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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Lipoprotein Particles in Cerebrospinal Fluid

The brain is the most lipid-rich organ in the body, and the intricate interplay between lipid metabolism and pathologies associated with neurodegenerative disorders is being increasingly recognized. The brain is bathed in cerebrospinal fluid (CSF), which, like plasma, contains lipid-protein complexes called lipoproteins that are responsible for extracellular lipid transport. Multiple CSF lipoprotein populations exist, some of which are produced de novo in the central nervous system and others that appear to be generated from protein constituents that are produced in the periphery. These CSF lipoproteins are thought to play key roles in maintaining lipid homeostasis in the central nervous system, while little else is known due to their limited accessibility and their low abundance in CSF. Recent work has provided new insights into the compositional complexity of CSF lipoprotein families and their metabolism in cerebral circulation. Finally, the purpose of this review is to summarize our current state of knowledge on the composition, origin, and metabolism of CSF lipoproteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Development and Validation of SAM Multi-dimensional Flow Model for Thermal Mixing and Stratification Modeling

Thermal mixing and stratification in large pools or enclosures are very important phenomena that are critical to nuclear reactor safety. Because of the wide ranges of time and length scales associated with such phenomena, accurate modeling and simulation of thermal mixing and stratification remain as the key unresolved, challenging problems for reactor transient analyses. In traditional system analysis codes, simplified zero-dimensional (0-D) models are widely used for their high numerical efficiency, but they generally suffer from very limited prediction accuracies or range of applicability. Like traditional system analysis codes, the current version of the SAM code has implemented such simplified 0-D and one-dimensional mixing models. On the other hand, high-resolution Computational Fluid Dynamics (CFD) tools are often used to model complex thermal mixing and stratification phenomena. They are, however, generally numerically expensive, and they require large amounts of computational resources. It is therefore desirable to implement advanced and efficient thermal mixing and stratification modeling capabilities embedded in a system analysis code. This approach will improve the accuracy of reactor safety analyses when thermal mixing and stratification are involved, and also avoid using the large computational resources needed for high-resolution CFD analysis. Currently, with the support of the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation program, an effort has been launched to develop and implement a multi-dimensional flow model in the system analysis code SAM, and demonstrate its applications to model thermal mixing and stratification phenomena in large enclosures. The main outcomes of this research and development activity are summarized in this report, which presents an attempt to include a built-in advanced multi-dimensional flow model in a system analysis code with the focus on overcoming the simulation challenges of thermal mixing and stratification phenomena. In this report, we start with the introduction of existing SAM code capabilities to simulate thermal mixing and stratification phenomena, which is followed by a short summary of the multi-dimensional model implemented in the SAM code, including both the physical model and the Finite Element Method code implementation. In this study, two options were implemented in the SAM code to model turbulent flows: a relatively simple built-in turbulence model and an interface to accept externally computed turbulent viscosities (e.g., from a high- resolution CFD simulation). Code validation studies on this newly added capability were then carried out to compare SAM simulation results with experimental data from the SUPERCAVNA facility, which was designed to study the complex flow recirculation and thermal stratification phenomena relevant to sodium fast reactor designs. In this study, one transient and two steady-state test cases were used for code validation. Different approaches have been used to model the complex turbulence flow fields in the SUPERCAVNA facility. A highly simplified zero-equation turbulence model was first used, but it was determined that it is too simple to capture the complex turbulence flow fields in these test cases. Subsequently, the code validation continued with the use of turbulent viscosity data from high-resolution STAR-CCM+ CFD simulations to improve the accuracy of the results. Using this approach, the SAM simulation results showed very good agreement with both the SUPERCAVNA experimental data and STAR-CCM+ simulation results. In this report, we demonstrate the development, implementation, and successful validation of a multi-dimensional flow model in the SAM code, which aims to improve the simulation accuracy for complex thermal mixing and stratification phenomena. Lessons have also been learned, including that in cases where the flow fields are not well predicted by the zero-equation model, the iinput of turbulent viscosities from an external source can enhance the overall predictive capabilities needed to accurately capture complex thermal-hydraulic phenomena. Therefore, future research will be needed to further improve the code’s capabilities, such as by developing a more efficient and robust approach to capture the turbulence effects in the SAM code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Editorial: Particulate Matter Emissions From Conventional and Reformulated Fuel Combustion: Advances in Experiments and Simulations

Particulate matter (PM or soot) emissions generated by combustion of conventional and reformulated fuels adversely impact the environment and human health (Bond et al., 2013; Landrigan et al., 2018; World Health Organization (WHO), 2016), generating public awareness and motivating efforts towards the mitigation of their harmful effects. Soot formation is one of the most complex phenomena in combustion, involving interactions between combustion chemistry, fluid mechanics, mass/heat transport, and particle dynamics, spanning different spatial and temporal scales. A fundamental understanding of soot formation process is thus necessary to achieve a strong reduction of PM emissions and design cleaner and more efficient combustion systems. This has motivated a longstanding and ongoing research activity aimed at improving our understanding of the physical and chemical processes involved in soot formation, well reviewed in these recent works (Wang and Chung, 2019; Michelsen et al., 2020; Martin et al., 2022). Despite the wide interest, the transition from gas-phase molecules to incipient soot particles is still elusive and the successive particle growth and oxidation processes are far from being fully understood, especially in conditions relevant to real-world applications. Recent advances in combustion PM emission diagnostic and computational capabilities helped in improving the predictability of fundamental chemical and aerosol models for practical applications, thus tackling some of the above-mentioned challenges. The aim of this research topic is to display the ongoing research efforts in addressing the existing gaps on particulate formation from various fuel sources and in conditions typical of practical combustion applications (e.g. flames, engines, pool fires), through both experimental and numerical approaches.

42 ENGINEERING↗
DOE OSTI2025

Ship Motion Testing Needs Evaluation

The American Bureau of Shipping performed an evaluation of national maritime nuclear testing capabilities and determined there currently is an inability to test maritime nuclear power plants in a ship motion environment. A Ship Motion Test Facility (SMTF) is proposed to fill this gap. To inform design of this facility, this report documents an evaluation performed by a panel of technical experts that identifies key physical phenomena associated with maritime nuclear power plant operation that are important to safety and reliability and have a low state of knowledge. This evaluation concluded that all of the major test needs to understand a nuclear plant's behavior in a ship motion environment are for thermal-hydraulics related phenomena. Based on this finding, the evaluation panel concluded that the SMTF would not be required to use nuclear fuel to provide a heat source for the fluids. This would significantly decrease the cost, timeline, and complexity for this test facility to enable the advancement of maritime nuclear technology.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Realistic fuel spray modeling for gasoline direct injection engine applications

Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. In conclusion, quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

FSVPy: A python-based package for fluorescent streak velocimetry (FSV)

Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and electrical systems. In this work, we explore the use of fluorescent particle-streak analysis to directly measure the local velocity field of a pressure-driven flow, introducing a new Python package (FSVPy) to perform the analysis. Fluorescent streak velocimetry combines high-speed imaging with highly fluorescent particles to produce images that contain fluorescent streaks, whose length and intensity can be related to the local flow velocity. By capturing images throughout the sample volume, the three-dimensional velocity field can be quantified and reconstructed. We demonstrate this technique by characterizing the channel flow profiles of several non-Newtonian fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and Polyethylene Glycol. We then explore more complex flows, where significant acceleration is created due to microscale features encountered within the flow. We demonstrate the ability of FSVPy to process streaks of various shapes and use the variable intensity along the streak to extract position-specific velocity measurements from individual images. Thus, we demonstrate that FSVPy is a flexible tool that can be used to extract local velocimetry measurements from a wide variety of fluids and flow conditions.

Mechanics↗
DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A quantum liquid of magnetic octupoles on the pyrochlore lattice

Spin liquids are highly correlated yet disordered states formed by the entanglement of magnetic dipoles. Theories define such states using gauge fields and deconfined quasiparticle excitations that emerge from a local constraint governing the ground state of a frustrated magnet. For example, the ‘2-in–2-out’ ice rule for dipole moments on a tetrahedron can lead to a quantum spin ice in rare-earth pyrochlores. However, $f$-electron ions often carry multipole degrees of freedom of higher rank than dipoles, leading to intriguing behaviours and ‘hidden’ orders. In this paper we show that the correlated ground state of a Ce 3+ -based pyrochlore, Ce 2 Sn 2 O 7 , is a quantum liquid of magnetic octupoles. Our neutron scattering results are consistent with a fluid-like state where degrees of freedom have a more complex magnetization density than that of magnetic dipoles. The nature and strength of the octupole–octupole couplings, together with the existence of a continuum of excitations attributed to spinons, provides further evidence for a quantum ice of octupoles governed by a ‘2-plus–2-minus’ rule. Our work identifies Ce 2 Sn 2 O 7 as a unique example of frustrated multipoles forming a ‘hidden’ topological order, thus generalizing observations on quantum spin liquids to multipolar phases that can support novel types of emergent fields and excitations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigating the Interaction Between Circulating Tumor Cells and Local Hydrodynamics via Experiment and Simulations

Introduction: The biological and mechanical properties of circulating tumor cells (CTCs) in combination with the hemodynamics affect the preference of metastatic sites in the vasculature. Despite the extensive literature on the effects of biological properties on cell adhesion, the effects of hydrodynamic forces on primary attachment remains an active area of research. Here, using simulations in conjunction with experimentation, we provide new insight into the interplay of CTCs dynamics and local hydrodynamics. Methods: A flow experiment of CTC attachment was performed within a bioprinted, double branching endothelialized vessel. Simulations of fluid flow and CTC transport in the reconstructed and idealized bifurcated vessel were respectively performed by HARVEY, our in-house massively parallel computational fluid dynamics solver. HARVEY is based on the lattice Boltzmann and finite element methods to model the fluid and cells dynamics. The immersed boundary method is employed for resolving the fluid–structure interaction. Results: CTC attachment was quantified experimentally at all regions of the complex vessel. The results demonstrate a clear preference for CTCs to attach at the branch points. To elucidate the effect of the vessel topology on the location of attachment, a fluid-only simulation was performed assessing the differences in the hydrodynamics along the vessel. CTC transport in idealized bifurcated vessels was subsequently studied to examine the effects of cell deformability on the local hydrodynamics patterns and, thus, the preference of attachment sites. Conclusions: The current work provides evidence on the correlation of the hydrodynamics forces arising from the vessel topology and CTC properties on the attachment regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Effect of cold cap coverage and emissivity on the plenum temperature in a pilot-scale waste vitrification melter

Integrated computational fluid dynamics (CFD) models are being developed to model the complex physics occurring within the high-level waste melter for vitrification of legacy tank waste at the Hanford site. Here, we present a validation of the integrated CFD model by using data from two experimental runs in a pilot-scale melter. While the model uses several simplifying assumptions (such as constant heat sinks from a cooling jacket and inleakage of ambient air, steady state feed-to-batch conversion heat, and a cold cap model with a simplified shape), it closely predicts the molten glass (1150°C and 1175°C) and plenum temperatures (550°C) obtained from thermocouples during two pilot-scale tests, with an average cold cap coverage of 80%. Additional simulations were performed to explore the sensitivity of the predicted plenum temperatures to variations in cold cap coverage (fraction of melt surface covered by the glass batch) and batch emissivity. The plenum temperature was found to be in the range of 606°C when cold cap coverage decreased from 95% to 70%. Cold cap emissivity had a smaller effect, increasing the plenum temperature by as much as 179°C when cold cap emissivity increased from 0.2 to 0.8. Maintaining a high cold cap coverage without overfeeding is important for a sustained melter operation with high glass throughput. This work provides a tool for achieving that goal in terms of correlating the plenum temperature with the cold cap coverage.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

The solubility of thorium in carbonate-bearing solutions at hydrothermal conditions

Thorium mineralization is frequently hosted in carbonate-bearing rocks, and thorium commonly substitutes into the structures of carbonate-bearing minerals that have precipitated from or been modified by hydrothermal fluids. Given this common association, it is reasonable to consider the hypothesis that the presence of carbonate ligands in hydrothermal solutions promotes the transport of Th through the formation of stable aqueous complexes. Our ability to evaluate this hypothesis, however, is hindered by the lack of experimental data for Th-carbonate species at conditions beyond ambient. The low-temperature data indicate that carbonate is a strong complexing agent for Th. In this contribution, we investigate the solubility of Th in carbonate-bearing fluids relevant to natural systems (0.05–0.5 m NaHCO 3 /Na 2 CO 3 ; pH T ~ 7.8–9.8) at elevated temperature (175–250 °C). We demonstrate that, in contrast to the behavior of Th at low temperature, the stability of Th-carbonate complexes is not sufficient for them to predominate at these conditions. Instead, the solubility of Th is governed by hydrolysis reactions. Under the experimental conditions investigated, the predominant hydroxyl complexes are Th(OH) 4 0 and Th(OH) 5 -. Furthermore, thermodynamic formation constants were derived for these species at the temperatures considered in our experiments (log β 4 = 43.34 and 44.31 at 175 and 200 °C, respectively, and log β 5 = 46.15 and 47.9 at 225 and 250 °C, respectively) to permit forward modeling of Th mobility in natural systems. Our study indicates that carbonate ions are unlikely to play a role in transporting Th in hydrothermal fluids. Summarizing the results of this study and our previous studies of the solubility of Th in hydrothermal fluids, we conclude that SO 4 2- is the primary ligand responsible for the hydrothermal transport of Th.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Uranium carbonate complexes demonstrate drastic decrease in stability at elevated temperatures

Quantitative understanding of uranium transport by high temperature fluids is crucial for confident assessment of its migration in a number of natural and artificially induced contexts, such as hydrothermal uranium ore deposits and nuclear waste stored in geological repositories. An additional recent and atypical context would be the seawater inundated fuel of the Fukushima Daiichi Nuclear Power Plant. Given its wide applicability, understanding uranium transport will be useful regardless of whether nuclear power finds increased or decreased adoption in the future. The amount of uranium that can be carried by geofluids is enhanced by the formation of complexes with inorganic ligands. Carbonate has long been touted as a critical transporting ligand for uranium in both ore deposit and waste repository contexts. However, this paradigm has only been supported by experiments conducted at ambient conditions. We have experimentally evaluated the ability of carbonate-bearing fluids to dissolve (and therefore transport) uranium at high temperature, and discovered that in fact, at temperatures above 100 °C, carbonate becomes almost completely irrelevant as a transporting ligand. This demands a re-evaluation of a number of hydrothermal uranium transport models, as carbonate can no longer be considered key to the formation of uranium ore deposits or as an enabler of uranium transport from nuclear waste repositories at elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Same-sided successive-shock HED instability experiments

Inertial confinement fusion (ICF) and high-energy density (HED) physics experiments experience complicated forcing for instability growth and mix due to the ubiquitous presence of multiple shocks interacting with perturbations on multiple material interfaces. One common driver of instability growth is successive shocks from the same direction. However, there is a severe lack of analytic work and modeling validation for same-sided successive shocks since they are extremely difficult to achieve with conventional (non-HED) drivers. Successive shocks access a large instability parameter space; idealized fluid theory [K. O. Mikaelian, Phys. Rev. A 31, 410 (1985)] predicts 15 different interface evolution scenarios for a sinusoidal perturbation. Growth becomes more complex for multi-mode, compressible HED systems. The Mshock campaign is the first experiment in any fluid regime to probe a wide portion of successive shock parameter space. This is enabled by our development of a hybrid direct/indirect drive platform capable of creating independently controllable successive shocks on the National Ignition Facility. These experiments have delivered the first data capable of rigorously challenging our models and their ability to accurately capture Richtmyer–Meshkov growth under successive shocks. Single-mode and two-mode experiments have successfully demonstrated the ability to access and control the various growth scenarios of the shocked interface, including re-inversion, freeze out, and continued growth. Simulations and theoretical modeling are shown to accurately capture the experimental observations in the linear growth phase, giving us confidence in our ICF/HED design codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Inkjet printing of epitaxially connected nanocrystal superlattices

Access to a blossoming library of colloidal nanomaterials provides building blocks for complex assembled materials. The journey to bring these prospects to fruition stands to benefit from the application of advanced processing methods. Epitaxially connected nanocrystal (or quantum dot) superlattices present a captivating model system for mesocrystals with intriguing emergent properties. The conventional processing approach to creating these materials involves assembling and attaching the constituent nanocrystals at the interface between two immiscible fluids. Processing small liquid volumes of the colloidal nanocrystal solution involves several complexities arising from the concurrent spreading, evaporation, assembly, and attachment. The ability of inkjet printers to deliver small (typically picoliter) liquid volumes with precise positioning is attractive to advance fundamental insights into the processing science, and thereby potentially enable new routes to incorporate the epitaxially connected superlattices into technology platforms. In this study, we identified the processing window of opportunity, including nanocrystal ink formulation and printing approach to enable delivery of colloidal nanocrystals from an inkjet nozzle onto the surface of a sessile droplet of the immiscible subphase. We demonstrate how inkjet printing can be scaled-down to enable the fabrication of epitaxially connected superlattices on patterned sub-millimeter droplets. Furthermore, we anticipate that insights from this work will spur on future advances to enable more mechanistic insights into the assembly processes and new avenues to create high-fidelity superlattices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing

AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.

Coleman, John [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

Hydrothermal solubility of Dy hydroxide as a function of pH and stability of Dy hydroxyl aqueous complexes from 25 to 250 °C

The rare earth elements (REE) have important applications in green energy technologies. The formation of mineral deposits in geologic systems commonly involves hydrothermal fluids which can mobilize the REE. However, the REE speciation is not well known as a function of pH. The thermodynamic properties of REE hydroxyl complexes used in geochemical models are based on the Helgeson-Kirkham-Flowers (HKF) equation of state parameters which were derived by extrapolation of low temperature experimental and estimated data. In this study, Dy hydroxide solubility experiments are combined with available literature data to improve these models from 25 to 250 °C and optimize the thermodynamic properties of Dy 3+ and Dy hydroxyl complexes using GEMSFITS. Batch-type solubility experiments were conducted from 150 to 250 °C and at saturated water vapor pressure in perchloric acid solutions with initial pH values of 2 to 5 in 0.5 pH unit increments. The measured solubility of Dy hydroxide is retrograde with temperature and decreases with pH. The logarithm of total dissolved Dy molality ranges from –2.3 to –5.3 at 150 °C (pH 4.7–5.5), from –2.4 to –5.6 at 200 °C (pH 3.9–5.1), and from –3.7 to –6.9 at 250 °C (pH of 3.4 and 5.0). The optimized standard partial molal Gibbs energies of formation (Δ f G° T ) derived for Dy 3+ and DyOH 2+ display a close to linear relationship with temperature, fitting with previous optimizations based on DyPO 4 solubility data in the literature. A comparison of the optimized ΔfG°T values for aqueous Dy species with predictions from available HKF parameters indicates significant differences ranging from +11 to –26 kJ/mol between 25 and 250 °C. The experimental fits are used to derive the Dy hydroxide solubility products (K s0 ) and formation constants for the hydrolysis of Dy (β n with n = 1 to 3; Dy 3+ + nOH – = DyOH n 3-n ) as a function of temperature. The optimization method presented yields accurate thermodynamic properties for the Dy 3+ aqua ions and the DyOH 2+ species at the acidic to mildly acidic pH studied whereas more experimental work is needed at near-neutral and alkaline conditions to better constrain the other hydroxyl complexes. Furthermore, the optimized thermodynamic data have a significant impact on geochemical modeling of the mobility and solubility of REE minerals in acidic hydrothermal fluids.

58 GEOSCIENCES↗
DOE OSTI2023

In-situ thermodynamics measurements at metal oxides-solution interfaces using Flow Adsorption Microcalorimetry.

Mineral-fluid interfaces are the principal sites of geochemical processes near Earth’s surface, hosting chemical reactions that play a fundamental role in (bio)geochemical cycles and in the fate and transport of anthropogenic contaminants, and that effectively control the compositions of soil and water environments. These complex interfaces are critical for our energy and environmental future. The mineral-fluid interface has been studied in an unprecedented level of detail with both experimental and computational approaches, separately and in combination. However, conspicuously missing from studies of the mineral-fluid interface are direct measurements of the energies of ion sorption and exchange. The literature on energetics and enthalpies of exchange, adsorption, dissolution, precipitation, and surface protonation reactions, especially those directly supported by experimental data, remains scarce despite their fundamental nature. The overarching goal of this project is to complete a systematic study of the thermodynamics properties of interfacial reactions at four MO surfaces (Rutile (α-TiO2), Quartz (SiO2), boehmite (γ-AlOOH) and goethite (α-FeOOH)) through the application and construction of novel flow adsorption microcalorimetry techniques and instrumentations. These unique and specialized microcalorimeters will operate at various temperatures and solution chemical compositions allowing for in-situ measurements across metal oxides and ligands of various characteristics. The overall research goal will be accomplished by completing the following three specific objectives (O): O1) Determine the energetics of surface protonation and deprotonation, ion exchange and ligand sorption reactions; O2) Investigate the surface charge thermodynamic properties under a range of temperature and solution chemical compositions; and O3) Develop predictive trends of the interplay between MO structure, surface coverage and surface reactivity. In addition to key thermodynamics parameters, calorimetric measurements provide a wealth of mechanistic information about reactions energetics and kinetics, surface charge characteristics, and structure-reactivity or selectivity relationships, all obtained in-situ and in real-time. This report includes science highlights from various projects completed over the performance period of the project. Also listed are dissemination opportunities, people supported on the grant and the impact on available physical resources and the discipline as a whole.

58 GEOSCIENCES↗
DOE OSTI2025

Thermal Performance of Triply Periodic Minimal Surface Lattice Structures in Single-Phase Dielectric Fluid Cooling of Power Electronics

Additive manufacturing has transformed thermal management by enabling the production of complex, optimized geometries that conventional manufacturing methods cannot achieve. This study investigates the single-phase convective heat transfer performance of gyroid triply periodic minimal surface (TPMS) lattice structures with functional porosity. TPMS structures provide high surface area to volume ratios and are amenable to 3D printing. A gyroid numerical model was created and validated against an existing experimental study with a similar feature size to the investigated geometries. The TPMS structure has a periodic width of 1.6 mm, a length of 10 mm, and a height of 4 mm, with a functional porosity ranging from 0.5 to 0.8, decreasing with distance from the heated surface. Three different flow configurations were examined for an inlet fluid temperature of 70 °C. The inlet velocities range from 0.01 to 1.2 m/s, corresponding to a Reynolds number range of 10–900 with a heat flux of 50 W/cm 2 applied at the base. AmpCool ® AC-110 dielectric fluid (Prandtl number 59.5) was used as the coolant. Thermal performance and friction characteristics were studied for the three flow orientations. The parallel flow configuration was identified as the most efficient for heat removal. A detailed analysis of the numerical results highlights the underlying physics behind the thermal performance differences among the flow configurations.

33 ADVANCED PROPULSION SYSTEMS↗