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An ab initio electronic transport database for inorganic materials
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496472/ https://www.ncbi.nlm.nih.gov/pubmed/28675382 http://dx.doi.org/10.1038/sdata.2017.85 |
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author | Ricci, Francesco Chen, Wei Aydemir, Umut Snyder, G. Jeffrey Rignanese, Gian-Marco Jain, Anubhav Hautier, Geoffroy |
author_facet | Ricci, Francesco Chen, Wei Aydemir, Umut Snyder, G. Jeffrey Rignanese, Gian-Marco Jain, Anubhav Hautier, Geoffroy |
author_sort | Ricci, Francesco |
collection | PubMed |
description | 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. Our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties. |
format | Online Article Text |
id | pubmed-5496472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-54964722017-07-12 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 Sci Data Data Descriptor 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. Our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties. Nature Publishing Group 2017-07-04 /pmc/articles/PMC5496472/ /pubmed/28675382 http://dx.doi.org/10.1038/sdata.2017.85 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor 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 |
title | An ab initio electronic transport database for inorganic materials |
title_full | An ab initio electronic transport database for inorganic materials |
title_fullStr | An ab initio electronic transport database for inorganic materials |
title_full_unstemmed | An ab initio electronic transport database for inorganic materials |
title_short | An ab initio electronic transport database for inorganic materials |
title_sort | ab initio electronic transport database for inorganic materials |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496472/ https://www.ncbi.nlm.nih.gov/pubmed/28675382 http://dx.doi.org/10.1038/sdata.2017.85 |
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