上海交通大学姚振鹏 [打印本页]

作者: jia33 时间: 2022-10-31 18:43
标题: 上海交通大学姚振鹏
姚振鹏，长聘教轨副教授，博士生导师，海外引进高层次青年人才。2018年于美国西北大学材料科学与工程系获博士学位，师从第一性原理领域奠基人之一Chris Wolverton教授。并于次年加入量子化学、深度机器学习与机器自主实验室领域顶尖的哈佛大学化学与化学生物系Alan Aspuru-Guzik课题组进行博士后研究工作。研究领域包括高能电极材料与电解质、固态离子导体、二维材料、框架化学、化学信息学、基于深度机器学习的材料设计、材料基因组研究等。其中，提出了一种阴离子氧化还原电化学储能机理，在高能量密度锂离子电池的开发中取得理论性突破，该工作被选为突出论文发表在Nature Energy上，被包括美国能源部在内的 20 多家政府、新闻单位进行了报导，已获得相关专利，并获授美国化学储能协会优秀成果奖。在框架材料学领域，搭建了首座纳米多孔材料优化设计平台，以人工智能和材料基因组为核心，创造性实现了性能引导的有机金属框架机器自主设计，并在多个能源应用领域取得突破。Nature Machine Intelligence杂志发表了该工作，并为美国科学促进会AAAS等多家新闻媒体报导。此外，还参与发现了以钴酸锂为代表的层状氧化物的成分与结构的相关性，解决了长久以来的晶体学难题-层状材料结构预测问题，为基于层状氧化物的高性能电极材料的加速开发打下基础，该工作以发表在Science上。以第一/共一/通讯作者身份相关工作发表在Science, Nature Energy, Nature Review Materials, Nature Machine Intelligence, Science Advances, Nature Communications, JACS, Matter, Chem, Advanced Materials, Angew等杂志。长期担任Science Advances, Nature Communications, Joule, Matter, Chemistry of Materials等著名杂志审稿人。

姚振鹏
所属二级机构：复合材料研究所
硕导/博导：博导
通讯地址：上海市闵行区东川路800号上海交通大学材料学院D楼301室
电子邮箱：z.yao@sjtu.edu.cn

教育经历
2004-01 ~ 2008-01 华中科技大学  无  学士
2009-01 ~ 2012-01 上海交通大学  无  硕士
2012-01 ~ 2018-01 Northwestern University  无  博士

工作经历
2018-10 ~ 2021-10 Harvard University 博士后研究员
2021-10 ~ 至今上海交通大学长聘教轨副教授，博士生导师

研究方向
高能量密度电极与电解质材料开发，金属有机框架材料 (MOF, COF) 基因组，面向光电子应用的二维材料设计，面向储能与合金领域的高熵材料设计。
基于深度机器学习、第一性原理计算与自主实验室技术的闭环材料逆向设计。

论文信息

C. Zhao†, Q. Wang†, Z. Yao†, B. Sánchez-Lengeling, J. Wang, X. Bai, B. Li, A. Aspuru-Guzik, M. Wagemaker, L. Chen, Y.-S. Hu, Rational design of layered sodium oxides via the “Cationic potential”, Science, 370, 6517, 708-711 (2020). (†: Equal Contribution)
Z. Yao, S. Kim, J. He, V. I. Hegde, C. Wolverton, Interplay of Cation and Anion Redox in Li4Mn2O5 Material and Prediction of Improved Li4(Mn,M)2O5 Cathodes for Li-ion Batteries. Science Advances, 4, eaao6754 (2018).
H. Zhu†, Z. Yao†, H. Zhu, Y. Huang, J. Zhang, C. C. Li, K. M. Wiaderek, Y. Ren, H. Zhou, L. Fan, Y. Chen, H. Xia, L. Gu, Q. Liu, Unblocking oxygen charge compensation for stabilized high-voltage P2-type structure in sodium-ion cathode, Nature Communications, accepted and in press, (2021). (†: Equal Contribution)
Z. Yao, V. Hegde, A. Aspuru-Guzik, C. Wolverton, Discovery of the calcium-metal alloy anodes for reversible Ca-ion batteries, Advanced Energy Materials, 1802994 (2019).
C. Zhan†, Z. Yao†, J. Lu, L. Ma, V. Maroni, L. Li, E. Lee, E. E. Alp, T. Wu, J. Wen, Y. Ren, C. S. Johnson, M. M. Thackeray, M. Chan, C. Wolverton, K. Amine, Enabling the High Capacity of Lithium-rich Anti-fluorite Lithium Iron Oxide by Simultaneous Anionic and Cationic Redox, Nature Energy, 2, 963–971 (2017). (†: Equal Contribution, Editor Featured Article)
Z. Yao*, B. Sánchez-Lengeling, N. S. Bobbitt, B. J. Bucior, S. G. H. Kumar, S. P. Collins, T. Burns, T. K. Woo, O. K. Farha, R. Q. Snurr*, A. Aspuru-Guzik*, Inverse design of nanoporous crystalline reticular materials with deep generative models, Nature Machine Intelligence, 3, 76-86 (2021). (*: Corresponding author)
C.-P. Wang, Y. Feng, H. Sun, Y. Wang, J. Yin, Z. Yao*, X.-H. Bu*, J. Zhu*, Self-Optimized MOF Electrocatalysts with Structural Stability and High Current Tolerance for Water Oxidation, ACS Catalysis, 11, 7132-7143 (2021). (*: Corresponding author)
Q. Wang, Z. Yao, C. Zhao, T. Verhallen, D. P. Tabor, F. Ooms, F. Kang, A. Aspuru-Guzik, Y.-S. Hu, M. Wagemaker, B. Li, Interface chemistry of an amide electrolyte for highly reversible lithium metal batteries, Nature Communications, 11, 4188 (2020).
Y. Zhao, F. Jiang, H. Hong, D. Wang, Q. Li, Y. Meng, Z. Huang, Y. Guo, X. Li, A. Chen, R. Zhang, S. Zhang, J. C. Ho, Z. Yao*, W. Liu*, and C. Zhi*, Stable Bismuth-Antimony Alloy Cathode with a Conversion Dissolution/Deposition Mechanism for High-Performance Zinc Batteries, Materials Today, accepted and in press, (2021). (*: Corresponding author)
Q. Li†, Z. Yao†, E. Lee, Y. Xu, M.M. Thackeray, C. Wolverton, J. Wu, V.P. Dravid, Dynamic imaging of crystalline defects in lithium-manganese oxide electrodes during electrochemical activation to high voltage, Nature Communications, 10, 1692 (2019). (†: Equal Contribution, Editor’s Feature Article)
H. Wang†, Z. Yao†, G. S. Jung, Q. Song, M. Hempel, T. Palacios, G. Chen, M. J. Buehler, A. Aspuru-Guzik, J. Kong, Frank-van der Merwe Growth in Bilayer Graphene, Matter, 4, 1-15, (2021). (†: Equal Contribution)
C. Zhao†, Z. Yao†, Q. Wang, H. Li, J. Wang, Y. Lu, J. Cabana, Li, X. Bai, A. Aspuru-Guzik, M. Wagemaker, L. Chen, and Y.-S. Hu, Revealing High Na-Content P2-Type Layered Oxides for Advanced Sodium-Ion Cathodes, Journal of the American Chemical Society, 142, 12, 5742-5750 (2020). (†: Equal Contribution)
C. Zhao†, Z. Yao†, J. Wang, Y. Lu, X. Bai, A. Aspuru-Guzik, L. Chen, Y.-S. Hu, Ti-substitution stabilizing high-voltage plateau in Na2/3Mg1/3Ti1/6Mn1/2O2 cathode, Chem, 5, 11, 2913-2925 (2019). (†: Equal Contribution)
Z. Yao, S. Kim, K. Michel, Y. Zhang, M. Aykol, C. Wolverton, Stability and Conductivity Study of the Complex Lithium Borohydride Based Solid-state Electrolytes from First Principles, Physical Review Materials, 2, 065402-065408 (2018).
Z. Yao, S. Kim, M. Aykol, Q. Li, J. Wu, J. He, and C. Wolverton, Revealing the Conversion Mechanism of transition metal oxides during Lithiation from First Principles Calculations, Chemistry of Materials, 29, 21, 9011-9022 (2017).
S. Li†, Z. Yao†, J. Zheng, M. Fu, J. Chen, S. Hwang, A. Orlov, J. Zhang, S. Wang, Z. Chen, D. Su, Direct observation of defect-aided structural evolution in Ni-rich layered cathode during delithiation, Angewandte Chemie International Edition, 59, 2-10 (2020). (†: Equal Contribution)
X. Wang†, Z. Yao†, S. Hwang, Y. Pan, H. Dong, M. Fu, N. Li, K. Sun, H. Gan, Y. Yao, A. Aspuru-Guzik, Q. Xu, D. Su, In situ Electron Microscopy Investigation of Sodiation of Titanium Disulfide Nanoflakes, ACS nano, 13, 8, 9421-9430 (2019). (†: Equal Contribution)
Y. Cheng†, Z. Yao†, Q. Zhang, J. Chen, W. Ye, S. Zhou, H. Liu, and M.-S. Wang, In Situ Atomic-Scale Observation of Reversible Potassium Storage in Sb2S3@Carbon Nanowire Anodes, Advanced Functional Materials, 2005417 (2020). (†: Equal Contribution)
X. Wang†, Z. Yao†, S. Hwang, L. Zhang, M. Fu, S. Li, L. Mai, Q. Xu, D. Su, On the Irreversible Sodiation of Tin Disulfide, Nano Energy, 79, 105458 (2020). (†: Equal Contribution)
H. Wang, Z. Yao, L. Acauan, J. Kong, B. L. Wardle, Toward MXene interconnects, Matter, 4, 5, 1447-1449 (2021).
M. Fu†, Z. Yao†, X. Ma, H. Dong, K. Sun, S. Hwang, E. Hu, H. Gan, Y. Yao, E.A. Stach, C. Wolverton, and D. Su, Expanded Lithiation of Titanium Disulfide: Reaction Kinetics of Multi-Step Conversion Reaction, Nano Energy, 63, 103882 (2019). (†: Equal Contribution)
S. Kim, Z. Yao, J. Lim, M. C. Hersam, C. Wolverton, V. P. Dravid, Kai He, Atomic-Scale Observation of Electrochemically Reversible Phase Transformations in SnSe2 Single Crystals, Advanced Materials, 1804925 (2018). (Cover Featured Article)
Q. Li†, Z. Yao†, J. Wu†, S. Mitra, S. Hao, T. S. Sahu, Y. Li, C. Wolverton, V. P. Dravid, Intermediate Phases in Sodium Intercalation into MoS2 Nanosheets and Its Implications for Sodium-Ion Battery, Nano Energy, 38, 342-349 (2017). (†: Equal Contribution)
C. Zhao, Z. Yao, D. Zhou, L. Jiang, V. Murzin, Y. Lu, A. Aspuru-Guzik, L. Chen, and Y.-S. Hu, Constructing Na-Ion Cathodes via Alkali-Site Substitution, Advanced Functional Materials, 1910840 (2020).
R. Pollice†, G. dos Passos Gomes†, M. Aldeghi†, R. Hickman†, M. Krenn†, C. Lavigne†, M. Lindner-D'Addario†, K. A. Nigam†, C.-T., Ser†, Z. Yao†, A. Aspuru-Guzik, Data-Driven Strategies for Accelerated Materials Design, Accounts of Chemical Research, 54, 4, 849–860, (2021). (†: Equal Contribution).

作者: jia33 时间: 2022-10-31 18:44
近日，国际著名学术期刊《自然-材料综述》(Nature Reviews Materials)在线刊登了上海交通大学材料科学与工程学院姚振鹏副教授团队与合作团队的综述文章“Machine learning for a sustainable energy future”，为机器学习在能源材料、设备、管理等领域的相关推动作用提供了前瞻方向。该论文以上海交通大学为第一单位，上海交通大学材料科学与工程学院姚振鹏副教授为第一作者。
从化石能源过渡到可再生能源是一项重大的全球挑战，需要整个能源产业在材料、设备和系统层面取得进步，以实现可再生能源的高效收集、储存、转换和管理。能源领域研究人员已经开始利用机器学习技术来促成这些进步(图1)。

图1 传统与机器学习加速的材料开发范式

在材料综述中，团队重点介绍了机器学习推动的能源研究最新进展，概述了当前面对的挑战并前瞻了未来的发展方向，并同时描述了充分利用机器学习技术所需的前提条件。团队引入了一组材料加速开发性能指标 (XPIs)，用于比较不同机器学习范式对能源研究推进效果的区别与进步空间。同时讨论和评估了将机器学习应用于能量收集(光伏)、存储(电池)、转换(电催化)和管理(智能电网)的最新进展。最后，概述了机器学习在能源领域的潜在研究领域(图2)。

图2 机器学习在可再生领域的应用发展方向

此外，团队在同期《自然-物理综述》(Nature Reviews Physics) 上还发表了综述“On scientific understanding with artificial intelligence”，系统概括了人工智能在推动科学理论建立领域的最新进展。近年来，该团队在电化学储能、高通量实验与计算、深度机器学习等领域开展了广泛的研究，相继在Science、Nature Energy、Nature Catalysis、Nature Machine Intelligence、Science Advances、Nature Communications、Matter、Accounts of Chemical Research等学术期刊上发表了一系列研究论文。

欢迎光临 (http://cailiaoquan.com/)