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Automating Anharmonic Lattice Thermal Conductivity Calculations using Compressed Sensing Lattice Dynamics
Published Web Location
https://github.com/rees-c/atomate/tree/CSLDAbstract
Engineering heat transfer is critical for applications in heat exchangers, semiconductor devices, thermoelectrics and more. This demand motivates a high-throughput computational methodology for systematically designing materials with improved thermal properties. One emerging method which can rapidly and explicitly consider phonon-phonon interactions even for highly anharmonic materials is Compressive Sensing Lattice Dynamics (CSLD). In fact, CSLD accurately predicts 2nd (harmonic) and 3rd+ order (anharmonic) interatomic force constants (IFCs) with orders of magnitude fewer Density Functional Theory (DFT) calculations than conventional methods. However, doing CSLD can be an exhaustive, many-step process requiring an intimate knowledge of its sensitivity to parameters. Consequently, this work implements an automatic CSLD workflow capable of obtaining the thermal conductivity of potentially thousands of materials, benchmarks the stability of the workflow against materials with a range of anharmonicity, and begins constructing a dataset of thermal conductivity values and phonon dispersion curves to be stored in the Materials Project for public use.
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