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Universal machine learning interatomic potentials (uMLIPs) deliver near \emph{ab initio} accuracy in energy and force calculations at a low computational cost, making them invaluable for materials modeling. Although uMLIPs are pretrained on vast \emph{ab initio} data sets, rigorous validation remains essential for their ongoing adoption. [...]

Despite the significant application potential of laser powder bed fusion (L-PBF) processed Ti-6Al-4V components, a detailed understanding of their deformation mechanisms remains limited. This study investigates the deformation behavior of the {α^\prime} and α phases in the as-built and heat-treated specimens, respectively, using in-situ high-energy X-ray diffraction (HEXRD) combined with crystal plasticity modeling. [...]