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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Insights into controlling bacterial cellulose nanofiber film properties through balancing thermodynamic interactions and colloidal dynamics

In recent years, nanocellulose has emerged as a sustainable and environmentally friendly alternative to traditional petroleum-derived structural polymers. Sourced either from plants, algae, or bacteria, nanocellulose can be processed into colloid, gel, film and fiber forms. However, the required fundamental understanding of process parameters that govern the morphology and structure–property relationships of nanocellulose systems, from colloidal suspensions to bulk materials, has not been developed and generalized for all forms of cellulose. This further hinders the more widespread adoption of this biopolymer in applications. Our study investigates the dispersion of cellulose nanofibers (CNFs) produced by a bacterial–yeast co-culture, in solvents, highlighting the role of thermodynamic interactions in influencing their colloidal behavior. By adjusting Hansen solubility parameters, we controlled the thermodynamic relationship between CNFs and solvents across various concentrations, studying the dilute to semi-dilute regimes. Rheological measurements revealed that the threshold at which a concentration-based regime transition occurs is distinctly solvent-dependent. Complementing rheological analysis with small angle X-ray scattering and zeta potential measurements, our findings reveal that enhancing CNF–solvent interactions increases excluded volume in the dilute regime, emphasizing the importance of the balance between fiber–fiber and fiber–solvent interactions. Moreover, we investigated the transition from colloidal to solid state by creating films from dispersions with varying interaction parameters in semi-dilute regimes. Through mechanical testing and scanning electron microscopy imaging of the fracture surfaces, we highlight the significance of electrokinetic effects in such transitions, as dispersions with higher electrokinetic stabilization gave rise to stronger and tougher films despite having less favorable thermodynamic interaction parameters. Finally, our work provides insights into the thermodynamic and electrokinetic interplay that governs bacterial CNF dispersion, offering a foundation for future application and a deeper understanding of nanocellulose's colloidal and structure-property relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Development of High-Temperature Bonding Techniques to Enable High-Temperature Static or Dynamic Strain Measurements

Current light-water nuclear reactors rely on a variety of different sensors and sensor applications to meet their structural health monitoring needs throughout the entirety of the reactor primary, secondary, and containment systems. Optical fiber–based sensor technologies could provide solutions to reduce the sensor system footprint while enhancing the measurement fidelity and spatial resolution by leveraging distributed monitoring techniques. Moreover, advanced reactors may require optical fiber–based sensors for structural health monitoring because their operating temperatures will exceed the limits of conventional transducers used to acquire dynamic strain or acoustic data in nuclear power plants. Therefore, this report describes experiments targeting the development of high-temperature bonding techniques that would allow for potentially long lengths of fibers to be bonded to metallic reactor components in advanced reactor systems. The high temperatures experienced within target application, next-generation nuclear reactors, necessitate a high-temperature resistant bond to limit the amount of tension on the fiber at the target application temperature. The primary bonding method investigated in this work is brazing; hot-rolling has also been investigated to a lesser extent. Both techniques are well-suited to bonding optical fibers to large reactor components such as primary coolant piping, pressure vessels, or heat exchangers. Optical frequency domain reflectometry was used to monitor the strain in metal-coated optical fibers before, during, and after the high-temperature bonding process. On select optical fibers that were successfully bonded, additional thermal cycling was performed to assess the extent to which the fiber remained bonded based on the expected thermal expansion of the test specimen material. The results of the various experiments yielded the following general conclusions: (1) brazing is a viable technique for bonding and allows significant compressive strain to be applied to the fiber at room temperature; (2) hot-rolling is a viable technique as well, which has been more optimized than the brazing technique for bonding, but less residual compressive strain has been observed with this technique; and (3) both techniques will need further development and optimization to demonstrate bonding of a long length of fiber that can provably operate at relevant temperatures for an advanced nuclear reactor application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The Wave Energy Converter Design Process: Methods Applied in Industry and Shortcomings of Current Practices

Wave energy is among the many renewable energy technologies being researched and developed to address the increasing demand for low-emissions energy. The unique design challenges for wave energy converter design—integrating complex and uncertain technological, economic, and ecological systems, overcoming the structural challenges of ocean deployment, and dealing with complex system dynamics—have lead to a disjointed progression of research and development. There is no common design practice across the wave energy industry and there is no published synthesis of the practices that are used by developers. In this paper, we summarize the methods being employed in WEC design as well as promising methods that have yet to be applied. We contextualize these methods within an overarching design process. We present results from a survey of WEC developers to identify methods that are common in industry. From the review and survey results, we conclude that the most common methods of WEC design are iterative methods in which design parameters are defined, evaluated, and then changed based on evaluation results. This leaves a significant space for improvement of methods that help designers make better-informed decisions prior to sophisticated evaluation, and methods of using the evaluation results to make better design decisions during iteration. Despite the popularity of optimization methods in academic research, they are less common in industry development. We end this paper with a summary of the areas of WEC design in which the testing and development of new methods is necessary, and where more research is required to fully understand the influence of design decisions on WEC performance.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗
DOE OSTI2015

Establishing resolution-improved NMR spectroscopy in high magnetic fields with unknown spatiotemporal variations

A half-century quest for higher magnetic fields has been an integral part of the progress undergone in the Nuclear Magnetic Resonance (NMR) study of materials’ structure and dynamics. Because 2D NMR relies on systematic changes in coherences’ phases as a function of an encoding time varied over a series of independent experiments, it generally cannot be applied in temporally unstable fields. This precludes most NMR methods from being used to characterize samples situated in hybrid or resistive magnets that are capable of achieving extremely high magnetic field strength. Recently, “ultrafast” NMR has been developed into an effective and widely applicable methodology enabling the acquisition of a multidimensional NMR spectrum in a single scan; it can therefore be used to partially mitigate the effects of temporally varying magnetic fields. Nevertheless, the strong interference of fluctuating fields with the spatial encoding of ultrafast NMR still severely restricts measurement sensitivity and resolution. Here, we introduce a strategy for obtaining high resolution NMR spectra that exploits the immunity of intermolecular zero-quantum coherences (iZQCs) to field instabilities and inhomogeneities. The spatial encoding of iZQCs is combined with a J-modulated detection scheme that removes the influence of arbitrary field inhomogeneities during acquisition. This new method can acquire high-resolution one-dimensional NMR spectra in large inhomogeneous and fluctuating fields, and it is tested with fields experimentally modeled to mimic those of resistive and resistive-superconducting hybrid magnets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Characteristics of kinetic sprayed Ta in terms of the deposition behavior, microstructural evolution and mechanical properties: Effect of strain-rate-dependent response of Ta at high temperature

Highlights: • The effect of high-temperature rate-dependent response of BCC Ta on the deposition state of kinetic sprayed Ta particles with synergistic effect of powder oxidation • Abnormal increase of dislocation density above certain powder preheating temperature under the lower condition (N{sub 2} carrier gas), whereas considerable occurrence of grain refinement under the higher condition (He carrier gas). • Most significant dislocation density with the smallest volume-averaged domain size under the condition of 600 {sup o}C powder pre-heating with N{sub 2} carrier gas due to characteristic response of Ta. - Abstract: Numerous efforts have been focused on the fundamental research regarding kinetic spraying processes, but previous studies were biased to only few kinds of metallic materials. In particular, for Ta with body-centered cubic crystal structure, systematic studies are currently lacking in the literature. In this study, the characteristic deposition behaviors, microstructures, and mechanical properties of kinetic sprayed Ta under various impact conditions were systematically investigated. Generally, unusual features were usually related to strain-rate-dependent response (i.e. Peierls-Nabarro short range barriers) of Ta at high-temperature. This made thermal softening effect to be saturated above a certain degree of temperature, contributing to inferior deposition efficiency for the pre-heating at 600 °C than those of 400 and 500 °C by creating synergy with powder oxidation. In terms of microstructural evolutions, the dislocation density was abnormally increased at a certain powder preheating temperature (i.e., 600 °C), owing to the strain-rate-dependent response of Ta at high-temperature. On the other hand, grain refinement generated by rotational dynamic recrystallization was mainly observed under the higher kinetic energy condition (He carrier gas) at RT. Especially, the dislocation density and volume-average domain size evaluated via high-resolution X-ray diffraction peak profile analysis were corresponding to the results of the microstructural observations. Additionally, the nanomechanical properties (i.e., nanohardness and elastic modulus) evaluated via nanoindentation tests were in good agreement with the results from transmission electron microscopy investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2016

ON THE ORIGIN OF HIGH-ALTITUDE OPEN CLUSTERS IN THE MILKY WAY

We present a dynamical study of the effect of the bar and spiral arms on the simulated orbits of open clusters in the Galaxy. Specifically, this work is devoted to the puzzling presence of high-altitude open clusters in the Galaxy. For this purpose we employ a very detailed observationally motivated potential model for the Milky Way and a careful set of initial conditions representing the newly born open clusters in the thin disk. We find that the spiral arms are able to raise an important percentage of open clusters (about one-sixth of the total employed in our simulations, depending on the structural parameters of the arms) above the Galactic plane to heights beyond 200 pc, producing a bulge-shaped structure toward the center of the Galaxy. Contrary to what was expected, the spiral arms produce a much greater vertical effect on the clusters than the bar, both in quantity and height; this is due to the sharper concentration of the mass on the spiral arms, when compared to the bar. When a bar and spiral arms are included, spiral arms are still capable of raising an important percentage of the simulated open clusters through chaotic diffusion (as tested from classification analysis of the resultant high-z orbits), but the bar seems to restrain them, diminishing the elevation above the plane by a factor of about two.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Fundamental Investigations into the Properties and Performance of Advanced Materials

Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over ii the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.

Schichtel, Jacob J.↗
DOE OSTI2016

Coiled-coil forming peptides for the induction of silver nanoparticles

Biopolymers with defined sequence patterns offer an attractive alternative for the formation of silver nanoparticle (AgNP). A set of coiled-coil dimer forming peptides was tested for their AgNP formation ability. Seventeen of those peptides mediated the formation of AgNPs in aqueous solution at neutral pH, while the formation of a coiled-coil dimer inhibited the nanoparticle generation. A QSAR regression model on the relationship between sequence and function suggests that in this peptide type the patterns KXQQ and KXEE are favorable, whereas Ala residues appear to have an inhibitory effect. UV–VIS spectra of the obtained nanoparticles gave a peak at around 420 nm, typical for AgNPs in the size range around 40 nm, which was confirmed by dynamic light scattering and transmission electron microscopy. Peptide-induced AgNPs exhibited good antibacterial activity, even after a 15 min contact time, while they had low toxicity to human cells at the same concentrations. These results show that our designed peptides generate AgNPs with antibacterial activity at mild conditions and might be used for antibacterial coatings. - Highlights: • 17 of the 30 tested coiled-coil forming peptides induce AgNP formation. • Coiled-coil dimer formation suppresses AgNP generation of individual peptides. • Size of the peptide-induced silver nanoparticles is around 40 nm. • QSAR analysis points to the importance of KXQQ and KXEE motifs for AgNP generation. • Peptide-induced silver nanoparticles exhibit antibacterial activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Correlations in the Initial Conditions of Heavy-Ion Collisions

Ultracentral collisions of heavy nuclei, in which the impact parameter is nearly zero, are especially sensitive to the details of the initial state model and the microscopic mechanism for collective flow. In a hydrodynamic “flow” picture, the final state momentum correlations are a direct response to the fluctuating initial geometry, although models of the initial geometry differ widely. Alternatively, dynamical mechanisms based in the color glass condensate (CGC) formalism can naturally lead to many-body correlations with very different systematics. Here we present a calculation of event-by-event elliptic flow in both the hydrodynamic and CGC paradigms and show that they can be qualitatively distinguished in ultracentral collisions of deformed nuclei. Specifically, the multiplicity dependence in such collisions is qualitatively opposite, with the CGC correlations increasing with multiplicity while the hydrodynamic correlations decrease. The consistency of the latter with experimental data on UU collisions appears to rule out a CGC-mediated explanation. We find that these qualitative features also persist in small deformed systems and can therefore be a valuable test of the microscopic physics in that regime.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Carbon Dioxide Shuttling Thermochemical Storage Using Strontium Carbonate

Phase I concludes with significant progress made towards the SunShot ELEMENTS goals of high energy density, high power density, and high temperature by virtue of a SrO/SrCO 3 based material. A detailed exploration of sintering inhibitors has been conducted and relatively stable materials supported by YSZ or SrZO 3 have been identified as the leading candidates. In 15 cycle runs using a 3 hour carbonation duration, several materials demonstrated energy densities of roughly 1500 MJ/m 3 or greater. The peak power density for the most productive materials consistently exceeded 40 MW/m 3 —an order of magnitude greater than the SOPO milestone. The team currently has a material demonstrating nearly 1000 MJ/m 3 after 100 abbreviated (1 hour carbonation) cycles. A subsequent 8 hour carbonation after the 100 cycle test exhibited over 1500 MJ/m 3 , which is evidence that the material still has capacity for high storage albeit with slower kinetics. Kinetic carbonation experiments have shown three distinct periods: induction, kinetically-controlled, and finally a diffusion-controlled period. In contrast to thermodynamic equilibrium prediction, higher carbonation temperatures lead to greater conversions over a 1 hour periods, as diffusion of CO 2 is more rapid at higher temperatures. A polynomial expression was fit to describe the temperature dependence of the linear kinetically-controlled regime, which does not obey a traditional Arrhenius relationship. Temperature and CO 2 partial pressure effects on the induction period were also investigated. The CO 2 partial pressure has a strong effect on the reaction progress at high temperatures but is insignificant at temperatures under 900°C. Tomography data for porous SrO/SrCO 3 structures at initial stage and after multiple carbonation/decomposition cycles have been obtained. Both 2D slices and 3D reconstructed representations have been obtained from the raw data. Porosity and surface area have been computed based on tomography. The two parameters, permeability and Forchheimer constants, in the Darcy’s law for linear and non-linear range have been obtained from the fluid dynamics simulation. The structure is nearly isotropic from the hydrodynamics point of view. Thermal conductivity at elevated temperature has been obtained from the 3-D pore-scale simulations. The computed thermal conductivities of the structure compare well with an existing correlation. Computational models have been developed for solving the energy and mass transport equations with chemical reaction on the surface and inside the particles. The chemical kinetics or rate law is needed on the particle scale; however it is generally measured using a lumped model based on the average of reacted as well as unreacted mass. Many simulations have been conducted on a 2-D model to determine the effects of those pore scale parameters on the heat release based on the measured data. The simulation results using 2-D model show that average volumetric heat flow rate of 4 MW/m 3 in the first 5 minutes can be obtained. The insight gained from the 2-D simulation will be useful for the next stage simulation based on realistic 3-D structures. A probabilistic analysis has been conducted on the baseline system of recovering heat from the hot CO 2 evolved from the endothermic reaction and compressing the cooled CO 2 into a storage tank at 20-21 bar. Using a Monte Carlo simulation using 2,000,000 samples and both uniform and triangular probability distributions of four variables (heat exchanger pinch points, compressor efficiency, and power block efficiency), exergetic efficiency of 90% appears to be very likely.

14 SOLAR ENERGY↗
DOE OSTI2018

Mitigating Sulfidogenesis With Simultaneous Perchlorate and Nitrate Treatments

Sulfide biogenesis (souring) in oil reservoirs is an extensive and costly problem. Nitrate is currently used as a souring inhibitor but often requires high concentrations and yields inconsistent results. Recently, perchlorate has displayed promise as a more potent inhibitor in lab scale studies. However, combining the two treatments to determine synergy and effectiveness in a dynamic system has never been tested. Nitrate inhibits perchlorate consumption by perchlorate reducing bacteria, suggesting that the combined treatment may allow deeper penetration of the perchlorate into the reservoir matrix. Furthermore, the metabolic intermediates of perchlorate and nitrate reduction (nitrite and chlorite, respectively) are synergistic with the primary electron acceptors for inhibition of sulfate reduction. To assess the possible synergies between nitrate and perchlorate treatments, triplicate glass columns packed with pre-soured marine sediment were flushed with media containing sulfate and an inhibitor treatment [(i) perchlorate; (ii) nitrate; (iii) perchlorate and nitrate; or (iv) none]. Internal geochemistry and microbial community changes were monitored along the length of the columns during six phases of increasing treatment concentrations. In a final phase all treatments were removed. Sulfide production decreased in all treated columns in conjunction with increased inhibitor concentrations relative to the untreated control. Interestingly, the potency of the "mixed" treatment was additive relative to the individual treatments suggesting no interaction. Microbial community analyses indicated community shifts and clustering by treatment. The mixed treatment column community's trajectory closely resembled that of the community found in the perchlorate only treatment, suggesting that perchlorate was the dominant control on the "mixed" community structure. In contrast, the nitrate and untreated column communities had unique trajectories. This study indicates that concurrent nitrate and perchlorate treatment is not more effective than perchlorate treatment alone but is more effective than nitrate treatment. As such, treatment decisions may be based on economic factors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Serrated flow in $\mathrm{NaI:Tl}$ scintillator crystals

We report the serrated-flow behavior is an important phenomenon that unveils material-deformation mechanisms, as reported for various kinds of materials. NaI doped with Tl (NaI:Tl) is unique among scintillation materials in that the structure contains glide planes that are linked to serration behavior. In the present work, single crystals of NaI:Tl were subjected to room-temperature compression experiments at different strain rates. The serrated flow was observed, and complexity and multifractal analyses were performed to analyze the serration behavior. The findings revealed that the strain rate had a pronounced effect on the complexity and multifractality of the serrated flow, similar to what has been found in other alloy systems. The results also indicate that there may be a strong link between the complexity of the serrated flow behavior and the heterogeneity of the underlying dynamics. It is expected that the present work could be a step toward a better understanding of the deformation behavior and forgeability of NaI:Tl single crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in deep clay/shale/argillaceous rock. International collaboration activities such as heater tests and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests has as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum vs. discrete) to tackle issues related to flow and transport at various scales of the host-rock and EBS design concept. Consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the EBS design. This is particularly important for backfilled repository concepts where temperature plays a key role in the EBS behavior and long-term performance. This report describes multiple R&D efforts on disposal in argillaceous geologic media through development and application of coupled THMC process models, experimental studies on clay/metal/cement barrier and host-rock (argillite) material interactions, molecular dynamic (MD) simulations of water transport during (swelling) clay dehydration, first-principles studies of metaschoepite (UO 2 corrosion product) stability, and advances in thermodynamic plus surface complexation database development. Drift-scale URL experiments provides key data for testing hydrological-chemical (HC) model involving strong couplings of fluid mixing and barrier material chemical interactions. The THM modeling focuses on heater test experiments in argillite rock and gas migration in bentonite as part of international collaboration activities at underground research laboratories (URLs). In addition, field testing at an URL involves in situ analysis of fault slip behavior and fault permeability. Pore-scale modeling of gas bubble migration is also being investigated within the gas migration modeling effort. Interaction experiments on bentonite samples from heater test under ambient and elevated temperatures permit the evaluation of ion exchange, phase stability, and mineral transformation changes that could impact clay swelling. Advances in the development, testing, and implementation of a spent nuclear fuel (SNF) degradation model coupled with canister corrosion focus on the effects of hydrogen gas generation and its integration with Geologic Disposal Safety Assessment (GDSA). GDSA integration activities includes evaluation of groundwater chemistries in shale formations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

The Impact of Naphthenic Acids on Dynamic Fluid–Fluid Interactions: Implication for Enhanced Oil Recovery

Previous coreflooding results and wettability analyses in our group show that injection of naphthenic-acid-enriched water can improve oil recovery over traditional waterflooding. This observation is still a subject of research efforts without a definitive explanation. Naphthenic acids (NA) have been reported to drive wettability alteration and increase the water–oil interface elasticity. These alterations depend on the NA carbon number and aqueous-phase salinity, among other conditions, as reported in the literature. Smart-water flooding (SWF) research often links recovery to the initial wettability condition, being higher for initially oil-wet rock. SWF refers to a technique in which the aqueous-phase ion composition or/and salinity are changed to maximize oil recovery. Given NAs’ complex solution behavior, selecting acid combinations that prompt oil recovery is a difficult objective. The aim of this research is to determine the effects of select naphthenic acids on the oil–water interfacial rheology and wettability alteration and how these interfacial effects are associated with oil recovery under spontaneous imbibition. NAs were selected based on their carbon number, molecular structure, and solubility in the saline solution used in this research. We aimed at exploring which NAs should be used to regulate interfacial properties so as to either increase oil recovery or accelerate production. Time-domain nuclear magnetic resonance, interfacial dilatational rheology, and liquid-bridge experiments, i.e., proxy of snap-off, were conducted. A baseline was established using results obtained with a previously tested sulfate-rich aqueous phase, shown to be effective in recovering oil. Results show that NA14 and N18 increase the water–oil interfacial viscoelasticity and induce interfacial healing but led to different recovery factors. N10, while effective at inducing water wetness in oil-wet rock, is ineffective at increasing the recovery factor. We concluded that wettability and oil–water interfacial rheology are not exclusive, and instead they can synergistically favor EOR benefits. Moreover, oil recovery benefits under spontaneous imbibition are shown to depend strongly on the initial wettability conditions.

Medina-Rodriguez, Bryan X. (ORCID:0000000262922831↗
DOE OSTI2024

GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure

We propose GrainGNN, a surrogate model for the evolution of polycrystalline grain structure under rapid solidification conditions in metal additive manufacturing. High fidelity simulations of solidification microstructures are typically performed using multicomponent partial differential equations (PDEs) with moving interfaces. The inherent randomness of the PDE initial conditions (grain seeds) necessitates ensemble simulations to predict microstructure statistics, e.g., grain size, aspect ratio, and crystallographic orientation. Here, currently such ensemble simulations are prohibitively expensive and surrogates are necessary.In GrainGNN, we use a dynamic graph to represent interface motion and topological changes due to grain coarsening. We use a reduced representation of the microstructure using hand-crafted features; we combine pattern finding and altering graph algorithms with two neural networks, a classifier (for topological changes) and a regressor (for interface motion). Both networks have an encoder-decoder architecture; the encoder has a multi-layer transformer long-short-term-memory architecture; the decoder is a single layer perceptron.We evaluate GrainGNN by comparing it to high-fidelity phase field simulations for in-distribution and out-of-distribution grain configurations for solidification under laser power bed fusion conditions. GrainGNN results in 80%–90% pointwise accuracy; and nearly identical distributions of scalar quantities of interest (QoI) between phase field and GrainGNN simulations compared using Kolmogorov-Smirnov test. GrainGNN's inference speedup (PyTorch on single x86 CPU) over a high-fidelity phase field simulation (CUDA on a single NVIDIA A100 GPU) is 150×–2000× for 100-initial grain problem. Further, using GrainGNN, we model the formation of 11,600 grains in 220 seconds on a single CPU core.

36 MATERIALS SCIENCE↗