An ab initio electronic transport database for inorganic materials

• DOI: 10.1038/sdata.2017.85
• Publication Date: 2017-07-04T12:54:37Z
• Authors: Francesco Ricci; Wei Chen; Umut Aydemir; G. Jeffrey Snyder; Gian-Marco Rignanese; Anubhav Jain; Geoffroy Hautier
• Keywords: Statistics and Probability; Data Descriptor; 660; 02 engineering and technology; Library and Information Sciences; 7. Clean energy; Macromolecular and Materials Chemistry; Computer Science Applications; Education; Chemical Sciences; Statistics, Probability and Uncertainty; 0210 nano-technology; Information Systems

AbstractElectronic transport in materials is governed by a series of tensorial properties such as conductivity, Seebeck coefficient, and effective mass. These quantities are paramount to the understanding of materials in many fields from thermoelectrics to electronics and photovoltaics. Transport properties can be calculated from a material’s band structure using the Boltzmann transport theory framework. We present here the largest computational database of electronic transport properties based on a large set of 48,000 materials originating from the Materials Project database. Our results were obtained through the interpolation approach developed in the BoltzTraP software, assuming a constant relaxation time. We present the workflow to generate the data, the data validation procedure, and the database structure. Our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties.