Session Sheet - Characterization of Minerals, Metals and Materials 2025: In-Situ Characterization Techniques: Advanced Characterization Methods II

Characterization of Minerals, Metals and Materials 2025: In-Situ Characterization Techniques: Advanced Characterization Methods II
Sponsored by: TMS Extraction and Processing Division, TMS: Materials Characterization Committee
Program Organizers: Zhiwei Peng, Central South University; Kelvin Xie, Texas A&M University; Mingming Zhang, Baowu Ouyeel Co. Ltd; Jian Li, CanmetMATERIALS; Bowen Li, Michigan Technological University; Sergio Monteiro, Instituto Militar de Engenharia; Rajiv Soman; Jiann-Yang Hwang, Michigan Technological University; Eren Kalay, Middle East Technical University; Juan Escobedo-Diaz, University of New South Wales; John Carpenter, Los Alamos National Laboratory; Andrew Brown, Devcom Arl- Army Research Office; Shadia Ikhmayies, The University of Jordan

Monday 2:00 PM
March 24, 2025
Room: 121
Location: MGM Grand

Session Chair: Jiann-Yang Hwang, Michigan Technological University; John Carpenter, Los Alamos National Laboratory

2:00 PM
In-Situ Characterization Methods for Thermophysical Property Measurements Using the Electro-Magnetic Levitator On-Board the International Space Station: Marcelina Stasik¹; Stephan Schneider²; Wilhelmus Sillekens¹; ¹European Space Agency; ²German Aerospace Center (DLR)
    The Electro-Magnetic Levitator is one of the research facilities on-board the International Space Station which is operated by the European Space Agency for scientific investigations into solidification physics of metallic and semiconductor materials. It is used to observe structural evolution during the liquid-solid transition and to measure thermophysical properties in the liquid and undercooled state. The latter includes specific heat capacity, thermal conductivity, surface tension, viscosity, electrical conductivity, thermal expansion and hemispherical emissivity. The reduced-gravity environment hereby provides the best-possible experimental condition to arrive at highly accurate and reliable measurement data. This presentation gives an overview of the analytical methods (including modulation calorimetry and the oscillating drop method) that are being employed for these measurements. Different approaches are being considered and will be illustrated with measurement examples. Guidelines for the implementation will be given as well.

2:20 PM
In-Situ Mechanical Property Measurement Using Laser Ultrasound: Zilong Hua¹; Amey Khanolkar¹; Stephen Reese¹; William Chuirazzi¹; Michael McMurtrey¹; David Hurley¹; ¹Idaho National Laboratory
    In this talk we present the recent efforts of developing in-situ mechanical property measurement capabilities at Idaho National Laboratory (INL) using laser ultrasound techniques. In laser ultrasound measurements, a pump laser is used to introduce the acoustic wave or generate resonant vibration in the testing sample, which is captured by using a probe laser (usually a laser interferometry) through measuring the displacement of the sample surface. Young’s modulus, share modulus, and other constants in elasticity tensor, can be extracted from an inverse fitting procedure, from which the phase transition and/or recrystallization of alloy materials can be monitored in a desired temperature range. Using a similar mechanism, a fiber-based system was designed and tested in the INL Transient Reactor Test Facility.

2:40 PM
In-Situ Sensor Monitoring and Multiclass Porosity Defects Prediction for Laser Powder Bed Fusion With Machine Learning: Sandesh Giri¹; Sen Liu¹; Nick Calta²; Christopher Tassone³; ¹University of Louisiana at Lafayette; ²Lawrence Livermore National Laboratory; ³SLAC National Accelerator Laboratory
    Laser Powder Bed Fusion (LPBF) has emerged as a promising technology for advanced manufacturing and environmental sustainability. However, LPBF of Aluminum alloy is prone to porosity defects which affect the structural integrity and mechanical properties of manufactured components. Ensuring real-time, accurate defect detection and classification is critical for advancing the scalability of LPBF. We have developed a convolutional neural network (CNN) for real-time porosity detection in LPBF process with the signal registering of high-speed X-ray imaging. In contrast to traditional binary prediction of keyhole-porosity formation, our method defines porosity generation as multi-class (no pore, gas pore, and keyhole pore). Statistical analyses confirmed the efficacy of the multi-class approach, while time series regression further helped differentiate the relationships between the different pore types. CNN model successfully classified multi-class porosity with an accuracy of 85.71%. This research shows the potential for cost-effective, scalable flaw detection and process monitoring in additive manufacturing.

3:00 PM
Leveraging XRD, Total Scattering, and XAFS Techniques to Decipher Structure-Property-Performance Relationships in Ammonia Decomposition Catalysts: Tolga Han Ulucan¹; ¹SLAC National Accelerator Laboratory
    This study examines the structure-property-performance relationships of Ni and Co ammonia decomposition catalysts through the use of a comprehensive array of ex-situ, in situ, and operando characterization techniques. X-ray Absorption Fine Structure (XAFS), X-ray Diffraction (XRD), and total scattering were utilized to analyze the structural variations introduced by disparate synthesis and processing methods across different length scales. These techniques facilitated the investigation of the impact of synthesis and processing conditions on the structural and functional properties of the catalysts. Our findings highlight the significant influence of minor structural variations on overall catalytic performance. Integrating in situ and operando studies provided real-time insights into the structural evolution of the catalysts under operational conditions, underscoring the critical role of multiscale characterization techniques in material design and optimization. This research emphasizes the necessity of multiple in-situ and operando techniques to accurately determine the structure-property-performance relationships and develop efficient catalysts for energy applications.

3:20 PM
Opening Pandora’s Box: Addressing the Closed Nature of Post-Processing Methods for Computed Tomography (CT) Images With Application Perspectives for Energetic Materials: Stewart Youngblood¹; Sean Palmer¹; Alan Williams¹; ¹Sandia National Laboratories
    X-Ray Computed Tomography (CT) is a widely used tool for in-situ interrogation of microstructure and geometrical characteristics of materials. It is not uncommon to observe image artifacts resulting from beam hardening due to large disparities in density between the constituents or component materials. Alternatively, similarity in densities can obscure boundaries between materials and hide discontinuities. Typical post-processing of images to address these issues use commercial software packages with proprietary processing routines that are effectively “black boxes”. The closed nature of these approaches limit continuity across research efforts and there has been limited characterization of post-processing effects on measured micro- and meso-scale properties. Here we present current efforts in developing and assessing “open” box image processing approaches for addressing beam hardening artifacts and improving material segmentation. Application perspectives will be in regard to characterizing micro- and meso-scale features of energetic materials including mono-molecular explosives, heterogenous explosive compositions, and pyrotechnics.

3:40 PM Break

3:50 PM
Low Voltage Electron Back-Scatter Diffraction: Enabling High Resolution Mapping of Early Stage Recrystallization: Zehua Liu¹; Marc DeGraef¹; ¹Carnegie Mellon University
    Misorientation measurements at the early stage recrystallization of abnormal grains and subgrains are made using a fast heating stage and in-situ EBSD at low KeV. High purity aluminum (99.999%) was cold rolled to 75% reductions and annealed. Through EMsoft dictionary indexing, subgrain boundaries migration process during incubation time has been characterized and abnormal subgrains are observed in the process. High resolution mapping of the deformed Aluminum provided some insight into the evolution of the local deformation state. Experiments results offered some new insights of the misorientation changes of abnormal subgrain boundaries during the early-stage recrystallization. Subgrain boundaries are found to be surprisingly active for the high purity aluminum during the annealing process below typical recrystallization temperature. Subgrains with different textures exhibit different growth kinetics. We will also present comparison of the EMsoft derived maps with those generated by other high angular resolution EBSD approach, in particular the OpenXY package.

4:10 PM
Phase Evolution of a Spinodal Copper Alloy, Characterized by In Situ Synchrotron X Ray Diffraction: James Hogg¹; Nicole Church¹; Annie Andersson¹; Catherine Dejoie²; Howard Stone¹; ¹University of Cambridge; ²European Synchrotron Radiation Facility
    Cu-15Ni-8Sn (wt%) offers excellent mechanical properties through a combination of spinodal decomposition and precipitation of coherent D0₂₂ and L1₂ phases. However, during prolonged thermal exposure, discontinuous precipitation of D0_a and D0₃ phases occurs, deteriorating the mechanical performance. These processes must be understood for judicious selection of processing parameters. Phase evolution has typically been characterized using ex situ transmission electron microscopy and diffraction-based techniques. However, the concurrence of multiple phase transformations with overlapping diffraction signals has compromised studies of the precipitation sequence. In this work, high resolution synchrotron X-ray diffraction has been used to directly track the phase evolution of Cu-15Ni-8Sn (wt%). Data were acquired in situ during ageing over a range of temperatures. The high angular resolution enabled deconvolution of the sidebands formed from spinodal decomposition and the respective diffraction peaks from ordering and discontinuous precipitation. This allowed the precipitate sequence to be determined with a ~2 min time resolution.

4:30 PM
Put a Gleeble in the Beam: Concepts for the Materials Oscilloscope: Klaus-Dieter Liss¹; ¹University of Tennessee, Knoxville
     Over the past twenty years, unconventional neutron and synchrotron diffraction analyses have been refined to gather complementary information, primarily in situ and in real-time, to address materials development across multiple length scales—from atomic arrangements and nano- and microstructures to engineering dimensions. Synchrotron high-energy X-ray diffraction allows for tracking and decomposing phase composition, lattice strain and expansion, from the morphology, such as microstructural evolution, phase orientation correlations, and their defect kinetics. Multi-dimensional data analysis has been developed to track these features, underpinning algorithms for automated data analysis.For instance, integrating a Gleeble thermo-mechanical processor with a high-energy synchrotron beam and automated data recognition and reduction could accelerate materials development by two to three orders of magnitude. This system could be operated by a non-diffraction specialist, providing real-time results to materials experts in situ.

4:50 PM
Microstructural Evolution of Fe-Bearing Intermetallic Particle After Thermo-Mechanical Processing Using X-Ray Microcomputed Tomography: Satyaroop Patnaik¹; Eshan Ganju¹; XiaoXiang Yu²; Minju Kang²; Jaesuk(Jay) Park²; DaeHoon Kang²; Rajeev Kamat²; John Carsley²; Nikhilesh Chawla¹; ¹Purdue University; ²Novelis Global Research and Technology Center
    Fe-bearing intermetallic particles (Fe-IMPs) are formed during casting of aluminum alloys. These particles can affect the mechanical properties and formability of the alloys in part due to their complex interconnected morphologies. In this work, X-ray Computed Tomography (XCT) was used to capture the 3D morphology of Fe-IMPs in the Al-Mg based alloys with high Fe contents. The differences in morphologies of the Fe-IMCs in both alloys were quantified using a new 3D morphological descriptor - the particle-to-convex hull volume ratio. The morphology data of the Fe-IMPs was correlated with Energy Dispersive Spectroscopy (EDS) measurements, and nano-indentation data to develop a coherent understanding of Fe-IMP particle evolution during thermo-mechanical processing.

5:10 PM
In-Situ Multi-Scale Analysis of Local Deformation Behavior of Lath Martensite in Low-Carbon-Steel: Shuang Gong¹; Junya Inoue¹; ¹The University of Tokyo
     The particular anisotropic local deformation behavior poses challenges in understanding the deformation mechanism of lath martensite. This study investigates the dislocation dynamics underlying local deformation behavior in low-carbon steel lath martensite, employing a novel combination of in-situ tensile Electron Channeling Contrast Imaging (ECCI) and High-Resolution Digital Image correlation (HR-DIC).To determine how the lath interface affects dislocation activity, microscopic in-situ ECCI observations were conducted to directly track the behavior of intra-lath dislocation structures and boundary sliding. Boundary sliding was confirmed after a certain extent of deformation within the lath. The ECCI technique was also used to capture the dislocation structures in the vicinity of lath boundaries, which play an important role in local deformation. Meanwhile, the strain distribution of the local deformation was calculated using the HR-DIC technique, validating the microscopic observations of dislocation movement.

5:30 PM
High Energy Diffraction Microscopy as a Tool for In-Situ Characterization of Materials: Hemant Sharma¹; Weijian Zheng¹; Jun-Sang Park¹; Peter Kenesei¹; Rajkumar Kettimuthu¹; Antonino Miceli¹; ¹Argonne National Laboratory
    High Energy Diffraction Microscopy, or HEDM, is a non-destructive tool for in-situ mapping of material microstructures using High-Energy X-rays. This talk will show examples of different HEDM modes (far-field for strain characterization, near-field for grain boundary mapping, and point-focus for intra-granular strain characterization) that have been utilized to study deformation, thermal, and irradiation processes in materials. Furthermore, we will cover opportunities in HEDM capabilities with the APS-Upgrade, allowing for studies of more complex material structures at higher resolutions. Furthermore, we will describe how machine learning-enabled experimentation can extract rare insight from the materials during in-situ processing.