Accelerating Thermoelectric Materials Discovery via Dopability Predictions II
We will use Blue Waters to carry out automated, high-throughput first-principles calculations to assess the dopability of a large class of newly discovered semiconductors of interest for their thermoelectric properties. Nowadays, the experimental realization of new thermoelectric materials is greatly accelerated through computational guidance, with first-principles calculations providing relevant materials properties such as electronic and phonon transport and thermodynamic stability. The current bottleneck is that more than 90% of the materials identified as promising on a computer cannot be doped in the laboratory.
To overcome this, we will use Blue Waters to carry out a series of dopability assessments through defect calculations on a diverse set of candidate semiconductors including Zintl compounds, ordered vacancy compounds, layered materials, and diamond like semiconductors. This proposal extends our prior efforts in dopability prediction and will also assess a new strategy – the targeted removal of performance limiting ‘killer’ defects – to design new materials with large dopability windows.
The systems simulated on Blue Waters will be incorporated into TEDesignLab, an online open platform for easy, searchable data exchange to enable data-driven approaches to thermoelectrics design and discovery. The work we propose would not be possible without Blue Waters, which will allow the calculation of full defect properties of a class of 32 new candidate thermoelectric semiconductors.