Brgoch Superhard Materials Training Data

2574 (2494) materials used for training regressors that predict shear and bulk modulus. The xlsx file provided consists of the original data used to train models described in reference 1 below. The json.gz file includes structural and composition based data from the Materials Project as well as mpid values. Several entries have been marked suspect in this file as they could not be properly cross referenced on the Materials Project database. An additional goup of materials have been marked suspect due to large discrepancies in shear and bulk modulus from the source file and current MP values.Data is available as Monty Encoder encoded JSON and as a XLSX file. Recommended access method is with the matminer Python package using the datasets module.Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.Dataset discussed in:Machine Learning Directed Search for Ultraincompressible, Superhard Materials Aria Mansouri Tehrani, Anton O. Oliynyk, Marcus Parry, Zeshan Rizvi, Samantha Couper, Feng Lin, Lowell Miyagi, Taylor D. Sparks, and Jakoah Brgoch Journal of the American Chemical Society 2018 140 (31), 9844-9853 DOI: 10.1021/jacs.8b02717