The 7th International Congress on 3D Materials Science (3DMS 2025): 3D Data Processing, Software, and Reconstruction Algorithms II
Program Organizers: Henry Proudhon, Mines Paris Centre Des Materiaux; Can Yildirim, European Synchrotron Radiation Facility
Tuesday 9:00 AM
June 17, 2025
Room: Platinum Ballroom 1
Location: Anaheim Marriott
Session Chair: Thomas Avey, Naval Surface Warfare Center Carderock
9:00 AM Invited
A Polycrystalline X-Ray Virtual Diffractometer for Direct Comparisons to Experimental Data: Sven Gustafson1; Paul Dawson2; Matthew Miller2; Kelly Nygren1; 1Cornell High Energy Synchrotron Source; 2Cornell University
Micromechanical modeling routinely simulates spatially resolved fields for polycrystals with thousands of grains undergoing continuous in-situ deformation; however, current experimental techniques cannot probe such fields within all grains with the spatial, angular, and temporal resolution to facilitate direct comparison. Current reconstructions only extract grain averaged information even though experimental detector images from far-field high energy diffraction microscopy contain relevant spatially resolved information and the technique operates with sufficient temporal resolution. To facilitate an experiment to model comparison, a finite element based virtual diffractometer is presented here to produce realistic diffraction images from model generated microstructures, a spatially resolved x-ray beam, and a pixelated detector. The functionality of the virtual diffractometer is demonstrated with experimental to virtual detector image comparisons for an ideal crystal. The evolution of detector image data from an in-situ mechanical test is then compared with a virtual diffraction simulation of the corresponding model generated microstructure.
9:30 AM
Advancing 3D Grain Mapping Accessibility for the Materials Science Community: Insights into Recent Developments of Data Acquisition, Reconstruction and Analysis: Jun Sun1; Florian Bachmann1; Mario Heinig1; Frank Niessen1; Jette Oddershede1; Erik Lauridsen1; 1Xnovo Technology
Mapping the 3D-spatial crystallographic orientation of polycrystalline materials holds tremendous value for 3D materials science and related phenomena, as the properties and performance of materials are intricately linked to their 3D microstructural morphology. 3D non-destructive crystallographic imaging techniques emerged at synchrotron light sources in the early 2000s, and substantial efforts have been made over the past decades to establish and optimise X-ray diffraction contrast tomography (DCT) into the laboratory setup, with the mission to achieve wide accessibility for materials scientists to non-destructive 3D grain mapping techniques.In this talk, we will present the recent developments of lab-based 3D grain mapping responding to the needs of the 3D materials science community, including: 1) advanced diffraction data acquisition allowing characterisation of large, representative sample volumes, 2) reconstructing multiple crystalline phases allowing a wider coverage of sample systems, and 3) challenges and approaches in processing and analysis of 3D grain maps.
9:50 AM Cancelled
Comparative Analysis of Reconstruction Methods for Lab-Scale X-Ray Computed Tomography of 3D Defects in Semiconductor Packages: Eshan Ganju1; Yaw Obeng2; William Harris3; Charles Bouman1; Gregery Buzzard1; Nikhilesh Chawla1; 1Purdue University; 2NIST; 3Zeiss
Rapid co-design of semiconductor packages necessitates an efficient and non-destructive metrology to detect defects. Lab-scale X-ray Computed Tomography systems, while valuable, face challenges such as long scan times due to limited x-ray flux and imaging artifacts arising from density variations and reconstruction methods. This study critically evaluates three distinct reconstruction techniques for lab-scale XCT data: Filtered Back Projection (FBP), Model-Based Iterative Reconstruction (MBIR), and Deep Learning (DL) approaches. FBP serves as the baseline for comparison. MBIR leverages physical models and noise statistics to enhance image quality and potentially reduce scan times. DL methods, trained on extensive datasets, offer a data-driven approach to reconstruction. Reconstruction performance was assessed through quantitative metrics, scan and reconstruction time, and signal-to-noise ratio. The advantages and limitations of each method are discussed in detail, supplemented by visual assessments of exemplars in semiconductor packages, to provide insights into their suitability for high-fidelity lab-scale XCT semiconductor packaging applications.
10:10 AM
Optimizing CT Image Quality With Deep Learning for Enhanced 3D Materials Science Applications: Parisa Asadi1; Adrian Sarapata1; Andriy Andreyev1; 1Zeiss
X-ray computed tomography (CT) is fundamental to non-destructive 3D imaging, though image quality is often hampered by noise. This study examines the benefits of FAST Mode image acquisition (ability to scan in 20 seconds) for rapid sample inspection and DeepRecon Pro 3D-image reconstruction, a deep learning-based noise reduction method adaptable to various imaging conditions. Using a U-Net architecture, DeepRecon Pro processes projection images or volumes to produce noise-suppressed, high-fidelity reconstructions, outperforming traditional techniques like FDK and non-local means (NLM). The latest DeepRecon version integrates synthetic priors and a two-stage training process, introducing noise-matching models that further enhance accuracy. Quantitative metrics, including mean square error (MSE) and structural similarity index (SSIM), highlight DeepRecon’s effectiveness across diverse noise intensities and projection counts. These advancements support faster, more accurate CT imaging for critical 3D materials science applications where precision and efficiency are paramount.
10:30 AM Break
10:50 AM
PolyProc: A Computational Package for Processing 3D/4D PolyCrystalline Microstructure Data: Varun Srinivas Venkatesh1; Marcel Chlupsa1; Ashwin Shahani1; 1University of Michigan
Direct imaging of three-dimensional microstructures with X-ray diffraction techniques yields valuable insights into the crystallographic features that influence material properties and performance. Incorporating a temporal dimension allows for direct observations of the microstructural evolution. As these techniques and datasets become more widely available, the demand for processing inherently noisy, multi-dimensional, and multimodal data has increased. To address this demand, we present recent updates to the PolyProc package, a suite of algorithms that parse the full breadth of microstructure, including the grains, interfaces, and triple junctions, as well as time-resolved statistics. We introduce several new capabilities, including the quantification of grain boundary curvatures and velocities; grain boundary character and normal distributions; and grain boundary and triple junction percolation analyses. Finally, we present a novel algorithm that utilizes grain neighborhood information to track the same grains in time. Altogether, these advancements streamline the analysis and visualization of 3D/4D microstructural data.
11:10 AM
Real-Time 3D Visualization of Eutectic Solidification Dynamics Using Limited Angle Tomography: Soumyadeep Dasgupta1; Paul Chao2; Xianghui Xiao3; Ashwin Shahani1; 1University of Michigan; 2Sandia National Laboratory; 3Brookhaven National Laboratory
Multi-phase 3D structure from eutectic solidification brings versatile properties to alloys. By studying solidification in real-time, we gain insights into interfacial dynamics, enabling improved control and design of advanced materials. Synchrotron X-ray nanotomography provides a 3D perspective of microstructural evolution at the nanoscale; however, its temporal resolution is constrained by factors, e.g., the microscope hardware capabilities, sample shape etc. To achieve sub-10s temporal resolution, we employ Limited Angle Tomography (LAT). Using LAT, we investigate the directional solidification of a near-eutectic Al-Al₃Ni alloy as a proof-of-concept. A novel composite reconstruction approach termed ‘pseudo-4D imaging’ mitigates artifacts inherent to LAT, allowing us to visualize the solidification process in 3D space and time. This technique relies upon data fusion of real-time radiographs with postmortem 3D reconstruction of the fully-solidified specimen. The approach holds promise not only for solidification science but also for the 3D characterization of other time-sensitive phenomena within constrained viewing windows.
11:30 AM
Closed-Form Solution for the Deformation Gradient Tensor in Dark Field X-Ray Microscopy: Brinthan Kanesalingam1; Darshan Chalise1; Carsten Detlefs2; Leora Dresselhaus-Marais1; 1Stanford University; 2European Synchrotron Radiation Facility
Spatially resolved strain measurements are crucial for understanding material properties and phenomena that induce strain and lattice rotations. Dark Field X-ray Microscopy (DFXM) offers a unique opportunity with its ability to image bulk crystals at the nanoscale while providing a field-of-view approaching a few hundred micrometers. However, an inverse modeling framework to relate DFXM observables to strain and lattice rotation tensors has not been previously developed. By utilizing the oblique diffraction geometry for DFXM, which enables access to non-coplanar symmetry-equivalent reflections, we demonstrate that the reconstruction of the full deformation gradient tensor, and consequently the strain and lattice rotations, is analytically solvable in closed form. We developed a computational framework to both forward calculate the anticipated angular shifts and reconstruct the average deformation gradient tensor for individual pixels from DFXM experiments. This comprehensive approach will enable precise interpretation of existing DFXM data and guide the design of future DFXM experiments.