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Dynamic thermomechanical deformation map of FCC microparticles using additive micromanufacturing and machine learning

CORDIS · observation · Publication date unknown

Dynamic thermomechanical deformation map of FCC microparticles using additive micromanufacturing and machine learning The core aim of DyThM-FCC is to push the envelope of additive micro-manufacturing (AµM) and micromechanical testing under extreme conditions and identify a constitutive strengthening law by using machine learning (ML). A novel printing method, based on localized electrodeposition in a voxel-by-voxel manner, will be used to print metallic microparticles of Ni, Cu and Co. Subsequently, these microparticles will be subjected to thermal treatments to control the internal microstructure, i.e. change the dislocation content and grain size. These metallic microparticles will be tested under a combination of unprecedented strain rates (SR) up to 1000/s and temperatures from -150°C up to 600°C for assessing their suitability and reliability in extreme applications (e.g. sensors, where are subjected to high frequencies, or catalysis, where high temperatures can be expected). Depen

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recordType

award

status

CLOSED

region

EU

value

173847.36

unit

EUR