稀土元素配合物结构的大数据分析  

Big Data Analysis of Structures of Rare-Earth Coordination Compounds

作　　者：谢俊忠 杜骏豪 何嘉炜 胡皓然 沈辰熹 卞江[1] XIE Junzhong;DU Junhao;HE Jiawei;HU Haoran;SHEN Chenxi;BIAN Jiang(College of Chemistry and Molecular Engineering,Peking University,Beijing 100871,P.R.China)

机构地区：[1]北京大学化学与分子工程学院

出　　处：《大学化学》2019年第9期125-134,共10页University Chemistry

摘　　要：元素化学是一门经验性较强的学科,通过描述或枚举的方法讲述元素的性质在教材和文献中随处可见。在Scifinder数据库中,每年新增数以百万计的新物质,推动着对元素化学的认识不断深入发展。在大数据和人工智能迅猛发展的今天,尽管化学工作者在长期实验工作中积累的第一手经验和直觉仍然非常宝贵,但效率已不足以满足当前材料和分子设计对分子性质的需求。数据库中的海量资源为新规律的发现提供机遇。我们用大数据的方法分析稀土配合物的结构性质:将剑桥晶体结构数据库中的稀土配合物用定量的方法进行归类,统计有关配合物结构的相关信息。通过分析样本数据与典型案例,我们得出了稀土配合物结构的普遍规律。基于我们的研究成果以及研究过程中遇到的问题,我们总结与展望了大数据在化学中的应用。Element chemistry is a highly empirical subject,and descriptive or enumerative methods depicting the nature of elements can be seen in textbooks and publications.In the Scifinder database,millions of new compounds found every year considerably enhance the understanding of element chemistry.With the rapid development of Big Data and Artificial Intelligence,the chemists’long-term experimental experience and intuition,though precious,fail to meet the demand of molecular properties for the material and molecule design in efficiency.Massive data sources in the database provides a brand-new opportunity to discover new rules.We apply big-data methods to analyze the structural properties of the rare-earth coordination compounds,by gathering statistics from the Cambridge Structural Database System and classifying the entries quantitatively.We also give the general rules by analyzing the data and some representative examples.Based on the results and the problems in research,we summarize and outlook the application of big-data in chemistry.

关 键 词：大数据 统计 稀土配合物 配位数 配位几何结构 

分 类 号：G64[文化科学—高等教育学] O6[文化科学—教育学]