High-Temperature Cast Aluminum for Efficient EnginesPublic Deposited
Accurate thermodynamic databases are the foundation of predictive microstructure and property models. An initial assessment of the commercially available Thermo-Calc TCAL2 database and the proprietary aluminum database of QuesTek demonstrated a large degree of deviation with respect to equilibrium precipitate phase prediction in the compositional region of interest when compared to 3-D atom probe tomography (3DAPT) and transmission electron microscopy (TEM) experimental results. New compositional measurements of the Q-phase (Al-Cu-Mg-Si phase) led to a remodeling of the Q-phase thermodynamic description in the CALPHAD databases which has produced significant improvements in the phase prediction capabilities of the thermodynamic model. Due to the unique morphologies of strengthening precipitate phases commonly utilized in high-strength cast aluminum alloys, the development of new microstructural evolution models to describe both rod and plate particle growth was critical for accurate mechanistic strength models which rely heavily on precipitate size and shape. Particle size measurements through both 3DAPT and TEM experiments were used in conjunction with literature results of many alloy compositions to develop a physical growth model for the independent prediction of rod radii and rod length evolution. In addition a machine learning (ML) model was developed for the independent prediction of plate thickness and plate diameter evolution as a function of alloy composition, aging temperature, and aging time. The developed models are then compared with physical growth laws developed for spheres and modified for ellipsoidal morphology effects. Analysis of the effect of particle morphology on strength enhancement has been undertaken by modification of the Orowan-Ashby equation for ⟨110⟩α-Al oriented finite rods in addition to an appropriate version for similarly oriented plates. A mechanistic strengthening model was developed for cast aluminum alloys containing both rod and plate-like precipitates. The model accurately accounts for the temperature dependence of particle nucleation and growth, solid solution strengthening, Si eutectic strength, and base aluminum yield strength. Strengthening model predictions of tensile yield strength are in excellent agreement with experimental observations over a wide range of aluminum alloy systems, aging temperatures, and test conditions. The developed models enable the prediction of the required particle morphology and volume fraction necessary to achieve target property goals in the design of future aluminum alloys. The effect of partitioning elements to the Q-phase was also considered for the potential to control the nucleation rate, reduce coarsening, and control the evolution of particle morphology. Elements were selected based on density functional theory (DFT) calculations showing the prevalence of certain elements to partition to the Q-phase. 3DAPT experiments were performed on Q-phase containing wrought alloys with these additions and show segregation of certain elements to the Q-phase with relative agreement to DFT predictions.