Aluminum (Al) alloys exhibit exceptional mechanical properties, seeing widespread use in various industrial fields. Here, we use a multiscale simulation method combining phase field method, dislocation dynamics, and crystal plasticity finite element method to reveal the evolution law of precipitates, the interaction mechanism between dislocations and precipitates, and the grain-level creep deformation mechanism in 7A09 Al alloy under creep loading. The phase field method indicates that Al alloys tend to form fewer but larger precipitates during the creep process, under the dominant effect of stress-assisted Ostwald ripening. The dynamic equilibrium process of precipitate is not only controlled by classical diffusion mechanisms, but also closely related to the local strain field induced by dislocations and the elastic interaction between precipitates. Dislocation dynamics simulations indicate that the appearance of multiple dislocation loops around the precipitate during the creep process is the main dislocation creep deformation mechanism. A crystal plasticity finite element model is established based on experimental characterization to investigate the macroscopic creep mechanism. The dislocation climb is hindered by grain boundaries during creep, and high-density dislocation bands are formed around specific grains, promoting non-uniform plastic strain and leading to strong strain gradients. This work provides fundamental insights into understanding creep behavior and deformation mechanism of Al alloy for deep-sea environments.

The outstanding mechanical properties of nickel-based alloys are predominantly governed by the characteristics of their nano-precipitation. Traditional optimization approaches, however, have focused almost exclusively on average precipitation size, neglecting the non-uniform size distribution induced by the temperature gradient during the actual preparation process. This oversight leads to inaccurate optimization parameters, hindering the reliable design and broader engineering application of these alloys. This study investigates the coupling effect of average size and deviation on the mechanical behavior of nickel-based superalloys by experiment and simulation. The characterization of prepared nickel-based alloys confirms the spatial non-uniform distribution of the precipitation size and calibrates dislocation dynamics (DD) simulation inputs. When the precipitation size exhibits no deviation, conventional strengthening models align with simulation results, confirming the accuracy of the simulations. Under high size deviation, however, significant discrepancies arise between traditional models and simulation outcomes, indicating that conventional models fail to account for the effect of size deviation. This is because size deviation leads to spatial heterogeneity in precipitate distribution, which is difficult to describe using a unified theoretical framework. Machine learning (ML)-augmented analysis of the extensive DD dataset reveals a previously unrecognized synergistic effect governed by precipitation size heterogeneity. Surprisingly, contrary to the conventional preference for a uniform size distribution, we find that an appropriate size deviation increases the number of precipitates that effectively pin dislocations in three-dimensional space, thereby enhancing strength at a constant volume fraction. Our combined experimentally calibrated DD/ML approach identifies an optimal range of size variation that maximizes strengthening potential. These results provide a new strategy and an effective pathway for performance optimization of nickel-based alloys.