This NSF Engineering program (CFDA 47.041) grant award to Rutgers, The State University in the amount of $359,990 provides funding for a collaborative research project on metal additive manufacturing (AM) processes. The key objectives are to establish a physics-informed machine learning (PIML) framework to enable accurate prediction of fatigue life and scattering behavior in LPBF-printed metal components, and develop strategies to mitigate the fatigue scattering issue. The project will involve fabricating baseline fatigue test samples, characterizing material properties and defects, and conducting extensive fatigue testing to generate data to train the PIML models. The resulting knowledge and modeling capabilities are expected to advance the state of metal AM by providing an enabling predictive tool for fatigue life and quality, facilitating the printing of consistent high-quality components. The award period is from Sep 1, 2024 to Aug 31, 2027. No sub-awards are planned under this grant.