主讲人：崔予文教授 南京工业大学

题   目：New ICME Tasks for Materials Design: High-Throughput Screening, Computer Modeling, and Machine Learning

日   期：2024年4月9日     时   间：16:00-17：00

地   点：哈尔滨工业大学（深圳）, 信息楼L-416

*** 欢迎各界人士参加 ***

摘   要：In this talk, recent advances in our Integrated Computational Materials Engineering tasks for exploring and manufacturing new structural materials are addressed, including:

1) Promoting high-throughput kinetic diffusion multiple as robust experimentation tool for rapid screening of diffusion, microstructure and micro-mechanical properties of lightweight Al, Mg and Ti alloys for insertion into microstructure modeling, databases and machine learning models.

2) Construction of thermo-kinetic database for multicomponent Mg and Ti alloy systems; widening physics-inherent modeling tools, i.e. coupling mesoscale microstructure model up-streamingly to continuum mechanics, e.g. via phase fraction as indicator, and down-streamingly to lattice dynamics via vibrational modes.

3) Development of machine learning models informed by materials thermos-kinetics and processing knowledge for predicting the mechanical properties of high strength Ti alloys and hot rolling of thick steels plates with good generalization ability and ease of implementation.

These efforts enable to yield the new experimental and AI-based techniques necessary for accelerated materials design and development and foster widespread adoption of the ICME and MGI paradigms.

报告人简介：崔予文博士现任南京工业大学教授、长三角先进材料研究院材料人工智能设计平台技术负责人、国家重点研发计划首席科学家。曾在日本东北大学、比利时天主教鲁汶大学、俄亥俄州立大学等国际知名材料研发机构工作，回国前（2011-2017）担任西班牙马德里IMDEA材料研究所计算合金设计组组长。长期从事集成计算材料工程（ICME）研究，建立了国际认可的高温合金和轻合金体系热动力学数据库，提出了高通量动力学扩散多重方法，并主持了成都MatAI数据融合和机器学习平台的建设。迄今为止，在Acta Mater等期刊发表SCI论文100篇，专著3部。