Uncertainty quantification for first-principles simulations of thermoelectric properties

热电材料可以将废热转化为电能，极大地提高了从手持设备到运输到制造过程等广泛技术应用的能源效率，但目前的热电材料效率还不够高，无法实现成本效益。该项目的目的是开发基于第一性原理模拟的预测计算方法，包括所采用方法产生的不确定性。这些方法将使热电应用材料的快速筛选和材料特性的可靠建模成为可能。特别令人感兴趣的是新的热电材料的计算发现，以及在纳米尺度上对材料进行图案化以提高热电性能。

Thermoelectric materials can convert waste heat into electricity, dramatically improving energy efficiency across a wide range of technological applications, from handheld devices to transport to manufacturing processes, but current thermoelectric materials are not efficient enough to be cost-effective. The aims of this project are to develop predictive computational methods based on first-principles simulations, including the uncertainties arising from the methods employed. These methods will enable rapid screening of materials for thermoelectric applications, and reliable modelling of materials properties. Of particular interest are the computational discovery of new thermoelectric materials, and patterning materials at the nanoscale to improve thermoelectric performance.