Calculation of electronic properties of amorphous alloys

Abstract

We describe the application of the locally-self-consistent-multiple-scattering (LSMS)[1] method to amorphous alloys. The LSMS algorithm is optimized for the Intel XP/S-150, a multiple-instruction-multiple-data parallel computer with 1024 nodes and 2 compute processors per node. The electron density at each site is determined by solving the multiple scattering equation for atoms within a specified distance of the atom under consideration. Because this method is carried out in real space it is ideal for treating amorphous alloys. We have adapted the code to the calculation of the electronic properties of amorphous alloys. In these calculations we determine the potentials in the atomic sphere approximation self consistently at each site, unlike previous calculations[2] where we determined the potentials self consistently at an average site. With these self-consistent potentials, we then calculate electronic properties of various amorphous alloy systems. We present calculated total electronic densities of states for amorphous Ni$_{80}$P$_{20}$ and Ni$_{40}$Pd$_{40}$P$_{20}$ with 300 atoms in a supercell.Comment: 10 pages, plain tex, 2 figures. Paper accepted for publication in Proceedings of LAM-9 and Journal of non-Crystalline Solids. Please request preprints from J.C. Swihart (jcs@gibbs.physics.indiana.edu

The study on electronic density topology and bond character of amorphous alloy FenB2 (n=1–4) clusters by density functional theory

“…This method has been used for the large scale production of ultra fine amorphous alloy which has been extensively investigated. Many theoretical studies have been undertaken to investigate the structures, electronic and magnetic properties of amorphous alloys with various compositions and models, such as amorphous alloys clusters of Fe-B [4][5][6][7][8][9][10][11][12], Fe-P [4,7,13,14], Ni-P and Ni-Pd-P [15], Cu-Zr [16], Ni n BP (n = 1-6) [17], Ni x Fe and NiFe x (x = 1-5) [18], and MB n (M = Cr, Mn, Fe, Co, Ni, n 6 7) clusters [12].…”