Titanium germanium anti­monide, TiGeSb

TiGeSb adopts the PbFCl- or ZrSiS-type structure, with Ti atoms (4mm symmetry) centred within monocapped square anti­prisms generated by the stacking of denser square nets of Ge atoms ( m2 symmetry) alternating with less dense square nets of Sb atoms (4mm symmetry)

Orientational Disorder in Sodium Cadmium Trifluoride Trihydrate, NaCdF3·3H2O

Attempts to synthesize the hypothetical anhydrous fluoroperovskite NaCdF3, which has been predicted to be stable, resulted instead in a hydrated fluoride of nominal composition NaCdF3·3H2O. It decomposes to sodium fluoride, cadmium fluoride, and water at 60 °C. Its structure has been determined by single-crystal X-ray diffraction. Na0.92(2)Cd1.08F3.08·2.92H2O crystallizes in the cubic space group with a = 8.2369(4) Å and Z = 4. The structure is based on the NaSbF6-type (an ordered variant of the ReO3-type) and features tilted sodium- and cadmium-centred octahedra that are linked by shared vertices to form a three-dimensional network. Substitutional disorder occurs on the nonmetal site, which is occupied by both F and O atoms, and on one of the metal sites, which is occupied by 92% Na and 8% Cd. A four-fold orientational disorder of the tilted octahedra is manifested as partial occupancy (25%) of the nonmetal site. A scheme to synthesize the anhydrous fluoride is presented

Perspective: Web-based machine learning models for real-time screening of thermoelectric materials properties

The experimental search for new thermoelectric materials remains largely confined to a limited set of successful chemical and structural families, such as chalcogenides, skutterudites, and Zintl phases. In principle, computational tools such as density functional theory (DFT) offer the possibility of rationally guiding experimental synthesis efforts toward very different chemistries. However, in practice, predicting thermoelectric properties from first principles remains a challenging endeavor [J. Carrete et al., Phys. Rev. X 4, 011019 (2014)], and experimental researchers generally do not directly use computation to drive their own synthesis efforts. To bridge this practical gap between experimental needs and computational tools, we report an open machine learning-based recommendation engine (http://thermoelectrics.citrination.com) for materials researchers that suggests promising new thermoelectric compositions based on pre-screening about 25 000 known materials and also evaluates the feasibility of user-designed compounds. We show this engine can identify interesting chemistries very different from known thermoelectrics. Specifically, we describe the experimental characterization of one example set of compounds derived from our engine, RE12Co5Bi (RE = Gd, Er), which exhibits surprising thermoelectric performance given its unprecedentedly high loading with metallic d and f block elements and warrants further investigation as a new thermoelectric material platform. We show that our engine predicts this family of materials to have low thermal and high electrical conductivities, but modest Seebeck coefficient, all of which are confirmed experimentally. We note that the engine also predicts materials that may simultaneously optimize all three properties entering into zT; we selected RE12Co5Bi for this study due to its interesting chemical composition and known facile synthesis.We thank the National Science Foundation for support of this research through NSF-DMR 1121053, as well as the Natural Sciences and Engineering Research Council of Canada (NSERC), and the DARPA SIMPLEX program N66001-15-C-4036. Additionally, this research made extensive use of shared experimental facilities of the Materials Research Laboratory: a NSF MRSEC, supported by NSF-DMR 1121053. MWG is thankful for support from NSERC through a Postgraduate Scholarship, support from the US Department of State through an International Fulbright Science & Technology Award, and support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska–Curie grant agreement No. 659764. BM and GJM are founders and significant shareholders in Citrine Informatics Inc

The Role of Ni-Mn Hybridization on the Martensitic Phase Transitions in Mn-rich Heusler Alloys

Room temperature x-ray diffraction, dc magnetization, and ac susceptibility measurements have been performed on a series of Mn rich Ni50Mn37-xCrxSb13 and Ni50+xMn37-xSb13 Heusler alloys. Depending on the value of x, the room temperature crystal structures of the samples are either L21 cubic or orthorhombic. It is a commonly accepted idea that the martensitic transition temperatures in Ni-Mn-Z (Z = Ga, In, Sb, Sn) based Heusler alloys decrease (increase) with decreasing (increasing) valence electron concentration, e/a. However, the present work shows that regardless of the change in e/a, the martensitic transition temperature (TM) decreases with increasing Cr or Ni concentration. These results support the model where, in the case of Mn rich Heusler alloys, it is the hybridization between the Ni atoms and the Mn atoms in the Z sites that plays the dominant role in driving the martensitic transformation