Efficient thermoelectric materials are highly desirable, and the quest forfinding them has intensified as they could be promising alternatives to fossilenergy sources. Here we present a general first-principles approach to predict,in multicomponent systems, efficient thermoelectric compounds. The methodcombines a robust evolutionary algorithm, a Pareto multiobjective optimization,density functional theory and a Boltzmann semi-classical calculation ofthermoelectric efficiency. To test the performance and reliability of ouroverall framework, we use the well-known system Bi$_2$Te$_3$-Sb$_2$Te$_3$.
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机译：高效的热电材料是非常需要的，而对它们的寻找也越来越强烈，因为它们可能是化石能源的有前途的替代品。在这里，我们提出了一种通用的第一性原理方法来预测多组分系统中的有效热电化合物。该方法结合了鲁棒的进化算法，帕累托多目标优化，密度泛函理论和热电效率的玻尔兹曼半经典计算。为了测试整体框架的性能和可靠性，我们使用了著名的系统Bi $ _2 $ Te $ _3 $ -Sb $ _2 $ Te $ _3 $。
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