K. K. Sahu

Experimental and computer simulation determination of the structural changes occurring through the liquid-glass transition in Cu-Zr alloys

Molecular dynamics (MD) simulations were performed of the structural changes occurring through the liquid–glass transition in Cu–Zr alloys. The total scattering functions (TSF), and their associated primary diffuse scattering peak positions (K p), heights (K h) and full-widths at half maximum (K FWHM) were used as metrics to compare the simulations to high-energy X-ray scattering data. The residuals of difference between the model and experimental TSFs are ∼0.03 for the liquids and about 0.07 for the glasses. Over the compositional range studied, Zr1− x Cu x (0.1 ≤ x ≤ 0.9), K p, K h and K FWHM show a strong dependence on composition and temperature. The simulation and experimental data correlate well between each other. MD simulation revealed that the Cu–Zr bonds undergo the largest changes during cooling of the liquid, whereas the Cu–Cu bonds change the least. Changes in the partial-pair correlations are more readily seen in the second and third shells. The Voronoi polyhedra (VP) in glasses are dominated by only a few select types that are compositionally dependent. The relative concentrations of the dominant VPs rapidly change in their relative proportion in the deeply undercooled liquid. The experimentally determined region of best glass formability, x Cu ∼ 65%, shows the largest temperature dependent changes for the deeply undercooled liquid in the MD simulation. This region also exhibits very strong temperature dependence for the diffusivity and the total energy of the system. These data point to a strong topological change in the best glass-forming alloys and a concurrent change in the VP chemistry in the deeply undercooled liquid.

Detecting hidden spatial and spatio-temporal structures in glasses and complex physical systems by multiresolution network clustering

We elaborate on a general method that we recently introduced for characterizing the “natural” structures in complex physical systems via multi-scale network analysis. The method is based on “community detection” wherein interacting particles are partitioned into an “ideal gas” of optimally decoupled groups of particles. Specifically, we construct a set of network representations (“replicas”) of the physical system based on interatomic potentials and apply a multiscale clustering (“multiresolution community detection”) analysis using information-based correlations among the replicas. Replicas may i) be different representations of an identical static system, ii) embody dynamics by considering replicas to be time separated snapshots of the system (with a tunable time separation), or iii) encode general correlations when different replicas correspond to different representations of the entire history of the system as it evolves in space-time. Inputs for our method are the inter-particle potentials or experimentally measured two (or higher order) particle correlations. We apply our method to computer simulations of a binary Kob-Andersen Lennard-Jones system in a mixture ratio of A80B20 , a ternary model system with components “A”, “B”, and “C” in ratios of A88B7C5 (as in Al88Y7Fe5 , and to atomic coordinates in a Zr80Pt20 system as gleaned by reverse Monte Carlo analysis of experimentally determined structure factors. We identify the dominant structures (disjoint or overlapping) and general length scales by analyzing extrema of the information theory measures. We speculate on possible links between i) physical transitions or crossovers and ii) changes in structures found by this method as well as phase transitions associated with the computational complexity of the community detection problem. We also briefly consider continuum approaches and discuss rigidity and the shear penetration depth in amorphous systems; this latter length scale increases as the system becomes progressively rigid.

Evolution of magnetic anisotropy and thermal stability during nanocrystal-chain growth

We compare measurements and simulations of ferromagnetic resonance spectra of magnetite nanocrystal-chains at different growth-stages. By fitting the spectra, we extracted the cubic magnetocrystalline anisotropy field and the uniaxial dipole field at each stage. During the growth of the nanoparticle-chain assembly, the magnetocrystalline anisotropy grows linearly with increasing particle diameter. Above a threshold average diameter of D ≈ 23 nm, a dipole field is generated, which then increases with particle size and the ensemble becomes thermally stable. These findings demonstrate the anisotropy evolution on going from nano to mesoscopic scales and the dominance of dipole fields over crystalline fields in one-dimensional assemblies.

Modelling local voids using an irregular polyhedron based on natural neighbourhood and application to characterize near-dense random packing (DRP)

A model has been developed for finding local voids in randomly packed monodisperse spheres. The voids are polyhedral in shape and are based on the natural neighbourhood concept. The natural neighbourhood is defined in the same spirit of Sibson, who introduced the concept as a refinement of Voronoi tessellation. The model is basically the construction of a Delaunay star, where the centre of the Delaunay star is an arbitrary point in the void and the vertices of the star are the sphere centres. The method is best suited for sampling study. Since the model does not use the radius of the spheres, it can even be used for point distribution in three-dimensional (3-D) space. The model can be improved by using Voronoi vertices as seed points (instead of the arbitrary points) and can be used for crystallochemical studies, where only the electron density distribution is known. It is applicable to non-spherical atoms/particles also. The method is used to analyze near-dense random packing (DRP) and the statistical properties of void structures, e.g. number of vertices per void, cell volume, void volume and void fraction, which do not change from packing to packing in the limit of DRP. The overall local void properties are insensitive to sampling; repeatedly taking 500 void samples in an ensemble did not show considerable change. Most of the voids have 9–12 vertices.

Gravity Packing of Same Size Spheres and Investigation of Wall Ordering

In the first part of the present study, Discrete Element Method (DEM) is adopted as a numerical simulation technique for studying gravity packing of randomly distributed monodispersed particles in a box of a rectangular cross section (can be thought as a fluidized bed). Packing density, coordination number distribution and radial distribution function (RDF) are calculated. Stability of the packing, spatial and temporal effects of the wall on packings are analyzed. Qualitatively and quantitatively, the results agree well with the existing literatures. Since this model uses structural reconstruction, many of the features of random packing like clear second peak split in the RDF plot have been observed. From experiments, it is well known that the confining walls impart some order in the near-wall regions. However to the best of the authors knowledge, the actual symmetries of these orderings (of walls) have never been analyzed and these have been the focus of the second part of this study. Taking a cue from structural analysis of amorphous (glassy) atomic systems, the Honeycutt-Andersen (HA) index and Bond Order Orientation (BOO) order have been employed to study the local symmetries of both near wall and core regions. It shows that the 1551 HA index, signifying icosahedral order, is more predominate in the core part than the wall. There is also some good amount of cubic symmetries both in the wall and core regions. However the most predominate structure is distorted icosahedra, which is probably appearing because of a competing effect between the icosahedral order and cubic symmetries.