SOURCE-LINKED INTELLIGENCE
A radically new approach to laser additively manufacture metals with periodic coarse-fine grain structures for breaking the strength-ductility trade-off
cation of PLMs; 2) Microstructural tailoring and anisotropic tensile evaluation; 3) Characterization of the strengthening and toughening mechanisms; 4) Prediction of anisotropic tensile properties by machine learning. This project aims to evolve the current in-situ alloying strategy employed during SLM, enable the tailoring of heterogeneous microstructures, and provide an excellent strength-ductility balance over the homogeneous-grained counterparts. It is expected that the new knowledge generated from this project will facilitate the 3D printing of high-performance metals. This proposal involves both the transfer of knowledge to the host institution and the training of the candidate in new advanced techniques. The expected results have the potential capacity to increase the competitiveness and provide room for further studies at both the fundamental and applied levels in additive manufacturing. selective laser melting, periodic lamellar metals, heterogeneous microstructures, anisotropic tensile properties, strength-ductility synergy, machine learning
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 268568.64
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T03:21:21.440Z. This is not the publication date.