Accelerating the discovery and optimization of thermoelectric materials

Abstract

Widespread application of the Materials Genome Initiative (MGI) promises to revolutionize the discovery and realization of next-generation materials for a diverse set of applications. Fundamental to the success of the MGI is the synergistic effect of computational and experimental material science, wherein computation serves as a guide for experimentation, as opposed to the \textit{ex-post-facto} approach which has dominated the literature in the prior decades. The field of thermoelectrics, in particular, has historically been dominated by experimental work motivated largely by chemical intuition. Complex coupling between scattering phenomena, electronic transport, and thermal transport renders optimization in thermoelectric systems difficult, both experimentally and computationally. We have formulated a computationally inexpensive metric, deemed $\beta_{SE}$, which was applied in a high-throughput computational survey of over 40,000 compounds. This metric was validated and refined through the experimental work within this thesis. Our survey revealed many intriguing material classes, two of which were examined experimentally in detail: 1) the n-type Zintl phases, and 2) the quaternary diamond-like semiconductors. The n-type Zintl phases are a particularly interesting example of where chemical intuition and historical precedent can mislead the discovery of new materials. The p-type Zintl phases are a well-known and historically successful family of thermoelectric materials. The thermoelectric community has long-held that Zintl phases must be p-type due to the proclivity of the typical chemistries to form alkali or alkali-earth vacancies. However, our computational search indicated that the n-type Zintl phases should both outnumber and outperform their p-type counterparts. We proceeded to discover and dope two n-type Zintls, KAlSb$_4$ and KGaSb$_4$, finding them to be promising thermoelectric materials. The quaternary diamond-like (DLS) semiconductors are another class of materials identified through our search. The quaternary materials were predicted to exhibit both high electronic mobility and low lattice thermal conductivity, properties that are generally inversely related to each other. We experimentally investigated the 3x3 matrix of compositions Cu$_2$(Zn,Cd,Hg)(Si, Ge, Sn)Te$_4$, finding the Hg-containing DLS to have an unusually high electronic mobility and abnormally low lattice thermal conductivity- ideal for thermoelectrics. However, while computations predict high performance when doped n-type, all of the quaternary DLS present as degenerately doped p-type semiconductors. To overcome the degenerate p-type doping, applied the concept of ``phase boundary mapping'' to reduce the carrier concentration nearly 5 orders of magnitude through intrinsic defect manipulation alone. Our work within the quaternary DLS demonstrated that material discovery in thermoelectrics is also an optimization problem with many dimensions -- which is onerous to perform using classical synthesis techniques. The complex optimization problem presented by the DLS was the impetus for the last study presented in this work. We demonstrated that high-throughput experimental synthesis (particularly with bulk ceramics) has the potential to dramatically increase the rate of material optimization, potentially allowing better synergy with existing high-throughput computational efforts. Together, our work ultimately moves the field of thermoelectrics towards the vision described by the MGI. We have produced new metrics for understanding thermoelectric materials, identified potential materials for thermoelectric applications, and built-upon existing experimental techniques to accelerate material optimization. Together these efforts have begun to unravel the complex structure-property relations that dictate thermoelectric performance.