Publications by authors named "Raymond Atta-Fynn"

X-ray diffraction, Amorphous silicon, Multi-objective optimization, Monte Carlo methods. This paper addresses a difficult inverse problem that involves the reconstruction of a three-dimensional model of tetrahedral amorphous semiconductors via inversion of diffraction data. By posing the material-structure determination as a multiobjective optimization program, it has been shown that the problem can be solved accurately using a few structural constraints, but no total-energy functionals/forces, which describe the local chemistry of amorphous networks.

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The paper presents an ab initio study of temperature-induced nanostructural evolution of hydrogen-rich voids in amorphous silicon. By using large a-Si models, obtained from classical molecular-dynamics simulations, with a realistic void-volume density of 0.2%, the dynamics of Si and H atoms on the surface of the nanometer-size cavities were studied and their effects on the shape and size of the voids were examined using first-principles density-functional simulations.

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In this paper, we provide evidence that low density nano-porous amorphous carbon (a-C) consists of interconnected regions of amorphous graphene (a-G). We include experimental information in producing models, while retaining the power and accuracy of ab initio methods with no biasing assumptions. Our models are highly disordered with predominant sp2 bonding and ring connectivity mainly of sizes 5-8.

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It is widely accepted in the materials modeling community that defect-free realistic networks of amorphous silicon cannot be prepared by quenching from a molten state of silicon using classical or ab initio molecular-dynamics (MD) simulations. In this work, we address this long-standing problem by producing nearly defect-free ultra-large models of amorphous silicon, consisting of up to half a million atoms, using classical MD simulations. The structural, topological, electronic, and vibrational properties of the models are presented and compared with experimental data.

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The presence of counterions in solutions containing highly charged metal cations can trigger processes such as ion-pair formation, hydrogen bond breakages and subsequent re-formation, and ligand exchanges. In this work, it is shown how halide (Cl, Br) and perchlorate (ClO) anions affect the strength of the primary solvent coordination shells around Th using explicit-solvent and finite-temperature ab initio molecular dynamics modeling methods. The 9-fold solvent geometry was found to be the most stable hydration structure in each aqueous solution.

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Ab initio molecular dynamics simulations at 300 K, based on density functional theory, are performed to study the hydration shell geometries, solvent dipole, and first hydrolysis reaction of the uranium(IV) (U(4+)) and uranyl(V) (UO(2)(+)) ions in aqueous solution. The solvent dipole and first hydrolysis reaction of aqueous uranyl(VI) (UO(2)(2+)) are also probed. The first shell of U(4+) is coordinated by 8-9 water ligands, with an average U-O distance of 2.

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Results of ab initio molecular dynamics (AIMD), quantum mechanics/molecular mechanics (QM/MM), and classical molecular dynamics (CMD) simulations of Cm(3+) in liquid water at a temperature of 300 K are reported. The AIMD simulation was based on the Car-Parrinello MD scheme and GGA-PBE formulation of density functional theory. Two QM/MM simulations were performed by treating Cm(3+) and the water molecules in the first shell quantum mechanically using the PBE (QM/MM-PBE) and the hybrid PBE0 density functionals (QM/MM-PBE0).

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Localized basis ab initio molecular dynamics simulation within the density functional framework has been used to generate realistic configurations of amorphous silicon carbide (a-SiC). Our approach consists of constructing a set of smart initial configurations that conform to essential geometrical and structural aspects of the materials obtained from experimental data, which is subsequently driven via a first-principles force field to obtain the best solution in a reduced solution space. A combination of a priori information (primarily structural and topological) along with the ab initio optimization of the total energy makes it possible to model a large system size (1000 atoms) without compromising the quantum mechanical accuracy of the force field to describe the complex bonding chemistry of Si and C.

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