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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

CCE Phase 2: System-of-System Analysis

During Phase 1, Consequence Prioritization, the CCE Team identified High Consequence Events (HCEs) that can be accomplished through cyber means to impact critical functions, services, and processes. During Phase 2, System-of-Systems Analysis (SoS Analysis), the CCE Team will conduct a systematic review and analysis of information related to the equipment, systems, processes, operations, maintenance, testing, and procurement practices based on the HCEs identified in Phase 1.

99 GENERAL AND MISCELLANEOUS↗

Computer-aided process intensification of natural gas to methanol process

The recent revolution in shale gas has presented opportunities for distributed manufacturing of key commodity chemicals, such as methanol, from methane. However, the conventional methane-to-methanol process is energy intensive which negatively affects the profitability and sustainability. Here an intensified process configuration that is both economically attractive and environmentally sustainable. This flowsheet is systematically discovered using the building block-based representation and optimization methodology. The new process configuration utilizes membrane-assisted reactive separations and can have as much as 190% higher total annual profit compared to a conventional configuration. Additionally, it has 57% less CO 2 -equivalent greenhouse gas emission. Such drastic improvement highlights the advantages of building block-based computer-aided process intensification method.

42 ENGINEERING↗

Effect of glass forming additives on low-activity waste feed conversion to glass

A significant effort was invested in the past to develop and refine mathematical models that relate the composition of nuclear waste glasses with their properties, such as viscosity, electrical conductivity, or chemical durability. However, less attention has been paid to the formulation of the melter feed itself, such as the chemical form and the particle size of the glass forming and modifying additives (GFMA), which have a significant effect on the feed-to-glass conversion process during melting. To address this issue, we systematically changed the mineral composition of a simulated low-activity waste melter feed and inspected its melting behavior. When substituting minerals with corresponding oxides and hydroxides, we found that different alumina sources (kyanite, gibbsite, boehmite, or corundum) had the strongest effect on the feed melting process, whereas the sources of Ca, Mg, and Zr had little effect. Further, the x-ray diffraction analysis showed that the alumina sources differ in their dissolution kinetics: early dissolving alumina sources, such as gibbsite (Al(OH) 3 ) and boehmite (AlO(OH)), increase the transient glass-forming melt viscosity at early stages, when gases still evolve, causing extended foaming, whereas alumina sources that dissolve at high temperatures, such as kyanite (Al 2 SiO 5 ) and corundum (Al 2 O 3 ), keep the transient glass-forming melt viscosity low and lead to a faster foam collapse. Using viscosity-composition relationship to estimate the viscosity of transient glass-forming melts in the primary foaming range, we found that the primary foam began to collapse at 360 to 800 Pa s, and fully collapsed between 65 and 260 Pa s. This result agrees with our previous studies, according to which the glass-forming melt viscosity at the cold cap foam bottom ranged from 24 to 85 Pa s.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Position Papers for the ASCR Workshop on the Science of Scientific-Software Development and Use

Software is an increasingly important component in the pursuit of scientific discovery. Both its development and use are essential activities for many scientific teams. At the same time, very little scientific study has been conducted to understand, characterize, and improve the development and use of software for science. Computational science teams have diversified over time to include contributions from domain scientists who provide expertise in scientific and engineering disciplines, applied mathematicians and computer scientists who provide optimal algorithms and data structures, and software and data engineers who provide methodologies and tools adapted and adopted from other software domains. These diverse contributions have enabled tremendous advances in the pursuit of scientific discovery, even as models, computer architectures, and software environments have become more complicated. With this increasing diversity, we believe the next opportunity for qualitative improvement comes from applying the scientific method to understanding, characterizing, and improving how scientific software is developed and used. We believe that this pursuit requires expertise from computational scientists themselves, and from the cognitive and social sciences as well as the software engineering research community. As we look to increase the productivity and sustainability of the scientific-software-development-and-use cycle, a more systematic application of the scientific method to understand processes for software development and use will be a valuable tool to guide future work and result in more usable and sustainable software. This workshop will bring together computer scientists, software engineering researchers, computational scientists, applied mathematicians, social scientists, cognitive scientists, and others, to explore how we can conduct such systematic investigations, what can be learned, and how doing so will benefit the scientific enterprise. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees — from DOE, industry, and academia — will produce a report for ASCR that summarizes the findings of the workshop.

42 ENGINEERING↗

An effective field theory approach to quarkonium at small transverse momentum

In this work we apply effective field theory (EFT) to observables in quarkonium production and decay that are sensitive to soft gluon radiation, in particular measurements that are sensitive to small transverse momentum. Within the EFT framework we study χQ decay to light quarks followed by the fragmentation of those quarks to light hadrons. We derive a factorization theorem that involves transverse momentum distribution (TMD) fragmentation functions and new quarkonium TMD shape functions. We derive renormalization group equations, both in rapidity and virtuality, which are used to evolve the different terms in the factorization theorem to resum large logarithms. This theoretical framework will provide a systematic treatment of quarkonium production and decay processes in TMD sensitive measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Internal consistency and diversity scenario development: A comparative framework to evaluate energy model scenarios

Energy modeling frameworks and scenario analysis help us explore the potential impact of our actions and uncertainties in future energy systems. Despite their importance, there is no systematic procedure for evaluating the scenario development process. In a literature review, we identify two core elements of the scenario development process: internal consistency and diversity which are oftentimes missing from scenarios. Here, to address this gap, we create the Internal consistency and Diversity Scenario Development (IDSD) comparative framework which aims to assess the feasibility and diversity of scenarios for a given energy model. With this framework, we review commonly used energy models and demonstrate our framework on their scenarios. The IDSD comparative framework can serve several purposes absent from previous scenario development work by aiding energy modelers and report writers in crafting high-quality scenarios. First, the IDSD is a reflective tool which can improve the quality of the scenario development process, enabling a comparative assessment of energy models and scenarios. Second, the IDSD can provide guidance to modeling frameworks with existing scenarios and those still in development; this feedback will enable modelers to improve the development and the communication of the limitations of their scenarios. Third, this study has highlighted areas for improvement in the scenario development of some commonly used energy model frameworks. Finally, there is a complete lack of explanation regarding the stakeholder selection process. Addressing these identified items could increase opportunities for advanced energy technology uptake and improve our options for achieving a more resilient energy system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fundamental mechanistic insights into the catalytic reactions of Li-S redox by Co single-atom electrocatalysts via operando methods

Lithium-sulfur batteries represent an attractive option for energy storage applications. A deeper understanding of the multistep lithium-sulfur reactions and the electrocatalytic mechanisms are required to develop advanced, high-performance batteries. We have systematically investigated the lithium-sulfur redox processes catalyzed by a cobalt single-atom electrocatalyst (Co-SAs/NC) via operando confocal Raman microscopy and x-ray absorption spectroscopy (XAS). The real-time observations, based on potentiostatic measurements, indicate that Co-SAs/NC efficiently accelerates the lithium-sulfur reduction/oxidation reactions, which display zero-order kinetics. Under galvanostatic discharge conditions, the typical stepwise mechanism of long-chain and intermediate-chain polysulfides is transformed to a concurrent pathway under electrocatalysis. In addition, operando cobalt K-edge XAS studies elucidate the potential-dependent evolution of cobalt’s oxidation state and the formation of cobalt-sulfur bonds. Our work provides fundamental insights into the mechanisms of catalyzed lithium-sulfur reactions via operando methods, enabling a deeper understanding of electrocatalysis and interfacial dynamics in electrical energy storage systems.

36 MATERIALS SCIENCE↗

Radioactive decay of $\mathrm {{}^{90}Sr}$ in cement: a non-equilibrium first-principles investigation

Cement is an inexpensive and relatively easily manageable material that is used as a last barrier for nuclear waste disposal. Under these conditions, the cement is in contact with low radiation doses, but there is a distinct possibility of being contaminated with radioactive products. Of particular concern is the medium lived half-life product 90 Sr (28.8 years) due to its ability to replace Ca. 90 Sr undergoes β-decay to 90 Y which, in turn, β-decays to stable 90 Zr. In this work, we discuss systematically the chain of non-equilibrium processes that result as a consequence of β-decay events in cement. We first use density functional-based methods to study the consequences of the sudden increase of the nuclear charge from Z to Z+1, a possible induced ionization and the perturbation of the surrounding electronic charge. Secondly, we use molecular dynamics simulations to study the recoil of the daughter nucleus. Finally, we discuss the damage caused by the ionization cascade produced during the propagation of the β-electron and the resulting chemical and structural perturbation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Predicting drug-metagenome interactions: Variation in the microbial β-glucuronidase level in the human gut metagenomes

Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.

59 BASIC BIOLOGICAL SCIENCES↗

High-Resolution Simulations of Geological CO 2 Injection: Application to the SPE11 Benchmark

Geological carbon sequestration (GCS) will play a critical role in decarbonization and in facilitating the transition to clean energy systems. Because CO 2 is highly mobile, ensuring its safe and permanent injection into subsurface geological formations involves monitoring over larger spatial domains and longer time periods than is typical for hydrocarbon reservoirs. This can benefit from simulation tools capable of modeling key CO 2 trapping mechanisms, particularly those optimized for speed and scalability on high-performance computing systems. Using isothermal versions of the SPE11B and SPE11C benchmark cases, we conduct a mesh refinement study simulating CO 2 injection into kilometer-scale rock formations at centimeter resolution with the GEOS open-source simulation framework. We focus on how mesh refinement improves the accuracy of convective mixing in both 2D and 3D simulations. The computational costs associated with achieving a converged solution highlight the need for predictive upscaling techniques. A systematic performance scaling analysis—including both central processing unit (CPU) and graphics processing unit (GPU) architectures—complements the “Results” section.

Geosciences↗

Coupling Thermomechanical Processing and Alloy Design to Improve Textures in Mg-Zn-Ca Sheet Alloys

Abstract The effect of Ca and Zn additions on the microstructure and texture evolution during thermomechanical processing of Mg-Zn-Ca sheet alloys was systematically investigated and quantified. Plane strain compression testing in a Gleeble thermomechanical simulator was used to physically simulate a 10-pass rolling schedule, while allowing for careful control and monitoring of the processing parameters. Textures in the as-deformed ternary alloy samples demonstrate a weak maximum basal intensity and spreading in the transverse direction. Increasing the Zn content to 3.2 wt.% in the ternary alloys resulted in samples that exhibited weak textures in the as-deformed state. Importantly, static recrystallization (SRX) during post-deformation annealing of these alloys promoted a desirable annular texture, with the c -axis tipped from the normal direction and a lower basal texture intensity. The evolution in texture during SRX is associated with as-deformed microstructures with broad grain orientation spreads and a low degree of recrystallization.

36 MATERIALS SCIENCE↗

A functional modeling approach for quality assurance in metal additive manufacturing

Purpose: Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. Here, a systematically integrated holistic view is proposed to achieve QA for AM. Design/methodology/approach: A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling. Findings: The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility. Research limitations/implications: A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study. Social implications: This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system. Originality/value: This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

36 MATERIALS SCIENCE↗

Systematic Study of Al Impurity for NCM622 Cathode Materials

Many recycling processes have been developed for spent Li-ion batteries (LIBs), such as pyrometallurgy, hydrometallurgy, and direct recycling. For all the recycling methods, however, impurities are always introduced from the current collectors or casing materials, especially aluminum (Al), which might lead to negative effects on recovered electrode materials. Therefore, it is significant to determine the impacts of Al impurity on recovered materials. Here, the influence of the Al impurity for the synthesized LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) precursor and cathode is systematically studied. The cell with 0.2 at % Al impurity displays the highest reversible capacities (145.2, 130.5, and 100.3 mAh g -1 from 2, 3, and 5 C, respectively) and striking cycling capability at 2 C after 100 cycles with the highest retention capacity of 138.5 mAh g -1 . Meanwhile, the excess Al ions (5 at %) lead to the Li/Mn superlattice structure and deteriorate electrochemical performance of the synthesized NCM622 cathode.

25 ENERGY STORAGE↗

Molten Salt Corrosion Tests of Additively Manufactured Stainless Steel 316H

Molten salt reactors (MSRs) have drawn considerable interest due to their favorable safety features, high thermal efficiency, and compatibility with different fuel cycles. Yet, the success of MSRs hinges critically on the performance of structural materials to be used in these aggressive molten salt environments, where corrosion and material compatibility remain primary challenges to long-term reliability. Additively manufactured (AM) nuclear structural materials prompt the use of novel geometries and compositions to enhance material performance and reduce costs of constructing MSRs. The rapid solidification conditions inherent to AM processing impart distinctive microstructural features, including cellular sub-structures, dislocation densities, residual stress, and oxide inclusions, which can influence material performance in MSR components. While the mechanical properties of AM stainless steels have been widely studied, their corrosion behavior, particularly in molten salt environments, has received far less attention. Addressing these needs, the Advanced Materials and Manufacturing Technologies (AMMT) program provides a framework for systematically evaluating how unique microstructures produced by AM processes influence the performance of these materials in these demanding environments and for developing reproducible testing workflows that can support future code qualification efforts and standards development. Bridging this knowledge gap is essential for assessing the viability of AM alloys in MSRs and informing qualification strategies. A further challenge is the absence of standardized protocols for molten salt corrosion testing. Accordingly, this report provides an account of the corrosion evaluation of AM 316H stainless steel in NaCl 2 -MgCl 2 molten salt at 550 °C, with exposure times of 100 and 500 hours. It documents the experimental procedures implemented under the AMMT program, including salt preparation, exposure protocols, and post-test characterization methods, to establish reproducibility and transparency. Importantly, the study examines AM 316H samples in the as-fabricated condition, directly reflecting the surface state most relevant to engineering applications, and compares their behavior to machine-cut surfaces. Overall, preliminary evaluations have noted that surface conditions (e.g. morphology, contamination, etc.) have a noticeable impact on the corrosion resiliency. The impact of the corrosion is difficult to detect at 100h, unless, in the case of AM 316H, the specimen surface is decontaminated. After 500 h, as-fabricated surfaces of AM and wrought 316H display evidence of general versus preferential corrosion attack, respectively. Both AM and wrought 316H machine-cut surfaces exhibit a continuous Cr depletion zone, evident of general corrosion. While the estimated extent of corrosion appears within the same order of magnitude regardless of the surface condition, it is apparent that more predictable behavior is observed on machine-cut surfaces. Nonetheless, further investigation is necessary to fully elucidate the corrosion mechanism under these conditions.

36 - MATERIALS SCIENCE↗

Macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite with the effects of dissolved carbonates under anoxic conditions

Manganese and its compounds have been extensively researched because of their far-reaching roles in a wide range of biogeochemical processes in natural systems. The (ad)sorption behavior of Mn(II), however, is poorly understood despite its important role as the primary reaction step for surface-catalyzed Mn(II) oxidation that is the principal abiotic process forming various Mn (oxyhydr)oxides in nature. Here, we systematically examined Mn(II) (ad)sorption to one of the most common natural sorbents, goethite, in oxygen- and carbonate-free systems. Traditional sorption edge and isotherm experiments were conducted by varying sorbate-to-sorbent ratio (0.027–15 μmol∙m -2 ) and solution pH (pH 5.0–9.0). The effects of dissolved carbonates on Mn(II) sorption were also assessed in a range of naturally prevalent concentrations (0.5–10 mM NaHCO 3 ). The Mn(II) uptake on goethite followed a typical Langmuir isotherm in the absence of dissolved carbonates, with increasing maximum adsorption capacities (Γ max ) from 0.19 at pH 6.5 to 3.4 μmol∙m -2 at pH 9.0. The presence of dissolved carbonates raised the extent of Mn(II) adsorption, which appeared to be directly correspondent to that of the adsorption of dissolved carbonates. Extended X-ray absorption fine structure (EXAFS) analysis indicated that Mn(II) predominantly formed inner-sphere binuclear bidentate surface complexes. Mn(II) uptake became deviated from the Langmuir model and showed a clear indication of surface precipitation when the Mn(II) sorption density (Γ) exceeded a threshold value in a given solution composition. This secondary Mn(II) phase was identified as rhodochrosite using X-ray diffraction (XRD) and transmission electron microscope (TEM). Furthermore, it would be plausible that a minor fraction of adsorbed Mn(II) coexisted with the secondary rhodochrosite according to a linear combination fitting (LCF) of the X-ray absorption near edge structure (XANES) spectra of Mn reference and samples. These systematic investigations of the macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite provide a critical avenue for disentangling surface-catalytic Mn(II) oxidation processes, which ultimately lead to the formation of diverse Mn (oxyhydr)oxides in the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Covariant density functional theory input for r-process simulations in actinides and superheavy nuclei: The ground state and fission properties

A systematic investigation of the ground-state and fission properties of even-even actinides and superheavy nuclei with Z = 90–120 from the two-proton up to two-neutron drip lines with proper assessment of systematic theoretical uncertainties has been performed for the first time in the framework of covariant density functional theory (CDFT). Furthermore, these results provide a necessary theoretical input for the r-process modeling in heavy nuclei and, in particular, for the study of fission cycling. Four state-of-the-art globally tested covariant energy density functionals (CEDFs), namely, DD-PC1, DD-ME2, NL3*, and PC-PK1, representing the major classes of the CDFT models are employed in the present paper. Ground-state deformations, binding energies, two-neutron separation energies, α-decay Q α values and half-lives, and the heights of fission barriers have been calculated for all these nuclei. Theoretical uncertainties in these physical observables and their evolution as a function of proton and neutron numbers have been quantified and their major sources have been identified. Spherical shell closures at Z = 120, N = 184, and N = 258 and the structure of the single-particle (especially, high-j) states in their vicinities as well as nuclear matter properties of employed CEDFs are two major factors contributing to theoretical uncertainties. However, different physical observables are affected in a different way by these two factors. For example, theoretical uncertainties in calculated ground-state deformations are affected mostly by the former factor, while theoretical uncertainties in fission barriers depend on both of these factors.

190 ≤ A ≤ 219↗

A comparison of Gaussian processes and neural networks for computer model emulation and calibration

The Department of Energy relies on complex physics simulations for prediction in domains like cosmology, nuclear theory, and materials science. These simulations are often extremely computationally intensive, with some requiring days or weeks for a single simulation. In order to assure their accuracy, these models are calibrated against observational data in order to estimate inputs and systematic biases. Because of their great computational complexity, this process typically requires the construction of an emulator, a fast approximation to the simulation. In this paper, two emulator approaches are compared: Gaussian process regression and neural networks. Their emulation accuracy and calibration performance on three real problems of Department of Energy interest is considered. On these problems, the Gaussian process emulator tends to be more accurate with narrower, but still well-calibrated uncertainty estimates. The neural network emulator is accurate, but tends to have large uncertainty on its predictions. Finally, as a result, calibration with the Gaussian process emulator produces more constrained posteriors that still perform well in prediction.

97 MATHEMATICS AND COMPUTING↗

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then, the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we demonstrate an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially benchmark in electrocatalysts research.

Science & Technology - Other Topics↗