Toward Accelerated Thermoelectric Materials and Process Discovery

Thermoelectric materials have the ability to convert heat energy to electrical power and vice versa. While the thermodynamic upper limit is defined by the Carnot efficiency, the material figure of merit, zT, is far from this theoretical limit, typically limited by a complex interplay of non-equilibrium charge and phonon-scattering. Materials innovation is a slow, arduous process due to the complex correlations between crystal structure, microstructure engineering, and thermoelectric properties. Many physical concepts and materials have been unearthed in this path to discovery, supported ably by innovations in technology over many decades, revealing important material and transport descriptors. In this review, we look back at some case studies of inorganic thermoelectric materials employing a bird's-eye view of complementary advancements in scientific concepts and technological advancements and conclude that most high values of zT have emerged from developed scientific models fueled by moderately mature technologies. On the basis of this conclusion, we then propose that the recent emergence of data-driven approaches and high-throughput experiments, encompassing synthesis as well as characterization, with machine learning guided inverse design is perfectly suited to provide an accelerated pathway toward the discovery of next-generation thermoelectric materials, potentially providing a feasible alternative source of energy for a sustainable future.