Immiscibility was investigated in Group IV – Group V transition metal diboride pseudobinary systems (TiB2 – NbB2, TiB2 – TaB2, ZrB2 – NbB2, ZrB2 – TaB2, HfB2 – NbB2, and HfB2 – TaB2), revealing lamellar microstructures upon cooling from a laser-induced melt. Autocorrelation analysis of the microstructure length scales was used to validate that these microstructures showed characteristic length scales and self-similarity, indicating substantial immiscibility in the pseudobinary systems. These results indicate that substantial revisions are required for the pseudobinary phase diagrams of Group IV – Group V transition metal diborides available in the literature and explain several discrepancies between available thermochemical literature and reported microstructure results in these systems.
Shear-Coupled Grain Boundary Migration (SCGBM) plays an important role in the plastic deformation of FCC metals, particularly in nano-crystalline (NC) materials. However, the complex structural evolution, associated with disconnection-mediated migration, makes establishing atomic-scale structure-property correlations highly challenging. In this study, we employ a data-driven approach to characterize grain boundary (GB) structures and link them to the energy barrier associated with shear-coupled migration for Σ13(320)[001] and Σ13(05¯1)[100] tilt boundaries in FCC aluminum. We first simulated SCGBM using Molecular Statics (MS)-based shear deformation at 0 K, subsequently computing the minimum energy paths and activation barriers via the Nudged Elastic Band (NEB) method. While both boundaries exhibited a 〈110〉 mode of shear coupling, the Σ13(05¯1)[100] boundary demonstrated a higher energy barrier and a larger disconnection Burgers vector compared to the Σ13(320)[001] grain boundary. Furthermore, the associated stress drops and effective plastic strains obtained from these atomistic simulations agreed closely with predictions from a micromechanics-based continuum model. To characterize the 3D structural evolution of the GB configurations during SCGBM, we utilized Pair Correlation Functions (PCF) and Persistent Homology (PH). To handle the high-dimensional data structures inherent in these structural characterization methods, we applied Principal Component Analysis (PCA) for dimensionality reduction. The resulting principal component scores successfully captured disconnection nucleation and migration events, demonstrating a strong quantitative correlation with their corresponding energy barriers. Thus, the present study offers a novel integrated approach that can accelerate the atomic-scale structure-property correlation necessary for developing grain boundary engineering in nano-crystalline FCC materials.
