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Computational Material Design

From empirical material descriptions to computational material design: Our computational “toolkit” links traditionally separated research “silos” into one virtual laboratory.

Simulation tool kit

The predictive simulation-based optimisation of advanced materials represents a central challenge within simulation technology. Besides applications in the classical fields of engineering, the trend for miniaturisation of everyday-objects leads to the demand for highly sophisticated new materials also within the disciplines of computer science or chemical and bio-engineering.

As a result, advanced simulation technology is facing the ever-growing need to provide a “toolbox” that allows the development of “tailor-made molecules and materials” through the optimisation of material behaviour predicted in large-scale simulations of processes in engineering and natural science processes.

Linking traditionally separated disciplines

The toolkit,  by linking

  • quantum mechanical,
  • discrete, and
  • continuum modeling

serves as the foundation for holistic concepts of computational material design of both  hard and soft matter.

Our ultimate vision is to construct knowledge-based virtual test laboratories, which will allow us to optimize the microstructure of materials at the atomic, microscopic or mesoscopic scale. Using numerical simulations, we will be able to control and optimize the overall response of newly designed hybrid material systems.

Below, we briefly discuss the four key elements that make up our vision of advancing from empirical material description to computational material design.

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Physical phenomena at different scales
The physical phenomena governing the overall behaviour of materials appear on a wide range of length and time scales. Therefore, the necessary starting point for multiscale material modeling is understanding the multifield phenomena at each of these scales, such as:

  • atomic void clustering,
  • dislocation nucleation,
  • phase transitions, polymer network redistributions, and
  • crack propagation.

Computational tools at the individual scales
We develop computational tools applicable to the different length and time scales. These tools range from

  • density functional theory-based methods for electronic structure calculations, to
  • molecular dynamics-based methods for atomistic simulations, and
  • to finite element-based methods for macroscopic continuum computations.

Research Areas A, B, E, F

Linking of methods through scale bridging
Understanding the overall behavior of materials requires understanding the interplay of phenomena at different scales. This challenging task is accomplished through a variety of scale bridging methods. Our integrative toolkit and the application of fundamental concepts of multiscale material modelling let us couple spatial and temporal information on various physical phenomena.

Top-down and bottom-up approaches
Whereas engineers tend to incorporate information from smaller scales into their continuum scale simulations (top-down approach), chemists and physicists do the reverse (bottom-up approach).

 Collaboration between SimTech experts from these traditionally siloed disciplines plays a critical part as we work to achieve our goals of combining these approaches and bridging all time and length scales.

Research Areas A, B, F

 

Changes in material properties
With the integrated toolkit, it is now possible not only to predict the behavior of existing materials from their microstructure, but we can also test the behaviour of new materials on virtual microstructures at atomic, microscopic or mesoscopic scales.

Virtual testing
The construction of such “virtual test laboratories” allows virtual experiments with entirely new materials and molecules. Advanced functional materials with unprecedented properties can then be identified by a systematic exploration of microstructure modifications e.g. for multi-field problems involving thermo-electro-chemo-mechanical coupling effects spanning a multi-scale cascade of length and time scales.

Research Areas A, B, E, F

The vision: designer materials
The last step required to implement our vision of computational material design is optimizing the desired properties and functionalities of a material’s microstructure. Solving this reverse problem in a virtual test laboratory and thanks to a continually growing knowledge base will finally let us design new “tailor-made molecules and materials.”

Material systems design: the ultimate goal
At that point, we envision being able to both control and optimize the overall response of newly designed hybrid material systems. Our Excellence Cluster thus will contribute meaningfully to the promising future of integrative material systems design.

Research Areas A, B, D, E