Filiatraut, A. N.; Mianroodi, J. R.; Hamidi Siboni, N.; Zanjani, M. B.: Predicting micro/nanoscale colloidal interactions through local neighborhood graph neural networks. Journal of Applied Physics 134 (23), 234702 (2023)
Khorrami, M. S.; Mianroodi, J. R.; Svendsen, B.: Finite-deformation phase-field microelasticity with application to dislocation core and reaction modeling in fcc crystals. Journal of the Mechanics and Physics of Solids 164, 104897 (2022)
Rezaei, S.; Mianroodi, J. R.; Brepols, T.; Reese, S.: Direction-dependent fracture in solids: Atomistically calibrated phase-field and cohesive zone model. Journal of the Mechanics and Physics of Solids 147, 104253 (2021)
Mianroodi, J. R.; Svendsen, B.: Effect of Twin Boundary Motion and Dislocation-Twin Interaction on Mechanical Behavior in Fcc Metals. Materials 13 (10), 2238 (2020)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.