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DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale molecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗

DOE OSTI2023

Downselection and Basic Properties of Additively Manufactured ODS Alloys

In the AMMT program the work package for development of new materials aimed to explore the advanced manufacturing techniques that are feasible for the manufacturing of advanced materials components. A merit-based feasibility study was attempted to identify an accelerated development path for dispersion strengthened (ODS) alloys by creatively combining additive manufacturing (AM) technologies with the recent advances in ODS materials and traditional manufacturing technologies. For the fiscal year, the primary tasks were focused to develop additive manufacturing (AM) and post-build processing route for oxide dispersion strengthened (ODS) ferritic (Fe-Cr alloy or 14YWT) and austenitic (Fe-Cr-Ni alloys or 316L and 316H) alloys and to perform basic microstructural and mechanical characterizations to provide feedbacks to the alloy and processing design. Further, the multi-laboratory effort created collaboratively a decision criteria matrix to evaluate and downselect the new materials processed by advanced manufacturing methods. This report is to describe the ODS alloy processing routes combining AM processes and post-build thermomechanical treatments, mechanical and microstructural characteristics of the newly developed materials, and the application results of the decision criteria matrix for the AM ODS alloys including a downselected material and feasible processing route. Key mechanical test results including tensile strength, tensile ductility, and fracture toughness data and are reported and explained. Higher strength was measured from the ferritic ODS alloys, while higher ductility and fracture toughness were measured from the austenitic ODS alloys. Many of the decision criteria were scored the same for the AM ferritic and austenitic ODS alloys, however, the generally known fact that the austenitic alloys have higher corrosion resistance and significantly better ductility. Although these scores are not significantly different to make them highly discernable, the austenitic ODS alloys were downselected to be the primary materials group in the future research on ODS materials in AMMT program.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Feasibility Study of Advanced Manufacturing Techniques and Compositions of High Entropy Alloys

In line with the objectives of Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing technologies program (AMMT), this work focuses on new materials development and qualification research and development for next-generation, high-temperature nuclear reactors. While the currently qualified nuclear materials have demonstrated significant irradiation resistance at high temperatures, the community is still interested in materials that can sustain the harsh environments found in nuclear reactors for temperatures up to 1,000°C for nearly 100,000 hours. High entropy alloys (HEAs) have the potential to serve in these extreme environments of next generation nuclear reactors due to their unique phase transformation pathways and nanoscale and mesoscale microstructures. The current work focuses on understanding such nuclear energy relevant HEAs through a detailed literature survey and developing a decision matrix with criteria for identification of HEAs with may have most impact and value for further examination.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Characterization of micro-sandwich structures via direct ink writing epoxy based cores

Sandwich structured (SS) composites demonstrate considerable flexural stiffness and high strength-to-weight ratios and can be tailored as functional materials. Historically they have been constrained to specific material types and geometry due to limitations in manufacturing methods. However, employing additive manufacturing (AM), specifically direct ink writing (DIW), can provide an alternative method for making SS composites with complex and controllable micro and mesostructures with multifunctionality targeted at desired mechanical, thermal, and electrical properties. DIW, an extrusion-based AM technique, uses a viscous and thixotropic ink with desired components that, once printed, is cured to obtain the final complex net shape parts. In this paper, a novel hybrid AM technique is employed to manufacture SS composite materials containing bisphenol A-based epoxy core and carbon fiber reinforced polymer (CFRP) face sheets that are fabricated via DIW and vacuum infusion process (VIP), respectfully. We demonstrate that the fabrication of these SS composites can be tailored from a thermosetting material, from which additives and/or various lattice structures can be manufactured to achieve enhanced and desirable mechanical integrity with functional properties. Surface topology and mechanical testing techniques are used to characterize the fabricated hybrid SS composites to study and assess mechanical stability. A rheo-kinetic cure model was developed for the core material to allow for additive manufacturing process requirements while ensuring complete cross-linking for the thermoset-based core material. Because of the ability to obtain relatively small core-thickness and controlled architecture, this method now allows for fabricating layered micro-sandwich structures for realizing further light-weighting in relevant applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Material exploration towards high quality factor microwave resonators

Niobium and aluminum have been widely used to realize superconducting resonators and qubits. However, the native oxide at the metal air interface limits the devices results. This layer is highly disordered, and it induces losses limiting the performances of the resonators or qubits. Recently, tantalum led to great improvement in qubit relaxation time. This improvement has been attributed to a thinner and less disordered oxide layer compared to Nb and Al. This study is aimed to limit the formation of the oxide layer, by the introduction of novel superconducting materials such as rhenium or by encapsulating the Nb surface with other superconducting materials such as Ta, Al, Re or other non-superconducting materials such as Au. To better understand the results, we are realizing these studies on coplanar waveguide resonators where the relation between surface losses and quality factor is clear. We are also analyzing different fabrication techniques to completely characterize our devices, linking material properties to the performances. In this work we are also varying the participation ratio of the devices in order to extract with higher fidelity and precision the losses introduced by the involved interfaces.

Crisa, F.↗

DOE OSTI2023

Feasibility Studies and Downselection of New Materials and Manufacturing Technologies for Nuclear Applications

This report is intended to present the results of multi-laboratory collaborative studies on the feasibility and downselection of the structural materials that are newly considered for application to future nuclear energy technologies. The Advanced Materials and Manufacturing Techniques (AMMT) program has been implemented to develop cross-cutting technologies in support of a broad range of nuclear reactor technologies and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. In line with these program objectives, this collaborative studies aim to explore new materials utilizing advanced manufacturing technologies. The FY23 research scope consists of the feasibility studies on new materials and relevant advanced manufacturing technologies, collection of materials properties data and knowledge through experiments and literature survey, and development and application of decision criteria matrix for downselecting candidate materials and manufacturing technologies. The three-laboratory efforts for FY23 have focused on the three new material groups including oxide dispersion strengthened (ODS) materials, refractory composites and alloys, and high entropy alloys (HEAs) investigated, respectively, by Oak Ridge National Laboratory (ORNL) (work package: CT-23OR130406), Los Alamos National Laboratory (LANL) (CT-23LA130403) and Pacific Northwest National Laboratory (PNNL) (CT-23PN130408). The execution of this multi-lab research aimed to provide the AMMT program a merit-based feasibility study identifying an accelerated development path for these materials. A collaborative approach for achieving this goal was to develop a common materials evaluation criteria matrix and apply to all new candidate materials for the evaluation and prioritization of new materials using advanced manufacturing processes. The decision criteria matrix created is a matrix of criteria which a prospective material is scored against. The evaluation criteria are divided into four categories: Application Space, Environmental Compatibility, Physical & Mechanical Properties, and Manufacturability. Materials are given a score from 1−5 for each criterion, with the highest score (5) essentially mean that a material has the most near-term potential for application. Application of the decision criteria matrix will provide guidance to the future research on new materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Multimode Characterization Approach for Understanding Cell-Level PV Performance and Degradation

Cell-level degradation processes impact the economic viability and large-scale deployment prospects for both established and emerging photovoltaic (PV) technologies. This project addresses the need to develop experimental and device-modeling approaches for studying cell-level degradation processes in photovoltaic (PV) devices using a variety of characterization techniques that provide access to complementary material and device properties. Our results demonstrate that by coupling characterization results with device modeling it is possible to develop comprehensive understanding of processes leading to performance limitations and degradation. This project developed a suite of novel measurement techniques including pulsed-light-bias operando X-ray and photoelectron spectroscopy (popXPS), light-biased scanning microwave impedance microscopy (sMIM), and near-field transport imaging (TI). In addition, operando characterization methodologies and in situ stressing capabilities have been developed and applied for techniques including electron-beam-induced current (EBIC), cathodoluminescence (CL), and Kelvin probe force microscopy (KPFM). Device-physics models were developed and applied to simulate correlative, multi-mode measurements to extract material and device parameters that control performance degradation. These characterization and modeling techniques were applied in a multi-mode approach to probe cell-level degradation mechanisms in Cd(Se,Te) and hybrid perovskite PV devices. Together these efforts contribute to foundational PV degradation science by establishing a framework for understanding PV performance degradation at the cell level and benefit the U.S. PV industry by providing resources in the form of novel experimental capabilities, knowledge gained, and available expertise that can accelerate research and development of improved PV device materials and architectures. The project provided a comprehensive understanding of degradation in baseline Cd(Se,Te) solar cells provided by our collaborators at Colorado State University (CSU). EBIC and CL-based measurements and revealed unusual collection and recombination profiles in these devices, which underwent significant changes with during stressing. KPFM and operando XPS measurements showed that device stressing permanently alters energy-band alignments at the (Mg,Zn)O/Cd(Se,Te) interface, which in turn account for an observed loss in fill factor. Studies on hybrid perovskite devices were hampered to a significant extent by delays related to the pandemic. Nevertheless, a set of hybrid perovskite devices (supplied through an NREL-industry partnership) were stress tested and characterized with techniques including EBIC, sMIM, popXPS/popUPS and optically excited TI. Available results from these measurements informed the device modeling effort and suggest that defects and related band offsets at the C60/LiF/hybrid perovskite interface are the primary source of degradation in these devices.

14 SOLAR ENERGY↗

DOE OSTI2025

Develop Accurate Techniques for Passive SiC Temperature Monitoring of Miniature Samples for Cross-Cutting Applications

Passive thermometry is critically important because most fuels and materials irradiation experiments are not instrumented, and it is necessary to understand the irradiation temperature to properly interpret any post-irradiation examination data, including evolving properties and/or microstructures. The standard passive thermometry approach uses continuous dilatometry to evaluate changes in the instantaneous coefficient of thermal expansion during post-irradiation thermal annealing. This approach has limitations in terms of sample size (minimum length requirements) and the maximum irradiation temperature that can be accurately determined, which is limited by the reduced swelling (and therefore recovery) following higher temperature irradiation and limitations on the furnaces used with push-rod dilatometers. This work evaluates two new proposed techniques for post-irradiation evaluation of passive SiC temperature monitors: differential scanning calorimetry (DSC) and Raman spectroscopy. DSC is an extremely sensitive technique that can be used for any specimen geometry and is capable of higher temperature operation. Raman spectroscopy is similar in that it is a surface technique capable of examining extremely small samples (submillimeter), can be used with a heated stage up to 1,500°C (planned for future work), and is capable of mapping local irradiation temperatures throughout a sample. Existing SiC samples that were previously irradiated over a wide range of temperatures were cut into multiple pieces to allow for annealing studies using multiple different techniques: dilatometry, DSC, and Raman spectroscopy. This approach mitigates the concern that samples analyzed using one technique may have a slightly different irradiation history than those analyzed using a different technique. Recovery was clearly observed during annealing using both DSC and dilatometry. In some cases, a direct comparison could not be made due to some of the DSC runs accidentally including material from multiple specimens and issues with using an alternative DSC sample holder for the highest temperature annealing studies. Nevertheless, one trend was clear: the DSC runs resulted in higher irradiation temperatures compared to those of the dilatometry runs. Part of this could be attributed to the higher temperature ramp rates used during the DSC runs, which are often preferred to reduce noise in the measurements. By comparison, dilatometry has previously been shown to produce better data at lower ramp rates. Future work should further investigate the ideal ramp rate for both techniques to produce consistent results. Additional work should evaluate the best holder material to use for DSC runs exceeding 1,000°C to provide reliable data while preventing interactions between SiC and the holder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Develop Accurate Techniques for Passive SiC Temperature Monitoring of Miniature Samples for Cross-Cutting Applications

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Role of geometric dynamic recrystallization in nanocrystalline alloys

Nanocrystalline and near-nano-grained metals are plagued with an overall lack of ductility and formability. This is in part due to their inability to support the dislocation mechanisms or undergo the same types of transformations that conventional coarse-grained metals access in order to increase their workability. Therefore, despite their advanced properties such as high strength, the manufacturing of such fine-grained metals, which exposes them to multi-axial states of stress in operations such as rolling, drawing, extrusion, forging, and bending, has not been possible. In this work, we address this limitation and highlight an important aspect of geometric dynamic recrystallization (GDRX) in nanocrystalline materials as a way to improve manufacturability. In particular, using two different alloy compositions and two different processing techniques, this study points to the fact that if nanocrystalline or near nano metals can be truly stabilized, they can repeatedly undergo the same types of processes that conventional coarse-grained metals endure, increasing both their formability and hence manufacturability. The results reveal that due to a large number of initial high-angle grain boundaries and large applied compressive strains, GDRX is activated in the absence of any discontinuous dynamic recrystallization (DDRX) or continuous dynamic recrystallization (CDRX). This is a unique aspect of stabilized nanocrystalline materials, as traditionally fine-grained metals are not microstructurally stable enough to accommodate such an event.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Thermal Evolution of Internal Strain in Doped PbTe

Recent improvements in the efficiency of heat-to-electricity energy conversion in lead chalcogenide thermoelectrics involve reducing the thermal conductivity by incorporating large amounts of internal strain. The extent to which typical lead chalcogenide processing techniques (such as doping, ball milling, and densification) increase internal strain and dislocation density must be quantified to improve materials design. In this study, neutron powder diffraction is leveraged to evaluate the internal strain introduced by ball milling in doped and undoped powders. Doping with Na and/or Eu increases internal strain beyond ball milling alone, with the greatest increase from combining the two dopants. Strain recovery occurs in each powder above 400 K but can be suppressed by co-doping, indicating a strong dopant–dislocation interaction in this system. Therefore, high-temperature processing of PbTe powders should be avoided if high internal strain is desired. Low-temperature densification and/or rapid pressing techniques may be key to maintaining internal strain in the final pressed pellet. The diffraction peak asymmetry and correlated elastic softening measured in pressed PbTe pellets in past studies were not observed in the precursor powders measured here, suggesting that measurements of the Debye temperature on final pressed pellets are required to examine the influence of defect-induced elastic softening on thermal conductivity. This work provides key guidance for defect engineering to maximize internal strain and thermoelectric performance in PbTe thermoelectrics.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Past, present and future—sample environments for materials research studies in scattering and spectroscopy; a UK perspective

Small Angle X-Ray Scattering (SAXS) and X-Ray Absorption Fine Structure (XAFS) are two techniques that have been employed at synchrotron sources ever since their inception. Over the course of the development of the techniques, the introduction of sample environments for added value experiments has grown dramatically. This article reviews past successes, current developments and an exploration of future possibilities for these two X-ray techniques with an emphasis on the developments in the United Kingdom between 1980-2020.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling

Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property can lead to significant advancements in scientific discovery. Graph Neural Networks (GNNs) represent the state-of-the-art approach for modeling atomistic material data thanks to their capacity to capture complex relational structures. While machine learning performance has historically improved with larger models and datasets, GNNs for atomistic materials modeling remain relatively small compared to large language models (LLMs), which leverage billions of parameters and terabyte-scale datasets to achieve remarkable performance in their respective domains. To address this gap, we explore the scaling limits of GNNs for atomistic materials modeling by developing a foundational model with billions of parameters, trained on extensive datasets in terabytescale. Our approach incorporates techniques from LLM libraries to efficiently manage large-scale data and models, enabling both effective training and deployment of these large-scale GNN models. This work addresses three fundamental questions in scaling GNNs: the potential for scaling GNN model architectures, the effect of dataset size on model accuracy, and the applicability of LLM-inspired techniques to GNN architectures. Specifically, the outcomes of this study include (1) insights into the scaling laws for GNNs, highlighting the relationship between model size, dataset volume, and accuracy, (2) a foundational GNN model optimized for atomistic materials modeling, and (3) a GNN codebase enhanced with advanced LLM-based training techniques. Our findings lay the groundwork for large-scale GNNs with billions of parameters and terabyte-scale datasets, establishing a scalable pathway for future advancements in atomistic materials modeling.

Li, Chaojian [ORNL] (ORCID:0000000340309777)↗

DOE OSTI2023

Performance of Structural Alloys in Bio-oil Production, Upgrading, and Storage Systems

Selection of corrosion-resistant, cost-effective structural materials for the process and containment vessels required for the production, upgrading, and storage of biomass-derived oils has been the subject of study in our laboratory for many years. The wide variety of biomass resources and the many liquefaction techniques and processing conditions result in products with a broad range of properties and compositions. Here, this paper will address the materials issues in three distinct areas. In production, materials are exposed to temperatures that range from 350 to 550 °C depending upon the process. Generally, austenitic stainless steels have performed reasonably well, although thicker oxide scales and intergranular attack have sometimes been observed. For storage and transport of the bio-oil products, temperatures experienced by the containment materials are not expected to exceed 50 °C. Our studies have shown that most raw bio-oils contain significant concentrations of organic acids, and low-molecular-weight organic acids were quite corrosive to carbon and low alloy steels. For some applications, subsequent processing is required, which includes hydrotreating or co-processing with a petroleum-derived liquid. These processes utilize a catalyst that requires periodic retreatment with a sulfidizing gas, and the exposure to this gas at elevated temperatures can cause appreciable corrosion to the more common austenitic stainless steels. The materials considered most cost-effective and sufficiently corrosion-resistant for each of these environments were identified.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Nanoscale mapping of point defect concentrations with $\mathrm{4D-STEM}$

Vacancies are missing atoms in a crystalline material, and occur both at equilibrium (varying with temperature) and out of equilibrium such as when crystalline materials are damaged with radiation or corrosion. While we know of their importance, particularly regarding diffusive mechanisms, it is not straightforward to experimentally measure their concentration or to visualize them directly. Traditionally, measurements such as positron annihilation spectroscopy and to some degree X-ray diffraction can measure average concentrations, but generally lack the ability to visualize or quantify a heterogenous concentration of vacancies that can occur at the level of individual defects and microstructural features. Here, we present a method to map vacancy concentrations and their distribution using local lattice parameter measurements with a high-resolution electron microscope. Our method utilizes a Au thin film as a model to demonstrate the method via four-dimensional scanning transmission electron microscopy (4D-STEM) by correlating the differences between changes in lattice parameter and the volumetric thermal expansion during in situ heating experiments. The vacancy mapping methodology is also applied to non-equilibrium defects accumulated in pure Al via knock-on electron beam irradiation. Our method demonstrates the ability to map point defect concentrations in heterogeneous systems in situ with nanometer spatial resolution. The result is a technique that can provide direct measurements of vacancy concentrations at the level of individual defects in studies of materials in and out of equilibrium.

36 MATERIALS SCIENCE↗