SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Band structures are calculated for HgTe, CdTe, and ZnTe. A near band-edge approximation to the coherent potential approximation is used to compute the alloy band-gap variation and electron and hole effective masses in HgZnTe and HgCdTe. Both diagonal and off-diagonal disorder are included. The consequences for hole mobility are found to be significant if anion disorder is present because of a valence-band offset.
Extension of the single-site coherent potential approximation for random binary alloys to include the effect of off-diagonal randomness and pair scattering. This extension is achieved by analyzing a one-band model of a random binary alloy in terms of a two-sites coherent potential approximation. Numerical results are presented for a number of different alloys. In the overlapping-band case, the presence of off-diagonal randomness is shown to modify the bandwidths to values larger than those obtained from the virtual-crystal approximation. A simple iterative procedure is described for overcoming the convergence difficulties in the split-band case. In this limit, the inclusion of pair scattering and off-diagonal randomness is found to lead to the appearance of structure in the density of states of the minority component band.
In this work, we present a comparative study of different modeling approaches to the electronic properties of the Hf 0.05 Nb 0.05 Ta 0.8 Ti 0.05 Zr 0.05 high-entropy alloy. Common to our modeling is the methodology to compute the one-particle Green’s function in the framework of density functional theory. We demonstrate that the special quasi-random structures modeling and the supercell, i.e., the locally self-consistent multiple-scattering methods, provide very similar results for the ground state properties such as the spectral function (density of states) and the equilibrium lattice parameter. To reconcile the multiple-scattering single-site coherent potential approximation with the real space supercell methods, we included the effect of screening of the net charges of the alloy components. Based on the analysis of the total energy and spectral functions computed within the density functional theory, we found no signature for the long-range or local magnetic moments formation in the Hf 0.05 Nb 0.05 Ta 0.8 Ti 0.05 Zr 0.05 high-entropy alloy; instead, we find possible superconductivity below ~9K.
The out-of-time-order correlator (OTOC) serves as a powerful tool for investigating quantum information spreading and chaos in complex systems. We present a method employing non-equilibrium dynamical mean-field theory and coherent potential approximation combined with diagrammatic perturbation on the Schwinger–Keldysh contour to calculate the OTOC for correlated fermionic systems subjected to both random disorder and electron interaction. Furthermore, our key finding is that random disorder enhances the OTOC decay in the Hubbard model for the metallic phase in the weakly interacting limit. However, the current limitation of our perturbative solver restricts the applicability to weak interaction regimes.
We present a solution for the nonequilibrium dynamics of an interacting disordered system. The approach adapts the combination of the equilibrium dynamical mean-field theory and the equilibrium coherent potential approximation methods to the nonequilibrium many-body formalism, using the Kadanoff-Baym-Keldysh complex time contour, for the dynamics of interacting disordered systems away from equilibrium. We use our time domain solution to obtain the equilibrium density of states of the disordered interacting system described by the Anderson-Hubbard model, bypassing the necessity for the cumbersome analytical continuation process. We further apply the nonequilibrium solution to the interaction quench problem for an isolated disordered system. Here, the interaction is abruptly changed from zero (noninteracting system) to another constant (finite) value at which it is subsequently kept. We observe via the time dependence of the potential, kinetic, and total energies the effect of disorder on the relaxation of the system as a function of final interaction strength. Finally, the real-time approach has the potential to shed light on the fundamental role of disorder in the nonequilibrium dynamics of interacting quantum systems.
The locally self-consistent multiple scattering (LSMS) method can perform efficient first-principles calculations of systems with a large number of atoms. Here, in this paper, we combine the Kubo-Greenwood equation with LSMS, enabling us to calculate the first-principles residual resistivity of large systems. This has been implemented in the open-source code LSMS . We apply this method to selected pure elements and binary random alloys. The results compare well with experiment, and with values obtained from a first-principles effective medium technique (the Korringa-Kohn-Rostoker coherent potential approximation). We discuss future applications of this method to complex systems where other methods are not applicable.
The minority-spin Fe/MgO interface states are at the Fermi level in density functional theory (DFT), but experimental evidence and GW calculations place them slightly higher in energy. This small shift can strongly influence tunneling magnetoresistance (TMR) in junctions with a thin MgO barrier and its dependence on the concentration of Co in the electrodes. Here, in this study, an empirical potential correction to DFT is introduced to shift the interface states up to match the tunnel spectroscopy data. With this shift, TMR in Fe/MgO/Fe junctions exceeds 800% and 3000% at 3 and 4 monolayers (ML) of MgO, respectively. We further consider the effect of alloying of the Fe electrodes with up to 30% Co or 10% V, treating them in the coherent potential approximation (CPA). Alloying with Co broadens the interface states and brings a large incoherent minority-spin spectral weight to the Fermi level. Alloying with V brings the minority-spin resonant states close to the Fermi level. However, in both cases the minority-spin spectral weight at the Fermi level resides primarily at the periphery of the Brillouin zone, which is favorable for spin filtering. Using convolutions of k II -resolved barrier densities of states calculated in CPA, it is found that TMR is strongly reduced by alloying with Co or V but still remains above 500% at 4 ML of MgO up to 30% of Co or 5% V. At 5 ML, the TMR increases above 1000% in all systems considered. However, while TMR declines sharply with increasing bias up to 0.2 eV in the tunnel junctions with pure Fe leads, it remains almost constant up to 0.5 eV if leads are alloyed with Co.
A model calculation of the temperature dependence of the electronic density of states and the electrical conductivity of disordered binary alloys, based on the coherent-potential approximation is made by introducing thermal disorder in the single-band model (Velicky and others). Thermal disorder is found to broaden and smear the static-alloy density of states. The electrical resistivity in weak-scattering alloys always increases with temperature. However, in the strong-scattering case, the temperature coefficient of resistivity can be positive, zero, or negative, depending on the location of the Fermi energy.-
Monte Carlo simulations are performed on three high entropy alloys: Cr0.25Fe0.25Co0.25Ni0.25, Cr0.2Fe0.2Co0.2Ni0.2Pd0.2, and Cr0.2Mn0.2Fe0.2Co0.2Ni0.2, with exchange interactions extracted from The ab initio Korringa-Kohn-Rostoker method combined with the coherent potential approximation calculations. Using finite size scaling analyses, we estimate the magnetic phase transition temperature for the four component alloy to be 108(2) K, and although the individual critical exponents are different from 3D Heisenberg universality class, the reduced exponent follows Suzuki weak universality. With the additional Palladium component, the transition temperature elevates to about 200 K. In contrast, we find no magnetic order for the five component alloy with Manganese at any finite temperatures.
The capabilities of the Dense Media Radiative Transfer model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP) to reproduce measured radiometric data were tested using the University of Tokyo Ground Based Microwave Radiometer (GBMR-7) during the third Intensive Observation Period (IOP3) of the NASA Cold-land Processes Field Experiment (CLPX). The data were collected at the Local-Scale Observation Site (LSOS), a 0.8-ha study site consisting of two open meadows separated by trees. Intensive measurements were also made of snow depth and temperature, density, and grain size profiles. A DMRT model is needed to describe radiative transfer in a medium such as snow because the assumption of independent scattering used in classical radiative transfer theory (CRT) is not valid. Validation of the DMRT approach requires a relationship between measured snow grain size and the DMRT approximation of snow grain radius as spherical particles with a mean radius of the log-normal particle-size distribution. This relationship is very important for a better understanding of snow modelling and for practical applications. DMRT simulations were compared with observations of microwave brightnesses at 18.7, 36.5 and 89-GHz (V and H polarizations) collected on February-1 9-25, 2003. Observation angles ranged from 30\deg to 70\deg. Model inputs included measured snow parameters except mean grain size. The average snow temperature, fractional volume and depth were held constant, together with the ice and soil permittivities. The minimum and maximum measured mean grain sizes were used to test the capabilities of the DMRT to reproduce the brightnesses as upper and lower limits. The sensitivity to the largest and smallest measured grain size in the three classes of minimum, medium and maximum observed grain sizes was also investigated. DMRT particle sizes yielding a best-fit to the experimental data for each date were computed. Results show that the measured brightnesses fall within the range of simulated brightnesses using the smallest and largest measured grain size values. The DMRT best-fit radii are comparable to the average radii for the medium observed grain sizes.
Machine learning approaches have recently been applied to the study of various problems in physics. Most of these studies are focused on interpreting the data generated by conventional numerical methods or the data on an existing experimental database. An interesting question is whether it is possible to use a machine learning approach, in particular a neural network, for solving the many-body problem. In this paper, we present a neural network solver for the single impurity Anderson model, the paradigm of an interacting quantum problem in small clusters. We demonstrate that the neural-network-based solver provides quantitative accurate results for the spectral function as compared to the exact diagonalization method. This opens the possibility of utilizing the neural network approach as an impurity solver for other many-body numerical approaches, such as the dynamical mean field theory.
Microwave brightness temperatures at 18.7,36.5, and 89 GHz collected at the Local-Scale Observation Site (LSOS) of the NASA Cold-Land Processes Field Experiment in February, 2003 (third Intensive Observation Period) were simulated using a Dense Media Radiative Transfer model (DMRT), based on the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). Inputs to the model were averaged from LSOS snow pit measurements, although different averages were used for the lower frequencies vs. the highest one, due to the different penetration depths and to the stratigraphy of the snowpack. Mean snow particle radius was computed as a best-fit parameter. Results show that the model was able to reproduce satisfactorily brightness temperatures measured by the University of Tokyo s Ground Based Microwave Radiometer system (CBMR-7). The values of the best-fit snow particle radii were found to fall within the range of values obtained by averaging the field-measured mean particle sizes for the three classes of Small, Medium and Large grain sizes measured at the LSOS site.
Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.
In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.
General mixing formulas are derived for discrete scatterers immersed in a host medium. The inclusion particles are assumed to be ellipsoidal. The electric field inside the scatterers is determined by quasi-static analysis, assuming the diameter of the inclusion particles to be much smaller than one wavelength. The results are applicable to general multiphase mixtures, and the scattering ellipsoids of the different phases can have different sizes and arbitrary ellipticity distribution and axis orientation, i.e., the mixture may be isotropic or anisotropic. The resulting mixing formula is nonlinear and is suitable for iterative solutions. The formula contains a quantity called the apparent permittivity, and with different choices of this quantity, the result leads to the generalized Lorentz-Lorenz formula, the generalized Polder-van Santen formula, and the generalized coherent potential-quasicrystalline approximation formula. The results are applied to calculating the complex effective permittivity of dry and wet snow, and sea ice.
Improving coherence is a fundamental challenge in quantum simulation and sensing experiments with trapped ions. Here we discuss, experimentally demonstrate, and estimate the potential impacts of two different protocols that enhance, through motional parametric excitation, the coherent spin-motion coupling of ions obtained with a spin-dependent force. The experiments are performed on two-dimensional crystal arrays of approximately 100 9 Be + ions confined in a Penning trap. By modulating the trapping potential at close to twice the center-of-mass mode frequency, we squeeze the motional mode and enhance the spin-motion coupling while maintaining spin coherence. With a stroboscopic protocol, we measure 5.4 ± 0.9 dB of motional squeezing below the ground-state motion, from which theory predicts a 10-dB enhancement in the sensitivity for measuring small displacements using a recently demonstrated protocol [K. A. Gilmore et al., Science 373, 673 (2021)]. With a continuous squeezing protocol, we measure and accurately calibrate the parametric coupling strength. Theory suggests this protocol can be used to improve quantum spin squeezing, limited in our system by off-resonant light scatter. Finally, we illustrate numerically the trade-offs between strong parametric amplification and motional dephasing in the form of center-of-mass frequency fluctuations for improving quantum spin squeezing in our setup.
Using a multiple-scatter propagation theory, the characteristics of the transionospheric satellite-earth communication links are related to the parameters of the ionosphere. General equations for the frequency correlation functions are derived. Some approximate solutions are obtained and numerical examples are given. Also discussed are the degree of coherence and potential applications of the procedure to characterize the intense fading channel.
Femtolensoing is a gravitational lensing effect in which the magnification is a function not only of the position and sizes of the source and lens, but also of the wavelength of light. Femtolensing is the only known effect of 10(exp -13) - 10(exp -16) solar mass) dark-matter objects and may possibly be detectable in cosmological gamma-ray burst spectra. We present a new and efficient algorithm for femtolensing calculation in general potentials. The physical optics results presented here differ at low frequencies from the semiclassical approximation, in which the flux is attributed to a finite number of mutually coherent images. At higher frequencies, our results agree well with the semicalssical predictions. Applying our method to a point-mass lens with external shear, we find complex events that have structure at both large and small spectral resolution. In this way, we show that femtolensing may be observable for lenses up to 10(exp -11) solar mass, much larger than previously believed. Additionally, we discuss the possibility of a search femtolensing of white dwarfs in the Large Magellanic Cloud at optical wavelengths.