Session Sheet - The 7th International Congress on 3D Materials Science (3DMS 2025): 3D Data Processing, Software, and Reconstruction Algorithms I

The 7th International Congress on 3D Materials Science (3DMS 2025): 3D Data Processing, Software, and Reconstruction Algorithms I
Program Organizers: Henry Proudhon, Mines Paris Centre Des Materiaux; Can Yildirim, European Synchrotron Radiation Facility

Monday 1:30 PM
June 16, 2025
Room: Platinum Ballroom 1
Location: Anaheim Marriott

Session Chair: William Harris, Carl Zeiss Microscopy

1:30 PM  Invited
Reorganization of the Highly Extensible X-Ray Diffraction Library and Opportunities for Community Engagement: Paul Shade¹; Kelly Nygren¹; Patrick Avery²; Zack Singer³; Sven Gustafson¹; Saransh Singh⁴; Chris Budrow⁵; Donald Boyce¹; ¹Cornell University; ²Kitware; ³Verdant Evolution; ⁴Lawrence Livermore National Laboratory; ⁵Budrow Consulting LLC
    For over a decade, the open-source and community-built Highly Extensible X-ray Diffraction Toolkit (HEXRD) has been providing a library of tools for researchers to perform high-quality data reconstructions on x-ray diffraction datasets across many modalities - with ongoing updates to improve the user interface, documentation, bug fixes, and computational efficiency. In response to the size of the current code base and growing demand to integrate more features and user-generated tools/workflows, HEXRD is being modularized into core and technique-specific utilities within the repository. In addition to making the code-base searchable and easier to navigate for the user, this structure enables code-contributors to engage with the code on the topics specific to their science/technique. This talk will cover the blueprint for the restructuring of HEXRD and phased roll-out plan. We will also cover the many ways researchers can engage with the codebase going forward - whether as a user or future contributor.

2:00 PM
Enhancing Neutron Single Crystal Visualization With NeuXtalViz: Zachary Morgan¹; Zhongcan Xiao¹; Sylwia Pawledzio¹; Shiyun Jin²; Iris Ye³; Vickie Lynch¹; Thomas Proffen¹; Christina Hoffmann¹; Xiaoping Wang¹; ¹Oak Ridge National Laboratory; ²Gemological Institute of America; ³Next Generation STEM Internship Program Participant at ORNL
    Advancements in single crystal neutron diffraction require tools that integrate 3D visualization with advanced data reduction to interpret complex datasets. NeuXtalViz is a 3D visualization software developed to meet this need by enhancing Mantid’s platform with libraries like PyVista and scikit-learn. By consolidating wavelength-resolved tools into a single environment, NeuXtalViz supports intuitive 3D visualization and incorporates recent data reduction techniques with frameworks for structural refinement and defect modeling. This streamlined workflow improves data interpretation and builds a foundation for machine learning applications in 3D diffraction science. We discuss the technical approach, highlighting its visualization capabilities and interfaces with advanced reduction and analysis tools, and demonstrate its potential impact on the neutron scattering community. NeuXtalViz aims to address gaps in 3D data analysis, advancing future materials research in crystallography.

2:20 PM
Analysis of Extremely Large 3D Polycrystalline Aggregates: Sean Donegan¹; Michael Chapman²; Michael Uchic¹; ¹Air Force Research Laboratory; ²BlueHalo
    Modern 3D characterization techniques acquire extremely high-fidelity microstructural data, but are often limited to small volumes with typically only hundreds of grains. This restricts analysis of extreme microstructural events crucial for understanding phenomena like material failure. This work presents an unprecedented 3D dataset of a single-phase Ti-7Al alloy, comprising roughly 520 mm3 and containing over 1 million grains. Collected using serial sectioning and computational polarized light microscopy, this dataset enables investigation of rare microstructural features and their influence on material properties. We discuss the experimental techniques used to collect this data set, the specialized analysis approaches built to process the voluminous amount of data, and the resulting statistical features of this extremely large polycrystalline aggregate. This large-scale dataset provides new opportunities for understanding microstructure-property relationships and advancing materials design.

2:40 PM
Fouriera: Automated Spectral Methods for Multiphysics Problems via Symbolic Computing: Bo Wang¹; Tae Wook Heo¹; Kyle Pietrzyk¹; ¹Lawrence Livermore National Laboratory
     Multiphysics modeling of functional materials in the continuum scale can often be formulated into a set of partial differential equations (PDEs). Such models, along with the numerical recipes required to solve them efficiently, quickly become intractable as the model complexity grows. Despite several available software packages, most of them are based on the finite-element method, yet developing a numerical solver based on the spectral method for multiphysics problem remains a time-consuming task prone to human error.Here, we propose a method to automate the implementation of Fourier spectral methods to solve general PDEs using symbolic computing. By automating the tedious analytical work required to implement the numerical methods, Fouriera enables users to solve PDEs conveniently and interactively for multiphysics problems in an efficient manner through a graphical user interface. In this presentation, I will introduce the infrastructure of Fouriera and demonstrate its multiphysics modeling applications, such as in phase-field modeling.

3:00 PM Break

3:30 PM
Real Time Spot Tracking and Materials Characterization for High Energy X-Ray Diffraction Microscopy: Daniel Banco¹; Wiley Kirks²; Sven Gustaffson³; Katherine Shanks³; Kelly Nygren³; Matthew Miller³; Eric Miller¹; ¹Tufts University; ²Cornell University; ³Cornell High Energy Synchrotron Source
    3D high energy X-ray diffraction microscopy (HEDM) data captured in-situ for the characterization of structural materials reveal crystal lattice spacing and orientation changes related to plasticity and fatigue. Challenges associated with large data volumes and experiment complexity result in limited interaction with data during in-situ experiments and lead to data analysis becoming a bottleneck. Here we address this issue through the development and demonstration of data analysis methods providing real-time feedback during experiments. Our sparsity-based signal processing approach tracks diffraction spots in far-field HEDM data and computes time-evolving features indicative of plasticity. The algorithm is inherently parallelizable and provides interpretable features dynamically as the spots spread, move, and overlap during an experiment. While not necessary for processing, prior ex-situ HEDM measurements and virtual diffraction simulation provided crucial guidance to the data analysis. The approach was implemented at the CHESS structural materials beamlines and validated on both simulated and experimental data.

3:50 PM
Grain-Resolved Reorientation and Orientation Gradient Development in Cyclic Loading of α-Ti Using High Energy X-Ray Diffraction Microscopy: Rachel Lim¹; Sven Gustafson²; Darren Pagan³; Anthony Rollett⁴; ¹Lawrence Livermore National Laboratory; ²Cornell High Energy Synchrotron Source; ³Pennsylvania State University; ⁴Carnegie Mellon University
    On the grain scale, materials are heterogeneous and anisotropic which can lead to development of significant grain-scale stresses in polycrystals. Increasing understanding of the effects of this heterogeneity and anisotropy requires experiments which supply three-dimensional, in situ data. High energy X-ray diffraction microscopy (HEDM) is employed to study the in situ grain-resolved evolution of Ti-7Al under during 200 tensile loading cycles below macroscopic yield. Individual grain reorientations are tracked using grain-averaged orientations from far-field HEDM, while spatially-resolved orientations reconstructed via near-field HEDM show the development of slight orientation gradients in some of the grains after the 200 cycles. A comparison between the orientation changes calculated across these two measurements shows both grains with large average reorientations and some with orientation gradient development.