Computational Materials

 Simulate Today, Innovate Tomorrow: 

The Future of Materials Science

- Materials Computation and Informatics

Materials science is a critical element in the development of new products. The discipline lies at the intersection of engineering, physics, and chemistry and is crucial for advancing product design and manufacturing.

Computational materials science and engineering uses modeling, simulation, theory and informatics to understand materials. Key objectives include discovering new materials, determining material behavior and mechanisms, interpreting experiments, and exploring materials theory. It is similar to computational chemistry and computational biology as an increasingly important subfield of materials science. 

Computational modeling supports materials discovery, development, and fabrication of various material systems. Physical simulations reveal material behavior at every length scale, from electronics to microstructures to engineered systems. 

As data science and machine learning methods advance, we apply them to extract knowledge from rich and complex datasets.

- Computational Materials Science

Computational materials science is one of the most rapidly developing and exciting fields in materials science because of the revolutionary advances that have been made in computer processing speed and memory capacity.

Just as materials science encompasses all length scales from electronics to components, so does its computational subdiscipline. While many methods and variants have been and continue to be developed, the following seven main simulation techniques or themes have emerged: electronic structure, density functional theory, atomistic methods, molecular dynamics, Kinetic Monte Carlo, mesoscale methods, dislocation dynamics.

These computer simulation methods use underlying models and approximations to understand material behavior in more complex scenarios than pure theory typically allows, and with greater detail and precision than experimentation typically provides. 

Each method can be used independently to predict material properties and mechanisms, to inform other simulation methods run individually or concurrently, or to compare or contrast directly with experimental results.

Please refer to Wikipedia: Computational Materials Science for more details.

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- Integrated Computational Materials Engineering (ICME)

A notable subfield of computational materials science is Integrated Computational Materials Engineering (ICME), which seeks to combine computational results and methods with experimentation, with an emphasis on industrial and commercial applications. 

Major current themes in the field include uncertainty quantification and propagation throughout simulations for eventual decision making, data infrastructure for sharing simulation inputs and results, high-throughput materials design and discovery, and new approaches given significant increases in computing power and the continuing history of supercomputing.

- Computational Materials Engineering

Computational materials engineering is an advanced introduction to computer-aided modeling of fundamental material properties and behavior, including physical, thermal, and chemical parameters, and the mathematical tools used to perform simulations. Its focus will be on crystalline materials, which includes all metals. 

The foundations of computational materials engineering allow scientists and engineers to create virtual simulations of material behavior and properties to better understand how specific materials work and perform, and then use this knowledge to design improvements for specific material applications.

[More to come ...]