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000839055 005__ 20230213130114.0
000839055 0247_ $$2CORDIS$$aG:(EU-Grant)759419$$d759419
000839055 0247_ $$2CORDIS$$aG:(EU-Call)ERC-2017-STG$$dERC-2017-STG
000839055 0247_ $$2originalID$$acorda__h2020::759419
000839055 035__ $$aG:(EU-Grant)759419
000839055 150__ $$aA Multiscale Dislocation Language for Data-Driven Materials Science$$y2017-11-01 - 2023-10-31
000839055 371__ $$aCNRS - Institut des Sciences Biologiques$$bINSB$$dFrance$$ehttp://www.cnrs.fr/insb/$$vCORDIS
000839055 371__ $$aTECHNISCHE UNIVERSITAET BERGAKADEMIE FREIBERG$$bTU BAF$$dGermany$$ehttp://tu-freiberg.de$$vCORDIS
000839055 372__ $$aERC-2017-STG$$s2017-11-01$$t2023-10-31
000839055 450__ $$aMuDiLingo$$wd$$y2017-11-01 - 2023-10-31
000839055 5101_ $$0I:(DE-588b)5098525-5$$2CORDIS$$aEuropean Union
000839055 680__ $$aCrystalline defects in metals and semiconductors are responsible for a wide range of mechanical, optical and electronic properties. Controlling the evolution of dislocations, i.e. line-like defects and the carrier of plastic deformation, interacting both among themselves and with other microstructure elements allows tailoring material behaviors on the micro and nanoscale. This is essential for rational design approaches towards next generation materials with superior mechanical properties.

For nearly a century, materials scientists have been seeking to understand how dislocation systems evolve. In-situ microscopy now reveals complex dislocation networks in great detail. However, without a sufficiently versatile and general methodology for extracting, assembling and compressing dislocation-related information the analysis of such data often stays at the level of “looking at images” to identify mechanisms or structures. Simulations are increasingly capable of predicting the evolution of dislocations in full detail. Yet, direct comparison, automated analysis or even data transfer between small scale plasticity experiments and simulations is impossible, and a large amount of data cannot be reused.

The vision of MuDiLingo is to develop and establish for the first time a Unifying Multiscale Language of Dislocation Microstructures. Bearing analogy to audio data conversion into MP3, this description of dislocations uses statistical methods to determine data compression while preserving the relevant physics. It allows for a completely new type of high-throughput data mining and analysis, tailored to the specifics of dislocation systems. This revolutionary data-driven approach links models and experiments on different length scales thereby guaranteeing true interoperability of simulation and experiment. The application to technologically relevant materials will answer fundamental scientific questions and guide towards design of superior structural and functional materials.
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000839055 970__ $$aoai:dnet:corda__h2020::37419c71b3eb9d79f9562a5d8faeea14
000839055 980__ $$aG
000839055 980__ $$aCORDIS
000839055 980__ $$aAUTHORITY