Project description

In this research project mathematical methods will be developed to characterize precisely and comprehensively the complex microstructure of nanoporous metals. Based on such characterization, on the one hand machine learn-ing will be used to classify nanoporous metals with regard to their microstructure, which will allow quantitative statements how different production processes affect the microstructure and thus the physical properties of nanopo-rous metals. On the other hand, a new approach will be developed that combines the finite element method with machine learning in order to enable substantially acceler-ated micromechanical simulations of nanoporous metals.

The scientific objective of this project is to develop ad-vanced computational methods that can help to unravel the relation between processing, microstructure and me-chanical properties in nanoporous metals. These methods can be used in other projects of the SFB 986, in particular in the projects B2 and B4, to better understand and optimize the favorable properties of nanoporous metals.

Project leader
Prof. Dr.-Ing. Christian J. Cyron,






machine learning


... in progress


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