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.
• Databases of processing parameters, microstructure features, and properties from which one can draw correlations at various length scales

Integrating models

Model integration takes several forms, including the following:

• Small scale models calculate material properties, or relationships between properties and parameters, e.g. yield strength vs. temperature, for use in continuum models
• CALPHAD computational thermodynamics software predicts free energy as a function of composition; a phase field model then uses this to predict structure formation and development, which one may then correlate with properties.
• Process models calculate spatial distribution of structure features, e.g. fiber density and orientation in a composite material; small-scale models then calculate relationships between structure and properties, for use in a continuum models of overall part or system behavior
• Large scale models explicitly fully couple with small scale models, e.g. a fracture simulation might integrate a continuum solid mechanics model of macroscopic deformation with an FD model of atomic motions at the crack tip
• Suites of models (large-scale, small-scale, atomic-scale, process-structure, structure-properties, etc.) can be hierarchically integrated into a systems design framework to enable the computational design of entirely new materials. A commercial leader in the use of ICME in computational materials design is QuesTek Innovations LLC, a small business in Evanston, IL co-founded by Prof. Greg Olson of Northwestern University. QuesTek's high-performance Ferrium® steels were designed and developed using ICME methodologies.

See also

• Materials informatics
• ICME cyberinfrastructure
• Cyberinfrastructure

References

• JOM November 2006 issue focused on ICME
• Committee on Integrated Computational Materials Engineering, National Research Council, Integrated Computational Materials Engineering: A Transformational Discipline for Improved Competitiveness and National Security, National Academies Press, 2008. ISBN 0309119995, NAP Link
• G. Olson, Designing a New Material Word, Science, Vol. 288, May 12, 2000
• Horstemeyer 2009: Horstemeyer M.F., "Multiscale Modeling: A Review," Practical Aspects of Computational Chemistry, ed. J. Leszczynski and M.K. Shukla, Springer Science+Business Media, pp. 87-135, 2009

External links

• ICME section of Materials Technology @ TMS
• Cyberinfrastructure for ICME at Mississippi State University