Deep learning accelerated prediction of additive manufacturing solidification microstructures (deep-AM)

Description of the granted funding

The 3D printing of metals, or additive manufacturing (AM), is reshaping the product manufacturing in aerospace, energy, and healthcare industries. However, a lack of comprehensive understanding of the metal crystallization has limited the widespread adoption of AM. In collaboration with research group in USA, this project employs cutting-edge high-performance computing techniques, artificial intelligence via deep generative models, and advanced synchrotron X-ray laboratory experiments to illuminate, predict, and manage metal crystallization in AM. By unraveling the complexities of metal crystallization, this research is contributes to producing next-generation AM materials and components with fewer processing defects and faster production times. The insights gained will pave the way for future innovation, enabling manufacturers to harness AM for reliable use in novel metallic alloys.
Show more

Starting year

2026

End year

2028

Granted funding

Funder

Research Council of Finland

Funding instrument

Targeted Academy projects

Decision maker

Suomen akatemian muu päättäjä
16.12.2025

Other information

Funding decision number

373511

Fields of science

Physical sciences

Research fields

Tiiviin aineen fysiikka

Identified topics

3d printing