Advanced Characterization of Materials for Nuclear, Radiation, and Extreme Environments III: In Situ Microscopy
Sponsored by: TMS Nanomechanical Materials Behavior Committee, TMS Nuclear Materials Committee
Program Organizers: Cody Dennett, Commonwealth Fusion Systems; Samuel Briggs, Oregon State University; Christopher Barr, Naval Nuclear Laboratory; Michael Short, Massachusetts Institute of Technology; Janelle Wharry, Purdue University; Cheng Sun, Clemson University; Caitlin Kohnert, Los Alamos National Laboratory; Khalid Hattar, University of Tennessee Knoxville; Yuanyuan Zhu, University Of Connecticut

Tuesday 8:00 AM
October 11, 2022
Room: 329
Location: David L. Lawrence Convention Center

Session Chair: Samuel Briggs, Oregon State University; Cheng Sun, Idaho National Laboratory


8:00 AM  Invited
Utilizing In-situ Microscopy Techniques to Decipher the Micro-scale Dynamics of Materials in Extreme Environments: Eric Lang1; Samuel Briggs1; Nathan Heckman1; Anthony Monterrosa1; Trevor Clark1; Christopher Barr1; Daniel Buller1; Brad Boyce1; Khalid Hattar1; 1Sandia National Laboratories
    Materials in extreme conditions such as fusion reactors and cladding in advanced fission reactors undergo compositional, microstructural, and property changes in response to thermal, mechanical, and irradiation stimuli. Typical materials analysis examines two states: pristine and post-mortem. A complete picture of evolution requires in-situ monitoring to elucidate transient processes dictating the final state. The recently developed in-situ ion irradiation scanning electron microscope (I3SEM) at Sandia National Laboratories (SNL) offers an ideal platform for micro-scale analysis of material dynamics under irradiation, temperature, and straining. Coupling a 6 MV Tandem Accelerator, a 1.2 kV ion source, and an 808nm laser with an environmental high-resolution SEM with heating, cooling, liquid, and straining stages, materials can be probed under synergistic extreme conditions. This work focuses on the in-situ characterization of candidate materials, examining their behavior in simulated reactor quiescent and transient conditions. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

8:30 AM  Invited
In Situ Irradiation of TiO2 Nanotubes: Hui Xiong1; Chao Yang2; Tristan Olsen1; Miu Lun Lau1; Kassiopeia Smith3; Janelle Wharry2; Khalid Hattar4; Yongqiang Wang5; Wei-Ying Chen6; Yaqiao Wu1; Badri Narayanan7; Min Long1; Dewen Hou1; 1Boise State University; 2Purdue University; 3Fifth Gait Technologies; 4Sandia National Laboratory; 5Los Alamos National Laboratory; 6Argonne National Laboratory; 7University of Louisville
    Utilizing situ ion irradiation transmission electron microscopy (TEM) we investigate the morphological and structural evolution in TiO2 nanotubes under Au and Kr ion irradiation with complementary molecular dynamics (MD) simulations to calculate the volume of amorphous and anatase TiO2. It is found that anatase TiO2 nanotubes exhibit morphological stability throughout irradiation. Amorphous TiO2 nanotubes undergo irradiation-induced crystallization under Au ion irradiation. While the majority of the initially amorphous tubes become fully crystallized, some tubes remain only partially crystallized. These partially crystalline tubes also bend during irradiation, due to internal stresses associated with the densification that occurs through crystallization, as confirmed by MD calculations. This mechanism presents a novel irradiation-based pathway for tuning the structure and morphology of advanced energy storage materials. These results are discussed in the context of irradiation-induced order/disorder transformations.

9:00 AM  Invited
Radiation Resistance of Metallic Glass Coatings of Crystalline Nanostructures: Mehrdad Kiani1; Khalid Hattar2; Wendy Gu3; 1Yale University; 2Sandia National Laboratories; 3Stanford University
    In radiation environments, crystalline nanostructures suffer from enhanced surface damage and sputtering due to their high surface area to volume ratio. In contrast, ultrathin metallic glass films have been shown to be highly resistant to crystallization and surface damage. Here, we use in situ TEM ion irradiation to probe whether a metallic glass coating can mitigate sputtering and structural damage of crystalline nanostructures. Colloidally synthesized Au nanocubes with a Ni-B metallic glass coating were bombarded with 2.8 MeV Au4+ ions and morphological changes were tracked as a function of fluence. For bare Au nanocubes, sputtering and surface roughening began at 4 × 1012 ions/cm2 (0.04 dpa) whereas coated Au nanocubes showed minimal changes at a fluence of 1.9 × 1013 ions/cm2 (0.2 dpa). There was no intermixing at the metallic glass-Au interface and the coating remained amorphous for all conditions.

9:30 AM  
High-temperature Stable Nanolamellar Transition Metal Carbides Derived from Two-dimensional MXenes for Extreme Environments: Brian Wyatt1; Kartik Nemani1; Annabelle Harding1; Wyatt Highland1; Babak Anasori1; 1Indiana University - Purdue University Indianapolis
    Two-dimensional transition metal carbides, known as MXenes, have wide use in energy storage and catalysis applications, but few studies take advantage of the inherent stability of the interior transition metal carbide core for use in extreme environment conditions. In this talk, we present the high-temperature behavior of two different MXenes of Ti3C2Tx and Mo2TiC2Tx from room temperature to 2,000 °C using in-situ up to 1,100 °C using two-dimensional x-ray diffraction (XRD2) and ex-situ XRD2 up to 2,000 °C. We also show scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and transmission electron microscopy (TEM) data to demonstrate the transformation of MXenes to nanolamellar cubic structures with strong preferential (111) plane orientation. Using these methods, our studies identify that these preferentially ordered nanolamellar phases are stable up to 2,000 °C in inert environments, which permits MXenes’ use as nanosized building blocks for ultra-high temperature coatings or ceramic composite additives.

9:50 AM Break

10:10 AM  Invited
Machine Learning Algorithms for High-throughput Characterization of Structure and Microstructure of Metals for Extreme Environments: Nishan Senanayake1; Thaddeus Rahn2; Nathaniel Tomczak1; Assel Aitkaliyeva2; Jennifer Carter1; 1Case Western Reserve University; 2University of Florida
    A major bottleneck in the nuclear materials research/design space is the near-ubiquitous requirement that gray-scale micrographs require manual interpretation of microstructural features. Conventional image segmentation algorithms often require manual intervention, making it difficult to generalize from one challenge to another. In this work, we present trained machine learning (ML) algorithms for high-throughput 1) classification of phases from selected-area diffraction patterns in the Pu-Zr system and 2) segmentation of secondary electron micrographs in 𝛾′′, 𝛾′ strengthened nickel-based superalloys. The Pu-Zr algorithm utilizes a convolutional neural network (CNN), without integration of materials domain knowledge, to index between the α and δ phases. The proof-of-concept model indicates that full automation of the diffraction pipeline is attainable. The classification of 𝛾′′ and 𝛾′ pixels shows the ML can either increase (random forest, CNN) or decrease (support vector machine) computational efficiency compared to conventional image segmentation without negatively impacting accuracy.

10:40 AM  
Microstructural Evolution of Alloy 718 under High Temperature In-situ Ion Irradiation with Machine Learning: Stephen Taller1; Timothy Lach1; Kai Sun2; 1Oak Ridge National Laboratory; 2University of Michigan
    Ni-based superalloys are a candidate alloy class for advanced reactor applications because of their intrinsic resistance to creep and high strength primarily from intermetallic phases δ, γʹ or γʹʹ. Two heats of Inconel 718 with large pre-existing precipitate densities were evaluated using the in-situ dual ion irradiation TEM at the University of Michigan. Irradiations were conducted up to 10 dpa using Kr ions with ~400 appm He/dpa co-injected at temperatures from 500-700°C. STEM HAADF images were continuously collected to capture the time-dependence of the microstructure. A dynamic segmentation convolutional neural network classified features in each frame of in-situ video with several computer vision algorithms to track the size of each feature. Pre-existing precipitates dissolved early (< 1 dpa) for all conditions. Cavities nucleated shortly after with phases with similar contrast to γ″ and δ emerging at higher fluences. With increasing temperature, both cavity nucleation and precipitate dissolution and re-emergence accelerated.

11:00 AM  Invited
Recent Innovations in Machine Learning-based Techniques for In-situ Microscopy Data Analysis : Kevin Field1; Priyam Patki1; Matthew Lynch1; Ryan Jacobs2; T.M. Kelsy Green1; Robert Renfrow1; Wei-Ying Chen3; Dane Morgan2; Christopher Field4; 1University of Michigan; 2University of Wisconsin; 3Argonne National Laboratory; 4Theia Scientific, LLC
    Machine learning (ML) techniques are emerging as an attractive means for in-situ microscopy data analysis. The driving factors are inference at exceptional speeds with minimal tuning of hyperparameters during in-situ experiments. Given this, a range of challenges exist including the need for significant amounts of training data, the applicability to ML techniques to variations in imaging or materials domains (e.g., transmission versus scanning transmission electron microscopy imaging – S/TEM), and the limited computational and software infrastructure for the adoption of ML techniques on-the-microscope. Here, we will present recent studies and advances to overcome these challenges including the adoption of synthetic data generation for training workflows in cavity-based imaging. Additional discussion will be centered on imaging domain applicability for dislocation loops and evaluation of performance of in-situ microscopy data analysis compared to conventional, human-based ex-situ analysis during in-situ TEM dual ion irradiations.