A recently introduced hybrid Potts-phase field method has demonstrated the ability to evolve microstructures in conjunction with compositional fields tied to different phases. In this approach, Monte Carlo Potts methods are used to evolve the microstructure while phase field methods are used to evolve the composition, and the two fields are coupled through free energy functionals. Recent developments of the model allow different multi-component alloy systems to be simulated by using thermodynamic databases and kinetic quantities to dictate the behavior. An example of the method using the aluminum-silicon binary system is demonstrated.

An optimization technique is coupled with crystal plasticity based finite element (CPFE) computations to aid the microstructural design of a wrought magnesium alloy for improved strength and ductility. The initial microstructure consists of a collection of sub-micron sized grains containing deformation twins. The variables used in the simulations are crystallographic texture, and twin spacing within the grains. It is assumed that plastic deformation occurs mainly by dislocation slip on two sets of slip systems classified as hard and soft modes. The hard modes are those slip systems that are inclined to the twin planes and the soft mode consists of dislocation glide along the twin plane. The CPFE code calculates the stress-strain response of the microstructure as a function of the microstructural parameters and the length-scale of the features. A failure criterion based on a critical shear strain and a critical hydrostatic stress is used to define ductility. The optimization is based on the sequential generation of an initial population defined by the texture and twin spacing variables. The CPFE code and the optimizer are coupled in parallel so that new generations are created and analyzed dynamically. In each successive generation, microstructures that satisfy at least 90% of the mean strength and mean ductility in the current generation are retained. Multiple generation runs based on the above procedure are carried out in order to obtain maximum strength-ductility combinations. The implications of the computations for the design of a wrought magnesium alloy are discussed. Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy.

The birefringence of a cellulose triacetate (CTA) polymer film was evaluated based on density functional theory and molecular dynamics (MD) simulation. The polarizability of the monomer unit of CTA was initially calculated to determine the intrinsic properties of the birefringence of CTA. The most important conformational freedom of the CTA monomer unit is derived from the C-6 acetyl methyl groups. This exocyclic group is known to have three low energy conformers referred to as gg, gt, and tg according to the rotation of the different torsion angles. Because the polarizability can be viewed as dependent on the conformation of CTA, the polarizability of these three conformers was evaluated. The results demonstrated that negative intrinsic birefringence was associated with the CTA repeating units having gg or gt structures, whereas the monomer units with tg structures were characterized by positive intrinsic birefringence. A model of the polymer film was constructed based on MD simulation and the birefringence of the model was evaluated using the calculated monomer birefringence values. The birefringence of the CTA film was found to be negative because most of the CTA repeating units adopt the gg conformation in the film. The negative value of the simulated birefringence is in good agreement with the result obtained by the experiment.

Within an inverse design approach applied to a nitrogen-fixation catalyst we discuss options for calculating “jacket” potentials that fulfill a purpose-oriented target requirement. As a target requirement we choose the vanishing geometric gradients on all atoms of a subsystem consisting of a metal center binding the small molecule to be activated - in our case dinitrogen. The additional potential can be represented within a full quantum model or by a sequence of approximations of which a field of electrostatic point charges is the simplest. In order to analyze the feasibility of this approach, we dissect a known dinitrogen-fixating complex and analyze its ligand environment expressed by the “jacket” potential. It is discussed how this ligand-bypotential replacement can be generalized for future applications that eventually allow us to find a competitive synthetic nitrogen-fixation transition metal complex. It can be expected that such a ligand-by-potential replacement approach will be applicable to any type of host-guest chemical process.

A necessary prerequisite for a successful theory-guided up-scale design of materials with application-driven elastic properties is the availability of reliable homogenization techniques. We report on a new software tool that enables us to probe and analyze scale-bridging structure-property relations in the elasticity of materials. The newly developed application, referred to as SC-EMA (Self-consistent Calculations of Elasticity of Multi-phase Aggregates) computes integral elastic response of randomly textured polycrystals. The application employs a Python modular library that uses single-crystalline elastic constants Cij as input parameters and calculates macroscopic elastic moduli (bulk, shear, and Young's) and Poisson ratio of both single-phase and multi-phase aggregates. Crystallites forming the aggregate can be of cubic, tetragonal, hexagonal, orthorhombic, or trigonal symmetry. For cubic polycrystals the method matches the Hershey homogenization scheme. In case of multi-phase polycrystalline composites, the shear moduli are computed as a function of volumetric fractions of phases present in aggregates. Elastic moduli calculated using the analytical self-consistent method are computed together with their bounds as determined by Reuss, Voigt and Hashin-Shtrikman homogenization schemes. The library can be used as (i) a toolkit for a forward prediction of macroscopic elastic properties based on known single-crystalline elastic characteristics, (ii) a sensitivity analysis of macro-scale output parameters as function of input parameters, and, in principle, also for (iii) an inverse materials-design search for unknown phases and/or their volumetric ratios.

The formation of realistic, polycrystalline microstructures can be simulated by modeling the kinetics of nucleation and growth. However, it is difficult to perform the inverse simulation, where details of the nucleation and growth process are inferred from geometric properties of the final microstructure. In the present study, we develop a methodology for solving the inverse problem for interface-limited growth in 1D, utilizing a reverse Monte Carlo (RMC) algorithm. The algorithm produces a time dependent nucleation rate that gives a grain size distribution closest to a target distribution. Its results may be used to understand the limitations of manipulating the grain boundary distributions through temperature alone.

We use data over an extended Q range from 0.01 to 100Å-1 from the recently commissioned NIMROD instrument at the ISIS pulsed neutron source to develop a multi-scale inverse modeling procedure which will provide insight in to the phase transformations of polymer systems. The first level of our procedure is atomistic and we use internal coordinates (bond length, bond angles and torsion angles) to define the polymer chain in full atomistic detail. Values were assigned to each internal coordinate within the chain using a stochastic Monte Carlo method in which the probabilities were drawn from distributions representing the possible range of values. Using this approach, random chain configurations could be rapidly built and the intrachain structure factor calculated utilizing a small set of parameters and compared with the experimental function. Parameters representing the probability distribution functions were systematically varied using a grid search to find the values which gave the best fit to the structure factor for Q > 3Å-1 in order to determine the details of the chain conformation in the molten phase. This process was repeated for data over the same extended Q range obtained at lower temperatures where the polymer was expected to crystallize. Polymers crystallize via chainfolded thin lamellae crystals. Such crystals give rise to an intense peak at Q ∼ 0.03Å-1. This scattering can be calculated using a lamellar stack model, coarse-grained from the single chain structure. We describe this approach using data obtained on the crystallization from the melt phase of perdeuterated polymers. The objective here is to follow the three key length scales; the chain folded lamellar thickness of ∼ 10nm, the crystal unit cell ∼ 1nm and the detail of the chain conformation is ∼ 0.1nm.

Deposition of semiconductor films is a key process for production of thin-film solar cells, such as CdTe or CIGS cells. In order to optimize photovoltaic properties of the film a comprehensive model of the deposition process should be build, which can relate deposition conditions and film properties. We have developed a multiscale model of deposition of CdTe film in close space sublimation (CSS) process. The model is based on kinetic Monte Carlo method on the rigid lattice, in which each site can be occupied by either Cd or Te atom. The model tabulates the energy of the site as a function of its local environment. These energies were obtained from first-principles calculates and then approximated with analytical formulas. Based on determined energies of each site we performed exchange (diffusion) processes using Metropolis algorithm. In addition the model included adsorption and desorption processes of Cd and Te2 species. The results of the model show that a steady-state structure of the surface layer is formed during film growth. The model can reproduce transition from film deposition to film etching depending on external conditions. Moreover, the model can predict deposition rates for non-stoichiometric gas compositions.