Disorder by design: A data-driven approach to amorphous semiconductors without total-energy functionals.

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.

Temperature-induced nanostructural evolution of hydrogen-rich voids in amorphous silicon: a first-principles study.

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.

Amorphous graphene: a constituent part of low density amorphous carbon.

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.

Nearly defect-free dynamical models of disordered solids: The case of amorphous silicon.

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.

Inversion of diffraction data for amorphous materials.

The general and practical inversion of diffraction data-producing a computer model correctly representing the material explored-is an important unsolved problem for disordered materials. Such modeling should proceed by using our full knowledge base, both from experiment and theory. In this paper, we describe a robust method to jointly exploit the power of ab initio atomistic simulation along with the information carried by diffraction data.

Sculpting the band gap: a computational approach.

Materials with optimized band gap are needed in many specialized applications. In this work, we demonstrate that Hellmann-Feynman forces associated with the gap states can be used to find atomic coordinates that yield desired electronic density of states. Using tight-binding models, we show that this approach may be used to arrive at electronically designed models of amorphous silicon and carbon.

Nanoscale structure of microvoids in a-Si:H: a first-principles study.

In this paper, we have studied the shape, size, and number density of atomic microvoids in hydrogenated amorphous silicon (a-Si:H). By jointly employing experimental infrared data and ab initio simulations, we propose a simple and effective hydrogenation scheme, which is capable of producing large atomistic models of a-Si:H for studying microvoids. Our results suggest that hydrogen atoms in the networks are distributed in sparse (or isolated) and clustered environments.

A study of hydrogen microstructure in amorphous silicon via inversion of nuclear magnetic resonance spectra.

We present an inverse approach for studying hydrogen microstructure in amorphous silicon. The approach consists of generating a prior distribution (of spins/hydrogen) by inverting experimental nuclear magnetic resonance (NMR) data, which is subsequently superimposed on a network of amorphous silicon. The resulting network is then relaxed using a total-energy functional to obtain a stable, low-energy configuration such that the initial spin distribution is minimally perturbed.

Vacancies, microstructure and the moments of nuclear magnetic resonance: the case of hydrogenated amorphous silicon.

Recent experiments on hydrogenated amorphous silicon using infrared absorption spectroscopy have indicated the presence of mono- and divacancies in samples for concentrations of up to 14% hydrogen. Motivated by this observation, we study the microstructure of hydrogen in two model networks of hydrogen-rich amorphous silicon with particular emphasis on the nature of the distribution (of hydrogen), the presence of defects and the characteristic features of the nuclear magnetic resonance spectra at low and high concentrations of hydrogen. Our study reveals the presence of vacancies, which are the built-in features of the model networks.

Atomistic modeling of amorphous silicon carbide: an approximate first-principles study in constrained solution space.

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.

Materials modeling by design: applications to amorphous solids.

In this paper, we review a host of methods used to model amorphous materials. We particularly describe methods which impose constraints on the models to ensure that the final model meets a priori requirements (on structure, topology, chemical order, etc). In particular, we review work based on quench from the melt simulations, the 'decorate and relax' method, which is shown to be a reliable scheme for forming models of certain binary glasses.

Maximum entropy and the problem of moments: a stable algorithm.

We present a technique for entropy optimization to calculate a distribution from its moments. The technique is based upon maximizing a discretized form of the Shannon entropy functional by mapping the problem onto a dual space where an optimal solution can be constructed iteratively. We demonstrate the performance and stability of our algorithm with several tests on numerically difficult functions.

Numerical simulations of air-driven granular separation.

Recently it has been shown that binary mixtures of equal-sized fine granular materials exhibit spontaneous separation under vertical vibration in the presence of air [Science 295, 1877 (2002)]. Here we describe a model of this behavior based on soft-sphere molecular dynamics coupled to the motion of the surrounding air. It exhibits many of the features observed experimentally including almost complete separation of the components into well defined regions with extremely sharp boundaries.