UC San Diego

The defects of materials have a significant impact on their mechanical properties and deformation behavior. For example, defects can sabotage desired strength or ductility, but they can also strengthen the materials if the proper element and defects combination is selected. This thesis will discuss the impacts of various defects on the mechanical properties of structural materials ranging from intermetallic to elemental metals and multi-principal element alloys (MPEAs).First, in chapter 2, the impacts of defects on the brittleness of intermetallic were studied using density functional theory (DFT) calculations in the MoSi2 model system. The application of MoSi2 is limited by the oxygen embrittlement at temperatures of 400-600 °C. Our DFT calculations verified the fact the oxygen interstitials (Oint ) are the main detrimental defects for grain boundary intergranular fracture. We found that Zr substitution defects (ZrMo) reduce the embrittling effects of oxygen interstitials at MoSi2 grain boundaries by being a charge donor to oxygen. However, a more substantial effect is observed when Zr is present as a secondary getter nanoparticle phase. Oxygen interstitials have a strong thermodynamic driving force to migrate into the Zr subsurface at the Zr/MoSi2 interface, and the energy penalty for breaking the oxygen-contaminated Zr/MoSi2 interfaces are much higher than that of MoSi2 grain boundaries. Thus, the introduction of Zr into MoSi2 can mitigate the embrittling effect of oxygen on grain boundary fracture. In chapter 3, we further investigated the GBs effects of a broader class of materials. We constructed the largest DFT-computed GB database using the high-throughput workflow to overview GB energies distribution of different elemental systems. The database encompasses 327 GBs of 58 elemental metals, including ten typical twist and symmetric tilt GBs for bcc and fcc metals and Σ7(0001) for hcp metals. Using this large GB dataset, we develop an improved predictive model for the GB energy of different elements based on the cohesive energy and shear modulus. The open GB database would help guide the future design of polycrystalline materials Nevertheless, DFT calculations are too expensive for simulating large systems or the longtime dynamic evolution of materials under certain conditions. Classical molecular dynamics (MD) simulation is a good alternative for the dynamic evolution of materials if an accurate interatomic potential (IAP) is available. The recently developed machine learning interatomic potential (ML-IAP) for bcc MoNbTaW multi-principal element alloy (MPEA) facilitates MD simulations to achieve high accuracy with low computational cost. In chapter 4, we applied the ML-IAP to explore the performance of materials under heat treatment and tensile/compressive deformation. We found that differences in annealing temperatures introduced different degrees of local chemical short-range orders (SROs) in MPEA. The presence of SROs influences the corresponding stacking fault energy, critical resolved shear stress of dislocation, and therefore the strength and ductility of MPEA under the uniaxial tensile/compressive tests.