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Register a new userGenerating Periodic Grain Boundary Structures: Algorithm and Open-Source Python Library
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An algorithm implemented in an open-source python library was developed for building periodic coincidence site lattice (CSL) grain boundary models in a universal fashion. The software framework aims to generate tilt and twist grain boundaries from cubic and tetragonal crystals for ab-initio and classical atomistic simulation. This framework has two useful features: i) it can calculate all the CSL matrices for generating CSL from a given Sigma ({Sigma}) value and rotation axis, allowing the users to build the specific CSL and grain boundary models; ii) it provides a convenient command line tool to enable high-throughput generation of tilt and twist grain boundaries by assigning an input crystal structure, {Sigma} value, rotation axis, and grain boundary plane. The developed algorithm in the open-source python library is expected to facilitate studies of grain boundary in materials science. The software framework is available on the website: aimsgb.org.
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A detailed theoretical and numerical investigation of the infinitesimal single-crystal gradient plasticity and grain-boundary theory of Gurtin (2008) A theory of grain boundaries that accounts automatically for grain misorientation and grain-boundary orientation. Journal of the Mechanics and Physics of Solids 56 (2), 640-662, is performed. The governing equations and flow laws are recast in variational form. The associated incremental problem is formulated in minimization form and provides the basis for the subsequent finite element formulation. Various choices of the kinematic measure used to characterize the ability of the grain boundary to impede the flow of dislocations are compared. An alternative measure is also suggested. A series of three-dimensional numerical examples serve to elucidate the theory.
While it is known that alloy components can segregate to grain boundaries (GBs), and that the atomic mobility in GBs greatly exceeds the atomic mobility in the lattice, little is known about the effect of GB segregation on GB diffusion. Atomistic computer simulations offer a means of gaining insights into the segregation-diffusion relationship by computing the GB diffusion coefficients of the alloy components as a function of their segregated amounts. In such simulations, thermodynamically equilibrium GB segregation is prepared by a semi-grand canonical Monte Carlo method, followed by calculation of the diffusion coefficients of all alloy components by molecular dynamics. As a demonstration, the proposed methodology is applied to a GB is the Cu-Ag system. The GB diffusivities obtained exhibit non-trivial composition dependencies that can be explained by site blocking, site competition, and the onset of GB disordering due to the premelting effect.
Mg grain boundary (GB) segregation and GB diffusion can impact the processing and properties of Al-Mg alloys. Yet, Mg GB diffusion in Al has not been measured experimentally or predicted by simulations. We apply atomistic computer simulations to predict the amount and the free energy of Mg GB segregation, and the impact of segregation on GB diffusion of both alloy components. At low temperatures, Mg atoms segregated to a tilt GB form clusters with highly anisotropic shapes. Mg diffuses in Al GBs slower than Al itself, and both components diffuse slowly in comparison with Al GB self-diffusion. Thus, Mg segregation significantly reduces the rate of mass transport along GBs in Al-Mg alloys. The reduced atomic mobility can be responsible for the improved stability of the microstructure at elevated temperatures.
The PyProcar Python package plots the band structure and the Fermi surface as a function of site and/or s,p,d,f - projected wavefunctions obtained for each $k$-point in the Brillouin zone and band in an electronic structure calculation. This can be performed on top of any electronic structure code, as long as the band and projection information is written in the PROCAR format, as done by the VASP and ABINIT codes. PyProcar can be easily modified to read other formats as well. This package is particularly suitable for understanding atomic effects into the band structure, Fermi surface, spin texture, etc. PyProcar can be conveniently used in a command line mode, where each one of the parameters define a plot property. In the case of Fermi-surfaces, the package is able to plot the surface with colors depending on other properties such as the electron velocity or spin projection. The mesh used to calculate the property does not need to be the same as the one used to obtain the Fermi surface. A file with a specific property evaluated for each $k$-point in a $k-$mesh and for each band can be used to project other properties such as electron-phonon mean path, Fermi velocity, electron effective mass, etc. Another existing feature refers to the band unfolding of supercell calculations into predefined unit cells.
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