A review of recent progress in thermoelectric materials through computational methods
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(2020) 9:16
REVIEW PAPER
A review of recent progress in thermoelectric materials through computational methods J. Julio Gutiérrez Moreno1,2 · Jiang Cao3 · Marco Fronzi4 · M. Hussein N. Assadi5 Received: 28 February 2020 / Accepted: 26 June 2020 © The Author(s) 2020
Abstract Reducing our overwhelming dependence on fossil fuels requires groundbreaking innovations in increasing our efficiency in energy consumption for current technologies and moving towards renewable energy sources. Thermoelectric materials can help in achieving both goals. Moreover, because of recent advances in high-performance computing, researchers more increasingly rely on computational methods in discovering new thermoelectric materials with economically feasible performance. In this article, significant thermoelectric materials discovered through these computational methods are systematically reviewed. Furthermore, the primary computational tools that aid the design of the next-generation thermoelectric materials are introduced and discussed. These techniques include various levels of density functional theory, electronic transport simulations, and phonon calculations. Keywords Thermoelectric materials · Heterostructures · Density functional theory · DFT + U · Transport phenomena · Phonon dispersion List of symbols AIMD Ab initio molecular dynamics DFPT Density functional perturbation theory DFT Density functional theory DFTB Density functional tight-binding DOS Density of states E Electric field EF Fermi level EMC Ensemble Monte Carlo * Jiang Cao [email protected] * M. Hussein N. Assadi [email protected] 1
Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), C/ Jordi Girona 29, 08034 Barcelona, Spain
2
Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China
3
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
4
School of Mathematical and Physical Science, University of Technology Sydney, Sydney, NSW 2007, Australia
5
School of Materials Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia
f Energy function g Degeneracy GGA General gradient approximation GW Self-energy correction approximation IFC Interatomic force constant IoT Internet of Things j Current density J Exchange term k Momentum vector K Kelvin kB Boltzmann constant L Lorenz number LDA Local density approximation MD Molecular dynamics n Carrier concentration ND Concentration of donor atoms nref Reference carrier concentration P Pressure PBTE Peierls–Boltzmann transport equation PDOS Partial density of states PGEC Phonon-glass electron-crystal Rc Critical distance S Entropy SCoeff Seebeck coefficient Max Maximum Seebeck coefficient SCoeff
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SSCHA Stochastic self-consistent harmonic approximation T Temperature TC Temperature of cold reservoir TE Thermoelectric TH Temperature of hot reservoir t1 Hopping integ
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