報告題目：Discovery of New Advanced Materials by High-throughput Calculations and Machine Learning

報告人：Lei Shen (沈雷),National University of Singapore

主持人（邀請人）：賀欣、張立軍

報告時間：2022年12月8日9:00 AM---10:30 AM

線上會議ID：騰訊會議 778-418-487

主辦單位：汽車材料教育部重點實驗室，伟德bv1946

報告摘要：

There is no doubt that technology will be the key driver of future world economy. New technologies may also bring solutions to many of the world challenges we are facing currently, such as energy crisis. Developing most new technologies are on the basis of new materials. For example, Si-based electronics and Li-based batteries. Unfortunately, it takes typically 15-20 years to move a newly discovered advanced material from the laboratory to the commercial market place in the traditional approach. The high-throughput calculation is an essential idea to shorten this materials development continuum and reduce its cost.

As a matter of fact, our ability to generate and collect enormous volumes of materials data has greatly surpassed our capability to analyze it, boosting the emergence of a new paradigm of materials science and engineering-data-driven materials innovation with machine learning (ML). “Big data” is driving important changes in all fields of science and engineering, and is now beginning to revolutionize the way materials researchers work and interact. For instance, scientists can discover and design new materials using failed experiments with the assistance of ML techniques.

In this talk, I will review the cutting-edge development of high-throughput calculations and machine learning in the field of materials science and engineering, especially the discovery of new materials that exist as 2D crystals with tunable electronic properties. Since the discovery of graphene, the first 2D material, in 2004, there has been a surge of interest in 2D materials. To date, about 700 2D materials have been predicted to be stable and many remain to be synthesized. The global market for 2D materials is expected to reach US$390 million within a decade, in the semiconductor, electronics, battery energy and composites markets.

報告人簡介：

Dr. Lei Shen is a Senior Lecturer in Department Mechanical Engineering, and Engineering Science Programme at National University of Singapore (NUS) https://www.eng.nus.edu.sg/me/staff/shen-lei. He got his PhD degree from the NUS in 2011. Before joining NUS in 2014, he was a Scientist in Data Storage Institute Singapore. His interest lies in cross-disciplinary computational materials and physics, focusing mainly on the understanding of fundamental properties of materials for advanced technologies, and prediction of advanced materials based on high-throughput calculations, and machine learning. He has published 150+ papers in international peer-reviewed journals with 6700+ citations and h-index of 46 in Google Scholar.