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Register a new userDynamic behavior of mechanical cloaks designed by direct lattice transformation
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Steering waves in elastic solids is more demanding than steering waves in electromagnetism or acoustics. As a result, designing material distributions which are the counterpart of optical invisibility cloaks in elasticity poses a major challenge. Waves of all polarizations should be guided around an obstacle to emerge on the downstream side as though no obstacle were there. Recently, we have introduced the direct-lattice-transformation approach. This simple and explicit construction procedure led to extremely good cloaking results in the static case. Here, we transfer this approach to the dynamic case, i.e., to elastic waves or phonons. We demonstrate broadband reduction of scattering, with best suppressions exceeding a factor of five when using cubic coordinate transformations instead of linear ones. To reliably and quantitatively test these cloaks efficiency, we use an effective-medium approach.
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The macroscopic control of ubiquitous heat flow remains poorly explored due to the lack of a fundamental theoretical method. Here, by establishing temperature-dependent transformation thermotics for treating materials whose conductivity depends on temperature, we show analytical and simulation evidence for switchable thermal cloaking and a macroscopic thermal diode based on the cloaking. The latter allows heat flow in one direction but prohibits the flow in the opposite direction, which is also confirmed by our experiments. Our results suggest that the temperature-dependent transformation thermotics could be a fundamental theoretical method for achieving macroscopic heat rectification, and provide guidance both for macroscopic control of heat flow and for the design of the counterparts of switchable thermal cloaks or macroscopic thermal diodes in other fields like seismology, acoustics, electromagnetics, or matter waves.
We present an absolute extraction method of optical constants of metal from the measured reflection electron energy loss (REELS) spectra by using the recently developed reverse Monte Carlo (RMC) technique. The method is based on a direct physical modeling of electron elastic and electron inelastic scattering near the surface region where the surface excitation becomes important to fully describe the spectrum loss feature intensity in relative to the elastic peak intensity. An optimization procedure of oscillator parameters appeared in the energy loss function (ELF) for describing electron inelastic scattering due to the bulk- and surface-excitations was performed with the simulated annealing method by a successive comparison between the measured and Monte Carlo simulated REELS spectra. The ELF and corresponding optical constants of Fe were obtained from the REELS spectra measured at incident energies of 1000, 2000 and 3000 eV. The validity of the present optical data has been verified with the f- and ps-sum rules showing the accuracy and applicability of the present approach. Our data are also compared with previous optical data from other sources.
We present a new version of the Ogre open source Python package with the capability to perform structure prediction of epitaxial inorganic interfaces by lattice and surface matching. In the lattice matching step a scan over combinations of substrate and film Miller indices is performed to identify the domain-matched interfaces with the lowest mismatch. Subsequently, surface matching is conducted by Bayesian optimization to find the optimal interfacial distance and in-plane registry between the substrate and film. For the objective function, a geometric score function is proposed, based on the overlap and empty space between atomic spheres at the interface. The score function reproduces the results of density functional theory (DFT) at a fraction of the computational cost. The optimized interfaces are pre-ranked using a score function based on the similarity of the atomic environment at the interface to the bulk environment. Final ranking of the top candidate structures is performed with DFT. Ogre streamlines DFT calculations of interface energies and electronic properties by automating the construction of interface models. The application of Ogre is demonstrated for two interfaces of interest for quantum computing and spintronics, Al/InAs and Fe/InSb.
Two granular systems (I and II) corresponding oxide nanopowders having different agglomeration tendency are simulated by the granular dynamics method. The particle size is 10 nanometer. The interaction of particles involves the elastic forces of repulsion, the tangential forces of friction, the dispersion forces of attraction, and in the case of II system the opportunity of creation/destruction of hard bonds of chemical nature. The processes of the uniaxial compaction, the biaxial (radial) one, the isotropic one, the compaction combined with shear deformation as well as the simple shear deformation are studied. The effect of the positive dilatancy is found out in the processes of shear deformation. The loading surfaces of nanopowders are constructed in the space of stress tensor invariants, i.e., the hydrostatic pressure and the deviator intensity. It is revealed that the form of the loading surfaces is similar to an ellipse, which is shifted along the hydrostatic axis to compressive pressures. The associated flow rule is analyzed. The nonorthogonality of the deformation vectors to the loading surface is established in the both systems modeled.
Recently, high-entropy alloys (HEAs) have attracted wide attention due to their extraordinary materials properties. A main challenge in identifying new HEAs is the lack of efficient approaches for exploring their huge compositional space. Ab initio calculations have emerged as a powerful approach that complements experiment. However, for multicomponent alloys existing approaches suffer from the chemical complexity involved. In this work we propose a method for studying HEAs computationally. Our approach is based on the application of machine-learning potentials based on ab initio data in combination with Monte Carlo simulations. The high efficiency and performance of the approach are demonstrated on the prototype bcc NbMoTaW HEA. The approach is employed to study phase stability, phase transitions, and chemical short-range order. The importance of including local relaxation effects is revealed: they significantly stabilize single-phase formation of bcc NbMoTaW down to room temperature. Finally, a so-far unknown mechanism that drives chemical order due to atomic relaxation at ambient temperatures is discovered.
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