Error convolution structure in discrete Caputo derivatives and global consistency analysis
2019-08-14 10:30 - 11:30 (Asia/Macau) | E11-1006
Instructors/Speakers
Prof. Jiwei ZHANG
School of Mathematics and Statistics
Wuhan University
China
Abstract
Nonuniform time-stepping methods are promising for Caputo reaction sub-diffusion problems because they would be simple and effectiveness in resolving the initial singularity and other nonlinear behaviors occurred away from the initial time. Compared with traditional local methods for the first-order derivative, the numerical analysis for nonlocal time-stepping schemes on non-uniform time meshes are challenging due to the convolution integral (nonlocal) form of fractional derivative. We develop a general framework for the stability and convergence analysis with three tools: a family of complementary discrete convolution kernels, a discrete fractional Gronwall inequality (DFGI) and a global (convolutional) consistency analysis, which is not limited to a specific time mesh by building a convolution structure of local truncation error. It seems that the present techniques are extendable to the variable-order, distributed-order diffusion equations and other nonlocal-in-time diffusion problems.
Biography
Prof Zhang is a Professor of School of Mathematics and Statistics, Wuhan University. He got his PhD degree in Hong Kong Baptist University in 2009. His research area include fast algorithms for fractional PEDs and numerical methods for PDEs.

Multi-View Fusion and Representation for Image Analysis
2019-08-14 11:15 - 12:00 | E11-G015 (University of Macau)
Instructors/Speakers
Prof. Zhe XUE
Beijing University of Posts and Telecommunications
China
Abstract
Real-world data can be described from multiple views. For instance, an image can be described by color histogram, SIFT, HOG and other features. The content of a Web page can be described by texts, images and videos. Describing an object from multiple perspectives constitutes multi-view data. Multi-view learning is to use the complementary nature of different views to improve the learning performance than using a single view. In this talk, I will first briefly introduce some basic concepts and issues in multi-view learning. Then I will introduce some of our recent multi-view learning works for image analysis including multi-view dimensionality reduction, multi-view clustering and incomplete multi-view classification. This report aims to help the audience understand the basic tasks and latest developments of multi-view learning.
Biography
Dr. Zhe Xue received his Ph,D. degree in Computer Science from school of computer and control engineering, University of Chinese Academy of Sciences (UCAS) in 2017. After that, he became an assistant professor at school of computer science, Beijing University of Posts and Telecommunications. His research interest is generally in machine learning and data mining, and particularly in multi-view learning and image analysis. Dr. Xue has published over 20 papers in international conferences and journals such as AAAI, IJCAI, IEEE TCSVT, CVIU, Information Sciences. He has undertook and participated in many projects, including National Key R&D Program of China, 973 Program, National Natural Science Foundation of China and so on. He is the reviewer of ACM MM, DASFAA, IEEE TIFS, Multimedia Tools and Applications and other international journals and conferences. He is also a member of the Intelligent Service Committee of the Chinese Association for Artificial Intelligence.

Integrating Learning with Game Theory for Societal Challenges
2019-08-14 15:15 - 16:00 | N1-1004, Centre for Innovation and Entrepreneurship, Guest House, University of Macau
Instructors/Speakers
Prof. Fei Fang
Institute for Software Research
School of Computer Science
Carnegie Mellon University
USA
Abstract
There is a rising interest in developing artificial intelligence-based tools to help address societal challenges. Motivated by these challenges, we have proposed game theory and machine learning/reinforcement learning-based models and algorithms for problems with strategic interactions among agents. In this talk, I will introduce our models and algorithms that have led to two successfully deploy applications: one used by US Coast Guard for protecting the Staten Island Ferry in New York City since April 2013, the other used in multiple conservation areas around the world for anti-poaching effort. In addition, I will highlight our most recent advances in integrating deep learning with game theory, including computing equilibrium by learning from self-play and end-to-end learning of game parameters.
Biography
Fei Fang is an Assistant Professor at the Institute for Software Research in the School of Computer Science at Carnegie Mellon University. Before joining CMU, she was a Postdoctoral Fellow at the Center for Research on Computation and Society (CRCS) at Harvard University. She received her Ph.D. from the Department of Computer Science at the University of Southern California in June 2016. She received her bachelor degree from the Department of Electronic Engineering, Tsinghua University in July 2011. Her research lies in the field of artificial intelligence and multi-agent systems, focusing on integrating game theory and mechanism design with machine learning. Her work has been motivated by and applied to security, sustainability, and mobility domains, contributing to the theme of AI for Social Good. Her work has won the Distinguished Paper at the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI’18), Innovative Application Award at Innovative Applications of Artificial Intelligence (IAAI’16), the Outstanding Paper Award in Computational Sustainability Track at the International Joint Conferences on Artificial Intelligence (IJCAI’15). Her dissertation is selected as the runner-up for IFAAMAS-16 Victor Lesser Distinguished Dissertation Award, and is selected to be the winner of the William F. Ballhaus, Jr. Prize for Excellence in Graduate Engineering Research as well as the Best Dissertation Award in Computer Science at the University of Southern California. Her work has been deployed by the US Coast Guard for protecting the Staten Island Ferry in New York City since April 2013. Her work has led to the deployment of PAWS (Protection Assistant for Wildlife Security) in multiple conservation areas around the world, which provides predictive and prescriptive analysis for anti-poaching effort.

AI: A Networking and Communication Perspective
2019-08-14 16:30 - 17:30 | E11-1006
Instructors/Speakers
Prof. Quee Seng QUEK
Tenured Associate Professor
Singapore University of Technology and Design (SUTD)
Singapore
Abstract
Recent breakthroughs in artificial intelligence and machine learning, including deep neural networks, the availability of powerful computing platforms and big data are providing us with technologies to perform tasks that once seemed impossible. In the near future, autonomous vehicles and drones, intelligent mobile networks, and intelligent internet-of-things (IoT) will become a norm. At the heart of this technological revolution, it is clear that we will need to have artificial intelligence over a massively scalable, ultra-high capacity, ultra-low latency, and dynamic new network infrastructure. In this talk, we will provide a simple overview of AI for the perspective of networking and communications and share some interesting applications. In addition, we will also share some of our preliminary works in this area.
Biography
Tony Quek is IEEE Fellow, IEEE ComSoc Distinguished Lecturer. He is also the Acting Head of Information System Technology and Design Pillar, Sector Lead for SUTD AI Program, and the Deputy Director of SUTD-ZJU IDEA. Singapore University of Technology and Design. His current research topics include wireless communications and networking, big data processing, network intelligence, URLLC, and IoT.
Tony Quek received the B.E. and M.E. degrees in Electrical and Electronics Engineering from Tokyo Institute of Technology, Tokyo, Japan, respectively. At Massachusetts Institute of Technology (MIT), Cambridge, MA, he earned the Ph.D. in Electrical Engineering and Computer Science. Currently, he is a tenured Associate Professor with the Singapore University of Technology and Design (SUTD).
Dr. Quek has been actively involved in organizing and chairing sessions and has served as a TPC member in numerous international conferences. He is serving as the General Chair for IEEE ICCC 2020. He is currently serving as the Chair of IEEE VTS Technical Committee on Deep Learning for Wireless Communications as well as an elected member of the IEEE Signal Processing Society SPCOM Technical Committee. He was an Executive Editorial Committee Member of the IEEE Transactions on Wireless Communications, an Editor of the IEEE Transactions on Communications, and an Editor of the IEEE Wireless Communications Letters. He is a co-author of a few books published by Cambridge University Press.
Dr. Quek received the 2008 Philip Yeo Prize for Outstanding Achievement in Research, the 2012 IEEE William R. Bennett Prize, the 2016 IEEE Signal Processing Society Young Author Best Paper Award, 2017 CTTC Early Achievement Award, 2017 IEEE ComSoc AP Outstanding Paper Award, and 2016-2018 Clarivate Analytics Highly Cited Researcher.

Gap probability in critical random matrix ensembles and the coupled Painleve II system
2019-08-16 11:15 - 12:15 | E11-1006
Instructors/Speakers
Dr. Shuai-Xia XU
Lecturer
Sun Yat-sen University
China
Abstract
We study the gap probabilities in the critical unitary invariant random matrix ensembles, where the Painleve II and Painleve XXXIV kernels arise. By studying the Fredholm determinants of the Painleve II and Painlev XXXIV kernels, we obtain integral expression of the gap probabilities by using solutions to the coupled Painleve II system. Moreover, the large gap asymptotics are derived with the constant terms given explicitly in terms of the Riemann zeta-function. This talk is based on a joint work with Dan Dai from City University of HongKong.
Biography
Prof. Xu Shuaixia got his PhD degree from Sun Yat-sen University in 2011. From 2011 to 2013, he worked as a postdoctoral fellow at Sun Yat-sen and is currently a lecturer at Sun Yat-sen University. His research areas include nuclear science and technology-other disciplines of nuclear science and technology.

History of the Generalized Inverse & Linear Least Squares
2019-09-09 10:30 - 23:30 | E11-1035
Instructors/Speakers
Prof. Yimin WEI
Professor
School of Mathematical Sciences
Fudan University
China
Abstract
In this talk, we will introduce the history of the generalized inverse and linear least squares problem. Some recent research in this area will be given. Possible future work will also be discussed.
Biography
Prof. Yimin WEI is a professor in Fudan University, China. He has published over 100 papers in mathematics. His recent interest includes matrix analysis, least squares problems and study of multilinear systems.

Security design of IoT products
2019-09-11 14:30 - 15:30 | E11-1006 (University of Macau)
Instructors/Speakers
Mr. Zexin JIANG
Guangzhou Bonson Information System Co. Ltd.
Abstract

簡單自我介紹

平凡的我出生在不平凡的地方
不吃辣椒，卻孤身一路向北
明明可以安穩舒適，卻非要折騰

大四之後的求學

沒有畢業合照的大四
我是如何保送到清華進修的
國家高鐵系統真的運行著我寫的代碼嗎
深深地遺憾

職場折騰

內地壟斷國企是一種什麼樣的存在
獨檔一面是一種什麼樣的感受
如何避免當背鍋俠
我在電網工作5年獲得的5個第一
辭職之後我拿著兩份工資
民企與國企的差異極大
一年時間從產品經理到CTO
技術、產品、工程有什麼區別，變現的誤區

幾點感悟分享

選擇比努力重要
多做事少計較得失
適當包裝自己
風險管理與自我保護

Biography
廣東省普寧人，高級工程師职称，（ISC）2會員、全國電力運行與控制標準委員會標準工作組成員、廣東省電機工程學會成員、廣州市科技評審專家，獲得國家授權專利56項，發表論文12篇，出版專著1本，獲省級科技進步壹等獎、獲2018年廣州市“珠江科技新星”專項資助、2019年廣州市“產業急需緊缺人才”補貼。擁有國際註冊信息安全專家和國家重要信息系統保護人員等職業資格。
2004年-2008年，南京理工大學自動化專業本科學習（專業第1名，GPA 3.9/4.0）。參加全國大學生電子設計大賽獲國家二等獎、全國大學生智能汽車比賽獲得國家二等獎、江蘇省大學生機器人比賽獲得壹等獎、江蘇省優秀本科畢業論文壹等獎、獲得學校最高榮譽獎學金以及每年特等獎學金。
2008年-2011年，清華大學（免試）控制科學與工程專業碩士研究生。期間參與“十壹五”國家重大科技攻關（中國高鐵國產化裝備研發）項目以及和諧號CRH5動車組網絡控制系統的引進消化吸收創新的產品研發工作。研發了支持硬件在環的大規模分布式半實物仿真引擎，研發成果支撐應用於武廣、京津、北京地鐵等線路設備的上線前驗證。
2011年至2016年，廣東電網電力科學研究院（南方電網自動化重點實驗室），歷任助理專責、專責、技術專家、電力機器人攻關團隊組長。從事電力物聯網和電力監控安全防護體系領域的研究工作，主筆編制了南方電網電力監控系統最頂層安全防護技術規範和管理規範等多項企業標準，參與電力行業信息安全標準編制2項，推動商用密碼技術在電力行業的應用，相關成果於2012年獲得廣東省電力行業協會科技創新成果獎、於2013年南方電網青工創新創效成果壹等獎、2014年獲得南方電網科技進步壹等獎。2015年在南方電網全網信息安全攻防競賽獲第1名。
2016年至今，廣州邦訊信息系統有限公司（深交所股票代碼：300366），歷任產品經理、產品副總監、CTO。主要從事工業物聯網和物聯網安全相關產品研發管理工作。創建了公司商用密碼產品線，帶領團隊研發多款物聯網及安全產品，獲得國家密碼局型號認證和公安部檢測認證。

Image Authentication and Tamper Localization
2019-09-11 15:00 - 16:00 | E11-4045
Instructors/Speakers
Prof. Yulin WANG
Full Professor of Wuhan University
China
Abstract
Image authentication can be used in many fields, including e-government, e-commerce, national security, news pictures, court evidence, medical image, engineering design, and so on. Since some content-preserving manipulations, such as JPEG compression, contrast enhancement, and brightness adjustment, are often acceptable—or even desired—in practical application, an authentication method needs to be able to distinguish them from malicious tampering, such as removal, addition, and modification of objects. Therefore, the traditional hash-based authentication is not suitable for the application. As for the semi-fragile watermarking technique, it meets the requirements of the above application at the expense of severely damaging image fidelity. In this talk, we propose a hybrid authentication technique based on what we call fragile hash value. The technique can blindly detect and localize malicious tampering, while maintaining reasonable tolerance to conventional content-preserving manipulations. The hash value is derived from the relative difference between each pair of the selected DCT coefficient in a central block and its counterpart which is estimated by the DC values of the center block and its adjacent blocks. In order to maintain the relative difference relationship when the image undergoes legitimate processing, we make a pre-compensation for the coefficients. Finally, we point out the direction using deep leaning technique for image authentication.
Biography
Prof. Yulin Wang is a full professor and PhD supervisor in the School of Computer Science, Wuhan University, China. He got PhD degree in 2005 from University of London, UK. Before that, he had worked in National Institute of Research and Huawei@ for more than ten years. He has involved more than 20 national and international research projects, and hold 8 patents. He got his master and bachelor degree in 1990 and 1987 respectively from Xi-Dian University, and Huazhong University of Science and Technology, both in China. His research interests include image and video processing, software engineering, information security and artificial intelligence. In recently 10 years, Prof. Wang has published as first author 3 books, 40 conference papers and 45 journal papers, including in IEEE Transactions and ACM Transactions journals. Prof. Wang served as editor-in-chief for International Journal of Advances in Multimedia in 2010. He served as reviewer for many journals, including IEEE Transactions on Image Processing, IEEE Transactions on CSVP and IEEE Transactions on Multimedia. He served as reviewer for many research funds, including National High Technology Research and Development Program of China (‘863’ project). Prof. Wang was the external PhD adviser of Dublin City University, Ireland during 2013-2016. He has served as chairman and keynote speaker at more than 30 international conferences since 2008. He bas been listed in Marcus “who’s who in the world” since 2008. He was selected as scientific and technological innovative talents in Hubei Province in 2014. Since 2012, he has served as Deputy Director of Hubei Science and Technology Commission of China Association for the Promotion of Democracy (CAPD).

Sinotools: a computational framework to analyze cancer genomic sequencing data for precision oncology
2019-09-19 14:30 - 15:30 | E12-G004
Instructors/Speakers
Prof. Bingding HUANG
College of Big Data and Internet
Shenzhen University
Abstract
We have developed a computational framework called Sinotools to analyze cancer genomic sequencing data for precision oncology. First of all, Sinotools can identify very low-frequency variants in ctDNA samples from cancer patients using duplex barcode sequencing technology. Sinotools also includes a novel computational algorithm to identify actionable gene fusion events from targeted sequencing data. Sinotools is available at https://github.com/SinOncology.
Biography
Prof. Bingding Huang received his BSc in Cell Biology from University of Science and Technology of China in 2002. Then he received his Master degree in Computer Science from Saarland University and Max Planck Institute for Informatics under Scholarship from International Max Planck Research School in 2004. Afterwards, he joined the Bioinformatics group in Technical University of Dresden where he received his PhD (Dr.ret.nat) in Computer Science from the Computer Science department in 2007. Then he joined the Molecular and Cellular Modeling group in Heidelberg Institute for Theoretical Studies for one year postdoc training. From 2009 to 2012 he was a Adjunct Associate Professor in Division of Systems Biology, Zhejiang-California International NanoSystems Institute, Zhejiang University China. From 2012 to 2015 Dr. Huang worked as a Bioinformatics Scientist in German Cancer Research Center Heidelberg. Then from 2015 to 2017 he worked as a Senior Computational Biologist in Neo New Oncology AG (Part of Siemens Healthineers). Afterwards, he joined Sinotech Genomics Inc. Shanghai as Vice President of Research and Development and Head of Bioinformatics. Recently Dr. Huang joined the College of Big Data and Internet, Shenzhen University as a full Professor in Bioinformatics and Big data.

Exploring Deep Learning from Feedforward Neural Network Experiments
2019-09-23 15:00 - 16:00 | E11-1006
Instructors/Speakers
Prof. Qin SHENG
Professor
Department of Mathematics
Baylor University
USA
Abstract
Neural network based deep learnings have been used for solving high dimensional (number of dimensions may reach more than several hundreds) partial differential equations. But what is a neural network and how to use it for approximating, or predicting, natural phenomena? In this exploration, we tend to consider approximations of multivariate data through an explicit feedforward neural network (FNN) which is the basic type of neural network. The easy-to-follow formula provides a piecewise constant function for the data. Our FNN architecture has two hidden layers, where the weights and thresholds are explicitly defined and no numerical optimization is required for training. The explicit algorithm does not rely on any tensor structure in multiple dimensions. Instead, it automatically creates Voronoi tessellation of the domain based on the given data, and generates a reliable piecewise constant approximation of the targeted function. These make the construction more practical for multiple applications.
Biography
Prof. Sheng is a professor of Department of Mathematics, Baylor University, USA. He got his PhD degree from the University of Cambridge under the supervision of Professor Arieh Iserles in 1990. His research area include splitting and adaptive numerical methods for solving linear and nonlinear partial differential equations.

Summability and Lebesgue points of two-dimensional Fourier transforms
2019-09-25 10:00 - 11:00 | E11-1015
Instructors/Speakers
Prof. Weisz FERENC
Professor
Department of Numerical Analysis
Eötvös L. University
Hungary
Abstract

Biography
Professor Ferenc Weisz works for Eötvös Loránd University, Department of Numerical Analysis, Budapest, Hungary, Europe. His special field is harmonic analysis, one and higher dimensional Fourier analysis, summability theory, martingale theory, Hardy spaces, spaces with variable exponents, Gabor- and wavelet analysis. He is author of four books published by Springer and Birkhäuser, two course books and of about 200 papers published by international journals. He has got several prizes and awards, amongst other in the last two years the Gabor prize and teh Prize of the Hungarian Academy of Sciences. He has got the Doctor of Science (DSc) degrree of the Hungarian Academy of Sciences in 2001 and the Habilitation of the Eötvös Loránd University, Budapest in 2002.

Ecological models and evaluations in a changing environment - a selection from recent results
2019-09-25 11:00 - 12:00 | E11-1015
Instructors/Speakers
Prof. Marta LADANYI
Head and Assistant Professor
Department of Biometry and Agricultural Informatics
Szent Istvan University
Hungary
Abstract
Agricultural activities are responsible for human well-being while they are facing challenges of increasing impact in a changing environment. Hungary is highly exposed to climate change due to its special location in the middle of Europe. Because of their wide-spread interdependencies, problems aroused in agriculture need interdisciplinary cooperation to be explored.
In our talk, we introduce some new results from the recent researches performed at Szent Istv´an University, Faculty of Horticultural Sciences.
We outline the structure of some problems and the way of communication between researchers from different disciplines. Questions, amongst others, are discussed about

how to find easily measurable and effective indicators to describe the biodiversity quality of agricultural landscapes or the suitability of agricultural soil;
how to measure and manage warming and drought stress from different aspects such as in cases of soil microarthropod communities or medicinal and aromatic plants or invasive pests or the development process and frost volatility of fruit varieties.

We show the exciting process of how from a complex but well formulated ecology problem we can create a simple mathematical model with which we can highlight the main points of the issue.
Biography
Professor Marta Ladanyi works for Szent István University, Faculty of Horticulture, Dpt. of Biometrics and Agricultural Informatics, Budapest, Hungary, Europe. She is an associate professor, the head of the department. Her special field is applied statistics in life sciences including modelling, advanced data management and multivariate statistical analysis.
She has experience in applications in pomology, entomology, plant protection, soil sciences, climate change impact studies, viticulture, botany, vegetable, mushroom, medical and aromatic plant cultivation, dendrology etc. She usually uses statistical softwares, amongst others, SPSS and R.
She has 30 years of teaching experience in applied statistics for BSc, MSc and PhD students in horticultural studies. Most of her students are Hungarian, however, she has several students from several countries, from time to time, also from China.

Luminescent Materials
2019-09-25 14:00 - 15:00 | E11-1028
Instructors/Speakers
Prof. Elena V. USHAKOVA
Associate Professor
Department of Materials Science and Engineering
City University of Hong Kong
Abstract
Nanostructured hybrid materials nowadays are prospective for utilizing them as an active media in novel photovoltaic and optoelectronic devices, such as solar cells and light-emitting diodes. An implementing of lead sulfide quantum dots (PbS QDs) and lead-based perovskite films and nanocrystals (NCs) for future photonic devices with a focus on their optical properties will be discussed.
While designing the nanostructured complex materials one of the main points that should be concerned is the interaction of the material compounds which can result, for instance, in the desired increase of the charge transfer efficiency or in the uncontrollable quenching of luminophore emission. The enhancement of the optical properties, such as absorbance and emission of nanoparticles, is achieved by the fabrication of hybrid material with plasmonic nanoparticles. In particular, I will discuss strong enhancement of near‐infrared emission of PbS QDs induced by Cu2−xSe semiconductor plasmonic NCs both embedded into nanoporous silicate matrix which comes from resonant interaction of QD optical transition dipole with the near field of plasmons of semiconductor plasmonic NCs. Photocurrent and fill‐factor enhancements in meso‐superstructured perovskite solar cells with resonant silicon NPs resulted in increased light absorption will be also discussed. Another important issue in implementing of the nanostructured materials is the stability of their morphology and optical responses while operating at ambient conditions. Here, the optical properties of highly luminescent colloidal perovskite NCs (CsPbX3, where X=Cl/Br, Br, I) embedded in porous glass or opal matrices will be discussed. The use of a nanoporous glass or opal matrices allow obtaining the samples with blue, green, and red perovskite NCs and their mixtures possessing reproducible optical characteristics that are almost similar to that of colloidal solution. Such matrices also prevent the fast degradation of nanocrystals both at the storage in ambient and under UV-light exposure/increasing of the humidity.
Biography
Prof. Elena V. Ushakova is currently a Visiting Associate Professor at the Department of Materials Science and Engineering in City University of Hong Kong. She received her PhD in optics at ITMO University in 2013. After that, she became an Assistant Professor and a Senior Researcher in Prof. Baranov’s group at ITMO University. She has received several personal grants and awards, including the “St. Petersburg Government Grant for young scientists” and the “Grant of the Russian President for young scientists” (2017-2018). Her research interests are focused on the optical properties of colloidal semiconductor quantum dots, metal nanoparticles, perovskite nanocrystals, carbon dots and self-assembled nanostructured materials with optical transitions in the visible and near infrared region.

Electron-Lattice Interactions in Lead and Lead-Free Perovskite Single Crystals
2019-09-27 14:30 - 15:30 | E11-1028
Instructors/Speakers
Prof. Bo WU
Professor
South China Academy of Advanced Optoelectronics
South China Normal University in Guangzhou
China
Abstract
Recently, perovskite materials have gained widespread attentions due to their high potential in optoelectronic applications from solar cells, light-emitting diodes, lasers to photodetectors. For example, the certificated power conversion efficiencies of perovskite solar cells have exceeded 25%, on par with that of silicon. The external quantum efficiencies of perovskite green and red light emitting diodes have reached 20%, a value approaching the best performed OLEDs. Despite the rapid progresses in improving the efficiencies, there remain a lot of questions to be answered about the physical mechanisms lying behind the great successes. In this talk, I will focus on the interactions between the electrons and the perovskite lattice, which are complicated by the soft lead-halide bonds, the hybrid nature of the lattice comprising of both organic and inorganic parts. The talk will be divided into two parts: (1) the thermal-driven dynamical Rashba splitting in lead perovskite single crystals and (2) the strong electron-phonon interactions in bismuth perovskite single crystals. In the first part, through temperature-dependent photoluminescence, Raman spectroscopy and molecular dynamical simulations, we revealed that thermal driven lattice anharmonic polar motions result in dynamical Rashba splitting in lead halide perovskite single crystals, which may lead to indirect tail states and prolong the carrier lifetimes. In the second part, through photoluminescence and transient reflection techniques, we show that a bismuth perovskite single crystal has a carrier mobility of only 0.05 cm2s-1V-1 and relative bright indirect emission, which imply strong carrier localization effect by the electron-phonon coupling in the system. These findings provide significant insights on the underlying physical mechanisms of perovskites, which may pave the way to further development of perovskite optoelectronic materials and their commercialization.
Biography
Professor Wu Bo obtained his bachelor degree in Beijing Normal University in 2009 and Ph.D. degree in Nanyang Technological University in 2014. Now he is a professor in the South China Academy of Advanced Optoelectronics, South China Normal University. His research interest is using spectroscopies and ultrafast spectroscopies to uncover the physical mechanisms of optoelectronic materials and devices, e.g., perovskite solar cells and light emitting diodes, organic solar cells, etc. Till now, he has published more than 40 papers in high-impact journals such as Nature Communications, Advanced Materials, Advanced Functional Materials, ACS Nano etc. He has also published a book on plasmonic organic solar cells and a book chapter on perovskite single crystals in Springer and Wiley, respectively.

Fiber Metal Laminates：Design, Manufacture and Application
2019-10-04 10:00 - 11:30 | E12-G004
Instructors/Speakers
Prof. Jie TAO
College of Material Science & Technology
Nanjing University of Aeronautics and Astronautics
China
Abstract
Fiber metal laminates (FMLs) are composed of metal layers and fiber layers, which are stacked in an alternating sequence of an aluminum or titanium alloy sheet and glass or carbon fiber reinforced resin prepreg. As a novel lightweight hybrid material in the aviation industry, FMLs offer a unique combination of properties such as high specific static properties and excellent impact resistance, along with outstanding fracture and fatigue resistance; these materials have been successfully utilized in the upper fuselage skin structures of the Airbus 380 and the cargo floor of the Boeing 777. In this presentation, I will briefly overview the recent development of novel FMLs based on aluminum-lithium alloys, forming technology for FMLs components, evaluation methods for some mechanical properties, and modification technique of the interface through grafting carbon nanotubes. Apart from the aviation industry, FMLs will also find their application in skin panel of high-speed train and energy absorber of new energy vehicle.
Biography
Prof. Jie Tao is currently a professor at College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics (NUAA). From February 2001 to January 2002, he worked in the Manchester Materials Science Centre at the University of Manchester and UMIST as a visiting scholar. He was the dean of the College of Materials Science and Technology, NUAA from 1998-2008. Now he is the director of Institute of Advanced Materials and Forming Technology, NUAA. He has become Ford Motor Company Professor of materials science at NUAA since 2008. His current research interests are mainly focused on functional coatings, fiber metal laminates and forming technology of metallic materials. He has published 260 papers and 4 books, and acquired 36 patents granted.

Mechanically durable water-repellent coatings for easy-cleaning, anti-corrosion, and anti-icing applications: connecting the dots
2019-10-04 10:00 - 11:30 | E12-G004
Instructors/Speakers
Prof. Zhong CHEN
School of Materials Engineering
Nanyang Technological University
Singapore
Abstract
Water-repellent coatings have a number of engineering applications, including easy-cleaning, anti-corrosion, and anti-icing. In this talk, I will begin with the materials science fundamentals on water repellence, and then explain how these fundamental principles are applied to the development of water-repellent and icephobic coatings. Specific examples will be given for coatings on composites and aluminum alloys, two important classes of industrial materials. Practically useful coatings have to meet manifold requirements including mechanical durability, low cost (non-reliance on expensive equipment and can be easily processed), scalability (large quantity for large area), and applicability to complex shapes, etc. These requirements can be taken into consideration at the coating formulation stage. Future outlooks on water-repellent coatings will be shared. Prof. Chen will also take the chance to share a reflection on his personal research journey so far, using the well quoted “connecting dots” by Steve Jobs.
Biography
Prof. Chen obtained his PhD in 1997 at the University of Reading, U.K. After completing the study, he joined the newly established Institute of Materials Research and Engineering, a national research institute funded by Singapore government. In March 2000, he moved to Nanyang Technological University (NTU) as an Assistant Professor, and has since been promoted to Associate Professor and Professor in the School of Materials Science and Engineering. Prof. Chen’s research interests include 1) Surface Engineering, Thin Films & Nanostructured Materials, and 2) Mechanical Behaviour of Materials. He is an author of over 350 peer-reviewed journal papers, 5 book chapters and 5 granted patents. According to Google Scholar, his journal articles have received over 13,000 citations with the h-index of 58. Since joining NTU, Prof. Chen has graduated 30 PhD and 5 MEng students. Prof. Chen has served as an editor / editorial board member for 8 academic journals. He has also served as a reviewer for more than 70 academic journals and a number of research funding agencies including the European Research Council.

Geometry of Discrete Integrable Systems
2019-10-25 10:30 - 11:30 | E11-1009
Instructors/Speakers
Prof. Anton DZHAMAY
Professor
School of Mathematical Sciences
College of Natural and Health Sciences
University of Northern Colorado
U.S.A.
Abstract
Many interesting examples of discrete integrable systems can be studied from the geometric point of view. In this talk we will consider two classes of examples of such system: autonomous (QRT maps) and non-autonomous (discrete Painlevé equations). We introduce some geometric tools to study such systems, such as the blowup procedure to construct algebraic surfaces on which the mappings are regularized, linearization of the mapping on the Picard lattice of the surface and, for discrete Painlevé equations, the decomposition of the Picard lattice into complementary pairs of the surface and symmetry sub-lattices and construction of a binational representation of affine Weyl symmetry groups that gives a complete algebraic description of our non-linear dynamic.
Biography
Prof. Anton Dzhamay got his undergraduate degree from Moscow Institute of Electronics and Mathematics and his PhD degree from Columbia University under the direction of Professor Igor Krichever. After a postdoc position at the University of Michigan in Ann Arbor, where he worked with Professor Igor Dolgachev, Anton moved to the University of Northern Colorado in 2005, where he is currently a Full Professor. Anton is interested in applications of algebro-geometric techniques to the study of various problems related to the theory of integrable systems and soliton equations, such as theory of Frobenius manifolds and WDVV equations, Whitham hierarchies, isospectral and isomonodromic transformations, and so on. Over the last 10 years his research has been on the geometric theory of discrete Painlevé equations (Sakai’s Theory) and its various applications.

Recurrence coefficients for discrete orthogonal polynomials with hypergeometric weight and discrete Painlevé equations
2019-10-25 12:00 - 13:00 | E11-1009
Instructors/Speakers
Prof. Anton DZHAMAY
Professor
School of Mathematical Sciences
College of Natural and Health Sciences
University of Northern Colorado
U.S.A.
Abstract
Over the last decade it became clear that the role of discrete Painlevé equations in applications has been steadily growing. Thus, the question of recognizing a certain non-autonomous recurrence as a discrete Painlevé equation and understanding its position in Sakai’s classification scheme, recognizing whether it is equivalent to some known (model) example, and especially finding an explicit change of coordinates transforming it to such example, becomes one of the central ones. Fortunately, Sakai’s geometric theory provides an almost algorithmic procedure of answering this question. In this work we illustrate this procedure by studying an example coming from the theory of discrete orthogonal polynomials. There are many connections between orthogonal polynomials and Painlevé equations, both differential and discrete. In particular, often the coefficients of three-term recurrence relations for orthogonal polynomials can be expressed in terms of solutions of some discrete Painlevé equation. In this work we study orthogonal polynomials with general hypergeometric weight and show that their recurrence coefficients satisfy, after some change of variables, the standard discrete Painlevé-V equation. We also provide an explicit change of variables transforming this equation to the standard form. This is joint work with Galina Filipuk (University of Warsaw, Poland) and Alexander Stokes (University College, London, UK)
Biography
Prof. Anton Dzhamay got his undergraduate degree from Moscow Institute of Electronics and Mathematics and his PhD degree from Columbia University under the direction of Professor Igor Krichever. After a postdoc position at the University of Michigan in Ann Arbor, where he worked with Professor Igor Dolgachev, Anton moved to the University of Northern Colorado in 2005, where he is currently a Full Professor. Anton is interested in applications of algebro-geometric techniques to the study of various problems related to the theory of integrable systems and soliton equations, such as theory of Frobenius manifolds and WDVV equations, Whitham hierarchies, isospectral and isomonodromic transformations, and so on. Over the last 10 years his research has been on the geometric theory of discrete Painlevé equations (Sakai’s Theory) and its various applications.

Periodic homogenization of non-symmetric Levy-type processes
2019-10-28 11:00 - 12:00 | E11-1006
Instructors/Speakers
Prof. Xin CHEN
Special Research Fellow
School of Mathematical Sciences
Shanghai Jiao Tong University
China
Abstract
In this paper, we consider the homogenization problem for a non-symmetric L´evy-type operator in a medium with a periodic structure. Under a proper scaling of this operator, we establish the limit behavior of the rescaled operator as the scaling parameter tends to zero. This talk is based on a joint work with Zhen-qing Chen, Takashi Kumagai and Jian Wang.
Biography
Prof. Chen received his PhD at Warwick University, and is now a special research fellow (equal to associate professor) at Shanghai Jiao Tong University. His main research fields are stochastic process and stochastic analysis. Prof. Chen has published nearly 20 papers in top journals such as Probability Theory and Related Fields, Communication in Mathematical Physics, Journal of Functional Analysis and so on.

Will artificial intelligence save the Mathematics?
2019-10-29 08:30 - 09:30 | E22-G013

Couplings and Wasserstein-type distances for SDEs with Lévy noises
2019-10-29 15:00 - 16:00 | E11-1009
Instructors/Speakers
Prof. Jian WANG
Professor
College of Mathematics and Informatics
Fujian Normal University
China
Abstract
In this talk we review some recent works on couplings of SDEs with Levy noises. As applications, we consider the corresponding ergodic properties in term of the total variation and the $W_1$-distance.
Biography
Prof. Jian WANG received his PhD from Beijing Normal University, and is now a full professor at Fujian Normal University. His main research fields are stochastic process and stochastic analysis. Prof. Wang has published more than 80 papers in top journals such as Journal of European Mathematical Society, Memoir of American Mathematical Society, Communication in Mathematical Physics, Journal of Functional Analysis and so on.

'Digital Hong Kong' Multi-hazard Risk Evaluation in Extreme Weather Conditions
2019-11-01 15:30 - 16:30 | E11-1009
Instructors/Speakers
Prof. Limin ZHANG
Chair Professor of Geotechnical Engineering
Director of Geotechnical Centrifuge Facility
Associate Director of Great Smart Cities Institute
Associate Head of Department of Civil and Environmental Engineering
Hong Kong University of Science and Technology
Hong Kong
Abstract
An extreme storm may trigger a large number of flood spots, landslides and debris flows in Hong Kong. The consequences can be catastrophic. To develop strategies to cope with geohazrads induced by extreme rainstorms, a good understanding of the generation and propagation of hazards during a storm is essential. HKUST is in the process of developing a “Digital Hong Kong” multi-hazard simulation platform to evaluate possible hazardous processes in critical rainstorms in the entire Hong Kong. The simulation framework is introduced and its potential use in enhancing the resilience of Hong Kong is discussed in this seminar.
Biography
Prof. Limin Zhang is Chair Professor of Geotechnical Engineering, Director of Geotechnical Centrifuge Facility and Associate Director of Great Smart Cities Institute at the Hong Kong University of Science and Technology. His research areas include slopes, dams, geotechnical risk assessment and management, and centrifuge modeling. Prof. Zhang is Chair of ISSMGE TC210 on Embankment Dams and Chair of ASCE Risk Assessment and Management Committee. He is also Editor-in-Chief of International Journal Georisk, Associate Editor of ASCE’s Journal of Geotechnical and Geoenvironmental Engineering, and editorial board member of Engineering Geology, Computers and Geotechnics and several other journals.

Web Identity Security (WIS) in Big Data Er
2019-11-06 10:30 - 11:30 | E11-4045 (University of Macau)
Instructors/Speakers
Dr. Wenyin LIU
WIS Lab
Guangdong University of Technology
Abstract
A web identity is an identifier that uniquely identifies and represents an entity in the Cyberspace. Web identity security focuses on accurate identity verification and prevention of identity impersonation, fraud, leakage, theft, etc. Nowadays, the increasing scale of the Web gives rise to the problems of “Password Fatigue”, “Phishing Attacks” and “Brute Force Password Attacks”, and brings great challenges to the currently dominant password-based web identity authentication scheme.
In this talk, we will first present the threats and challenges to Web identity security and then introduce our solutions and suggestions. In particular, we propose a new web identity authentication mechanism by introducing a module named “Trusted User Agent” in the authentication process, which is compatible with the current password-based mechanism. Specifically, the user account information is automatically generated by, stored in the trusted user agent, and directly sent to the corresponding server, which authorizes the corresponding session on the specific terminal after successful authentication. This forms a secure closed authentication loop, in which credentials will never be sent to, and stolen by phishers at the browser. The proposed mechanism helps users automatically register new accounts with unlinkable identities and strong passwords, thus free from password cracking. We develop a system based on this mechanism and implement automatic change of passwords as well. Analyses and user studies have been conducted to show its security, usability, and deployability, being superior to the current password-based mechanism.
A phishing detection mechanism based on parasitic community will then be presented, which not only reaches an accuracy of 99.2%, but is the only system in the world capable of discovering phishing targets. A deep learning based solution will also be presented, which can detect a phishing URL with a very fast speed (20ms) and a very high precision (TPR=98.45% while FPR=0.01%).
Biography
Dr. Liu Wenyin is currently a Professor in School of Computer Science and Technology, Guangdong University of Technology. He was Deputy Director of Multimedia software Engineering Research Centre at the City University of Hong Kong from 2013 to 2016, an assistant professor in the Department of Computer Science at the City University of Hong Kong from 2002 to 2012, and a full time researcher at Microsoft Research China/Asia from 1999 to 2001. His current research interests include blockchain, anti-phishing, Web identity authentication and management. He has BEng and MEng degrees in computer science from Tsinghua University, Beijing and a doctoral degree from the Technion, Israel Institute of Technology, Haifa. In 2003, he was awarded the IAPR/ICDAR Outstanding Young Researcher Award. In 2010, he was elected to IAPR Fellow for his contributions to graphics recognition and anti-phishing. He had been TC10 chair of IAPR for two terms 2006-2010. He had been on the IAPR Fellow Committee for three terms 2010-2016. He had been on the editorial boards of the International Journal of Document Analysis and Recognition (IJDAR) from 2006 to 2011 and the IET Computer Vision journal from 2011-2012. He is also an angel investor in the areas of cybersecurity, blockchain, big data, and Robots.

The Technology and Application of Speech Translation
2019-11-08 10:30 - 11:30 | E12-G003
Instructors/Speakers
Dr. Boxing CHEN
Machine Intelligence Lab
DAMO Academy of Alibaba Group
Abstract
With the significant performance improvement of automatic speech recognition and machine translation, speech translation comes to the real life from the science fiction. There are two paradigms for speech translation: cascaded and end2end speech translation systems. Due to the size of the available training data, cascaded speech translation system still over-performs the end2end speech translation system. However, cascaded speech translation system also suffers the error propagation problem. ASR errors, punctuation restoration, language informality, and disfluency etc. are the main challenges for speech translation. We invest effort in all components of the cascaded speech translation system. We achieve improvement for each component in the pipeline, therefor result better overall speech translation performance. We show some scenarios at Alibaba, which we apply speech translation for technical lecture, communications between buyer and seller, oversea traveling, etc.
Biography
Boxing Chen is a Senior Algorithm Expert at Machine Intelligence Lab, DAMO Academy of Alibaba Group. He works on natural language processing, mainly focus on machine translation. Prior to Alibaba, he was a Research Officer at the National Research Council Canada (NRC), Senior Research Fellow at the Institute for Infocomm Research in Singapore, a Postdoc at FBK-IRST in Italy and a Postdoc at the University of Grenoble in France. He received his PhD degree from Chinese Academy of Science and Bachelor degree from Peking University in China. He has co-authored more than 50 papers in the NLP conferences and journals. He has received the “The best paper award” from MT Summit 2013, and “The best paper award nomination” from ACL 2013. His teams ranked the first place in WMT 2018 for five translation tasks and six quality estimation sub-tasks; the first place in WMT 2017 Russian-to-English translation, the first place in the NIST 2012 OpenMT Chinese-to-English translation, the first place in the IWSLT 2007 Chinese-to-English translation and IWSLT 2005 Chinese-to-English and Japanese-to-English translation, etc.

The “smart water” application on urban water network distribution real-time monitoring and control system
2019-11-08 11:00 - 12:00 | E11-1009
Instructors/Speakers
Prof. Jeffrey Y. CHENG
Associate Professor of Civil Engineering
School of Engineering
University of Guam
Guam
Abstract
The “smart water systems” have been introduced to China since 2010 summer in EXPO 2010, which could be the leading way to improve the urban water distribution problems. In the network age of “4G” going to be “5G”, leveraging recent advances in technologies surrounding the Internet devices, urban water distribution systems are poised to transform water supplies management by enabling ubiquitous real-time sensing and control.
This paper introduces the methodology of urban water distribution system data collection, database creation and management, GIS and BIM applications, EPA-NET hydraulic and water quality model creation, real-time sensing and control application. And combined them into a completed real time urban water distribution monitoring program, the program not only be able to monitoring the metro water distribution but also utilize artificial intelligence (AI) and machine learning to predict the potential issues in the system and provide the optimized solution.
Biography
Prof. Jeffrey Y. CHENG is currently an Associate Professor of Civil Engineering of the University of Guam. Prof. Cheng obtained his PhD Degree in Civil Engineering from the University of Colorado in 2011. He has been teaching in St Cloud State University, University of Colorado Denver, Metro State University of Denver and Los Angeles Pierce College before his current position in University of Guam. Prof. Cheng also has rich industrial experience for over 20 years, he is currently a senior water resource engineering in Engineering Analytics Inc. Ft Collins CO. Prof. Zhang is working on multiple research projects namely “Flood Mitigation and Water Quality Improvement of City McGregor”, “Quarry Park and Nature Preserve Water Quality Concern Analysis”, “Digital Open Channel Flume Design and Construction” , “Statistical hydrology data analysis for Minnesota regional area” and “Reclamation Action Plan, Design and Construction of Idorado Mine Site”.

Depth-based Image Processing for Occlusion and Reflection Removal
2019-11-25 11:30 - 12:30 | E11-1006 (University of Macau)
Instructors/Speakers
Prof. Daniel P. K. LUN
Department of Electronic and Information Engineering
Hong Kong Polytechnic University
Abstract
In 3D computer graphics, the depth map of a scene is a dataset that provides information about the distance of the surfaces of scene objects from a viewpoint. Nowadays, we can effectively estimate the depth map of a scene using different hardware or software techniques. It is particularly the case with the recent high-end mobile devices which are all equipped with multiple cameras. The depth map can be estimated using different triangulation methods based on the multiple images captured by the cameras. Once the depth map is obtained, the next question is what we can do with such additional information of the scene. In this seminar, the use of the depth information in occlusion removal and reflection removal is discussed. It will be shown that the depth information enables some interesting image processing functions that can hardly be achieved in the past. By using modern data-driven methods, these depth-based image processing applications can be accomplished within a couple of seconds when running with a GPU. They will be the next applications of modern mobile devices with GPU support.
Biography
Daniel, P.K. Lun received his B.Sc.(Hons.) degree with 1st Class Honours from the University of Essex, U.K., and PhD degree from the Hong Kong Polytechnic University (formerly called Hong Kong Polytechnic) in 1988 and 1991, respectively. In 1991, he joined the Hong Kong Polytechnic University, and is now an Associate Professor and Associate Head of the Department of Electronic and Information Engineering. Dr Lun is active in research. He has published more than 150 international journals and conference papers in the areas of wavelets theory, signal and image enhancement, computational imaging and deep neural networks. One of his research projects “A study of the Computer Tomography and the Wavelet Transform” was rate as Excellent by the Hong Kong Research Grants Council. He and his research students have also received three best paper awards in international conferences. Dr Lun was the Chairman of the IEEE Hong Kong Chapter of Signal Processing in 1999-00. He was the General Chair of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing (ISIMP 2004), and General Co-Chair of 19th International Conference on Digital Signal Processing (DSP 2014). He was also the Technical Co-Chair of 2015 APSIPA Annual Summit and Conference (APSIPA ASC 2015), and Technical Co-Chair of 2015 IEEE 20th International Conference on Digital Signal Processing (DSP 2015). He was the executive committee members of a number of other conferences including the 2003 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2003), 2010 IEEE International Conference on Image Processing (ICIP 2010) and 2017 IEEE International Conference on Multimedia and Expo (ICME 2017). He received the Certificate of Merit from the IEEE Signal Processing Society for dedication and leadership in organizing the 2010 IEEE International Conference on Image Processing (ICIP). He is a member of the IEEE Circuits and Systems Society VSPC and DSP Technical Committees. He was the Editor of HKIE Transactions published by the Hong Kong Institution of Engineers in the area of Electrical Engineering. He was also the leading guest editor of a special issue of EURASIP journal of Advances in Signal Processing. He is currently an Associate Editor of IEEE Signal Processing Letters and IEEE Open Journal of Circuits and Systems. Dr Lun is a Chartered Engineer, a fellow of IET, a corporate member of HKIE and a senior member of IEEE.

BIM and its Development in Hong Kong
2019-11-28 16:00 - 17:00 | E12-G004

Synthesis of Mg based Metal Hydrides for Hydrogen Storage
2019-11-29 11:00 - 12:00 | E12-G003
Instructors/Speakers
Dr. Kohta ASANO
Senior Researcher of Senior Researcher of Research Institute of Energy Frontier
National Institute of Advanced Industrial Science and Technology (AIST)
Japan
Abstract
Metal hydrides have a number of properties that may be utilized to promote the use of hydrogen as an energy carrier. Those with a high hydrogen permeability can be applied as membranes for hydrogen separation, while the optical changes occurring in metal thin films upon hydrogenation can be used for hydrogen sensing. Even better known is the fact that the high volumetric density of hydrogen makes metal hydrides an attractive option to store energy. The applicability of metal hydrides for storage applications depends on its affinity to hydrogen which determines the equilibrium pressure for (de-)hydrogenation. One of the most attractive hydride forming metals is Mg because of its light weight and low material costs. However, the Mg-H system has thermodynamic and kinetic limitations associated with hydrogen absorption and desorption processes: the high stability of the MgH2 phase and the slow diffusion of hydrogen in Mg and MgH2 at moderate temperatures and pressures.
A possible way to destabilize MgH2 and enhance the reaction kinetics is to reduce the size of Mg. It has been calculated that MgH2 is destabilized by decreasing the size on a nanometer scale. We have successfully synthesized nanometer-sized MgH2 clusters, which form in a self-organized way by the hydrogenation of non-equilibrium Mg-TM (TM: Ti, Mn, Cr, Fe etc.) alloys. Here MgH2 is destabilized by the interface energy between the two metal hydrides. Our results suggest that we can tune the thermodynamics and kinetics of hydrogen absorption and desorption in Mg-H. This concept paves the way for the development of lightweight and cheap Mg-based functional materials in the metal-hydrogen system.
Biography
Dr. Kohta Asano, (Ph.D. Eng.), now is a Senior Researcher, Hydrogen Industrial Use and Storage Group, Research Institute of Energy Frontier, National Institute of Advanced Industrial Science and Technology (AIST) in Tsukuba. He got his B. Eng., M. Eng. and Ph.D. Eng. in Materials Science at Tohoku University in Sendai. He has studied metal hydrides for hydrogen storage applications at AIST from 2005. His main research topics are diffusion of hydrogen studied by solid state NMR and synthesis of novel Mg based alloys and hydrides. He has studied them also at Delft University of Technology in the Netherlands from 2013 to 2014.

Novel Mg-based Amorphous Alloys and Nanocomposites Induced from Amorphous Alloys for Hydrogen Storage
2019-11-29 11:00 - 12:00 | E12-G003
Instructors/Speakers
Prof. Huai-Jun LIN
Associate Professor of Institute of Advanced Wear & Corrosion Resistance and Functional Materials
Jinan University
China
Abstract
MgH2 has been widely considered as a promising candidate for hydrogen storage because it stores 7.6 wt% of hydrogen, however thermodynamics and kinetics for hydrogen absorption and desorption are not well satisfied. Abundant efforts have been devoted to prepare nanostructured Mg-based materials with enhanced hydrogen storage. Although kinetics improvements could be well achieved, thermodynamics issues are remained in Mg-based hydrogen storage materials.
We attempted to prepare novel Mg-based amorphous alloys for hydrogen storage applications. The results could be summarized as follows: (1) A hydrogen-induced glass-to-glass transition in Mg-Ce-Ni amorphous alloys with a storage capacity of 5 wt%-H is reported. The hydrogen storage capacity of amorphous hydrides is obviously higher than that of their crystalline counterparts owing to the free volume and disordered atomic structure associated with glasses. (2) The dehydrogenation temperature of the amorphous hydrides can be efficiently tuned as it shows a close relationship with the enthalpy of mixing between the alloying element and hydrogen. (3) Further study on the five-component Mg60Ce10Ni20Cu5X5 (X = Co, Zn) amorphous alloys shows that addition of Co greatly improves the hydrogenation kinetics and capacity, indicating that geometry issue is not a key factor on influencing the hydrogenation properties of the studied Mg-based amorphous alloys. (4) Similarly, minor alloying addition of Ag improves the hydrogen storage capacity and reduces the dehydrogenation temperature of the amorphous Mg65Cu25Y10 alloy. (5), High-pressure torsion (HPT) is applied to reduce the hydrogenation temperature and improve the hydrogenation kinetics of Mg-based amorphous alloy, which is due to the introduction of nanoglasses regions and interfaces among them providing abundant pathways for fast hydrogenation.
Moreover, hydrogenation treatment of the Mg-based amorphous alloys at temperature above the crystallization temperatures will lead to the formation of hydrides nanocomposites consisting of MgH2, Mg2NiH4 and so on. Hydrogen storage properties of the nanocomposites could be well tuned by designing the chemical compositions and phase structures, by controlling the hydrogen activation treatments, and by designing subsequent oxidation treatment upon the nano-hydrides composites etc.
Biography
Prof. Huai-Jun Lin serves as associate professor in Jinan University, Guangzhou, China from 2017. During his PhD study, he obtained a CSC scholar and studied as a visiting student in Kyushu University, Japan from 2013 to 2014. After completing his Ph.D. degree in Materials Science and Engineering from South China University of Technology, China in 2014, he worked in Kyushu University as a Postdoctoral fellow from 2015 to 2016. His research interests include hydrogen storage materials, functional applications of amorphous alloys and battery etc.

11th IEEE PES Asia-Pacific Power and Energy Engineering Conference (IEEE APPEEC 2019)
2019-12-01 - 2019-12-04
