To predict C Q values for Al with machine learning, we constructed a VASP calculated database with 1681 aluminum-containing solid crystalline materials utilizing the high-throughput DFT framework of the Materials Project . The sites in the database can be classified as belonging to three types of local coordination environments: 4-coordinate tetrahedron (termed "T:4"), 5coordinate trigonal bipyramidal ("T:5") and 6-coordinate octahedron ("O:6"). Unusual geometries such as 2-coordinate linear or bent geometries, 3-coordinate trigonal planar, or 4-coordinate square planar were excluded.