Integrated Computational Materials Engineering

Integrated Computational Materials Engineering (ICME) is an approach to design products, the materials that comprise them, and their associated materials processing methods by linking materials models at multiple length scales. Key words are "Integrated", involving integrating models at multiple length scales, and "Engineering", signifying industrial utility. The focus is on the materials, i.e. understanding how processes produce material structures, how those structures give rise to material properties, and how to select materials for a given application. The key links are process-structures-properties-performance (see G. Olson 2000). The National Academies report describes the need for using multiscale materials modeling (Horstemeyer 2009) to capture the process-structures-properties-performance of a material.

• Structural scale: Finite element, finite volume and finite difference partial differential equation are solvers used to simulate structural responses such as solid mechanics and transport phenomena at large (meters) scales.
  • process modeling/simulations: extrusion, rolling, sheet forming, stamping, casting, welding, etc.
  • product modeling/simulations: performance, impact, fatigue, corrosion, etc.
• Macroscale: constitutive (rheology) equations are used at the continuum level in solid mechanics and transport phenomena at millimeter scales.
• Mesoscale: continuum level formulations are used with discrete quantities at multiple micrometre scale. "Meso" is an ambiguous term that means "intermediate" so it has been used as representing different intermediate scales. In this context it can represent modeling from crystal plasticity for metals, Eshelby solutions for any materials, homogenization methods, and unit cell methods.
• Microscale: modeling techniques that represent the micrometre scale such as dislocation dynamics codes for metals and phase field models for multiphase materials. Phase field models of phase transitions and microstructure formation and evolution on nanometer to millimeter scales.
• Nanoscale: semi-empirical atomistic methods are used such as Lennard-Jones, Brenner potentials, embedded atom method (EAM) potentials, and modified embedded atom potentials (MEAM) in molecular dynamics (MD), molecular statics (MS), Monte Carlo (MC), and kinetic Monte Carlo (KMC) formulations.
• Electronic scale: Schroedinger equations are used in computational framework as density functional theory (DFT) models of electron orbitals and bonding on angstrom to nanometer scales.

There are some codes that operate on different length scales such as:

• CALPHAD computational thermodynamics for prediction of equilibrium phase diagrams and even non-equilibrium phases.
• Phase field codes for simulation of microstructure evolution
• Databases of processing parameters, microstructure features, and properties from which one can draw correlations at various length scales
• GeoDict virtual material laboratory