Computational design of advanced engineering materials
Recent advances in technology, among others the development of 3-D printing, opened the possibilities for synthetizing nearly any conceivable material. In order to efficiently explore these new possibilities, the rules are needed for designing materials with required mechanical (strength), thermal and electrical (conductivity) properties aa well as the specific chemical and biological characteristics (corrosion resistance, interactions with living cells). Fundamentally, such design rules are based on the understanding of the processes taking place in solids under the applied loads, which in turn depend on their chemical composition and on their structure, as defined by underlying type of the arrangements of the atoms (crystal-like, amorphous) and the specific point-like (e.g. vacancies), linear (e.g. dislocations), planar (e.g. grain boundaries) and volumetric deviations from these, termed as the defects.
It has been a great achievement of the modern materials science to show that there are properties of the engineering materials, which are governed by the atom-to-atom interactions (e.g. elastic modulus), by the arrangement of the atoms (e.g. elastic anisotropy) and by various deviations from the underlying pattern, (e.g. conductivity, plasticity, etc.). The respective relationships between the given type of the defects and the properties of interest are qualitatively quite well explained by the solid-state physics, mechanics and chemistry. The challenge is, however, to quantify these relationships, and in such a way that they can be used for predicting, and thus designing, materials of the desired functionalities. Because of the multi-length scale complexity of the modern engineering material this challenge can be efficiently addressed only by adopting a computational modelling approach.
In this context one should acknowledge that over the recent years a major progress has been made in the numerical methods for predicting the properties of the engineering materials. The methods are available for modelling the properties determined by arrangement of atoms in relatively small representative unit volume, – e.g. DFT calculations – and in large assemblies – e.g. molecular dynamics, MD, computations. The models have been also developed for explaining the properties of materials, structure of which can be defined only using relatively large representative unit volumes –e.g. finite element method combined with DFT and molecular dynamics.
The lecture provides examples of the application of the above-mentioned methods to modelling, predicting and optimizing (thus for designing) advanced engineering materials.
These examples include design of so called nano-materials, structure of which is controlled at the length scale below 100 nm. The examples given concern mechanical strength, thermal properties, thermal stability, diffusivity and conductivity of nano-metals and nano-composites, also with graphene. The results of the modelling are validated with the experimental results. Based on the results of modelling the rules of optimising/design of nano-materials are proposed.
Prof K.J. Kurzydlowski
Warsaw University of Technology
Materials Science and Engineering
Materials Design Group