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We investigate the parametrization and optimization of thermal conductivity in silicon-germanium alloy nanowires by the cluster-expansion technique. Si1−xGex nanowires are of interest for thermoelectric applications and the reduction in lattice thermal conductivity (κL) is desired for enhancing the thermoelectric figure of merit. We seek the minimization of κL with respect to arrangements of Si and Ge atoms in 1.5 nm diameter [111] Si1−xGex nanowires, by obtaining κL from equilibrium classical molecular-dynamics (MD) simulations via the Green-Kubo formalism, and parametrizing the results with a coarse-grained cluster expansion. Using genetic algorithm optimization with the coarse-grained cluster expansion, we are able to predict configurations that significantly decrease κL as verified by subsequent MD simulations. Our results indicate that superlatticelike configurations with planes of Ge show drastically lowered κL.
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