StructRDM: Prototype-Anchored Residual Diffusion for Titanium Alloy Microstructure Generation

Titanium alloy microstructures are jointly influenced by alloy composition, processing parameters and mechanical properties. In limited-data regimes, however, these low-dimensional conditions underdetermine the spatial arrangement of phase regions and the geometry of phase boundaries in high-dimensional microstructure images, making end-to-end conditional generation prone to fragmented phase regions and unstable boundaries. To address these issues, we propose StructRDM, a reliability-aware, prototype-anchored residual diffusion framework. StructRDM follows a “structure first, texture second” strategy. It first predicts structural statistics from multi-source material conditions and estimates their reliability through conformal calibration. It then retrieves type-consistent structural prototypes through reliability-weighted matching and generates the target phase structure using latent residual diffusion. Finally, the generated phase-structure map provides spatial guidance for microstructural texture synthesis. Compared with the direct condition-to-image diffusion baseline, StructRDM improves F1 by 26.9% while reducing Gradient W1 and Autocorrelation MAE by 21.0% and 35.4%, respectively, indicating broader distributional coverage and improved spatial-statistical consistency.