Electronic Scattering Effects in Europium-Based Iron Pnictides

In a comprehensive study, we investigate the electronic scattering effects in EuFe$_{2}$(As$_{1-x}$P$_{x}$)$_{2}$ by using Fourier-transform infrared spectroscopy. In spite of the fact that Eu$^{2+}$ local moments order around $T_\text{Eu} \approx 20$\,K, the overall optical response is strikingly similar to the one of the well-known Ba-122 pnictides. The main difference lies within the suppression of the lower spin-density-wave gap feature. By analysing our spectra with a multi-component model, we find that the high-energy feature around 0.7\,eV -- often associated with Hund's rule coupling -- is highly sensitive to the spin-density-wave ordering, this further confirms its direct relationship to the dynamics of itinerant carriers. The same model is also used to investigate the in-plane anisotropy of magnetically detwinned EuFe$_{2}$As$_{2}$ in the antiferromagnetically ordered state, yielding a higher Drude weight and lower scattering rate along the crystallographic $a$-axis. Finally, we analyse the development of the room temperature spectra with isovalent phosphor substitution and highlight changes in the scattering rate of hole-like carriers induced by a Lifshitz transition

Emergence of chaotic scattering in ultracold Er and Dy

We show that for ultracold magnetic lanthanide atoms chaotic scattering emerges due to a combination of anisotropic interaction potentials and Zeeman coupling under an external magnetic field. This scattering is studied in a collaborative experimental and theoretical effort for both dysprosium and erbium. We present extensive atom-loss measurements of their dense magnetic Feshbach resonance spectra, analyze their statistical properties, and compare to predictions from a random-matrix-theory inspired model. Furthermore, theoretical coupled-channels simulations of the anisotropic molecular Hamiltonian at zero magnetic field show that weakly-bound, near threshold diatomic levels form overlapping, uncoupled chaotic series that when combined are randomly distributed. The Zeeman interaction shifts and couples these levels, leading to a Feshbach spectrum of zero-energy bound states with nearest-neighbor spacings that changes from randomly to chaotically distributed for increasing magnetic field. Finally, we show that the extreme temperature sensitivity of a small, but sizeable fraction of the resonances in the Dy and Er atom-loss spectra is due to resonant non-zero partial-wave collisions. Our threshold analysis for these resonances indicates a large collision-energy dependence of the three-body recombination rate

Two-band second moment model and an interatomic potential for caesium

A semi-empirical formalism is presented for deriving interatomic potentials for materials such as caesium or cerium which exhibit volume collapse phase transitions. It is based on the Finnis-Sinclair second moment tight binding approach, but incorporates two independent bands on each atom. The potential is cast in a form suitable for large-scale molecular dynamics, the computational cost being the evaluation of short ranged pair potentials. Parameters for a model potential for caesium are derived and tested

Numerical Methods for the Stochastic Landau-Lifshitz Navier-Stokes Equations

The Landau-Lifshitz Navier-Stokes (LLNS) equations incorporate thermal fluctuations into macroscopic hydrodynamics by using stochastic fluxes. This paper examines explicit Eulerian discretizations of the full LLNS equations. Several CFD approaches are considered (including MacCormack's two-step Lax-Wendroff scheme and the Piecewise Parabolic Method) and are found to give good results (about 10% error) for the variances of momentum and energy fluctuations. However, neither of these schemes accurately reproduces the density fluctuations. We introduce a conservative centered scheme with a third-order Runge-Kutta temporal integrator that does accurately produce density fluctuations. A variety of numerical tests, including the random walk of a standing shock wave, are considered and results from the stochastic LLNS PDE solver are compared with theory, when available, and with molecular simulations using a Direct Simulation Monte Carlo (DSMC) algorithm

Use of the Richtmyer-Meshkov Instability to Infer Yield Stress at High-Energy Densities

We use the Richtmyer-Meshkov instability (RMI) at a metal-gas interface to infer the metal’s yield stress (Y) under shock loading and release. We first model how Y stabilizes the RMI using hydrodynamics simulations with a perfectly plastic constitutive relation for copper (Cu). The model is then tested with molecular dynamics (MD) of crystalline Cu by comparing the inferred Y from RMI simulations with direct stress-strain calculations, both with MD at the same conditions. Finally, new RMI experiments with solid Cu validate our simulation-based model and infer Y~0.47 GPa for a 36 GPa shock

Simulation of the thermally induced austenitic phase transition in NiTi nanoparticles

The reverse martensitic ("austenitic") transformation upon heating of equiatomic nickel-titanium nanoparticles with diameters between 4 and 17 nm is analyzed by means of molecular-dynamics simulations with a semi-empirical model potential. After constructing an appropriate order parameter to distinguish locally between the monoclinic B19' at low and the cubic B2 structure at high temperatures, the process of the phase transition is visualized. This shows a heterogeneous nucleation of austenite at the surface of the particles, which propagates to the interior by plane sliding, explaining a difference in austenite start and end temperatures. Their absolute values and dependence on particle diameter are obtained and related to calculations of the surface induced size dependence of the difference in free energy between austenite and martensite.Comment: 6 pages, 4 figures, accepted for publication in "The European Physical Journal B

Restructuring of colloidal aggregates in shear flow: Coupling interparticle contact models with Stokesian dynamics

A method to couple interparticle contact models with Stokesian dynamics (SD) is introduced to simulate colloidal aggregates under flow conditions. The contact model mimics both the elastic and plastic behavior of the cohesive connections between particles within clusters. Owing to this, clusters can maintain their structures under low stress while restructuring or even breakage may occur under sufficiently high stress conditions. SD is an efficient method to deal with the long-ranged and many-body nature of hydrodynamic interactions for low Reynolds number flows. By using such a coupled model, the restructuring of colloidal aggregates under stepwise increasing shear flows was studied. Irreversible compaction occurs due to the increase of hydrodynamic stress on clusters. Results show that the greater part of the fractal clusters are compacted to rod-shaped packed structures, while the others show isotropic compaction.Comment: A simulation movie be found at http://www-levich.engr.ccny.cuny.edu/~seto/sites/colloidal_aggregates_shearflow.htm

Direct Observation of Martensitic Phase-Transformation Dynamics in Iron by 4D Single-Pulse Electron Microscopy

The in situ martensitic phase transformation of iron, a complex solid-state transition involving collective atomic displacement and interface movement, is studied in real time by means of four-dimensional (4D) electron microscopy. The iron nanofilm specimen is heated at a maximum rate of ∼10^(11) K/s by a single heating pulse, and the evolution of the phase transformation from body-centered cubic to face-centered cubic crystal structure is followed by means of single-pulse, selected-area diffraction and real-space imaging. Two distinct components are revealed in the evolution of the crystal structure. The first, on the nanosecond time scale, is a direct martensitic transformation, which proceeds in regions heated into the temperature range of stability of the fcc phase, 1185−1667 K. The second, on the microsecond time scale, represents an indirect process for the hottest central zone of laser heating, where the temperature is initially above 1667 K and cooling is the rate-determining step. The mechanism of the direct transformation involves two steps, that of (barrier-crossing) nucleation on the reported nanosecond time scale, followed by a rapid grain growth typically in ∼100 ps for 10 nm crystallites

Computer simulation of model cohesive powders: Plastic consolidation, structural changes and elasticity under isotropic loads

The quasistatic behavior of a simple 2D model of a cohesive powder under isotropic loads is investigated by Discrete Element simulations. The loose packing states, as studied in a previous paper, undergo important structural changes under growing confining pressure P, while solid fraction \Phi irreversibly increases by large amounts. The system state goes through three stages, with different forms of the plastic consolidation curve \Phi(P*), under growing reduced pressure P* = Pa/F0, defined with adhesion force F0 and grain diameter a. In the low-confinement regime (I), plastic compaction is negligible, and the structure is influenced by the assembling process. The following stage (regime II) is independent of initial conditions. The void ratio varies linearly with log P, as described in the engineering literature. In the last stage of compaction (III), a maximum solid fraction is approached, and properties of cohesionless granular packs are retrieved. Under consolidation, while the fractal range of density correlations decreases, force patterns reorganize, and elastic moduli increase by a large factor. Plastic deformation events correspond to very small changes in the network topology, while the denser regions tend to move like rigid bodies. Elastic properties are dominated by the bending of thin junctions in loose systems. For growing RR those tend to reduce to particle chains, the folding of which, rather than tensile ruptures, controls plastic compaction

Stochastic particle packing with specified granulometry and porosity

This work presents a technique for particle size generation and placement in arbitrary closed domains. Its main application is the simulation of granular media described by disks. Particle size generation is based on the statistical analysis of granulometric curves which are used as empirical cumulative distribution functions to sample from mixtures of uniform distributions. The desired porosity is attained by selecting a certain number of particles, and their placement is performed by a stochastic point process. We present an application analyzing different types of sand and clay, where we model the grain size with the gamma, lognormal, Weibull and hyperbolic distributions. The parameters from the resulting best fit are used to generate samples from the theoretical distribution, which are used for filling a finite-size area with non-overlapping disks deployed by a Simple Sequential Inhibition stochastic point process. Such filled areas are relevant as plausible inputs for assessing Discrete Element Method and similar techniques