microstructurenetwork

A microstructurenetwork is a representation of a material’s microstructure as a graph or network, where discrete microstructural units such as grains, particles, pores, or phases are modeled as nodes and their relationships—such as physical adjacency, shared interfaces, or transport pathways—are modeled as edges. This framework provides a way to analyze the topology and connectivity of complex microstructures and to link microlevel features to macrolevel properties.

Construction typically begins with imaging data from techniques like electron backscatter diffraction (EBSD), scanning electron microscopy, X-ray tomography, or focused ion beam tomography. After segmentation identifies individual features, a graph is formed by assigning a node to each feature and drawing edges between neighboring features or along interfaces. Edge weights can reflect boundary length, shared surface area, contact strength, diffusion resistance, or mechanical interaction. Nodes can carry attributes such as size, orientation, phase, or anisotropy.

Analytical methods draw on graph theory and network science. Metrics such as degree distribution, clustering, shortest paths, and centrality reveal connectivity and potential pathways for transport or deformation. Community detection can identify phase domains or feature clusters, while percolation analysis assesses whether a continuous path exists through the network. Spectral properties relate to effective stiffness or diffusivity, and dynamic or evolving networks model microstructure changes during processes like annealing, phase transformation, or plastic deformation.

Applications include predicting mechanical, thermal, and transport properties from microstructural topology, guiding materials design and processing, and characterizing porosity or grain-boundary networks in metals, ceramics, composites, and porous media. Limitations arise from data quality and segmentation, the choice of how features are represented as nodes and edges, and the scale at which the network is constructed, which can influence results.