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Title: An ab initio electronic transport database for inorganic materials

Abstract

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.

Authors:
 [1];  [2];  [3];  [3]; ORCiD logo [1];  [4];  [1]
  1. Univ. catholique de Louvain, Louvain-la-Neuve (Belgium)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Illinois Institute of Technology, Chicago, IL (United States)
  3. Northwestern Univ., Evanston, IL (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1398997
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Data
Additional Journal Information:
Journal Volume: 4; Journal ID: ISSN 2052-4463
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Ricci, Francesco, Chen, Wei, Aydemir, Umut, Snyder, G. Jeffrey, Rignanese, Gian-Marco, Jain, Anubhav, and Hautier, Geoffroy. An ab initio electronic transport database for inorganic materials. United States: N. p., 2017. Web. doi:10.1038/sdata.2017.85.
Ricci, Francesco, Chen, Wei, Aydemir, Umut, Snyder, G. Jeffrey, Rignanese, Gian-Marco, Jain, Anubhav, & Hautier, Geoffroy. An ab initio electronic transport database for inorganic materials. United States. doi:10.1038/sdata.2017.85.
Ricci, Francesco, Chen, Wei, Aydemir, Umut, Snyder, G. Jeffrey, Rignanese, Gian-Marco, Jain, Anubhav, and Hautier, Geoffroy. Tue . "An ab initio electronic transport database for inorganic materials". United States. doi:10.1038/sdata.2017.85. https://www.osti.gov/servlets/purl/1398997.
@article{osti_1398997,
title = {An ab initio electronic transport database for inorganic materials},
author = {Ricci, Francesco and Chen, Wei and Aydemir, Umut and Snyder, G. Jeffrey and Rignanese, Gian-Marco and Jain, Anubhav and Hautier, Geoffroy},
abstractNote = {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.},
doi = {10.1038/sdata.2017.85},
journal = {Scientific Data},
number = ,
volume = 4,
place = {United States},
year = {2017},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 15 works
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Figures / Tables:

Table 1. Table 1.: Transport properties stored in the first dataset with their units and data size. See Table 5 for the available keys inside each of these root keys. The electronic conductivity and the electronic contribution of the thermal conductivity are stored divided by τ. For the electronic conductivity, the electronicmore » contribution of the thermal conductivity, and the Seebeck coefficient both the full tensor and its sorted (in ascending order) eigenvalues are provided.« less

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