신소재공학과

Seminar

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Date 20190128

<MSE SPECIAL SEMINAR>

 

■ Title : Computational Discovery and Design of Materials for Energy Technologies

 

■ Speaker : Prof. Yongjin Lee (ShanghaiTech Univ.) 


■ Date and Time : 2019/1/28 (Mon) 16:00 

 

■ Venue : Applied Engineering Building (W1-1) Room #2427 

 

■ Abstract :

With the amazing advance in computer technology since the late 20th century, computational research is increasingly important particularly in the fields of materials science. In today’s materials science, a critical issue is to gain a deeper understanding about quantitative and qualitative relationship among their synthesis conditions, structures, and properties. In this regard, computational modeling can provide researchers with significant insights into atomic-level interactions and underlying fundamental theories. Furthermore, nowadays, while novel synthetic methodologies allow experimentalists to create billions of possible materials, however, in practice we can only synthesize and test a small fraction of them. Therefore, a key challenge is to develop rational strategies to find the best performing materials given these experimental constraints. Big data techniques and machine learning can contribute to solve this issue by uncovering complex relations between observed behavior and the underlying mechanisms.

In this talk, I will discuss our efforts into computational discovery and design of novel materials for energy related applications. In the first part, I will focus on development of silicon-based thermoelectric (TE) materials. To develop high performance silicon-based TE materials, a key issue has been how to further reduce thermal conductivity (k) beyond the so-called alloy limit which is the minimum k of silicon germanium (SiGe) alloy. I will first describe critical factors determining k of SiGe, and then discuss the possibility of lowering κ below the alloy limit with utilizing ternary alloying and poly-crystallizing. In the second part, I will present development of a descriptor to identify nanoporous materials using big-data analysis and show that our descriptor successfully discovered top-performing structures for methane storage applications from nanoporous materials genome. Furthermore, using big-data analysis it will be explained that top performing materials can be divided into topologically distinct classes and that each class requires different optimisation strategies.


List of Articles
No. Category Subject Author Date Views
Notice Regular 03/26 (Tue) Prof. Jae-Byum Chang (KAIST MSE) ADMINI 2019.03.22 9
Notice Regular 03/19 (Tue) Dr. YangKoo Cho (Korea Research Institute of Standard and Science) ADMINI 2019.03.18 95
Notice Regular 3/12 (Tue) Prof. Chang Dong Yoo (KAIST EE) ADMINI 2019.03.12 93
Notice Regular 2/26 (Tue) Dr. Hye-Young Kim (Senior Venture Association) ADMINI 2019.02.22 201
» Special 1/28 (Mon) Prof. Yongjin Lee (Shanghai Tech Univ.) ADMINI 2019.01.23 518
Notice Regular 12/4 (Tue) Prof. Doo Seok Jeong (Hanyang Univ., Department of MSE) ADMINI 2018.11.30 864
Notice Regular 11/27 (Tue) Prof. Seong-Jun Jeong (Soongsil Univ.) ADMINI 2018.11.26 709
282 Regular 11/20 (Tue) Prof. Youn Soo Kim (Department of MSE, POSTECH) ADMINI 2018.11.19 751
281 Special 11/14 (Wed) Prof. Hui-Ming Cheng (Director and Professor, Tsinghua University, IMR CAS) ADMINI 2018.11.13 446
280 Special 11/20 (Tue) Prof. Alfonso H. W. Ngan (Department of Mechanical Engineering, University of Hong Kong) file ADMINI 2018.11.13 710
279 Regular 11/13 (Tue) Dr. Kang-Wook Lee (SK Hynix) ADMINI 2018.11.13 270
278 Regular 11/6 (Tue) Prof. Dongchan Jang (KAIST NQE) ADMINI 2018.11.02 371
277 Special 11/2 (Fri) Dr. Sungbong Park (Intel Corporation) ADMINI 2018.10.30 515
276 Regular 10/30 (Tue) Dr. Myung-Il Park (Korea Technology Finance Corporation) ADMINI 2018.10.26 278
275 Regular 10/23 (Tue) Dr. Sang-Soo Han (H&P International Patent & Law Office) ADMINI 2018.10.19 276
274 Regular 10/2 (Tue) Prof. Dohwan Kim (Hanyang Univ.) ADMINI 2018.10.01 435
273 Regular 9/18 (Tue) Prof. Seong Jun Kang (Kyung Hee Univ.) ADMINI 2018.09.17 514
272 Regular 9/11 (Tue) Dr. Byeongdu Lee (Argonne National Laboratory) ADMINI 2018.09.07 648
271 Regular 9/4 (Tue) Prof. Kibum Kang (Department of MSE, KAIST) ADMINI 2018.09.03 585
270 Regular 8/28 (Tue) Prof. Kyung-Min Kim (Department of MSE, KAIST) ADMINI 2018.08.24 942
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