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DOE OSTI2024

Process–Property–Performance Mapping of Additively Manufactured 316H Stainless Steel Components

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development of advanced materials and components fabricated via additive manufacturing, and is using laser powder bed fusion (LPBF) of 316H stainless steel as an initial case study. In the previous fiscal year, miniature high-throughput specimens were printed on multiple LPBF systems to provide initial processing windows to minimize porosity and limit epitaxial grain growth during prints. This fiscal year, scaled builds were completed on three different LPBF systems at ORNL: a GE Concept Laser M2, a Renishaw AM400, and an EOS M290. Builds on the Concept Laser were conducted on multiple powder lots and processing parameter ranges to provide microstructure effects on time-independent and time-dependent mechanical properties. Builds on the Renishaw were produced using Oak Ridge National Laboratory (ORNL)-optimized printing parameters and Argonne National Laboratory (ANL)-optimized printing parameters to compare outcomes of parallel process optimization efforts at different national laboratories on the same LPBF system. Similarly, the build completed on the EOS M290 replicated the processing parameters of builds completed at Los Alamos National Laboratory (LANL). Optical microscopy and electron backscatter diffraction characterization was completed on all builds. In addition to the general round robin characterization, this work-package generated time-independent data, including tensile and fracture toughness test data on scaled Concept Laser builds as a function of processing parameters and post-build heat treatment. This analysis is complimentary to work in parallel work packages aiming to establish heat treatment and processing effects on time-dependent properties. It was found that although the stress-relief heat treatment provides the highest strength at lower-temperatures, tensile strength begins to converge at higher temperatures regardless of heat treatment condition. In addition, the more rigorous solution annealing and hot-isostatic pressing post-build heat treatments result in higher fracture toughness than the stress-relieved condition. The root-causes of the lower fracture toughness of the stress-relieved LPBF 316H material was informed via a stress-relief optimization study on a scaled concept laser print, where it was found that although dislocation recovery was largely complete after only a couple hours at 650°C, the extended hold of the current 24h heat treatment employed on scaled builds likely caused increased carbide volume fractions along the LPBF 316H grain boundaries, thereby deteriorating crack propagation resistance. This trend was seen to become more deleterious with additional increases of stress-relief temperature to 750°C or 850°C. These results have helped inform a new optimal stress-relief annealing condition for LPBF 316H for future campaign testing (650°C for 2h).

36 MATERIALS SCIENCE↗

DOE OSTI2024

In situ coherent x-ray scattering reveals polycrystalline structure and discrete annealing events in strongly coupled nanocrystal superlattices

Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials of increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the self-assembly kinetics in these systems have been elucidated and related to the product characteristics, the weak interparticle bonding interactions suggest the superstructures formed could continue to order within the solution long after the primary nucleation and growth have occurred, even though the mechanism of annealing remains to be elucidated. Here, we use a combination of Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy to create real-space maps of supercrystalline order along with a real-time view of the strain fluctuations in aging strongly coupled nanocrystal superlattices while they remain suspended and immobilized in solution. By combining the results, we deduce that the self-assembled superstructures are polycrystalline, initially comprising multiple nucleation sites, and that shear avalanches at grain boundaries continue to increase crystallinity long after growth has substantially slowed. This multimodal approach should be generalizable to characterize a breadth of materials in their native chemical environments, thus extending the reach of high-resolution coherent x-ray characterization to the benefit of a much wider range of physical systems. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

DOE OSTI2025

X-ray Diffraction Studies of Single-Crystal Materials for Broad Battery Applications

Single-crystal materials have attracted growing interest in battery research due to their well-defined crystallographic orientation, absence of grain boundaries, and enhanced mechanical and electrochemical stability. This Review provides a comprehensive overview of recent advances in the synthesis, structural evolution, and performance optimization of single-crystal electrodes and solid electrolytes. Particular focus is placed on the application of advanced X-ray diffraction (XRD) techniques, including operando synchrotron diffraction, reciprocal space mapping, and Bragg coherent diffraction imaging, which have enabled in-depth investigations of lattice strain, cation disorder, phase transitions, and defect formation. Representative case studies across Ni-rich layered oxides, spinel-type cathodes, and garnet-based electrolytes are examined to highlight the structural features unique to single crystals. Additionally, the synergistic integration of XRD with machine learning, tomography, and spectroscopy is discussed as a powerful direction for real-time analysis and predictive modeling. Furthermore, these insights provide critical guidance for the rational design of high-performance single-crystal materials in lithium, sodium, and solid-state battery systems.

25 ENERGY STORAGE↗

DOE OSTI2024

Revealing the hidden structure of disordered materials by parameterizing their local structural manifold

Abstract Durable interest in developing a framework for the detailed structure of glassy materials has produced numerous structural descriptors that trade off between general applicability and interpretability. However, none approach the combination of simplicity and wide-ranging predictive power of the lattice-grain-defect framework for crystalline materials. Working from the hypothesis that the local atomic environments of a glassy material are constrained by enthalpy minimization to a low-dimensional manifold in atomic coordinate space, we develop a generalized distance function, the Gaussian Integral Inner Product (GIIP) distance, in connection with agglomerative clustering and diffusion maps, to parameterize that manifold. Applying this approach to a two-dimensional model crystal and a three-dimensional binary model metallic glass results in parameters interpretable as coordination number, composition, volumetric strain, and local symmetry. In particular, we show that a more slowly quenched glass has a higher degree of local tetrahedral symmetry at the expense of cyclic symmetry. While these descriptors require post-hoc interpretation, they minimize bias rooted in crystalline materials science and illuminate a range of structural trends that might otherwise be missed.

36 MATERIALS SCIENCE↗

DOE OSTI2025

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from 7 Perennial and 7 Intermittent Streams across San Antonio, Texas (v3)

This dataset supports a broader study examining the effects of intermittency on sediment respiration. The dataset provides sediment and surface water geochemistry and in situ sensor data from 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). Related data were collected and will be published separately in collaboration with A. Veach. The data package was originally published in April 2025. It was updated in June 2025 (v2; modified and new files) and September 2025 (v3; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) sediment grain size data; (4) sediment iron (II) data and averages; (5) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment percent carbon and nitrogen; (11) sediment X-ray diffraction (XRD) data; (12) gravimetric moisture and averages; (13) a subfolder with sediment incubation respiration data, scripts, and plots; (14) surface water and sediment FTICR methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: The data processing methods for FTICR described in “v3_WHONDRS_AV1_Methods_Codes.csv” mistakenly indicate that users should process the data in Formultitude. The corrected description should read: “Both unprocessed and processed data are provided to allow users flexibility in data processing. Instructions and scripts for processing the data using CoreMS are included.” CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Synthesis and properties of bulk cobalt-carbide permanent magnets

Nanocrystalline bulk Co-C permanent magnets were produced by rapid hot consolidation of ball milled powder precursors. Bulk magnets with an average grain size of 20 nm and densities up to 94 percent of the theoretical density were successfully processed at pressures exceeding 1 GPa for the first time. Their microstructural and magnetic properties along with their magnetocrystalline anisotropy values are reported. Presence of iron contamination that results from the use steel milling media in milling was confirmed by elemental mapping of the bulk magnets. It is concluded that iron bonds in the form of hematite and does not adversely affect coercivity values. Here, this study shows that the Co 3 C compound does possess a sizable magnetocrystalline anisotropy, making it a suitable candidate as a rare earth free permanent magnet.

Co3 C↗

DOE OSTI2026

Emergence of vorticity and viscous stress in finite-scale quantum hydrodynamics

The Madelung equations offer a hydrodynamic description of quantum systems, from single particles to quantum fluids. In this formulation, the probability density is mapped onto the fluid density and the phase is treated as a scalar potential generating the velocity field. As examples of potential flows, quantum fluids described in this way are inherently irrotational, but quantum vortices may arise at discrete points where the phase is undefined. In this paper, starting from this irrotational description of a quantum fluid, a coarse-graining procedure is applied to arrive at a macroscopic description of the quantum fluid in terms of a hierarchy of moments in which the role of velocity is played by a Favre average of the microscopic velocity field. This hierarchy is truncated using an explicit closure derived from an expansion in a finite length scale. The resulting coarse-grained fields are shown to allow for finite vorticity at any point in the fluid. Additionally, it is shown that this vorticity obeys a similar equation to the vorticity equation in classical hydrodynamics and includes a vortex-stretching term. The particular closure employed here also gives rise to a novel stress term in the fluid equations, which in the appropriate limit appears analogous to an artificial viscous stress from computational fluid dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

DOE OSTI2025

DeepAndes: A Self-Supervised Vision Foundation Model for Multispectral Remote Sensing Imagery of the Andes

By mapping sites at large scales usingremotely sensed data, archaeologists can generate unique insights into long-term demographic trends, interregional social networks, and human adaptations in the past. Remote sensing surveys complement field-based approaches, and their reach can be especially great when combined with deep learning and computer vision techniques. However, conventional supervised deep learning methods face challenges in annotating fine-grained archaeological features at scale. In addition, while recent vision foundation models have shown remarkable success in learning large-scale remote sensing data with minimal annotations, most off-the-shelf solutions are designed for RGB images rather than multispectral satellite imagery, such as the eight-band data used in our study. In this article, we introduce DeepAndes, a transformer-based vision foundation model trained on three million multispectral satellite images, specifically tailored for Andean archaeology. DeepAndes incorporates a customized DINOv2 self-supervised learning algorithm optimized for eight-band multispectral imagery, marking the first foundation model designed explicitly for the Andes region. We evaluate its image understanding performance through imbalanced image classification, image instance retrieval, and pixel-level semantic segmentation tasks. Our experiments show that DeepAndes achieves superior F1 scores, mean average precision, and Dice scores in few-shot learning scenarios, significantly outperforming models trained from scratch or pretrained on smaller datasets. This underscores the effectiveness of large-scale self-supervised pretraining in archaeological remote sensing.

Guo, Junlin [Vanderbilt Univ., Nashville, TN (Unit↗

DOE OSTI2025

Σ3(111) Grain Boundaries Accelerate Hydrogen Insertion into Palladium Nanostructures

Grain boundaries (GBs) are frequently implicated as key defect structures facilitating metal hydride formation, yet their specific role remains poorly understood due to their structural complexity. Here, we investigate hydrogen insertion in Pd nanostructures enriched with well-defined Σ3(111) GBs (Pd GB ) synthesized via electrolysis-driven nanoparticle assembly. In situ synchrotron X-ray diffraction reveals that Pd GB exhibits dramatically accelerated hydriding and dehydriding kinetics compared with ligand-free and ligand-capped Pd nanoparticles with similar crystallite sizes. Strain mapping using environmental transmission electron microscopy shows that strain is highly localized at GBs and intensifies upon hydrogen exposure, indicating preferential hydrogen insertion along GB sites. Density functional theory calculations provide mechanistic insight supporting these findings, showing that hydrogen insertion near Σ3(111) GBs is energetically more favorable and that tensile strain lowers insertion barriers. Furthermore, these results provide atomic-level insights into the role of GBs in hydride formation and suggest new design strategies for GB-engineered Pd-based functional materials.

Anions↗

DOE OSTI2024

Elucidating the mechanical and thermal response of nanotwinned Ni alloys

Transformative advances in nanoscale materials synthesis, characterization and modeling are enabling the synthesis of materials with unprecedent properties and greater understanding of the nanoscale mechanisms that underpin these properties. Nanotwinned Cu alloys have received considerable attention due to their impressive balance of strength and ductility, but they have limited microstructural stability. Recent instantiation of nanotwins in sputter deposited Ni-Mo-W, and several commercial Ni-based superalloys, point to the potential development of a new class of high temperature materials with a very beneficial suite of mechanical and physical properties. The experimental study described in this report was undertaken to elucidate the nanoscale origins of the thermal and mechanical behavior of nanotwinned Ni alloys. Micropillar compression experiments have shown nanotwinned Ni 85 Mo 15-x W x alloys to possess unusually high strengths above 3.5GPa and enhanced microstructural stability. The strength of these nanotwinned alloys is determined by the abrupt formation of shear bands. This study focused on identifying the nanoscale trigger, or triggers, for shear banding in nanotwinned materials using in situ experiments and atomic-scale postmortem analysis. Contrasting and comparing the mechanical response and postmortem nanostructures of “Mo-rich” and “W-rich” nanotwinned specimens elucidated the importance of the lateral motion of easy glide defects that results in erasure of twins and local coarsening of the nanotwinned microstructure. This twin coarsening was then associated with very localized plasticity, strain softening, and shear band formation. The difference between alloys was further studied by considering the role of various material factors: stacking fault energy, coherent twin boundary spacing and flatness, grain size, and the interactions of solute atoms with twin and grain boundaries. The effect of alloy composition and sputtering power and temperature were also investigated and used to control twin spacing and geometry. Combined with atomic-scale simulations, these experiments insights should allow us to identify strategies for achieving concomitant ultrahigh strength and ductility in nanotwinned Ni alloys. In parallel but synergistic studies, our work was buoyed by collaborative state-of-the-art nanoscale orientation and strain mapping at the DOE National Center for Electron Microscopy (NCEM). For example, novel 4D-STEM techniques were used to acquire nanoscale strain maps. The extremely fine twin spacing limited our measurements of atomic-scale thermal expansion within twins, but recent results from NCEM suggest that it will soon be possible to conduct such measurements and to unravel the origins of the novel thermal expansion characteristics of nanotwinned Ni alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Effect of Propagating Dopant Reactivity on Lattice Oxygen Loss in LLZO Solid Electrolyte Contacted with Lithium Metal

Lithium lanthanum zirconium oxide (LLZO) is widely known as the most stable solid electrolyte against lithium metal electrodes. This thermodynamic stability can be lost by the presence of dopants which are required to stabilize the cubic phase of LLZO and can be reduced by lithium metal. However, the role of oxygen in such reactions is taken for granted. In this work, the reduction of Nb-substituted LLZO (Nb-LLZO) is explored by Li metal and shows that interfacial reactions propagate and lead to the decomposition with substantial Nb 5+ reduction deep into the bulk electrolyte. Scanning Transmission Electron Microscopy with Energy Dispersive X-ray Spectroscopy and thermogravimetric analyses show much of the reduction is due to oxygen vacancies formed, leading to increased electronic conductivity mapped with conductive Atomic Force Microscopy. Density functional theory calculations indicate oxygen release is favored by increased excess lithiation of Nb-LLZO. Electrochemical impedance of polycrystalline Nb-LLZO shows the continuous evolution of ionically resistive interphases near the lithium metal interface with Nb-LLZO while single crystals show little reactivity at room temperature and self-limiting reduction at 60°C. This work underlines the role of grain boundaries in propagating destructive solid electrolyte reactions and highlights previously unseen mechanisms involving lattice oxygen in LLZO.

Li metal, solid-state electrolytes↗

DOE OSTI2025

Boron Nitride-Driven Strengthening of Aluminum Composites via Friction Stir Processing

Friction stir welding and processing (FSW/P) has emerged as an effective solid-state joining technique for fabricating metal matrix composites (MMCs), offering improved mechanical properties through refined microstructural evolution. In this study, an aluminum-boron nitride nanoparticle (Al-BNNP) composite was synthesized via FSW, and its indentation-based mechanical properties were systematically evaluated. Microhardness mapping across the weld cross-section revealed a progressive increase in hardness toward the stir zone (SZ), attributed to severe plastic deformation, dynamic recrystallization (DRX), and the reinforcing effect of BNNPs. Profilometry-based indentation plastometry (PIP) inferred yield strength (YS) demonstrates a 47.8% increase compared to the base metal (BM) and a 75% improvement compared to FSP pure aluminum reported in literature. This enhancement is attributed to strengthening mechanisms, including grain boundary pinning, load transfer, and increased dislocation density. The strain rate sensitivity (SRS) measurements at the nanoscale demonstrated a substantial decrease in the SZ, correlated with ultrafine grain structures and strong BNNP-matrix interactions. Activation volume analysis revealed a significant reduction in the SZ, suggesting that dislocation motion is increasingly restricted by dislocation-dislocation and dislocation-particle interactions. These findings suggest that incorporating BNNPs in FSW/P enables tailoring the microstructure without thermal degradation of the secondary particles, thereby significantly enhancing the mechanical performance of aluminum composites, particularly for structural applications in aerospace and automotive industries.

Aluminum↗

DOE OSTI2025

Multimodal characterization of Te inclusions in Cd 1−x Zn x Te and Cd 1−x Zn x Te 1−y Se y for gamma and X-ray detectors

While CdZnTe (CZT) and CdZnTeSe (CZTS) semiconductors have emerged as compounds for room-temperature gamma and X-ray detection materials, they continue to be constrained by the formation of Te-inclusion defects generated during the growth and post-growth phases of the material, which adversely affect the detector performance. We demonstrate the utility of multimodal microscopic imaging and analysis for the characterization of the optical and electronic properties of Te inclusions in CZT and CZTS crystals at both micron and nanometer length scales. Having first identified regions with micron-scale Te inclusions using confocal Raman microscopy techniques, optically coupled infrared scattering near-field optical microscopic mapping was performed to map the distribution of these inclusions with nanometer spatial resolution and correlate the presence of Te inclusions in the matrix with other properties. Kelvin probe force microscopy was then utilized to characterize the variations of the work function associated with the presence of Te inclusions. Here, we observe an increase of ~ 240 mV in the work function associated with Te inclusions compared to the bulk CZT/CZTS crystals. Additionally, we observe that individual bulk grains in CZT can exhibit slight potential variations. Our findings develop a portrait of the charge trapping mechanisms in CZT and CZTS that act to degrade detector performance, while the demonstration of these combined microscopy techniques provides a new analytical tool that can be utilized for further optimization of the detector performance for these semiconducting compounds.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Correlating microstructure and mechanical properties of harvested high dose Zorita light water reactor internals

Here, in this study, microstructural studies and micro-mechanical testing of an ex-plant material harvested from the decommissioned pressurized water reactor (PWR) is carried out. Irradiated 304 stainless steel (SS) components were harvested by the Electric Power Research Institute, U.S. Nuclear Regulatory Commission, and members of the José Cabrera Nuclear Power Station (Zorita) in Spain. The bi-crystalline micro-tensile specimens, atom probe tomography (APT) tips, and transmission electron microscopy (TEM) lamellae were fabricated from the baffle plate materials irradiated to 0.05, 15 and 50 dpa to elucidate microstructural, microchemical, and local mechanical properties changes as a function of dose. TEM and APT studies reveal radiation induced Ni, Cr, and Si rich precipitates in the 15 dpa sample that become smaller and partially redissolve into the matrix of the 50 dpa sample (decreasing size and number density). Dislocation loop and cavity number density and size were quantified as a function of dose as well as swelling. Intergranular Ni and Si enrichments with concomitant Fe and Cr depletion were observed in the 15 dpa sample and were more pronounced in the 50 dpa sample. Micro-tensile testing performed in the scanning electron microscope (SEM) at room temperature and 300 °C shows that the material's local yield strength and ultimate tensile strength decreases with increased dose and elevated test temperature and provides further insights via localized strain mapping. Current and previous mechanical data was compared with calculated values using the dispersed barrier hardening model with inputs of dislocation loops, precipitates, and cavities from microstructural characterization.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Interface instabilities in hafnium hydride entrained iron metal matrix composites

The chemical interactions in Fe–HfH 2 metal matrix composites (MMCs) are studied across multiple length scales to elucidate the decomposition of the parent phases and corresponding reaction zone physics during direct current sintering. Fe–HfH 2 composites were synthesized with increasing as-mixed hydride contents of Fe–25% HfH 2 , Fe–40% HfH 2 , Fe–55% HfH 2 , and Fe–70% HfH 2 (all in vol. %) to demonstrate the ability to achieve sintered MMCs with target hydride contents. Samples were probed across multiple length scales through a multi-modal workflow employing x-ray diffraction, scanning electron microscopy and segmentation analysis, and synchrotron techniques including hard x-ray fluorescence mapping and nanoprobe x-ray absorption near-edge structure measurements. Under the selected sintering temperature and pressure conditions, hydrogen evolution is seen to evolve through parallel paths: thermal decomposition from during the transformation of HfH 2 to HfH x<2 and through subsequent reaction with the Fe matrix leading to intermetallic phase formation. Specifically, HfFe and HfFe 2 intermetallic formation accelerates the release of hydrogen with a subsequent HfO 2 phase forming at grain boundaries. For this MMC, the consumption or loss of hydrogen can be considerable in compacts with initial hydride loading of 25%–40% HfH 2 approaching 83% hydrogen loss for the lower volume fraction composites. Increasing the volume fraction of HfH 2 to 70% enhanced the retained hydrogen content to 53% and attributed to the reduced interfacial area intrinsic to the increased HfH 2 loading in this MMC.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Dual-RNA-sequencing to elucidate the interactions between sorghum and Colletotrichum sublineola

In warm and humid regions, the productivity of sorghum is significantly limited by the fungal hemibiotrophic pathogen Colletotrichum sublineola , the causal agent of anthracnose, a problematic disease of sorghum ( Sorghum bicolor (L.) Moench) that can result in grain and biomass yield losses of up to 50%. Despite available genomic resources of both the host and fungal pathogen, the molecular basis of sorghum− C. sublineola interactions are poorly understood. By employing a dual-RNA sequencing approach, the molecular crosstalk between sorghum and C. sublineola can be elucidated. In this study, we examined the transcriptomes of four resistant sorghum accessions from the sorghum association panel (SAP) at varying time points post-infection with C. sublineola . Approximately 0.3% and 93% of the reads mapped to the genomes of C. sublineola and Sorghum bicolor , respectively. Expression profiling of in vitro versus in planta C. sublineola at 1-, 3-, and 5-days post-infection (dpi) indicated that genes encoding secreted candidate effectors, carbohydrate-active enzymes (CAZymes), and membrane transporters increased in expression during the transition from the biotrophic to the necrotrophic phase (3 dpi). The hallmark of the pathogen-associated molecular pattern (PAMP)-triggered immunity in sorghum includes the production of reactive oxygen species (ROS) and phytoalexins. The majority of effector candidates secreted by C. sublineola were predicted to be localized in the host apoplast, where they could interfere with the PAMP-triggered immunity response, specifically in the host ROS signaling pathway. The genes encoding critical molecular factors influencing pathogenicity identified in this study are a useful resource for subsequent genetic experiments aimed at validating their contributions to pathogen virulence. This comprehensive study not only provides a better understanding of the biology of C. sublineola but also supports the long-term goal of developing resistant sorghum cultivars.

Vela, Saddie↗

DOE OSTI2025

Combining four-point bending and corrosion to map stress-dependent corrosion susceptibility of 316H stainless steel in FLiNaK

Understanding the effect of stress on the corrosion of steels in molten salts is important for material screening and safety assessment of molten salt reactors. We present a method that combines four-point bending with corrosion testing, enabling the mapping of corrosion susceptibility as a function of local stress from a single specimen. Guided by finite element analysis, a four-point bending setup was used to bend a 316H stainless-steel bar under controlled elastic stress during a 100-hour exposure in FLiNaK at 700 °C. Post-exposure characterization using scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed a pronounced correlation between stress and corrosion. Regions under tensile stress exhibited significantly deeper attack depths and greater chromium depletion along grain boundaries, whereas compressive zones showed shallower corrosion cracks. The stress effect is attributed to stress concentration under tensile loading, which promotes chromium dissolution and crack propagation. This technique can be readily applied to other structural alloys, enabling quantitative measurement of corrosion susceptibility as a function of local stress.

316H↗