An ab initio electronic transport database for inorganic materials

Ricci, Francesco; Chen, Wei; Aydemir, Umut; Snyder, G. Jeffrey; Rignanese, Gian-Marco; Jain, Anubhav; Hautier, Geoffroy

doi:10.1038/sdata.2017.85

Title: An ab initio electronic transport database for inorganic materials

Journal Article · 04 July 2017 · Scientific Data

DOI: https://doi.org/10.1038/sdata.2017.85 · OSTI ID:1398997

Ricci, Francesco ^[1]; Chen, Wei ^[2]; Aydemir, Umut ^[3]; Snyder, G. Jeffrey ^[3];

^[1]; Jain, Anubhav ^[4]; Hautier, Geoffroy ^[1]

Univ. catholique de Louvain, Louvain-la-Neuve (Belgium)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Illinois Institute of Technology, Chicago, IL (United States)
Northwestern Univ., Evanston, IL (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Electronic 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. In conclusion, our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1398997

Journal Information:: Scientific Data, Vol. 4; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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High-throughput computational discovery of In2Mn2O7 as a high Curie temperature ferromagnetic semiconductor for spintronics Chen, Wei; George, Janine; Varley, Joel B. npj Computational Materials, Vol. 5, Issue 1 https://doi.org/10.1038/s41524-019-0208-x	journal	July 2019
New horizons in thermoelectric materials: Correlated electrons, organic transport, machine learning, and more Urban, Jeffrey J.; Menon, Akanksha K.; Tian, Zhiting Journal of Applied Physics, Vol. 125, Issue 18 https://doi.org/10.1063/1.5092525	journal	May 2019
First-principles study of electronic transport coefficients of point-defective metallic species: aluminum and its bimetallic alloys Choi, Garam; Kim, Hyo Seok; Park, Sang Hyun Modelling and Simulation in Materials Science and Engineering, Vol. 27, Issue 3 https://doi.org/10.1088/1361-651x/ab0af4	journal	March 2019
First-principles calculations and experimental studies of XYZ ₂ thermoelectric compounds: detailed analysis of van der Waals interactions Pöhls, Jan-Hendrik; Luo, Zhe; Aydemir, Umut Journal of Materials Chemistry A, Vol. 6, Issue 40 https://doi.org/10.1039/c8ta06470a	journal	January 2018
Transparent conducting materials discovery using high-throughput computing Brunin, Guillaume; Ricci, Francesco; Ha, Viet-Anh npj Computational Materials, Vol. 5, Issue 1 https://doi.org/10.1038/s41524-019-0200-5	journal	June 2019
Data from: An ab initio electronic transport database for inorganic materials Ricci, F.; Chen, W.; Aydemir, U. Dryad, vp https://doi.org/10.5061/dryad.gn001	dataset	June 2017