Materials
Modeling and simulation for Materials include the development of systematic approaches, based on sound theoretical models that integrate across many length and time scales, to understand materials properties and provide a foundation for the design of materials with specified properties. This domain includes computation for physical and chemical impacts on material properties as well as first-principle predictions of material behavior.
- Computational materials science is concerned with modeling and simulation of the macroscopic constitutive behaviors of materials by incorporating the influences of microstructure and processing parameters.
- Modeling tools are used to better understand material behavior.
- Materials informatics seeks to ascertain how materials properties vary with structure by employing theory, experimental data, calculated data, and statistical and pattern-analysis techniques.
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Integration of materials informatics with computational materials modeling and simulation provides
- structure, function, and dynamics of multifunctional materials
- comparative analysis of large-scale molecular simulation
- multiscale modeling of materials response to link materials behavior across scales.
- Materials property-composition modeling uses statistical methods combined with subject matter knowledge to develop and validate empirical and semi-empirical models for materials properties as functions of composition and other variables such as temperature. This approach is especially valuable when property-composition relationships are more complicated than can be adequately predicted by theoretical or mechanistic models, such as for nuclear waste forms.
- Monte Carlo simulation applied to models provides for propagating model uncertainty as well as uncertainties in composition or other model variables.