Role of atomic coordination on superconducting properties of boron-doped amorphous carbon

We study the effect of atomic coordination (orbital hybridization) on superconducting properties of boron-doped amorphous carbon. The ratio of threefold coordinated (sp2-hybridized) and fourfold coordinated (sp3-hybridized) atoms in the system is found to have an impact on their electronic, vibrational, and superconducting properties. Our findings show that a high proportion of fourfold coordination in both carbon and boron atoms is important for realizing a high superconducting transition temperature

Doping Nanocrystals And The Role Of Quantum Confinement

Recent progress in developing algorithms for solving the electronic structure problem for nanostructures is illustrated. Key ingredients in this approach include pseudopotentials implemented on a real space grid and the use of density functional theory. This procedure allows one to predict electronic properties for many materials across the nano-regime, i.e., from atoms to nanocrystals of sufficient size to replicate bulk properties. We will illustrate this method for doping silicon nanocrystals with phosphorous.Institute for Computational Engineering and Sciences (ICES

Parallel Self-Consistent-Field Calculations via Chebyshev-Filtered Subspace Acceleration

Solving the Kohn-Sham eigenvalue problem constitutes the most computationally expensive part in self-consistent density functional theory (DFT) calculations. In a previous paper, we have proposed a nonlinear Chebyshev-filtered subspace iteration method, which avoids computing explicit eigenvectors except at the first SCF iteration. The method may be viewed as an approach to solve the original nonlinear Kohn-Sham equation by a nonlinear subspace iteration technique, without emphasizing the intermediate linearized Kohn-Sham eigenvalue problem. It reaches self-consistency within a similar number of SCF iterations as eigensolver-based approaches. However, replacing the standard diagonalization at each SCF iteration by a Chebyshev subspace filtering step results in a significant speedup over methods based on standard diagonalization. Here, we discuss an approach for implementing this method in multi-processor, parallel environment. Numerical results are presented to show that the method enables to perform a class of highly challenging DFT calculations that were not feasible before