Curtin, WilliamHu, Yi2021-12-092021-12-092021-12-09202110.5075/epfl-thesis-8723https://infoscience.epfl.ch/handle/20.500.14299/183769Precipitation strengthening is one of the key strengthening strategies in many industrial alloys like aluminum alloys, nickel-based superalloys, etc. The yield strength of alloy is improved by forming precipitates in materials and employing them as obstacles for dislocation movement. In this study, we calibrate Discrete Dislocation Dynamics (DDD) to include one of the essential atomistic information, dislocation core energy, to make quantitative strength predictions. Then we attempt to predict peak-aged strength of Al--Mg--Si alloys using experimental characterizations and via modeling the Orowan mechanism in DDD. Extensive mesoscale studies show that matrix misfit stress has small effects on Critical Resolved Shear Stress (CRSS). In contrast, CRSS depends largely on the precipitate edge-to-edge spacing and the dislocation core energy within 5.4 b. However, with the most faithful mesoscale simulation, the alloy tensile yield strength is overestimated by about 33%. Detailed analysis of forces on precipitates shows that multiple precipitates are sheared prior to be looped. Then atomistic simulations using the near-chemically-accurate Al--Mg--Si Neural Network Potential are performed to investigate dislocation-precipitate interactions. Results show that a given precipitate can show shearing or looping depending on the relative orientation of the precipitate and dislocation, as influenced by the precipitate internal misfit stresses, direction-dependence of precipitate shearing energies, and dislocation line tension. Analytic models for shearing and calibrated discrete dislocation models of looping can accurately capture the trends and magnitudes of strengthening in most cases. Reasonable quantitative agreement with experiments is then achieved by using the theories together with the more-accurate first-principles material properties. The combination of theories and simulations demonstrated here constitutes a quantitative path for understanding and predicting the role of chemistry and microstructure on alloy strength that can be applied in many different alloys.endislocation core energynon-singular theoryDiscrete Dislocation Dynamicsprecipitation strengtheningOrowan mechanismshearing mechanismatomistis simulationNeural Network Potentialyield strength predictionthesis::doctoral thesis