A dome-shaped superconducting region appears in the phase diagrams of many unconventional superconductors. In doped band insulators, however, reaching optimal superconductivity by the fine-tuning of carriers has seldom been seen. We report the observation of a superconducting dome in the temperature-carrier density phase diagram of MoS(2), an archetypal band insulator. By quasi-continuous electrostatic carrier doping achieved through a combination of liquid and solid gating, we revealed a large enhancement in the transition temperature T(c) occurring at optimal doping in the chemically inaccessible low-carrier density regime. This observation indicates that the superconducting dome may arise even in doped band insulators.

The valley degree of freedom of electrons is attracting growing interest as a carrier of information in various materials, including graphene, diamond and monolayer transition-metal dichalcogenides. The monolayer transition-metal dichalcogenides are semiconducting and are unique due to the coupling between the spin and valley degrees of freedom originating from the relativistic spin-orbit interaction. Here, we report the direct observation of valley-dependent out-of-plane spin polarization in an archetypal transition-metal dichalcogenide--MoS2--using spin- and angle-resolved photoemission spectroscopy. The result is in fair agreement with a first-principles theoretical prediction. This was made possible by choosing a 3R polytype crystal, which has a non-centrosymmetric structure, rather than the conventional centrosymmetric 2H form. We also confirm robust valley polarization in the 3R form by means of circularly polarized photoluminescence spectroscopy. Non-centrosymmetric transition-metal dichalcogenide crystals may provide a firm basis for the development of magnetic and electric manipulation of spin/valley degrees of freedom.

Pressure‐stabilized hydrides are a new rapidly growing class of high‐temperature superconductors, which is believed to be described within the conventional phonon‐mediated mechanism of coupling. Here, the synthesis of one of the best‐known high‐TC superconductors—yttrium hexahydride Im3¯m‐YH6 is reported, which displays a superconducting transition at ≈224 K at 166 GPa. The extrapolated upper critical magnetic field Bc2(0) of YH6 is surprisingly high: 116–158 T, which is 2–2.5 times larger than the calculated value. A pronounced shift of TC in yttrium deuteride YD6 with the isotope coefficient 0.4 supports the phonon‐assisted superconductivity. Current–voltage measurements show that the critical current IC and its density JC may exceed 1.75 A and 3500 A mm−2 at 4 K, respectively, which is higher than that of the commercial superconductors, such as NbTi and YBCO. The results of superconducting density functional theory (SCDFT) and anharmonic calculations, together with anomalously high critical magnetic field, suggest notable departures of the superconducting properties from the conventional Migdal–Eliashberg and Bardeen–Cooper–Schrieffer theories, and presence of an additional mechanism of superconductivity.

Kohn–Sham density functional theory (DFT) is the basis of modern computational approaches to electronic structures. Their accuracy heavily relies on the exchange-correlation energy functional, which encapsulates electron–electron interaction beyond the classical model. As its universal form remains undiscovered, approximated functionals constructed with heuristic approaches are used for practical studies. However, there are problems in their accuracy and transferability, while any systematic approach to improve them is yet obscure. In this study, we demonstrate that the functional can be systematically constructed using accurate density distributions and energies in reference molecules via machine learning. Surprisingly, a trial functional machine learned from only a few molecules is already applicable to hundreds of molecules comprising various first- and second-row elements with the same accuracy as the standard functionals. This is achieved by relating density and energy using a flexible feed-forward neural network, which allows us to take a functional derivative via the back-propagation algorithm. In addition, simply by introducing a nonlocal density descriptor, the nonlocal effect is included to improve accuracy, which has hitherto been impractical. Our approach thus will help enrich the DFT framework by utilizing the rapidly advancing machine-learning technique.

arXiv:1502.00936v2 [cond-mat.supr-con] 7 Jul 2015First-principles study of the pressure and crystal-structure dependences of the superconducting transition temperature in compressed sulfur hydrides We calculate superconducting transition temperatures (Tc) in sulfur hydrides H2S and H3S from first principles using the density functional theory for superconductors. At pressures of 150 GPa, the high values of Tc (≥130 K) observed in the recent experiment [A. P. Drozdov, M. I. Eremets, and I. A. Troyan, arXiv:1412.0460] are accurately reproduced by assuming that H2S decomposes into R3m-H3S and S. For the higher pressures, the calculated Tcs for Im3m-H3S are systematically higher than those for R3m-H3S and the experimentally observed maximum value (190 K), which suggests the possibility of another higher-Tc phase. We also quantify the isotope effect from first principles and demonstrate that the isotope effect coefficient can be larger than the conventional value (0.5) when multiple structural phases energetically compete.