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Medasani, Bharat

Publications and source records attributed to Medasani, Bharat.

Large Rashba spin splittings in bulk and monolayer of BiAs

There is great interest in developing new materials with Rashba split bands near the Fermi level for spintronics. Here, using first-principles calculations, we predict BiAs as a semiconductor with large Rashba splitting in bulk and monolayer forms. Bulk BiAs has a layered crystal structure with two atoms in a rhombohedral primitive cell, derived from the structure of the parent Bi and As elemental phases. It is a narrow band gap semiconductor, and it shows a combination of Rashba and Dresselhaus spin splitting with a characteristic spin texture around the L point in the Brillouin zone of the hexagonal conventional unit cell. It has sizable Rashba energies and Rashba coupling constants in the valence and conduction bands at the band edges. The 2D monolayer of BiAs has a much larger band gap at Γ, with a circular spin texture characteristic of a pure Rashba effect. The Rashba energy and Rashba coupling constant of monolayer BiAs are large compared to other known 2D materials and rapidly increase under biaxial tensile strain.

36 MATERIALS SCIENCE↗

Predicting band gaps and band-edge positions of oxide perovskites using density functional theory and machine learning

Density functional theory (DFT) within the local or semilocal density approximations, i.e., the local density approximation (LDA) or generalized gradient approximation (GGA), has become a workhorse in the electronic structure theory of solids, being extremely fast and reliable for energetics and structural properties, yet remaining highly inaccurate for predicting band gaps of semiconductors and insulators. The accurate prediction of band gaps using first-principles methods is time consuming, requiring hybrid functionals, quasiparticle GW, or quantum Monte Carlo methods. Efficiently correcting DFT-LDA/GGA band gaps and unveiling the main chemical and structural factors involved in this correction is desirable for discovering novel materials in high-throughput calculations. In this direction, we, in this study, use DFT and machine learning techniques to correct band gaps and band-edge positions of a representative subset of ABO 3 perovskite oxides. Relying on the results of HSE06 hybrid functional calculations as target values of band gaps, we find a systematic band-gap correction of ~1.5 eV for this class of materials, where ~1 eV comes from downward shifting the valence band and ~0.5 eV from uplifting the conduction band. The main chemical and structural factors determining the band-gap correction are determined through a feature selection procedure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stellarator optimization for good magnetic surfaces at the same time as quasisymmetry

A method is demonstrated to optimize a stellarator's geometry to eliminate magnetic islands and achieve other desired physics properties at the same time. For many physics quantities that have been used in stellarator optimization, including quasisymmetry, neoclassical transport, and magnetohydrodynamic stability, it is convenient to use a magnetic equilibrium representation that assures the existence of magnetic surfaces. However, this representation hides the possible presence of magnetic islands, which are typically undesirable. To include both surface-based objectives and island widths in a single optimization, two fixed-boundary equilibrium calculations are run at each iteration of the optimization: one that enforces the existence of magnetic surfaces (the Variational Moments Equilibrium Code) [S. P. Hirshman and J. C. Whitson, Phys. Fluids 26, 3553 (1983)] and one that does not (the Stepped Pressure Equilibrium Code) [Hudson et al., Phys. Plasmas 19, 112502 (2012)]. By penalizing the island residues in the objective function, the two magnetic field representations are brought into agreement during the optimization. Here, an example is presented in which, particularly on the surface where quasisymmetry was targeted, quasisymmetry is achieved more accurately than in previously published examples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗