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Competition and cooperation: The plasticity of bacterial interactions across environments

Bacteria live in diverse communities, forming complex networks of interacting species. A central question in bacterial ecology is whether species engage in cooperative or competitive interactions. But this question often neglects the role of the environment. Here, we use genome-scale metabolic networks from two different open-access collections (AGORA and CarveMe) to assess pairwise interactions of different microbes in varying environmental conditions (provision of different environmental compounds). By computationally simulating thousands of environments for 10,000 pairs of bacteria from each collection, we found that most pairs were able to both compete and cooperate depending on the availability of environmental resources. This modeling approach allowed us to determine commonalities between environments that could facilitate the potential for cooperation or competition between a pair of species. Namely, cooperative interactions, especially obligate, were most common in less diverse environments. Further, as compounds were removed from the environment, we found interactions tended to degrade towards obligacy. However, we also found that on average at least one compound could be removed from an environment to switch the interaction from competition to facultative cooperation or vice versa. Together our approach indicates a high degree of plasticity in microbial interactions in response to the availability of environmental resources.

Biochemistry & Molecular Biology

Examining Graphite Degradation in Molten Salt Environments: A Chemical, Physical, and Material Analysis

Molten-salt reactors (MSRs) are Generation IV nuclear reactors that use liquid salt as a coolant and/or fuel. In several MSR designs, graphite serves as a moderator and/or reflector. However, due to limited experimental data and operational experience, our understanding of graphite behavior in molten salt environments remains incomplete. This report aims to identify the degradation mechanisms of nuclear graphite in MSRs, detail the mechanisms of each factor, and provide an initial assessment of their impact on the structural integrity of graphite components. This assessment is based on an extensive literature review and insights from subject matter experts. Furthermore, given the limited data, a modeling strategy using existing Grizzly software is proposed for a more thorough analysis where appropriate. Additionally, it presents mitigation strategies where applicable. The report covers physical degradation mechanisms such as infiltration, erosion, and abrasion, as well as chemical degradation mechanisms including fluorination, intercalation, corrosion, and oxidation. Molten salt can infiltrate the porous structure of graphite, leading to several detrimental effects. Entrapment of fissile products within the graphite pores can cause radiation damage and could pose challenges in the handling and disposal of contaminated components. The differential thermal expansion between the infiltrated salt and graphite, along with internal stress from pressurized molten salt and volumetric heating, can compromise the structural integrity of graphite. To mitigate these effects, employing ultra-fine graphite grades and applying sealants and coatings are effective strategies. A computational model based on coupled solid mechanics and heat transfer phenomena could be used to predict the internal stresses using Grizzly software. In pebble-bed MSRs, graphite fuel pebbles can cause abrasion against reactor components due to friction and wear. The severity of wear is influenced by various factors such as temperature, environment, and the presence of lubricants. Tribological studies reveal that higher temperatures and molten salt environments, such as FLiBe, significantly reduce wear rates compared to dry conditions. Additionally, the chemical composition of the salt can further optimize graphite's tribological performance. Long-term wear effects can be modeled by incorporating surface defects into the geometry and predict stresses under thermal and radiation effects using Grizzly software. Chemical degradation of graphite in a molten salt environment can occur through fluorination and intercalation. Fluorination can occur via replacement of hydrogen or oxygen atoms, or at the active sites, but does not cause structural degradation. Intercalation, on the other hand, can lead to exfoliation, where layers of graphite separate and peel away, damaging the graphite. Protective coatings can enhance graphite's resistance to intercalation. Graphite generally exhibits good chemical stability in molten salt environments, though it can corrode under specific conditions, particularly in the presence of impurities or oxidants. Studies have shown that protective coatings, such as plasma-sprayed partially stabilized zirconia (PSZ), can effectively prevent such degradation. Corrosion behavior varies significantly with different graphite grades and coating applications, underscoring the need for detailed studies on uncoated and coated graphite to understand and mitigate corrosion mechanisms in MSRs. Research indicates that the presence of oxidants and impurities can accelerate graphite degradation in molten salts, making it essential to explore acceptable impurity limits. Oxidation is another critical degradation mechanism, leading to weight loss and structural damage due to the formation of CO and CO 2 from the reaction of carbon atoms with oxygen. This process creates new porosity and compromises graphite's integrity. While extensive research on graphite oxidation has been conducted for gas-cooled reactors, studies specific to MSRs are limited. Findings from the coal industry suggest that molten alkali metal salts can significantly accelerate graphite oxidation, a hypothesis worth exploring for fluoride salts in MSRs. Understanding oxidation behavior in MSRs is vital for developing protective measures. The analysis of post-irradiated graphite from the MSRE experiment demonstrated exceptional chemical compatibility with molten fluoride salt, suggesting that the extent of chemical attack on graphite largely depends on the salt's infiltration capability. Therefore, the use of ultra-fine grade graphite could help mitigate chemical degradation effects. Existing oxidation modeling capabilities in Grizzly, which use reaction-diffusion equations to model graphite-air interactions, could be adapted to simulate the chemical degradation effects of graphite in molten salt environments.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Isoconversional Kinetic Analysis of Oxygen Desorption for Sr 0.75 Ca 0.25 FeO 3-δ Perovskite in Dry and Steam-Based Environments

The desorption kinetics of Sr 0.75 Ca 0.25 FeO 3-δ perovskite material are examined in both dry and steam-based environments using redox gaseous products of a laboratory-scale fixed bed. First, desorption kinetics associated with the dry environment are proposed based on Friedman’s isoconversional method. It is found from the reconstructed reaction model that the desorption kinetics of this perovskite are controlled by a three-step mechanism, where hypothetically, the phase-boundary reaction rapidly prevails first, followed by diffusion and/or nucleation, and finally, unimolecular decay or random nucleation-controlled reaction. Subsequent analyses of the Arrhenius parameters indicated that both the early and later desorption stages, respectively, controlled by the phase boundary and unimolecular/random nucleation reactions, are associated with low energetic demand. In contrast, a high energetic penalty is required for the diffusion/nucleation reaction. Further, a satisfactory a priori verification of the proposed kinetics suggested that the three-step reaction mechanism reasonably describes the desorption of this perovskite in a dry environment. With the presence of steam in the desorption environment, oxygen production is substantially inhibited, but the hypothetical three-step mechanism is still found to control the desorption. Meanwhile, the primary effects of the steam on these mechanisms include the widening of the conversion extent associated with the diffusion/nucleation reaction, along with a higher energetic demand compared to the dry environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE

STUDIES ON PIPELINE POLYETHYLENES IN HYDROGEN GAS ENVIRONMENTS USING IN-SITU AND EX-SITU CHARACTERIZATION METHODS

Polymeric materials are commonplace in the natural gas infrastructure as distribution pipes, coatings, seals, and gaskets. Under the auspices of the U.S. Department of Energy HyBlend program, one of the means to reduce greenhouse gas emissions is with replacing natural gas, either partially or completely, with hydrogen. This approach makes it imperative that we conduct near-term and long-term materials compatibility research in these relevant environments. Insights into the effects of hydrogen and hydrogen gas blends on polymer integrity can be gained through both ex-situ and in-situ analytical methods. Our work represented here highlights a study of the behavior of pipeline polyethylene (PE) materials, including HDPE (Dow 2490 and GDB50) and MDPE (Ineos and legacy Dupont Aldyl A), when exposed to hydrogen by means of in-situ X-ray scattering and ex-situ Raman spectroscopy techniques. Samples were tested in ex-situ hydrogen and argon gas environments and in-situ hydrogen environments to identify differences due to permeation and solubility of these gases. These methods complemented each other because Raman spectroscopy could capture permanent effects after materials were removed from gaseous environments, and in-situ X-ray scattering analysis collected real-time data to elucidate the impact of the gas environment on polymer microstructure. Data collected revealed that the aforementioned polymers did not show significant changes in crystallinity and microstructure under the exposure conditions tested. Our findings from these studies will help establish real-time effects caused by hydrogen gas transport through pipeline polyethylenes by way of its influence on polymer structure and chemistry, which is directly related to pipeline mechanical strength and longevity of service.

Hydrogen materials compatibility, Natural gas pipe

Comparative genomics reveals the high diversity and adaptation strategies of Polaromonas from polar environments

Abstract Background Bacteria from the genus Polaromonas are dominant phylotypes found in a variety of low-temperature environments in polar regions. The diversity and biogeographic distribution of Polaromonas have been largely expanded on the basis of 16 S rRNA gene amplicon sequencing. However, the evolution and cold adaptation mechanisms of Polaromonas from polar regions are poorly understood at the genomic level. Results A total of 202 genomes of the genus Polaromonas were analyzed, and 121 different species were delineated on the basis of average nucleotide identity (ANI) and phylogenomic placements. Remarkably, 8 genomes recovered from polar environments clustered into a separate clade (‘polar group’ hereafter). The genome size, coding density and coding sequences (CDSs) of the polar group were significantly different from those of other nonpolar Polaromonas . Furthermore, the enrichment of genes involved in carbohydrate and peptide metabolism was evident in the polar group. In addition, genes encoding proteins related to betaine synthesis and transport were increased in the genomes from the polar group. Phylogenomic analysis revealed that two different evolutionary scenarios may explain the adaptation of Polaromonas to cold environments in polar regions. Conclusions The global distribution of the genus Polaromonas highlights its strong adaptability in both polar and nonpolar environments. Species delineation significantly expands our understanding of the diversity of the Polaromonas genus on a global scale. In this study, a polar-specific clade was found, which may represent a specific ecotype well adapted to polar environments. Collectively, genomic insight into the metabolic diversity, evolution and adaptation of the genus Polaromonas at the genome level provides a genetic basis for understanding the potential response mechanisms of Polaromonas to global warming in polar regions.

54 ENVIRONMENTAL SCIENCES

Assessment of Vibration and Shock Loading Environments on Steels Used in Railroad Applications Considering Hydrogen Embrittlement

Studies that examine the combined effects of hydrogen and rail loading environments in the context of hydrogen embrittlement of steels have not been performed. Large-scale hydrogen storage requires either gaseous hydrogen stored in pressure vessels and tubing or liquid hydrogen in cryogenic, insulated tanks. Since the focus of this study is on steels, we examine the influence of hydrogen on stainless steel used for high pressure tubing and cryogenic tanks and Cr-Mo steel liners used in gaseous pressure vessels. Literature studies show that despite hydrogen degradation, these steels can be used effectively and safely if the stresses are managed. The shock and vibration environment on railcars present unique environments where stresses and loading rates can be high. A literature review was conducted to understand the accelerations experienced in rail by examining instrumented railcars of nuclear fuel casks. Hydrogen studies were examined that focused on steel pressure hardware with an emphasis on fatigue, fast loading rates, and low temperatures. A simplified fatigue assessment was performed to examine design cycles for three different hydrogen components: stainless steel tubing, stainless steel cryogenic tanks, and gaseous pressure vessels. The assessments were idealized and used bounding cases of accelerations in both normal rail conditions and coupling events. In normal shock and vibration environments when accelerations were less than 2 g, infinite design life was calculated. In extreme shock or coupling environments, finite design life was calculated which was shown to be dependent on unsupported lengths of pressure components. It was shown that adjusting the unsupported length can reduce the bending stress thereby increasing design life.

36 MATERIALS SCIENCE

Portable Software Environment for Ultrahigh-Resolution ELM Development on GPUs

This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development.

E3SM Land Model

Synthetic Digital Environments for Training Robots on Earth & Beyond [Poster]

Creating physical replicas of real-world environments to train robots for challenging outdoor tasks, whether constructing energy infrastructure like solar farms on Earth or on the Moon and Mars, is prohibitively expensive. This project will prototype a high-fidelity digital twin framework using NVIDIA IsaacSim to create realistic digital representations of robotic systems and their operating conditions, including varied terrains and environmental factors, allowing robots to learn and adapt in a faster, safer, and more affordable way to tackle unpredictable challenges in terrestrial and extraterrestrial applications. The Robotic Space Exploration (RoSE) Lab at Colorado School of Mines focused on the development and testing of synthetic digital twins to explore multi-physics interactions between robots and unstructured environments, with emphasis on lunar conditions such as deformable regolith, reduced gravity, and terrain-robot contact dynamics. The Industrialized Construction Innovation (ICI) team at National laboratory of the Rockies (NLR), simulated robotic apparatus and construction workflows using synthetic digital twins to inform real-world deployment, targeting application-driven use cases such as robotic construction of a scaled prototype of a photovoltaic energy infrastructure. Joint efforts between RoSE and ICI are continuing to explore how environment-scale multi-physics modeling and application-level robotic system simulation could be integrated to support robotic construction of energy infrastructure in highly unstructured environments, including scenarios relevant to the Lunar South Pole.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment

Cataloging and classifying trees in the urban environment is a crucial step in urban and environmental planning; however, manual collection and maintenance of this data is expensive and time-consuming. Although algorithmic approaches that rely on remote sensing data have been developed for tree detection in forests, they generally struggle in the more varied urban environment. This work proposes a novel end-to-end deep learning method for the detection of trees in the urban environment from remote sensing data. Specifically, we develop and train a novel PointNet-based neural network architecture to predict tree locations directly from LiDAR data augmented with multi-spectral imagery. We compare this model to a number of high-performing baselines on a large and varied dataset in the Southern California region, and find that our method outperforms all baselines in terms of tree detection ability (75.5% F-score) and positional accuracy (2.28 meter root mean squared error), while being highly efficient. We then analyze and compare the sources of errors, and how these reveal the strengths and weaknesses of each approach. Our results highlight the importance of fusing spectral and structural information for remote sensing tasks in complex urban environments.

54 ENVIRONMENTAL SCIENCES

The impact of environment on size: Galaxies are 50% smaller in the Fornax Cluster compared to the field

Size is a fundamental parameter for measuring the growth of galaxies and the role of the environment on their evolution. However, the conventional size definitions used for this purpose are often biased and miss the diffuse, outermost signatures of galaxy growth, including star formation and gas accretion. We address this issue by examining low surface brightness truncations or galaxy ‘edges’ as a physically motivated tracer of size based on star formation thresholds. Our total sample consists of ∼900 galaxies with stellar masses ranging from 10 5 M ⊙ < M ⋆ < 10 11 M ⊙ . This sample of nearby cluster, group satellite, and nearly isolated field galaxies was compiled using multi-band imaging from the Fornax Deep Survey, deep IAC Stripe 82, and Dark Energy Camera Legacy Surveys. We find that the edge radii scale as R edge ∝ M ⋆ 0.42 , with a very small intrinsic scatter (∼0.07 dex). The scatter is driven by the morphology and environment of galaxies. In both the cluster and field, early-type dwarfs are systematically smaller by approximately 20% compared to late-type dwarfs. However, galaxies in the Fornax cluster are the most impacted. At a fixed stellar mass, edges in the cluster can be found at about 50% smaller radii, and the average stellar surface density at the edges is a factor of two higher, ∼1 M ⊙ /pc 2 . Our findings support the rapid removal of loosely bound neutral hydrogen (H I ) in hot, crowded environments, which truncates galaxies outside-in earlier, preventing the formation of more extended sizes and lower density edges. Our results highlight the importance of deep imaging surveys to the study of low surface brightness imprints of the large-scale structure and environment on galaxy evolution.

Astronomy & Astrophysics

The beyond-halo mass effects of the cosmic web environment on galaxies

ABSTRACT Galaxy properties primarily depend on their host halo mass. Halo mass, in turn, depends on the cosmic web environment. We explore if the effect of the cosmic web on galaxy properties is entirely transitive via host halo mass, or if the cosmic web has an effect independent of mass. The secondary galaxy bias, sometimes referred to as ‘galaxy assembly bias’, is the beyond-mass component of the galaxy–halo connection. We investigate the link between the cosmic web environment and the secondary galaxy bias in simulations. We measure the secondary galaxy bias through the following summary statistics: projected two-point correlation function, $w_{\mathrm{p}}(r_{\mathrm{p}})$, and counts-in-cylinders statistics, $P(N_{\mathrm{CIC}})$. First, we examine the extent to which the secondary galaxy bias can be accounted for with a measure of the environment as a secondary halo property. We find that the total secondary galaxy bias preferentially places galaxies in more strongly clustered haloes. In particular, haloes at fixed mass tend to host more galaxies when they are more strongly associated with nodes or filaments. This tendency accounts for a significant portion, but not the entirety, of the total secondary galaxy bias effect. Secondly, we quantify how the secondary galaxy bias behaves differently depending on the host halo proximity to nodes and filaments. We find that the total secondary galaxy bias is relatively stronger in haloes more associated with nodes or filaments. We emphasize the importance of removing halo mass effects when considering the cosmic web environment as a factor in the galaxy–halo connection.

Astronomy & Astrophysics

The ancestral environment of teosinte populations shapes their root microbiome

Summary Background The composition of the root microbiome affects the host’s growth, with variation in the host genome associated with microbiome variation. However, it is not known whether this intra-specific variation of root microbiomes is a consequence of plants performing targeted manipulations of them to adapt to their local environment or varying passively with other traits. To explore the relationship between the genome, environment and microbiome, we sampled seeds from teosinte populations across its native range in Mexico. We then grew teosinte accessions alongside two modern maize lines in a common garden experiment. Metabarcoding was performed using universal bacterial and fungal primers to profile their root microbiomes. Results The root microbiome varied between the two modern maize lines and the teosinte accessions. We further found that variation of the teosinte genome, the ancestral environment (temperature/elevation) and root microbiome were all correlated. Multiple microbial groups significantly varied in relative abundance with temperature/elevation, with an increased abundance of bacteria associated with cold tolerance found in teosinte accessions taken from high elevations. Conclusions Our results suggest that variation in the root microbiome is pre-conditioned by the genome for the local environment (i.e. non-random). Ultimately, these claims would be strengthened by confirming that these differences in the root microbiome impact host phenotype, for example, by confirming that the root microbiomes of high-elevation teosinte populations enhance cold tolerance.

Genetics & Heredity

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY

Verifying LLM generative agents reflect human behavior in contested information environments to effectively simulate disinformation campaigns (Proteus)

Disinformation poses a significant and evolving threat to today’s online environment. Individuals encounter challenges in detecting disinformation, subsequently influencing their behavior and decision-making processes. Our research examines the potential use of large language model (LLM) generative agents (LGAs) to replicate human behavior to better understand how disinformation is spread in online environments. Using human subjects research, we first investigate how personality traits, individual differences, and demographic factors relate to decision-making in simulated online disinformation environments. Then, we examine whether LGAs can effectively replicate human responses in the same simulated online environments when assigned personality traits, demographic characteristics and behavioral attributes. Our findings indicate that LGAs can align with human decisions in these scenarios; however, alignment is contingent upon scenario context, persona settings and LLM selection. Results provide valuable insights for methodology refinement in future research and in utilizing LGAs to model complex national security challenges such as disinformation campaigns.

97 MATHEMATICS AND COMPUTING

Facies Analysis and Depositional Environments of the Upper Cambrian Eau Claire Formation in Central and Northern Illinois

The Cambrian Eau Claire Formation is a confining unit for geologic carbon dioxide (CO2) storage, and potentially a confining unit for hydrogen storage, within the underlying Mount Simon Sandstone in the Central and Northern Illinois Basin. However, extensive regional studies on lateral continuity, environment of deposition, and depositional fabric of the Eau Claire Formation in the Illinois Basin are minimal compared to studies of the underlying Mount Simon Sandstone. This study presents an integrated facies analysis using sedimentological, stratigraphic, ichnological, and mineralogical data to interpret the depositional environments of the Eau Claire Formation, emphasizing the dynamic nature of sedimentary systems. By combining core analyses, thin-section analysis, facies interpretation from geophysical logs, and regional stratigraphic framework interpretation, this work provides insights into the integrated depositional framework across diverse depositional environments. These findings suggest that the Eau Claire Formation in the Central and Northern Illinois Basin was deposited in a shallow marine environment, ranging from tidal flats to offshore settings. Its mixed siliciclastic-carbonate succession was primarily controlled by relative sea-level change.

58 GEOSCIENCES

Materials Degradation in Extreme Environments: Novel In-situ Measurements of Cracking in Molten Salt

The safety and reliability of next-gen reactors, i.e. molten salt reactors (MSR), depends on materials performance and longevity in extreme environments, yet no in-situ, validated measurement techniques for environmentally assisted cracking (EAC), one potential degradation mechanism, exist for these conditions. This project combined the use of in-situ direct current potential drop (DCPD) crack growth rate determination applied to a horizontal load frame with high temperature fittings and novel sample geometries to enable evaluation in MSR environments and develop a full in-situ SCC measurement capability for extreme environments (high conductivity and elevated T), necessary to predict materials reliability. A successful demonstration of DCPD measurement in molten NaNO 3 /KNO 3 salts at 340 o C was accomplished and validated through post-test fractography imaging. This is the first ever public example, to the authors knowledge, of an in-situ crack growth rate measurement in a molten salt environment.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Friction and wear of nuclear graphite exposed to molten FLiNaK salt environment

This report formally documents the completion of the Advanced Reactor Technologies Level 3 Milestone (M3TG-25OR0501104), “Initiate graphite wear studies of graphite samples exposed to molten salt environment,” due August 1, 2025. The report summarizes the ongoing activities aimed at characterizing the friction and wear behavior of graphite in molten LiF–NaF–KF (FLiNaK) salt environment. The wear and friction behavior of self-mated ET-10 nuclear graphite were tested at varying temperatures (550°C and 650°C), contact loads (40 and 80 N) and sliding speeds (1 and 10 mm/s) in a controlled argon environment. The results were compared to the wear and friction behavior of the same graphite material in a dry argon environment. This report presents initial studies on the friction and wear behavior of graphite in sliding contact mode, with future work focused on investigating the graphite matrix materials, as well as rolling and impact contact modes. The outcomes of this report could provide insights into assessing the integrity of the graphitic components of pebble-bed fluoride salt–cooled high-temperature reactors (PB-FHRs) to enhance their safe operation.

22 GENERAL STUDIES OF NUCLEAR REACTORS