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The emergence of data-driven science has opened up new avenues for understanding the thermophysical properties of materials. For decades, alloys are known to possess very low thermal conductivity, but the extreme thermal conductivity that can be achieved by alloying has never been identified. In this work, we combine the Bayesian optimization with a high throughput thermal conductivity calculation to search for the lowest thermal conductivity atomic configuration of SiGe alloy. It is founddoi:10.30919/esee8c356 fatcat:m35by3qxkfglblbubkj2lwvfnm