At the nanoscale, we calibrated the MEAM potential, derived from the Embedded Atom Method (EAM), using the EV and GSFE curves. We calculated the EV and GSFE curves with ab initio DFT simulations that we ran in QE. First, we downscaled (Step 1) the end-goal of modeling plastic behavior to the electronic scale, where we identified EV and GSFE curves as the quantities necessary to bridge information up (upscaling) to the nanoscale. In this work, we select pure Cr as our material of interest where we wish to model the plastic behavior at the structural scale. *Step 4: Validation at the higher length scale through experiment or simulation. Iteration is required to ensure a proper connection. *Step 3: Upscaling, where we pass information up to meet the requirements set at the higher length scale in step 1. *Step 2: Modeling and simulation at lower length scales (including calibration and verification) *Step 1: Downscaling, where we define the desired higher-level “effects,” or information needed. The fundamental steps required to achieve multiscale modeling with the ICME paradigm are as follows: Multiscale modeling with the ICME paradigm offers the accuracy required to predict failure, reduce design costs, and reduce time-to-market with the simulation-based design paradigm. Horstemeyer (Horstemeyer, 2018) proposed the ICME paradigm as a means to capture the multi-scale phenomenon of a material by bridging information between length scales from the electron scale to the structural (continuum) scale.
Keywords: Chromium (Cr), Modified Embedded Atom Method (MEAM), Density Functional Theory (DFT), Integrated Computational Materials Engineering (ICME), Generalized Stacking Fault Energy (GSFE), Molecular Dynamics (MD), Dislocation Dynamics (DD), Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), Multiscale Dislocation Dynamics Plasticity (MDDP)Īuthor(s): Cagle, M. Three sets of stress-strain curves were found from a single Frank-Read source in Multiscale Dislocation Dynamics Plasticity (MDDP) computations. Then, we generated position versus time plots for each simulation to calculate the dislocation velocity, dislocation mobility, and drag coefficient. The post-processing program OVITO was used to visualize the centrosymmetry parameter, thermal equilibrium, and track dislocation mobility. These calculations were run with three sets of MEAM parameters to find an upper and lower bound for our data.
The mobility is calculated from seven simulations at varying applied shear stresses from 250 MPa to 3000 MPa, or 2500 to 30000 bar, respectively. A convergence study is conducted on different sized crystal structures and dislocation mobility calculations with the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. Information is bridged from atomistics to the microscale by tracking dislocation mobility and quantifying the stress-strain behavior. These lower scale simulations are upscaled to Dislocation Dynamics (DD) computations.
Both sets of simulations were verified by comparison to values from literature, and a sensitivity analysis was conducted for the MEAM potential. The Modified Embedded Atom Method (MEAM) Parameter Calibration tool along with the DFT data was utilized to create a MEAM potential for Cr.
We used Density Functional Theory (DFT) in the open source software Quantum Espresso (QE) to generate energy versus volume (EV), energy versus atomic separation (EA), and generalized stacking fault energy (GSFE) curves along with the lattice parameter, bulk modulus, and cohesive energy at equilibrium. In this work, we apply multiscale modeling techniques associated with Integrated Computational Materials Engineering (ICME) in order to capture the plastic behavior of pure chromium (Cr). You can view and copy the source of this page: The action you have requested is limited to users in the group: Users.