Stimulated emission as the new intrinsic property of metal-organic frameworks is demonstrated in article number 1605637 by Roland A. Fischer and co-workers, by the observation of stimulated emission peak, and time-resolved photoluminescence, along with the support of density of state calculations. The results identify that immobilization of strong luminescent chromophores between the metal-nodes leads to the formation of the materials with enhanced stability and optical behavior for the next generation solid-state lasers. Dual-Ion Batteries In article number 1606805, Yongbing Tang and co-workers report a bubble-sheet-like aluminum foil used as anode and current collector in a dual-ion battery. This novel structure helps guide the Al-Li alloying position and confines the volumetric change, and thus results in excellent long-term cycling stability, featuring 99% capacity retention within 1500 cycles at 2 C. Ionic-Liquid Gating Ionic-liquid-gating control of interfacial magnetic aniso-tropy in Au/[DEME]+[TFSI]-/Co/SiO 2 multilayer structures is quantitatively determined by the electron spin resonance method, as described in article number 1606478 by Ziyao Zhou, Ming Liu and co-workers. A reproducible, reversible ferromagnetic resonance field shift of 219 Oe at an applied voltage of 1.5 V, with a large ME tunability of 146 Oe V −1 , is achieved, assisted by the electric double layers at the room temperature. Magnetic Memory In article number 1606748, Yossi Paltiel and co-workers use 30-50 nm ferromagnetic nanoplatelets (FMNPs) on top of an organic chiral molecule monolayer to demonstrate nano-based magnetless magnetic memory device at ambient temperatures. The memory is based on the chiral induced spin selectivity effect. This technology could make it possible to create inexpensive, high-density universal memory devices with much lower power consumption than existing technologies. Additive Manufacturing of Metal Structures at the Micrometer Scale To enable the additive manufacturing of metals at the micrometer scale, a variety of novel techniques are currently in use. The individual techniques are introduced, detailing their underlying principles. Furthermore, it critically compares their fabrication capabilities, in particular the minimum feature size, achievable geometry and obtained materials properties. Blue-color stimulated emission with low threshold power is observed from In-and Zn-MOFs, which feature a highly fluorescent chromophore densely packed and rigidly linked to the metal-ion centers in the solid state. The density-of-states and transition dipole moments are calculated and the stimulated emission phenomenon is correlated with these properties. Dual-Ion Batteries A bubble-sheet-like aluminum foil is developed and used as anode material and current collector in a dual-ion battery (DIB). This novel structure helps guide the AlLi alloying position within the hollow nano-spheres and confines the alloy sizes. As a result, this design significantly relieves the volumetric change, and thus maintains ultrasta...

Multi-photon absorption (MPA) is among the most prominent nonlinear optical (NLO) effects and has applications, for example in telecommunications, defense, photonics, and bio-medicines. Established MPA materials include dyes, quantum dots, organometallics and conjugated polymers, most often dispersed in solution. We demonstrate how metal-organic frameworks (MOFs), a novel NLO solid-state materials class, can be designed for exceptionally strong MPA behavior. MOFs consisting of zirconium- and hafnium-oxo-clusters and featuring a chromophore linker based on the tetraphenylethene (TPE) molecule exhibit record high two-photon absorption (2PA) cross-section values, up to 3600 GM. The unique modular building-block principle of MOFs allows enhancing and optimizing their MPA properties in a theory-guided approach by combining tailored charge polarization, conformational strain, three-dimensional arrangement, and alignment of the chromophore linkers in the crystal.

We measure the adsorption height of hydrogen-intercalated quasifreestanding monolayer graphene on the (0001) face of 6H silicon carbide by the normal incidence x-ray standing wave technique. A density functional calculation for the full (6√3×6√3)-R30° unit cell, based on a van der Waals corrected exchange correlation functional, finds a purely physisorptive adsorption height in excellent agreement with experiments, a very low buckling of the graphene layer, a very homogeneous electron density at the interface, and the lowest known adsorption energy per atom for graphene on any substrate. A structural comparison to other graphenes suggests that hydrogen-intercalated graphene on 6H-SiC(0001) approaches ideal graphene.

First-principles surface phase diagrams reveal that epitaxial monolayer graphene films on the Si side of 3C-SiC(111) can exist as thermodynamically stable phases in a narrow range of experimentally controllable conditions, defining a path to the highest quality graphene films. Our calculations are based on a van der Waals corrected density functional. The full, experimentally observed (6sqrt[3]×6sqrt[3])-R30° supercells for zero- to trilayer graphene are essential to describe the correct interface geometries and the relative stability of surface phases and possible defects.

The Density-Functional Tight Binding (DFTB) method is a popular semiempirical approximation to Density Functional Theory (DFT). In many cases, DFTB can provide comparable accuracy to DFT at a fraction of the cost, enabling simulations on lengthand time-scales that are unfeasible with first principles DFT. At the same time (and in contrast to empirical interatomic potentials and force-fields), DFTB still offers direct access to electronic properties such as the band-structure. These advantages come at the cost of introducing empirical parameters to the method, leading to a reduced transferability compared to true first-principle approaches. Consequently, it would be very useful if the parameter-sets could be routinely adjusted for a given project.While fairly robust and transferable parameterization workflows exist for the electronic structure part of DFTB, the so-called repulsive potential V rep poses a major challenge.In this paper we propose a machine-learning (ML) approach to fitting V rep , using Gaussian Process Regression (GPR). The use of GPR circumvents the need for nonlinear or global parameter optimization, while at the same time offering arbitrary flexibility in terms of the functional form. We also show that the proposed method can be applied to multiple elements at once, by fitting repulsive potentials for organic molecules containing carbon, hydrogen and oxygen. Overall, the new approach removes focus from the choice of functional form and parameterization procedure, in favour of a data-driven philosophy.

We address the stability of the surface phases that occur on the C side of 3C-SiC(111) at the onset of graphene formation. In this growth range, experimental reports reveal a coexistence of several surface phases. This coexistence can be explained by a Si-rich model for the unknown (3 × 3) reconstruction, the known (2 × 2) C adatom phase, and the graphene-covered (2 × 2) C phase. By constructing an ab initio surface phase diagram using a van der Waals corrected density functional, we show that the formation of a well defined interface structure like the "buffer layer" on the Si side is blocked by Si-rich surface reconstructions.

The structure of the SiC( 1 000 ) surface, the C-face of the {0001} SiC surfaces, is studied as a function of temperature and of pressure in a gaseous environment of disilane (Si2H6). Various surface reconstructions are observed, both with and without the presence of an overlying graphene layer (which spontaneously forms at sufficiently high temperatures). Based on cross-sectional scanning transmission electron microscopy measurements, the interface structure that forms in the presence of the graphene is found to contain 1.4 -1.7 monolayers (ML) of Si, a somewhat counterintuitive result since, when the graphene forms, the system is actually under C-rich conditions. Using ab initio thermodynamics, it is demonstrated that there exists a class of Si-rich surfaces containing about 1.3 ML of Si that are stable on the surface (even under C-rich conditions) at temperatures above 400 K. The structures that thus form consist of Si adatoms atop a Si adlayer on the C-face of SiC, with or without the presence of overlying graphene.

We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications -Algorithmic Extensions and Optimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects. In both collaboratory efforts, scientists from the application areas, mathematicians, and computer scientists work together to develop and make available efficient highly parallel methods for the solution of eigenvalue problems. Then we focus on a topic addressed in both projects, the use of mixed precision computations to enhance efficiency. We give a more detailed description of our approaches for benefiting from either lower or higher precision in three selected contexts and of the results thus obtained.Keywords ELPA-AEO · ESSEX · eigensolver · parallel · mixed precision IntroductionEigenvalue computations are at the core of simulations in various application areas, including quantum physics and electronic structure computations. Being able to best utilize the capabilities of current and emerging high-end computing systems is essential for further improving such simulations with respect to space/time resolution or by including additional effects in the models. Given these needs, the ELPA-AEO and ESSEX-II projects contribute to the development and implementation of efficient highly parallel methods for eigenvalue problems, in different contexts.Both projects are aimed at adding new features (concerning, e.g., performance and resilience) to previously developed methods and at providing additional functionality with new methods. Building on the results of the first ESSEX funding phase [14,34], ESSEX-II again focuses on iterative methods for very large eigenproblems arising, e.g., in quantum physics. ELPA-AEO's main application area is electronic structure computation, and for these moderately sized eigenproblems direct methods are often superior. Such methods are available in the widely used ELPA library [19], which had originated in an earlier project [2] and is being improved further and extended with ELPA-AEO.In Sections 2 and 3 we briefly report on the current state and on recent achievement in the two projects, with a focus on aspects that may be of particular interest to prospective users of the software or the underlying methods.Mixed precision in the ELPA-AEO and ESSEX-II projects 3In Section 4 we turn to computations involving different precisions. Looking at three examples from the two projects we describe how lower or higher precision is used to reduce the computing time. The ELPA-AEO projectIn the ELPA-AEO project, chemists, mathematicians and computer scientists from the Max Planck Computing and Data Facility in Garching, the Fritz Haber Institute of the Max Planck Society in Berlin, the Technical University of Munich, and the University of Wuppertal collaborate to provide highly scalable methods for solving moderately-sized (n 10 6 ) Hermitian eigenvalue problems. Such problems arise, e.g., in electronic structure computations, and during the earlier ELPA project, efficient...