Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood; prime among these is the connection between superconductivity and chemical/structural properties of materials. To bridge the gap, several machine learning schemes are developed herein to model the critical temperatures (Tc) of the 12, 000+ known superconductors available via the SuperCon database. Materials are first divided into two classes based on their Tc values, above and below 10 K, and a classification model predicting this label is trained. The model uses coarse-grained features based only on the chemical compositions. It shows strong predictive power, with out-of-sample accuracy of about 92%. Separate regression models are developed to predict the values of Tc for cuprate, iron-based, and "low-Tc" compounds. These models also demonstrate good performance, with learned predictors offering potential insights into the mechanisms behind superconductivity in different families of materials. To improve the accuracy and interpretability of these models, new features are incorporated using materials data from the AFLOW Online Repositories. Finally, the classification and regression models are combined into a single integrated pipeline and employed to search the entire Inorganic Crystallographic Structure Database (ICSD) for potential new superconductors. We identify more than 30 non-cuprate and non-iron-based oxides as candidate materials. arXiv:1709.02727v2 [cond-mat.supr-con] 6 Oct 2017 c )) and ln(Tc) ≡ ln(T meas c ).

Through neutron diffraction experiments, including spin-polarized measurements, we find a collinear incommensurate spin-density wave with propagation vector k = (0.4481(4) 0 1 2 ) at base temperature in the superconducting parent compound Fe1+xTe. This critical concentration of interstitial iron corresponds to x ≈ 12% and leads crystallographic phase separation at base temperature. The spin-density wave is short-range ordered with a correlation length of 22(3)Å, and as the ordering temperature is approached its propagation vector decreases linearly in the H-direction and becomes long-range ordered. Upon further populating the interstitial iron site, the spin-density wave gives way to an incommensurate helical ordering with propagation vector k = (0.3855(2) 0 1 2 ) at base temperature. For a sample with x ≈ 9(1)%, we also find an incommensurate spin-density wave that competes with the bicollinear commensurate ordering close to the Néel point. The shifting of spectral weight between competing magnetic orderings observed in several samples is supporting evidence for the phase separation being electronic in nature, and hence leads to crystallographic phase separation around the critical interstitial iron concentration of 12%. With results from both powder and single crystal samples, we construct a magnetic-crystallographic phase diagram of Fe1+xTe for 5% < x < 17%.

The Materials Genome Initiative (MGI) advanced a new paradigm for materials discovery and design, namely that the pace of new materials deployment could be accelerated through complementary efforts in theory, computation, and experiment. Along with numerous successes, new challenges are inviting researchers to refocus the efforts and approaches that were originally inspired by the MGI. In May 2017, the National Science Foundation sponsored the workshop "Advancing and Accelerating Materials Innovation Through the Synergistic Interaction among Computation, Experiment, and Theory: Opening New Frontiers" to review accomplishments that emerged from investments in science and infrastructure under the MGI, identify scientific opportunities in this new environment, examine how to effectively utilize new materials innovation infrastructure, and discuss challenges in achieving accelerated materials research through the seamless integration of experiment, computation, and theory. This article summarizes key findings from the workshop and provides perspectives that aim to guide the direction of future materials research and its translation into societal impacts.

We report the novel preparation of single crystals of tetragonal iron sulfide, FeS, which exhibits a nearly ideal tetrahedral geometry with S-Fe-S bond angles of 110.2(2) • and 108.1(2) • . Grown via hydrothermal de-intercalation of KxFe2−yS2 crystals under basic and reducing conditions, the silver, plate-like crystals of FeS remain stable up to 200 • C under air and 250 • C under inert conditions, even though the mineral "mackinawite" (FeS) is known to be metastable. FeS single crystals exhibit a superconducting state below Tc = 4 K as determined by electrical resistivity, magnetic susceptibility, and heat capacity measurements, confirming the presence of a bulk superconducting state. Normal state measurements yield an electronic specific heat of 5 mJ/mol-K 2 , and paramagnetic, metallic behavior with a low residual resistivity of 250 µΩ·cm. Magnetoresistance measurements performed as a function of magnetic field angle tilted toward both transverse and longitudinal orientations with respect to the applied current reveal remarkable two-dimensional behavior. This is paralleled in the superconducting state, which exhibits the largest known upper critical field Hc2 anisotropy of all iron-based superconductors, with H ||ab c2 (0)/H ||c c2 (0) =(2.75 T)/(0.275 T)=10. Comparisons to theoretical models for 2D and anisotropic-3D superconductors, however, suggest that FeS is the latter case with a large effective mass anisotropy. We place FeS in context to other closely related iron-based superconductors and discuss the role of structural parameters such as anion height on superconductivity.

CaFe_{2}O_{4} is a S=5/2 anisotropic antiferromagnet based upon zig-zag chains having two competing magnetic structures, denoted as the A (↑↑↓↓) and B (↑↓↑↓) phases, which differ by the c-axis stacking of ferromagnetic stripes. We apply neutron scattering to demonstrate that the competing A and B phase order parameters result in magnetic antiphase boundaries along c which freeze on the time scale of ∼1  ns at the onset of magnetic order at 200 K. Using high resolution neutron spectroscopy, we find quantized spin wave levels and measure 9 such excitations localized in regions ∼1-2 c-axis lattice constants in size. We discuss these in the context of solitary magnons predicted to exist in anisotropic systems. The magnetic anisotropy affords both competing A+B orders as well as localization of spin excitations in a classical magnet.