On Strong-Scaling and Open-Source Tools for High-Throughput Quantification of Material Point Cloud Data: Composition Gradients, Microstructural Object Reconstruction, and Spatial Correlations

TL;DR

This paper presents open-source software tools that combine computational geometry, collision analysis, and graph analytics to automate the analysis of microstructural point cloud data, enabling detailed reconstruction, composition profiling, and correlation analysis in materials science.

Contribution

It introduces novel integrated methods for automated microstructure analysis from point clouds, addressing parameter sensitivity and expanding to spatio-temporal studies.

Findings

Effective reconstruction of 3D microstructural objects from point clouds.

Automated characterization of composition profiles and spatial correlations.

Applicability demonstrated in atom probe microscopy for alloy microstructures.

Abstract

Characterizing microstructure-material-property relations calls for software tools which extract point-cloud- and continuum-scale-based representations of microstructural objects. Application examples include atom probe, electron, and computational microscopy experiments. Mapping between atomic- and continuum-scale representations of microstructural objects results often in representations which are sensitive to parameterization; however assessing this sensitivity is a tedious task in practice. Here, we show how combining methods from computational geometry, collision analyses, and graph analytics yield software tools for automated analyses of point cloud data for reconstruction of three-dimensional objects, characterization of composition profiles, and extraction of multi-parameter correlations via evaluating graph-based relations between sets of meshed objects. Implemented for point clouds with mark data, we discuss use cases in atom probe microscopy that focus on interfaces, precipitates, and coprecipitation phenomena observed in different alloys. The methods are expandable for spatio-temporal analyses of grain fragmentation, crystal growth, or precipitation.