<p style="text-align: justify">Superlattices with suppressing thermal conductivity are of great significance in the field of thermoelectricity and can improve the thermoelectric conversion efficiency of materials. Due to Anderson localization of coherent phonons, aperiodic superlattices have lower thermal conductivity than their periodic counterparts. At present, the thermal conductivity of superlattices is mostly predicted through molecular dynamics simulations, which is time consuming and limits the size of the system. Meanwhile, there are many structural combinations of aperiodic superlattice, so it is difficult to efficiently screen all the combinations to search structures that lead to the minimum thermal conductivity of aperiodic superlattices. In this work, a modified effective medium theory (MEMT) is established to predict the thermal conductivity of both periodic and aperiodic superlattices. The thermal conductivities of individual Si and Ge films and the Si/Ge interfacial thermal resistance are predicted from non-equilibrium molecular dynamics (NEMD) simulations and numerically extrapolated into empirical forms. After comparing against the thermal conductivity of the periodic superlattice predicted using NEMD simulations, we find that the conventional EMT based on the classic serial thermal-resistor model shows poor predictability, because it ignores the influence of phonon coherence and multi-layer interfaces. Introducing corrections for the coherent effect and degree of randomness in layer thickness, the accuracy in the predicted thermal conductivity using the MEMT is significantly improved in consonance with the MD and experimental results. Combined with the genetic algorithm, MEMT enables high-throughput screening of millions of aperiodic superlattice structures. It demonstrates that the thermal conductivity of aperiodic superlattices can be reduced by up to 40% of the period counterparts in the coherent phonon transport region.</p>

High-Throughput Screening of Aperiodic Superlattice for Minimum Thermal Conductivity Based on Atomistic Simulation-Informed Effective Medium Theory and Genetic Algorithm

Paper Proceedings: https://asmedigitalcollection.asme.org/HT/HT2021/volume/84874

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