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  1. Mg 3 Sb 2 –Mg 3 Bi 2 alloys have been heavily studied as a competitive alternative to the state-of-the-art n-type Bi 2 (Te,Se) 3 thermoelectric alloys. Using Mg 3 As 2 alloying, we examine another dimension of exploration in Mg 3 Sb 2 –Mg 3 Bi 2 alloys and the possibility of further improvement of thermoelectric performance was investigated. While the crystal structure of pure Mg 3 As 2 is different from Mg 3 Sb 2 and Mg 3 Bi 2 , at least 15% arsenic solubility on the anion site (Mg 3 ((Sb 0.5 Bi 0.5 ) 1−x As x ) 2 : x = 0.15) was confirmed. Density functional theory calculations showed the possibility of band convergence by alloying Mg 3 Sb 2 –Mg 3 Bi 2 with Mg 3 As 2 . Because of only a small detrimental effect on the charge carrier mobility compared to cation site substitution, the As 5% alloyed sample showed zT = 0.6–1.0 from 350 K to 600 K. This study shows that there is an even larger composition space to examine for the optimization of material properties by considering arsenic introduction into the Mg 3 Sb 2 –Mg 3 Bimore »2 system.« less
  2. The full-Heusler VFe 2 Al has emerged as an important thermoelectric material in its thin film and bulk phases. VFe 2 Al is attractive for use as a thermoelectric materials because of it contains only low-cost, non-toxic and earth abundant elements. While VFe 2 Al has often been described as a semimetal, here we show the electronic and thermal properties of VFe 2 Al can be explained by considering VFe 2 Al as a valence precise semiconductor like many other thermoelectric materials but with a very small band gap ( E g = 0.03 ± 0.01 eV). Using a two-band model for electrical transport and point-defect scattering model for thermal transport we analyze the thermoelectric properties of bulk full-Heusler VFe 2 Al. We demonstrate that a semiconductor transport model can explain the compilation of data from a variety of n and p-type VFe 2 Al compositions assuming a small band-gap between 0.02 eV and 0.04 eV. In this small E g semiconductor understanding, the model suggests that nominally undoped VFe 2 Al samples appear metallic because of intrinsic defects of the order of ∼10 20 defects per cm −3 . We rationalize the observed trends in weighted mobilities ( μmore »w ) with dopant atoms from a molecular orbital understanding of the electronic structure. We use a phonon-point-defect scattering model to understand the dopant-concentration (and, therefore, the carrier-concentration) dependence of thermal conductivity. The electrical and thermal models developed allow us to predict the zT versus carrier concentration curve for this material, which maps well to reported experimental investigations.« less
  3. Half-Heusler materials are strong candidates for thermoelectric applications due to their high weighted mobilities and power factors, which is known to be correlated to valley degeneracy in the electronic band structure. However, there are over 50 known semiconducting half-Heusler phases, and it is not clear how the chemical composition affects the electronic structure. While all the n-type electronic structures have their conduction band minimum at either the Γ - or X -point, there is more diversity in the p-type electronic structures, and the valence band maximum can be at either the Γ -, L -, or W -point. Here, we use high throughput computation and machine learning to compare the valence bands of known half-Heusler compounds and discover new chemical guidelines for promoting the highly degenerate W -point to the valence band maximum. We do this by constructing an “orbital phase diagram” to cluster the variety of electronic structures expressed by these phases into groups, based on the atomic orbitals that contribute most to their valence bands. Then, with the aid of machine learning, we develop new chemical rules that predict the location of the valence band maximum in each of the phases. These rules can be used to engineermore »band structures with band convergence and high valley degeneracy.« less
  4. Herein we study the effect alloying Yb onto the octahedral cite of Te doped Mg 3 Sb 1.5 Bi 0.5 has on transport and the material's high temperature stability. We show that the reduction in mobility can be well explained with an alloy scattering argument due to disrupting the Mg octahedral –Mg tetrahedral interaction that is important for placing the conduction band minimum at a location with high valley degeneracy. We note this interaction likely dominates the conducting states across n-type Mg 3 Sb 2 –Mg 3 Bi 2 solid solutions and explains why alloying on the anion site with Bi isn't detrimental to Mg 3 Sb 2 's mobility. In addition to disrupting this Mg–Mg interaction, we find that alloying Yb into the Mg 3 Sb 2 structure reduces its n-type dopability, likely originating from a change in the octahedral site's vacancy formation energy. We conclude showing that while the material's figure of merit is reduced with the addition of Yb alloying, its high temperature stability is greatly improved. This study demonstrates a site-specific alloying effect that will be important in other complex thermoelectric semiconductors such as Zintl phases.
  5. Semiconductor engineering relies heavily on doping efficiency and dopability. Low doping efficiency may cause low mobility and failure to reach target carrier concentrations or even the desired carrier type. Semiconducting thermoelectric materials perform best with degenerate carrier concentrations, meaning high performance in new materials might not be realized experimentally without a route to optimal doping. Doping in the classic PbTe thermoelectric system has been largely successful but reported doping efficiencies can vary, raising concerns about reproducibility. Here, we stress the importance of phase equilibria considerations during synthesis to avoid undesired intrinsic defects leading to sub-optimal doping. By saturation annealing at 973 K, we decidedly fix the composition in single crystal iodine-doped PbTe samples to be Pb-rich or Te-rich without introducing impurity phases. We show that, regardless of iodine concentration, degenerate n-type carrier concentrations with ideal doping efficiency require Pb-rich compositions. Electrons in Te-rich samples are heavily compensated by charged intrinsic Pb vacancy defects. From Hall effect measurements and a simple defect model supported by modern defect calculations, we map out the 973 K ternary Pb–Te–I phase diagram to explicitly link carrier concentration and composition. Furthermore, we discuss unintentional composition changes due to loss of volatile Te during synthesis and measurements.more »The methods and concepts applied here may guide doping studies on other lead chalcogenide systems as well as any doped, complex semiconductor.« less
  6. Abstract

    The thermoelectric material ZnSb utilizes elements that are inexpensive, abundant, and viable for mass production. While a high thermoelectric figure of meritzT, is difficult to achieve in Sn‐doped ZnSb, it is shown that this obstacle is primarily due to shortcomings in reaching high enough carrier concentrations. Sn‐doped samples prepared in different equilibrium phase spaces in the ternary Zn‐Sb‐Sn system are investigated using phase boundary mapping, and a range of achievable carrier concentrations is found in the doped samples. The sample with the highestzTin this study, which is obtained with a carrier concentration of 2 × 1019 cm−3when the material is in equilibrium with Zn4Sb3and Sn, confirms that the doping efficiency can be controlled by preparing the doped sample in a particular region of the thermodynamic phase diagram. Moreover, density functional theory calculations suggest that the doping efficiency is limited by the solubility of Sn in ZnSb, as opposed to compensation from native defects. Cognizance of thermodynamic conditions is therefore crucial for rationally tuning the carrier concentration, a quantity that is significant for many areas of semiconductor technologies.

  7. Abstract

    Carrier concentration optimization has been an enduring challenge when developing newly discovered semiconductors for applications (e.g., thermoelectrics, transparent conductors, photovoltaics). This barrier has been particularly pernicious in the realm of high-throughput property prediction, where the carrier concentration is often assumed to be a free parameter and the limits are not predicted due to the high computational cost. In this work, we explore the application of machine learning for high-throughput carrier concentration range prediction. Bounding the model within diamond-like semiconductors, the learning set was developed from experimental carrier concentration data on 127 compounds ranging from unary to quaternary. The data were analyzed using various statistical and machine learning methods. Accurate predictions of carrier concentration ranges in diamond-like semiconductors are made within approximately one order of magnitude on average across bothp- andn-type dopability. The model fit to empirical data is analyzed to understand what drives trends in carrier concentration and compared with previous computational efforts. Finally, dopability predictions from this model are combined with high-throughput quality factor predictions to identify promising thermoelectric materials.