【学术讲座】Acceleating the Discovery of Solid State Materials:From Traditional to Machine-Learning Approaches

发布时间:2019-05-13浏览次数:53


讲座题目:Acceleating the Discovery of Solid State Materials:From Traditional to Machine-Learning Approaches

主讲人:Arthur Mar教授 加拿大阿尔伯塔大学

主讲人简介:Arthur Mar教授1992年在美国西北大学获得博士学位,2004-至今为阿尔伯塔大学教授,2003-2008年担任Chemisty of Matenials杂志编委。Arthur Mar教授的主要研究方向为磷化物、砷化物以及硫族化合物的合成、结构测定及相关性能研究。在Accounts of Chemical Research, Journal of the American Chemical Society等国际著名期刊上发表研究论文数百余篇。

讲座内容简介:Traditional approaches to search for new solid state materials can involve systematic investigations (e.g., phase diagrams), serendipitous discoveries, or, for limited classes of compounds, rational strategies for manipulating building blocks.  Answering the call of the Materials Genome Initiative,1 launched in 2011, to discover, develop, and deploy new materials twice as fast,” we are applying high-throughput machine-learning methods to predict the structures of new compounds and optimize properties of materials.  An ambitious goal is to classify structures of intermetallics, including unknown ones, solely on the basis of their compositions; these encompass binary AB compounds, ternary ABC compounds, Heusler and half-Heusler phases.  In collaboration with Citrine Informatics,2 machine-learning approaches have also been used to search for unconventional candidates for thermoelectric materials.

讲座时间:2019年 515日 1000-1100

讲座地点:实训楼4号楼4405室

主办单位:化学化工学院