Unlocking nanoscale microstructural detail in aluminium alloys through differential phase contrast segmentation in STEM

TL;DR

This paper demonstrates a rapid, multi-scale imaging technique using differential phase contrast in STEM to identify and quantify various microstructural features in aluminium alloys, enhancing materials characterization.

Contribution

It introduces a novel DPC segmentation method combined with color decomposition and neural networks for detailed microstructural analysis in aluminium alloys.

Findings

Effective identification of nanoclusters, GP zones, and precipitates.

Automated grain boundary detection in nanocrystalline films.

Correlative analysis with STEM-EDX enhances microstructural insights.

Abstract

Differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM) maps projected electric 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 in advanced aluminium alloys. Decomposition of false-colour 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 aluminium 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.