Unlocking Nanoscale Microstructural Detail in Aluminum Alloys Through Differential Phase Contrast Segmentation in STEM

Differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM) maps projected electric/magnetic fields through the phase sensitivity of segmented low-angle detectors. Although typically applied to atomic-resolution imaging at low beam currents, STEM-DPC is here demonstrated as a rapid micro and nanoscale image-segmentation tool for materials characterization with particular focus on advanced aluminum alloys. Decomposition of false-color DPC micrographs in hue–saturation–value space enables simultaneous identification and quantification of nanoclusters, GP zones, intermediate precipitate phases, dislocation cores, and associated strain fields within a single field of view. The method is demonstrated across multiple alloy systems, including clustering and strain-field mapping in a deformed AlMgZn(Cu) crossover alloy, precipitate identification in a paint-baked automotive sheet alloy, phase-variant segmentation in overaged AA7075-T7, and nanopore and nanoparticle detection in an anodic coating on AA2024-T3. Coupling DPC with neural-network segmentation further enables automated grain-boundary delineation and quantification in nanocrystalline aluminum thin films. Combined with STEM-EDX, DPC-based segmentation enables correlative microstructural analysis, establishing DPC as a rapid complement to techniques such as SPED and 4D-STEM.