Computationally guided discovery of thermoelectric materials
Abstract
The potential for advances in thermoelectric materials, and thus solid-state refrigeration and power generation, is immense. Progress so far has been limited by both the breadth and diversity of the chemical space and the serial nature of experimental work. In this Review, we discuss how recent computational advances are revolutionizing our ability to predict electron and phonon transport and scattering, as well as materials dopability, and we examine efficient approaches to calculating critical transport properties across large chemical spaces. When coupled with experimental feedback, these high-throughput approaches can stimulate the discovery of new classes of thermoelectric materials. Within smaller materials subsets, computations can guide the optimal chemical and structural tailoring to enhance materials performance and provide insight into the underlying transport physics. Beyond perfect materials, computations can be used for the rational design of structural and chemical modifications (such as defects, interfaces, dopants and alloys) to provide additional control on transport properties to optimize performance. Through computational predictions for both materials searches and design, a new paradigm in thermoelectric materials discovery is emerging.
- Authors:
-
- Colorado School of Mines, Golden, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), NREL Laboratory Directed Research and Development (LDRD)
- OSTI Identifier:
- 1390034
- Report Number(s):
- NREL/JA-5K00-70094
Journal ID: ISSN 2058-8437
- Grant/Contract Number:
- AC36-08GO28308
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nature Reviews. Materials
- Additional Journal Information:
- Journal Volume: 2; Journal Issue: 9; Journal ID: ISSN 2058-8437
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE; computational methods; electronic properties; electronic materials; solid-state chemistry; thermoelectrics
Citation Formats
Gorai, Prashun, Stevanović, Vladan, and Toberer, Eric S. Computationally guided discovery of thermoelectric materials. United States: N. p., 2017.
Web. doi:10.1038/natrevmats.2017.53.
Gorai, Prashun, Stevanović, Vladan, & Toberer, Eric S. Computationally guided discovery of thermoelectric materials. United States. https://doi.org/10.1038/natrevmats.2017.53
Gorai, Prashun, Stevanović, Vladan, and Toberer, Eric S. Tue .
"Computationally guided discovery of thermoelectric materials". United States. https://doi.org/10.1038/natrevmats.2017.53. https://www.osti.gov/servlets/purl/1390034.
@article{osti_1390034,
title = {Computationally guided discovery of thermoelectric materials},
author = {Gorai, Prashun and Stevanović, Vladan and Toberer, Eric S.},
abstractNote = {The potential for advances in thermoelectric materials, and thus solid-state refrigeration and power generation, is immense. Progress so far has been limited by both the breadth and diversity of the chemical space and the serial nature of experimental work. In this Review, we discuss how recent computational advances are revolutionizing our ability to predict electron and phonon transport and scattering, as well as materials dopability, and we examine efficient approaches to calculating critical transport properties across large chemical spaces. When coupled with experimental feedback, these high-throughput approaches can stimulate the discovery of new classes of thermoelectric materials. Within smaller materials subsets, computations can guide the optimal chemical and structural tailoring to enhance materials performance and provide insight into the underlying transport physics. Beyond perfect materials, computations can be used for the rational design of structural and chemical modifications (such as defects, interfaces, dopants and alloys) to provide additional control on transport properties to optimize performance. Through computational predictions for both materials searches and design, a new paradigm in thermoelectric materials discovery is emerging.},
doi = {10.1038/natrevmats.2017.53},
journal = {Nature Reviews. Materials},
number = 9,
volume = 2,
place = {United States},
year = {2017},
month = {8}
}
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