Showing papers in "Annual Review of Materials Research in 2002"
TL;DR: The phase-field method has recently emerged as a powerful computational approach to modeling and predicting mesoscale morphological and microstructure evolution in materials as discussed by the authors, which is able to predict the evolution of arbitrary morphologies and complex microstructures without explicitly tracking the positions of interfaces.
Abstract: ■ Abstract The phase-field method has recently emerged as a powerful computational approach to modeling and predicting mesoscale morphological and microstructure evolution in materials. It describes a microstructure using a set of conserved and nonconserved field variables that are continuous across the interfacial regions. The temporal and spatial evolution of the field variables is governed by the Cahn-Hilliard nonlinear diffusion equation and the Allen-Cahn relaxation equation. With the fundamental thermodynamic and kinetic information as the input, the phase-field method is able to predict the evolution of arbitrary morphologies and complex microstructures without explicitly tracking the positions of interfaces. This paper briefly reviews the recent advances in developing phase-field models for various materials processes including solidification, solid-state structural phase transformations, grain growth and coarsening, domain evolution in thin films, pattern formation on surfaces, dislocation microstructures, crack propagation, and electromigration.
2,334 citations
TL;DR: An overview of the phase-field method for modeling solidification is presented, together with several example results as mentioned in this paper, which has been applied to a wide variety of problems including dendritic, eutectic, and peritectic growth in alloys; and solute trapping during rapid solidification.
Abstract: ▪ Abstract An overview of the phase-field method for modeling solidification is presented, together with several example results. Using a phase-field variable and a corresponding governing equation to describe the state (solid or liquid) in a material as a function of position and time, the diffusion equations for heat and solute can be solved without tracking the liquid-solid interface. The interfacial regions between liquid and solid involve smooth but highly localized variations of the phase-field variable. The method has been applied to a wide variety of problems including dendritic growth in pure materials; dendritic, eutectic, and peritectic growth in alloys; and solute trapping during rapid solidification.
1,431 citations
TL;DR: In this article, the authors discuss promising new methods, derived from transition state theory, for accelerating molecular dynamics simulations of these infrequent-event processes, such as hyperdynamics, parallel replica dynamics, temperature-accelerated dynamics, and on-the-fly kinetic Monte Carlo.
Abstract: ▪ Abstract Obtaining a good atomistic description of diffusion dynamics in materials has been a daunting task owing to the time-scale limitations of the molecular dynamics method. We discuss promising new methods, derived from transition state theory, for accelerating molecular dynamics simulations of these infrequent-event processes. These methods, hyperdynamics, parallel replica dynamics, temperature-accelerated dynamics, and on-the-fly kinetic Monte Carlo, can reach simulation times several orders of magnitude longer than direct molecular dynamics while retaining full atomistic detail. Most applications so far have involved surface diffusion and growth, but it is clear that these methods can address a wide range of materials problems.
665 citations
TL;DR: A review of the recent progress in understanding of the mechanical and electrical properties of carbon nanotubes, emphasizing the theoretical aspects, can be found in this paper, where the authors discuss the use of nanotube-reinforced composites in nanoscale sensors and devices.
Abstract: ▪ Abstract We review the recent progress in our understanding of the mechanical and electrical properties of carbon nanotubes, emphasizing the theoretical aspects. Nanotubes are the strongest materials known, but the ultimate limits of their strength have yet to be reached experimentally. Modeling of nanotube-reinforced composites indicates that the addition of small numbers of nanotubes may lead to a dramatic increase in the modulus, with only minimal crosslinking. Deformations in nanotube structures lead to novel structural transformations, some of which have clear electrical signatures that can be utilized in nanoscale sensors and devices. Chemical reactivity of nanotube walls is facilitated by strain, which can be used in processing and functionalization. Scanning tunneling microscopy and spectroscopy have provided a wealth of information about the structure and electronic properties of nanotubes, especially when coupled with appropriate theoretical models. Nanotubes are exceptional ballistic conducto...
390 citations
TL;DR: An introduction to the fundamentals of cellular automata and applications, particularly for those that predict recrystallization phenomena, are given and applications are reviewed.
Abstract: ▪ Abstract The paper is about cellular automaton models in materials science. It gives an introduction to the fundamentals of cellular automata and reviews applications, particularly for those that predict recrystallization phenomena. Cellular automata for recrystallization are typically discrete in time, physical space, and orientation space and often use quantities such as dislocation density and crystal orientation as state variables. Cellular automata can be defined on a regular or nonregular two- or three-dimensional lattice considering the first, second, and third neighbor shell for the calculation of the local driving forces. The kinetic transformation rules are usually formulated to map a linearized symmetric rate equation for sharp grain boundary segment motion. While deterministic cellular automata directly perform cell switches by sweeping the corresponding set of neighbor cells in accord with the underlying rate equation, probabilistic cellular automata calculate the switching probability of e...
266 citations
TL;DR: In this article, the authors review progress made in quantitatively ascertaining the various statistical correlation functions that are fundamental to determining the material properties of specific classes of disordered materials, including structural characterization from two-dimensional and three-dimensional images of materials, scalar order metrics and particle packings, and reconstruction techniques.
Abstract: ▪ Abstract We review progress made in quantitatively ascertaining the various statistical correlation functions that are fundamental to determining the material properties of specific classes of disordered materials. Topics covered include the definitions of the correlation functions, a unified theoretical means of representing and computing the different statistical descriptors, structural characterization from two-dimensional and three-dimensional images of materials, scalar order metrics and particle packings, and reconstruction techniques.
233 citations
TL;DR: In this article, the authors provide an overview of some of the more popular simulation methods for modeling polymeric materials and their properties and behavior, as well as the structural properties that lead to them.
Abstract: ▪ Abstract Polymers offer a wide spectrum of possibilities for materials applications, in part because of the chemical complexity and variability of the constituent molecules, and in part because they can be blended together with other organic as well as inorganic components. The majority of applications of polymeric materials is based on their excellent mechanical properties, which arise from the long-chain nature of the constituents. Microscopically, this means that polymeric materials are able to respond to external forces in a broad frequency range, i.e., with a broad range of relaxation processes. Computer simulation methods are ideally suited to help to understand these processes and the structural properties that lead to them and to further our ability to predict materials properties and behavior. However, the broad range of timescales and underlying structure prohibits any one single simulation method from capturing all of these processes. This manuscript provides an overview of some of the more p...
201 citations
TL;DR: In this paper, a review of atomistic aspects of dynamic fracture in a variety of brittle crystalline, amorphous, nanophase, and nanocomposite materials are reviewed.
Abstract: ▪ Abstract Atomistic aspects of dynamic fracture in a variety of brittle crystalline, amorphous, nanophase, and nanocomposite materials are reviewed. Molecular dynamics (MD) simulations, ranging from a million to 1.5 billion atoms, are performed on massively parallel computers using highly efficient multiresolution algorithms. These simulations shed new light on (a) branching, deflection, and arrest of cracks; (b) growth of nanoscale pores ahead of the crack and how pores coalesce with the crack to cause fracture; and (c) the influence of these mechanisms on the morphology of fracture surfaces. Recent advances in novel multiscale simulation schemes combining quantum mechanical, molecular dynamics, and finite-element approaches and the use of these hybrid approaches in the study of crack propagation are also discussed.
187 citations
TL;DR: In this article, it was shown that the transition metal d electrons essential for magnetism reduce the tendency for off-center ferroelectric distortion, and that an additional electronic or structural driving force must be present for ferromagnetism and electric polarization to occur simultaneously.
Abstract: ▪ Abstract Multiferroic magnetoelectrics are materials that are both ferromagnetic and ferroelectric in the same phase. As a result, they have a spontaneous magnetization that can be switched by an applied magnetic field and a spontaneous polarization that can be switched by an applied electric field. In this paper we show that density functional theory has been invaluable both in explaining the properties of known magnetically ordered ferroelectric materials, and in predicting the occurrence of new ones. Density functional calculations have shown that, in general, the transition metal d electrons essential for magnetism reduce the tendency for off-center ferroelectric distortion. Consequently, an additional electronic or structural driving force must be present for ferromagnetism and ferroelectricity to occur simultaneously.
173 citations
TL;DR: In this paper, various methods for calculating the free energies of fluids, solids, and discrete spin systems are reviewed with particular emphasis on applications relevant in materials science, and compared and contrast several related techniques and to provide an assessment of their relative strengths.
Abstract: ▪ Abstract Various methods for calculating the free energies of fluids, solids, and discrete spin systems are reviewed with particular emphasis on applications relevant in materials science. First, traditional methodologies based on harmonic approximations and thermodynamic integration are examined to highlight the workings of these very useful and robust techniques. Several newer and more specialized strategies are then discussed to provide a snapshot of current practices. Our aim here is to compare and contrast several related techniques and to provide an assessment of their relative strengths.
116 citations
TL;DR: There are many kinetic Monte Carlo approaches that can simulate chemical vapor deposition, ranging from coarse-grained model systems with hypothetical input parameters to physically realistic atomic simulations with accurate chemical kinetic input.
Abstract: ▪ Abstract The kinetic Monte Carlo method is a powerful tool for exploring the evolution and properties of a wide range of problems and systems. Kinetic Monte Carlo is ideally suited for modeling the process of chemical vapor deposition, which involves the adsorption, desorption, evolution, and incorporation of vapor species at the surface of a growing film. Deposition occurs on a time scale that is generally not accessible to fully atomistic approaches such as molecular dynamics, whereas an atomically resolved Monte Carlo method parameterized by accurate chemical kinetic data is capable of exploring deposition over long times (min) on large surfaces (mm2). There are many kinetic Monte Carlo approaches that can simulate chemical vapor deposition, ranging from coarse-grained model systems with hypothetical input parameters to physically realistic atomic simulations with accurate chemical kinetic input. This article introduces the kinetic Monte Carlo technique, reviews some of the major approaches, details ...
TL;DR: A review of recent advances in the calculation of density functionals for materials, with particular emphasis on fluids at walls and in porous media, on crystal nucleation and growth from the melt, and on complex fluids and biomolecules is emphasized in this paper.
Abstract: ▪ Abstract Methods of density functional theory in statistical mechanics have been applied extensively over the past 15 years to problems in the equilibrium and dynamic properties of materials. They allow the incorporation of microscopic atomic and molecular forces at a much lower computational cost than direct simulation. This review discusses recent advances in the calculation of density functionals for materials, with particular emphasis on fluids at walls and in porous media, on crystal nucleation and growth from the melt, and on complex fluids and biomolecules. The extension of equilibrium density functional methods to approximate theories of phase transition dynamics is emphasized.
TL;DR: In this paper, the effects of the macroscopic and microscopic degrees of freedom (DOFs) on grain boundary (GB) structure were investigated using lattice statics (0 K) and Monte Carlo (Metropolis algorithm) simulation.
Abstract: ▪ Abstract Lattice statics (0 K) and Monte Carlo (Metropolis algorithm) simulation are utilized to determine equilibrium and metastable structures of 21 [110] symmetric tilt boundaries between 0° and 180° at 800 K, employing a Ni embedded-atom method potential; attention is paid to the effects of the macroscopic and microscopic degrees of freedom (DOFs) on grain boundary (GB) structure. Segregation of Pd is studied at all GB structures at 800 K, employing Monte Carlo and overlapping distributions Monte Carlo simulation, which yield the Gibbsian interfacial excess of Pd (ΓPd) as a function of tilt angle for both stable and metastable structures, thereby demonstrating that ΓPd is an anisotropic function of a GB's five macroscopic DOFs. In addition, atom-probe experiments on GBs on an Fe-3 at.% Si alloy, whose five macroscopic DOFs are measured by transmission electron microscopy, directly yield ΓSi and thereby demonstrate experimentally that this quantity is an anisotropic function of these DOFs.
TL;DR: In this paper, a fracture mechanics framework has been developed for predicting crack initiation and growth in full-scale components and structures from test specimen data, and some analyses are reviewed that use micromechanical modeling to predict fracture toughness from the physics of separation and plastic flow processes.
Abstract: ▪ Abstract A fracture mechanics framework has been developed for predicting crack initiation and growth in full-scale components and structures from test specimen data. Much knowledge has also been gained about the mechanisms by which fracture occurs in a variety of materials. However, the development of quantitative connections between models of the physical processes of fracture and macroscale measures of fracture resistance is still at an early stage. A key difficulty is that fracture spans several length scales from the atomistic to the macroscopic scale. In this paper, some analyses are reviewed that use micromechanical modeling to predict fracture toughness from the physics of separation and plastic flow processes. Attention is confined to fracture by cleavage in metal crystals, under both monotonic and cyclic loading conditions. The role of models at the dislocation size scale in bridging the gap between atomistic and continuum descriptions is highlighted.
TL;DR: A review of some of the key ideas that have been set forth in both the materials and biological setting and to speculate on future developments along these lines can be found in this article.
Abstract: Computation is one of the centerpieces of both the physical and biological sciences. A key thrust in computational science is the explicit mechanistic simulation of the spatiotemporal evolution of materials ranging from macromolecules to intermetallic alloys. However, our ability to simulate such systems is in the end always limited in both the spatial extent of the systems that are considered, as well as the duration of the time that can be simulated. As a result, a variety of efforts have been put forth that aim to finesse these challenges in both space and time through new techniques in which constraint is exploited to reduce the overall computational burden. The aim of this review is to describe in general terms some of the key ideas that have been set forth in both the materials and biological setting and to speculate on future developments along these lines. We begin by developing general ideas on the exploitation of constraint as a systematic tool for degree of freedom thinning. These ideas are then applied to case studies ranging from the plastic deformation of solids to the interactions of proteins and DNA.
TL;DR: In this paper, a semi-empirical quantum molecular dynamics simulation performed within the tight-binding model was used to investigate the formation and migration of native point defects and investigate their interaction and clustering phenomena.
Abstract: ▪ Abstract Vacancies and self-interstitial defects in silicon are here investigated by means of semi-empirical quantum molecular dynamics simulations performed within the tight-binding model. We extensively discuss the process of formation and migration of native point defects and investigate their interaction and clustering phenomena. The formation of larger stable structures is further studied by combining tight-binding and Monte Carlo simulations. Tight-binding simulation results provide a global picture for defect-induced microstructure evolution in bulk silicon. These results are consistent with state-of-the-art experimental data and elucidate many relevant atomic-scale mechanisms.
TL;DR: The Computational Materials Workshop on Physico-Computational Materials as discussed by the authors aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites at a number of length scales: atomic, molecular, nano, and continuum.
Abstract: Computational Materials aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites. This workshop, the second coordinated by NASA Langley, reports progress in measurements and modeling at a number of length scales: atomic, molecular, nano, and continuum. Assembled here are presentations on quantum calculations for force field development, molecular mechanics of interfaces, molecular weight effects on mechanical properties, molecular dynamics applied to poling of polymers for electrets, Monte Carlo simulation of aromatic thermoplastics, thermal pressure coefficients of liquids, ultrasonic elastic constants, group additivity predictions, bulk constitutive models, and viscoplasticity characterization.