【摘要】 材料信息学或材料基因工程作为新兴的材料研究与设计范式,通过深度结合材料大数据与人工智能机器学习算法,正在加速新材料、新功能和新原则的创新发现.如何高效产生、收集、管理、学习和挖掘大规模材料数据是开展材料信息学或材料基因工程研究的关键. JAMIP (Jilin Artificial-intelligence-aided Materials-design Integrated Package)材料设计软件为满足这方面的研究需求而设计,涵盖半导体材料、介电材料、金属材料等材料体系,为基于功能材料大数据与机器学习算法结合的新材料发现和设计提供工具支撑.软件基于Python语言开发,代码开源,既可以基于结构原型数据库高效开展大规模高通量材料计算,也可以实现对计算任务更精细的控制及新任务流程的灵活定制.软件包主体框架包含以高通量材料计算为核心的数据产生、数据收集、管理工具及数据存储、机器学习/数据挖掘等功能模块.机器学习模块集成了数据预处理、数据特征工程,以及常用机器学习算法的模型构建和性能评估子模块.软件各模块之间高度融合,能够高效产生、分析、管理和学习计算材料大数据,为开展材料信息学或材料基因工程研究、实现新材料设计提供专业化的操作软件平台.更多还原

【Abstract】 Materials informatics has emerged as a promisingly new paradigm for accelerating materials discovery and design. It exploits the intelligent power of machine learning methods in massive materials data from experiments or simulations to seek new materials, functionality, and principles, etc. Developing specialized facilities to generate, collect, manage, learn, and mine large-scale materials data is crucial to materials informatics. We herein developed an artificial-intelligence-aided data-driven infrastructure named Jilin Artificial-intelligence aided Materials-design Integrated Package(JAMIP), which is an open-source Python framework to meet the research requirements of computational materials informatics. It is integrated by materials production factory, high-throughput first-principles calculations engine, automatic tasks submission and monitoring progress, data extraction, management and storage system, and artificial intelligence machine learning based data mining functions. We have integrated specific features such as an inorganic crystal structure prototype database to facilitate high-throughput calculations and essential modules associated with machine learning studies of functional materials. We demonstrated how our developed code is useful in exploring materials informatics of optoelectronic semiconductors by taking halide perovskites as typical case. By obeying the principles of automation, extensibility, reliability,and intelligence, the JAMIP code is a promisingly powerful tool contributing to the fast-growing field of computational materials informatics.更多还原