A mixture of structural heterogeneity has been a promising way to design materials with excellent mechanical properties. Yet, the significance of how structural heterogeneity tunes the deformability and its associated deformation mechanisms is still not lucid. In this work, we dive into two types of metallic materials, namely nanotwinned metals and monoatomic Ta metallic glass, to address this issue. In nanotwinned metals, we survey a range of nanotwinned materials that possess different stacking fault energies (SFEs), and understand the TB strengthening limit. Distinct from Cu and Al, the nanotwinned, ultralow SEF materials (Co, NiCoCr, and NiCoCrFeMn) intriguingly exhibit a continuous strengthening down to a twin thickness of 0.63 nm. Examining dislocation slip mode and deformation microstructure, we find the hard dislocation modes persist even when reducing the twin boundary spacing to a nanometer regime. Meanwhile, the soft dislocation mode, which causes detwinning in Cu and Al, results in phase transformation and lamellar structure formation in Co, NiCoCr, and NiCoCrFeMn. In monoatomic Ta metallic glass, it is found that deformability is directly associated with inherent structural heterogeneity on the level of atomic order. We find the dispersive and sparse distribution of local order is associated with necking, yet percolation of medium-range order constrains the deformability and results in brittle failure. These findings shed new light on the role of structural heterogeneity in metallic materials, which has important implications for the design of nanoscale metallic materials with tunable mechanical properties.

An emerging class of heterogeneous nanostructured materials, including bimodal, gradient, hierarchical structures, has attracted increasing attention due to the extraordinary mechanical behaviors such as ultrahigh strength and better tensile ductility, when compared with their homogeneous counterparts. This suggests that the structural heterogeneity intentionally engineered into the materials is essential to promote hardening mechanisms and improve the uniform tensile strain. In this thesis, we focus on plastic deformation and its associated mechanisms in bimodal nanostructured metals. By varying the size of small grain in bimodal structure, we find the intragranular plastic deformation is enhanced because of activation and storage of extra dislocations. This dislocation-mediated forest hardening increases the material strength, alleviating the strength softening in the reverse Hall-Petch regime. These findings may be beneficial to designing heterogeneous structured metals with improved ductility-strength synergy.

This thesis focuses on understanding the role of moiré patterns formed between graphene and metal substrate in governing the interfacial frictional behavior. The frictional system consists of graphene supported on a bulk copper substrate, which is investigated by atomistic simulations. The thesis first discusses moiré patterns appearing between graphene and copper, whose morphology depends on crystallographic orientation and relative positions. Depending on system temperature and the contacting nature, two extreme friction phenomena, namely superlubricity and supersticky, have been found, both of which are mediated by moiré patterns. The superlubricity effect can be achieved by tuning the rotation angle of moiré patterns to high value. However, such a condition only happens in metastable states with high potential energy, which induces the graphene layer spontaneously incline to lower energy state with small rotation angles, causing the disappearance of superlubricity. It is found that introducing grain boundaries in graphene can stabilize the high-angle moiré patterns and therefore retain superlubricity. On the other hand, supersticky effect was found to occur at ultra-low temperatures, at which stable moiré pattern persists and raises the resistance to sliding. In the end, the thesis provides details on the developed mathematical models, which describe the rotation and translation process of hexagonal moiré patterns, simplifying the generation of moiré patterns due to graphene rotation and lateral sliding movement.

The bimodal structure has become a promising way to alleviate the famous strength and ductility trade-off in metals. For conventional nanocrystalline metals, strong strength softening follows after the Hall-Petch effect within the continuous decrease of grain size. In our study, we conducted molecular dynamics (MD) study and discovered that as the decrease of small grain size in bimodal nano-grained structures, the softening rate of the inverse Hall-Petch effect is suppressed. With the increasing number of small grains around the large grains, the plasticity of large grains is enhanced, and they also undergo less intergranular grain boundary sliding and migration leading to the increasing stress of large grains. The discovery of this process could be beneficial to designing bimodal nano-grained structures with desired ductility and strength.

Dislocations, the line defects in a crystal lattice, dictate the material strength and deformation behaviors. The emergence of multi-principal element alloys (MPEAs) introduces a vast compositional space and local chemical fluctuations, inevitably impacting dislocation behaviors. There are vital fundamental questions remain to be understood: (i) how or whether dislocations behave differently in MPEAs than in traditional alloys; (ii) to what extent the local chemical variations influence the dislocation motion and the underlying energy landscape; and (iii) how to explore the dislocation behaviors in the ample compositional space.

This thesis utilizes atomistic simulation techniques, theoretical models, and machine learning methods to address these questions and reveal dislocation motions in MPEAs. By sampling and reconstructing the potential energy landscape of screw dislocation, it shows the landscape has a hierarchical and multilevel structure, which exerts a trapping force and back stress on dislocation motion, consequently retarding dislocation movement. With the introduced chemical short-range order (SRO), the energy barriers for migration mechanisms of screw dislocation increase but to different extents, leading to the dominant mechanism drifting from kink-glide to kink-pair nucleation. Concerning edge dislocation, the effect of SRO shows a cross-over from strengthening to softening, driven by the faster decrease of barriers in system with SRO under applied stress. This is related to the larger activation volume in the presence of SRO and diffuse anti-phase boundary generation. Lastly, a neural network model is proposed to predict Peierls barrier in the vast compositional space with significant local chemical fluctuation. By incorporating two inputs-local atomic type and atomic displacement field, the model captures the chemistry and structure of dislocation, enabling efficient prediction of its barriers. In conclusion, this thesis provides valuable insights into the behavior of dislocations in MPEAs, shedding light on the influence of local chemical fluctuation, and offers an efficient approach to exploring dislocation behaviors in diverse compositional spaces.