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Effective mass and Fermi surface complexity factor from ab initio band structure calculations

Gibbs, Zachary M. and Ricci, Francesco and Li, Guodong and Zhu, Hong and Persson, Kristin and Ceder, Gerbrand and Hautier, Geoffroy and Jain, Anubhav and Snyder, G. Jeffrey (2017) Effective mass and Fermi surface complexity factor from ab initio band structure calculations. npj Computational Materials, 3 . Art. No. 8. ISSN 2057-3960.

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The effective mass is a convenient descriptor of the electronic band structure used to characterize the density of states and electron transport based on a free electron model. While effective mass is an excellent first-order descriptor in real systems, the exact value can have several definitions, each of which describe a different aspect of electron transport. Here we use Boltzmann transport calculations applied to ab initio band structures to extract a density-of-states effective mass from the Seebeck Coefficient and an inertial mass from the electrical conductivity to characterize the band structure irrespective of the exact scattering mechanism. We identify a Fermi Surface Complexity Factor: N^∗_vK^∗ from the ratio of these two masses, which in simple cases depends on the number of Fermi surface pockets (N^∗_v) and their anisotropy K^*, both of which are beneficial to high thermoelectric performance as exemplified by the high values found in PbTe. The Fermi Surface Complexity factor can be used in high-throughput search of promising thermoelectric materials.

Item Type:Article
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URLURL TypeDescription
Ricci, Francesco0000-0001-5742-5980
Li, Guodong0000-0002-4761-6991
Persson, Kristin0000-0003-2495-5509
Hautier, Geoffroy0000-0003-1754-2220
Jain, Anubhav0000-0001-5893-9967
Snyder, G. Jeffrey0000-0003-1414-8682
Additional Information:© 2017 the Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit Received: 30 October 2016 Revised: 13 January 2017 Accepted: 25 January 2017. Published online 23 February 2017. We thank Georg Madsen, Eric Toberer, Vladan Stevanovic and David Singh for helpful discussions. Z.M.G. acknowledges contributions to the code base by Meera Kumar, a Caltech summer undergraduate researcher. This work was intellectually led by the Materials Project which is supported by the Department of Energy Basic Energy Sciences program under Grant No. EDCBEE, DOE Contract DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy. The work was supported by the F.R.S.-FNRS project HTBaSE (contract no. PDR-T.1071.15). Computational resources were provided by the supercomputing facilities of the Université catholique de Louvain (CISM/UCL), the Consortium des Equipements de Calcul Intensif en Federation Wallonie Bruxelles de (CECI) funded by the F.R.S.-FNRS. Author Contributions: This strategy was conceived by G.J.S. and Z.M.G. The code to implement the calculations was written by Z.M.G. with input from G.L., H.Z., F.R., A.J., and G.H. The high-throughput calculations were managed by A.J., G.H., F.R., G.C. and K.P. The manuscript was written by Z.M.G., G.J.S., F.R., G.H. and A.J. and approved by all authors. The authors declare no competing interest.
Funding AgencyGrant Number
Department of Energy (DOE)DE-AC02-05CH11231
Fonds de la Recherche Scientifique (FNRS)PDR-T.1071.15
Record Number:CaltechAUTHORS:20180709-131056129
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:87652
Deposited By: George Porter
Deposited On:09 Jul 2018 20:23
Last Modified:09 Mar 2020 13:19

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