A research team has developed a high-throughput screening strategy to identify two-dimensional (2D) thermoelectric materials with superior efficiency. This breakthrough is crucial for the development of devices that can directly convert waste heat into electricity, a key technology for energy sustainability. The methodology combines first-principles calculations with machine learning, enabling rapid evaluation of a large number of compounds and prediction of their thermoelectric performance.

The screening focused on the thermoelectric figure of merit, ZT, which quantifies a material's conversion efficiency. 2D materials are of particular interest due to their unique electronic and phononic properties, which can lead to exceptionally high ZT values compared to their three-dimensional counterparts. The researchers analyzed a database of over 1000 2D materials, predicting their electronic and phononic transport properties to determine their ZT.

Among the most notable findings, several materials with promising ZT values were identified, some significantly surpassing conventional thermoelectric materials. This high-throughput approach not only accelerates the discovery of new materials but also provides a deeper understanding of the mechanisms governing thermoelectric efficiency in 2D structures. The results open new avenues for the research and development of more efficient and cost-effective thermoelectric devices, with potential applications in energy harvesting and solid-state refrigeration.