CHILI

CHILI是一个化学信息丰富的大规模无机纳米材料数据集，旨在推动图形机器学习的发展。该数据集包含两种不同规模的纳米材料数据集：CHILI-3K和CHILI-100K。CHILI-3K是一个中等规模的数据集，包含超过600万个节点和4900万条边，专注于单金属氧化物纳米材料，由12种选定的晶体类型生成。CHILI-100K是一个大规模数据集，包含超过1.83亿个节点和12亿条边，由实验确定的晶体结构生成，涵盖68种金属和11种非金属的数据库条目。这两个数据集都以图形的形式表示纳米材料的不同尺度和属性，旨在解决无机材料化学中大规模图机器学习方法的挑战。

CHILI is a large-scale inorganic nanomaterial dataset rich in chemical information, aiming to advance the development of graph machine learning. This dataset consists of two nanomaterial datasets with different scales: CHILI-3K and CHILI-100K. CHILI-3K is a medium-scale dataset containing over 6 million nodes and 49 million edges, focusing on single-metal oxide nanomaterials, which is generated from 12 selected crystal types. CHILI-100K is a large-scale dataset containing over 183 million nodes and 1.2 billion edges, generated from experimentally determined crystal structures, and covering database entries of 68 metals and 11 nonmetals. Both datasets represent the different scales and properties of nanomaterials in the form of graphs, aiming to address the challenges of large-scale graph machine learning methods in inorganic materials chemistry.