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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 73 records · Page 4

Flow Instabilities in boiling channels and their suppression methodologies—A review

Small modular reactors (SMRs) are gaining significant attention as a promising solution for clean and sustainable nuclear-power generation. However, the operation of SMRs is subject to various challenges, including two-phase flow instabilities. Flow instability has the potential to trigger flow-induced vibration and cyclic fluctuations in local thermal stress. These instabilities frequently manifest because of the complex interplay among a multitude of factors, encompassing thermal-hydraulic conditions, the geometric configuration of the steam generator, and operational parameters. These conditions could subsequently lead to premature critical heat flux, equipment malfunctions, and other safety concerns. Here, the endeavor to address steam-generator flow instabilities is of utmost importance in augmenting the sustainability and efficiency of contemporary energy production. This study offers a comprehensive review of instabilities in two-phase flow, with a particular focus on the influential factors impacting the stability of flow boiling. Furthermore, it delves into the processes of identifying, characterizing, and ameliorating these instabilities, emphasizing pivotal findings, methodologies employed, and avenues for prospective research. The primary parameters of concern encompass the efficient transfer of thermal energy, the optimization of mass-flow rates, and the establishment of favorable boundary conditions, all in the context of steam generator design to alleviate instability for water-cooled SMRs. These discernments bear substantial ramifications for enhancing reactor performance and ensuring operational safety.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Understanding the transport and break up of reactive ejecta

This manuscript investigates reactive- versus hydrodynamic-breakup processes of ejecta. For this paper, the reactive metal is cerium (Ce) and the nonreactive metal is tin (Sn), the nonreactive gas is helium (He) and the reactive gas is deuterium (D 2 ) or hydrogen (H 2 ). Experiments were performed in vacuum and the reactive- and nonreactive-gases at various pressures, where we endeavored to match the post-shock gas densities to differentiate between reactive- versus hydrodynamic-breakup processes. Hydrodynamic breakup sensitively links to the Weber number (gas density, liquid fragment diameter, surface tension, and the square of the relative velocity between the fragment and the gas), whereas reactive breakup links to the reactive dynamics which includes two processes. In one case the reactive metal breaks up into smaller fragments as rapidly as the reaction rate, and in the other a crust grows on the liquid fragments as the reactions occur, a diffusion limited process. In the latter case, the particle diameters increase with time as the crust grows. In this process, which is indicated by the data, particles breakup as the CeD 2 loses strength with increasing temperature, leaving an exponentially increasing diameter.

36 MATERIALS SCIENCE↗

The anomalous magnetic moment of the muon in the Standard Model: an update

We present the current Standard Model (SM) prediction for the muon anomalous magnetic moment, a μ , updating the first White Paper (WP20) [1]. The pure QED and electroweak contributions have been further consolidated, while hadronic contributions continue to be responsible for the bulk of the uncertainty of the SM prediction. Significant progress has been achieved in the hadronic light-by-light scattering contribution using both the data-driven dispersive approach as well as lattice-QCD calculations, leading to a reduction of the uncertainty by almost a factor of two. The most important development since WP20 is the change in the estimate of the leading-order hadronic-vacuum-polarization (LO HVP) contribution. A new measurement of the e + e - → π + π - cross section by CMD-3 has increased the tensions among data-driven dispersive evaluations of the LO HVP contribution to a level that makes it impossible to combine the results in a meaningful way. At the same time, the attainable precision of lattice-QCD calculations has increased substantially and allows for a consolidated lattice-QCD average of the LO HVP contribution with a precision of about 0.9%. Adopting the latter in this update has resulted in a major upward shift of the total SM prediction, which now reads $a^{SM}_{μ}$ = 116 592 033 (62) x $10^{-11}$ (530 ppb). When compared against the current experimental average based on the E821 experiment and runs 1–6 of E989 at Fermilab, one finds $a^{exp}_{μ} -a^{SM}_{μ}= 38 (63)$ x $10^{-11}$, which implies that there is no tension between the SM and experiment at the current level of precision. The final precision of E989 (127 ppb) is the target of future efforts by the Theory Initiative. The resolution of the tensions among data-driven dispersive evaluations of the LO HVP contribution will be a key element in this endeavor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation

The ever-increasing demand for novel materials with superior properties inspires retrofitting traditional research paradigms in the era of artificial intelligence and automation. An autonomous experimental platform (AEP) has emerged as an exciting research frontier that achieves full autonomy via integrating data-driven algorithms such as machine learning (ML) with experimental automation in the material development loop from synthesis, characterization, and analysis, to decision making. In this review, we started with a primer to describe how to develop data-driven algorithms for solving material problems. Then, we systematically summarized recent progress on automated material synthesis, ML-enabled data analysis, and decision-making. Finally, we discussed the challenges and opportunities in an endeavor to develop the next-generation AEP for ultimately realizing an autonomous or self-driving laboratory. In conclusion, this review will provide insights for researchers aiming to learn the frontier of ML in materials science and deploy AEP in their labs for accelerating material development.

36 MATERIALS SCIENCE↗

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dense nuclear matter equation of state from heavy-ion collisions

The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics. With advances in microscopic theories for nuclear interactions, the availability of experiments probing nuclear matter under conditions not reached before, endeavors to develop sophisticated and reliable transport simulations to interpret these experiments, and the advent of multi-messenger astronomy, the next decade will bring new opportunities for determining the nuclear matter EOS, elucidating its dependence on density, temperature, and isospin asymmetry. Among controlled terrestrial experiments, collisions of heavy nuclei at intermediate beam energies (from a few tens of MeV/nucleon to about 25 GeV/nucleon in the fixed-target frame) probe the widest ranges of baryon density and temperature, enabling studies of nuclear matter from a few tenths to about 5 times the nuclear saturation density and for temperatures from a few to well above a hundred MeV, respectively. Collisions of neutron-rich isotopes further bring the opportunity to probe effects due to the isospin asymmetry. However, capitalizing on the enormous scientific effort aimed at uncovering the dense nuclear matter EOS, both at RHIC and at FRIB as well as at other international facilities, depends on the continued development of state-of-the-art hadronic transport simulations. Furthermore, this white paper highlights the essential role that heavy-ion collision experiments and hadronic transport simulations play in understanding strong interactions in dense nuclear matter, with an emphasis on how these efforts can be used together with microscopic approaches and neutron star studies to uncover the nuclear EOS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hybrid classical-quantum communication networks

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum–classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications.

Fiber-optic communication↗

A data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS

The processing of actinide samples is a complex and costly endeavor that requires compositional analysis at various stages. Laser-induced breakdown spectroscopy (LIBS) has been used to analyze actinide-containing samples in many nuclear applications including waste management, fuel processing and forensics. The LIBS spectrum obtained from actinide materials are generally extremely complex, exhibiting many thousands of strong emission lines. This makes it difficult to identify other elements within the sample of interest, given the rich and dominant actinide spectrum. Here, in this article, we describe a recent effort to identify and quantify impurities and alloying constituents in plutonium matrices using a hand-held LIBS instrument that is used to rapidly and efficiently measure an emission spectrum from a material sample. We tabulate the emission line positions and intensities of plutonium. We report the development of machine-learning software that can identify gallium and quantify its concentration in plutonium matrices. This work has the potential to provide a rapid and nearly non-destructive technique that allows more confidence in characterizing the composition of materials that are present within complex actinide associated targets. We describe how our LIBS measurements and data analysis methods have successfully quantified the gallium concentration in a variety of samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-targeted discovery-based analysis for gas chromatography with mass spectrometry: A comparison of peak table, tile, and pixel-based Fisher ratio analysis

The ability to discover minute differences between samples or sample classes for gas chromatography coupled to mass spectrometry (GC-MS) can be a challenging endeavor, especially when those differences are not a priori . Fisher ratio (F-ratio) analysis is an apt technique to probe the differences between GC-MS chromatograms. F-ratio analysis is a supervised, non-targeted, discovery-based method that compares two different samples (or sample classes) to reduce the GC-MS dataset into a hit list composed of class distinguishing compounds. Three different F-ratio techniques, peak table, tile, and pixel-based were used to “discover” nine non-native analytes that were spiked into gasoline at four different nominal concentrations of 250, 85, 25, 5 parts-per-million (ppm). For the tile and pixel-based F-ratio calculations, a novel methodology is introduced to improve the sensitivity of the F-ratio calculations while reducing false positives. Furthermore, we use a combinatorial technique using null class comparisons, termed null distribution analysis, to determine a statistical F-ratio cutoff for analysis of the hit lists. The pixel-based algorithm was the most sensitive method and was able to “discover” all nine spiked analytes at a nominal concentration of 250 ppm albeit with one false positive interspersed towards the bottom of the hit list. The pixel-based software was also able to “discover” more of the spiked analytes at the lower concentrations with seven of the spiked analytes “discovered” at 85 ppm, four of the spiked analytes “discovered” at 25 ppm, and one analyte “discovered” at 5 ppm.

47 OTHER INSTRUMENTATION↗

Proof-of-concept chemometric approach for environmental forensic sourcing of crude oil samples using SPME-GC-MS

Environmental exposure to crude oil through seepage and spillage poses risks to the immediate environment and the broader ecosystem as areas along the oil distribution path are affected by the influx of crude petroleum as well as the environmental, economic, and civil unrest that accompanies it. There is a large financial burden associated with the lost resources, including the cost of rehabilitation, and the affected sources of revenue for communities affected by oil spills. As such, it is crucial to determine the responsible parties. This work outlines an environmental forensics approach to determining the source of an un-weathered crude oil sample. The researchers employed solid phase microextraction coupled with gas chromatography mass spectrometry (SPME-GC-MS) to capture and analyze the gaseous components emitted by crude oil samples sourced from five locations. Samples were analyzed using Spearman's rank correlation and 3D covariance analysis. Both chemometric approaches yielded optimal performance results with no misclassifications, true positive rate (TPR) = 100 % and false positive rate (FPR) = 0 %. The similarity metrics calculated by each test noted clear delineations between the values of same-source and differently sourced samples. The Spearman's rank correlation test and 3D covariance calculations both demonstrated the ability to correctly identify sample source origin in this dataset. Finally, the authors outline an approach to the future application of these tests and suggest their joint use in future crude oil sourcing endeavors.

3D covariance mapping↗

MEP pathway products allosterically promote monomerization of deoxy-D-xylulose-5-phosphate synthase to feedback-regulate their supply

Isoprenoids are a very large and diverse family of metabolites required by all living organisms. All isoprenoids derive from the double-bond isomers isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP), which are produced by the methylerythritol 4-phosphate (MEP) pathway in bacteria and plant plastids. It has been reported that IPP and DMAPP feedback-regulate the activity of deoxyxylulose 5-phosphate synthase (DXS), a dimeric enzyme that catalyzes the main flux-controlling step of the MEP pathway. Here we provide experimental insights into the underlying mechanism. Isothermal titration calorimetry and dynamic light scattering approaches showed that IPP and DMAPP can allosterically bind to DXS in vitro, causing a size shift. In silico ligand binding site analysis and docking calculations identified a potential allosteric site in the contact region between the two monomers of the active DXS dimer. Modulation of IPP and DMAPP contents in vivo followed by immunoblot analyses confirmed that high IPP/DMAPP levels resulted in monomerization and eventual aggregation of the enzyme in bacterial and plant cells. Loss of the enzymatically active dimeric conformation allows a fast and reversible reduction of DXS activity in response to a sudden increase or decrease in IPP/DMAPP supply, whereas aggregation and subsequent removal of monomers that would otherwise be available for dimerization appears to be a more drastic response in the case of persistent IPP/DMAPP overabundance (e.g., by a blockage in their conversion to downstream isoprenoids). Our results represent an important step toward understanding the regulation of the MEP pathway and rational design of biotechnological endeavors aimed at increasing isoprenoid contents in microbial and plant systems.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrogen-Bonded Organic Frameworks: A Rising Class of Porous Molecular Materials

Hydrogen-bonded organic frameworks (HOFs) are a class of porous molecular materials that rely on the assembly of organic building blocks by means of hydrogen-bonding interactions to form two-dimensional (2D) and three-dimensional (3D) crystalline networks. The reversible nature of the hydrogen-bond formation endows HOFs with the attributes of solution processability and simple regeneration. High-quality single crystals of HOFs can be grown easily for unambiguous superstructure determination by single-crystal X-ray diffraction, which is crucial for the elucidation of superstructure–property relationships. During the past decade, considerable progress has been achieved in realizing stable HOFs with permanent porosities by focusing on the design of molecular building blocks in order to introduce rigidity, auxiliary [π···π] interactions, and interpenetration of their frameworks to sustain the extended networks. The applications of HOFs are far-reaching, spanning catalysis, energy, and biomedical products as well as the storage and separation of fine chemicals. In this paper, we, first of all, provide an overview of the chronological development of HOFs, starting from the seminal work by Marsh and Duchamp in 1969 on the crystal superstructure of the hydrogen-bonded networks of trimesic acid. We identify the development of novel hydrogen-bonding motifs such as diaminotriazine (DTA), the introduction of the concept of molecular tectonics, and the establishment of permanent porosity in HOFs as being some of the milestones, which incentivized the current burgeoning research endeavors on developing HOFs as multifunctional materials. This Account is focused primarily on surveying the strategies for constructing porous 3D HOFs based on organic building blocks with peripheral carboxyl groups. These strategies are presented in the following categories: (1) the polycatenation of 2D networks by trigonal building blocks to form global 3D frameworks, (2) the utilization of building blocks with 3D geometries—tetrahedral and trigonal prismatic—that are predisposed to form 3D networks, and (3) the docking by shape-fitting of geometrically labile building blocks. We emphasize how the molecular geometry of the building blocks plays an important role in modulating the superstructures of extended frameworks so as to address specific applications. Recognizing that the in silico design of HOFs is the ultimate goal of researchers in this field, we also discuss the recent advances in superstructure prediction that lead to the formation of porous supramolecular crystals and assess the complications in implementing computational methods for HOFs with complex superstructures. We hope this Account will inspire the development of new supramolecular designs and creative approaches to crystal engineering that aid and abet the assembly of multifunctional HOFs with customizable properties.

36 MATERIALS SCIENCE↗

Impact of Residual Lithium on the Adoption of High-Nickel Layered Oxide Cathodes for Lithium-Ion Batteries

High-nickel layered oxide cathodes are becoming appealing for lithium-ion batteries employed in portable electronics and electric vehicles because of their higher energy density, low or no cobalt content, and ability to be manufactured with existing infrastructure. However, high-nickel layered oxides are plagued by the formation of residual lithium species, such as LiOH and Li 2 CO 3 , on the surface, which are detrimental to the manufacturing process and performance. Despite the problems residual lithium causes for the industry, academia mainly focuses on the safety risks and electrochemical impacts of residual lithium. In this Perspective, we examine the residual lithium problem through a lens of its impact on cathode slurry instability and large-scale manufacturing of high-nickel layered oxides. Additionally, methods of measuring residual lithium are discussed from the perspective of their accuracy as well as practicality in the manufacturing process. Furthermore, we hope that this Perspective would encourage the academic endeavor to consider the practical obstacles caused by residual lithium on the industrialization of high-nickel layered oxides and their mitigation, while attempting to improve their electrochemical performance and safety through doping, surface modifications, or other approaches.

25 ENERGY STORAGE↗

Computationally Accelerated Discovery of High Entropy Pyrochlore Oxides

High entropy ceramics provide enhanced flexibility for tailoring a wide range of physical properties, emerging from the diverse chemical and configurational degrees of freedom. Expanding upon the endeavors of recently synthesized high entropy ceramics in rock salt, fluorite, spinel, and perovskite structures, we explore the relative feasibility of formation of high entropy pyrochlore oxides, A 2 B 2 O 7 , with multication occupancy of the B-site, estimated from first-principles-based thermodynamic descriptors. Subsequently, we used Monte Carlo simulations to estimate the phase composition, oxygen vacancy concentration, and local ionic segregation as a function of temperature and oxygen partial pressure. In synergy with the theoretical calculations, we have investigated the synthesis of several multicomponent oxides with a pyrochlore composition, related to our computational investigations, resulting in four phase pure and one 97.4% pure high entropy pyrochlore oxides. Ultimately, our approach allows us to evaluate potential impurity phases, ionic disorder, and oxygen vacancy concentration in response to the experimental variables, thereby making realistic predictions that can direct and accelerate experimental synthesis of novel multicomponent ceramics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of Metal Selection in the Radiation Stability of Isostructural M-UiO-66 Metal–Organic Frameworks

Robust and versatile metal–organic frameworks (MOFs) have emerged as sophisticated scaffolds to meet the critical needs of the nuclear community, but their performance depends on their underexplored structural integrities in high- radiation fields. The contributions of selected metal nodes in the radiation stability of MOFs within the isostructural M-UiO-66 series (where M = Zr, Ce, Hf, Th, and Pu; Zr-UiO-66 experiments were executed in a previous work) have been determined. Ce-, Hf-, and Th-UiO-66 MOF samples were irradiated via gamma and He-ion methodologies to obtain doses up to 3 MGy and 85 MGy, respectively, the latter strikingly higher than that obtained in most other studies. Appreciable self-irradiation constituted the total absorbed doses, up to 31 MGy of the gamma-irradiated Pu-UiO-66 samples. Structural degradation was ascertained by powder X-ray diffraction, X-ray total scattering, vibrational spectroscopy, and, where possible, N 2 physisorption isotherms. Diffuse reflectance infrared Fourier transform spectroscopy provided atomic-level mechanistic insights to reveal that the node-linker connection was most susceptible to radiation damage. Density functional theory calculations were performed on cluster models to evaluate the binding energy of the linkers to each metal node. Here, while the isostructures disclosed the same breakdown signatures, distinct radiation sensitivity as a function of metal selection was evident and followed the trend Hf-UiO-66 ~ Zr-UiO-66 > Th-UiO-66 > Pu-UiO-66 > Ce-UiO-66. We anticipate that these endeavors will contribute to the rational design of radiation-resistant materials for targeted applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-Temperature Processing of Pyrolysis Bio-Oil for Sustainable Biographite Production

Catalytic graphitization of pyrolysis bio-oil with iron (Fe) can produce an anode material for lithium-ion batteries (LIBs) at a moderate temperature. The key challenge to scaling up the process is foaming, which occurs due to the oxidation of Fe by the organic acids present in bio-oil. This study explored five different pathways to control foaming in bio-oil upon Fe addition, including (i) defoamers use, (ii) use of iron oxide (Fe2O3) as graphitization catalyst, (iii) pH adjustment of bio-oil, (iv) bio-oil coking (300-500 degrees C), and (v) low-temperature pretreatment of bio-oil (150-200 degrees C). The low-temperature pretreatment successfully avoided foaming by removing the volatile acids in bio-oil. The bio-oil was solidified and powdered for even mixing with the Fe catalyst. The biographite catalytically prepared at 1500 degrees C following this pathway demonstrated nearly theoretical specific gravimetric capacity (~370 mAh/g), high initial Coulombic efficiency (90.03%), and minimal capacity fading after 50 cycles in LIB half-cells. The low-temperature pretreatment pathway also addressed the viscosity, swelling, and aging issues associated with bio-oil processing and will make scale-up endeavors more attainable.

09 BIOMASS FUELS↗

Safety moments in chemical safety education.

Chemical safety education is a critical aspect of an integrated culture of safety in academic research settings. Showcasing best practices and sharing practical solutions for recognizing hazards and minimizing risks represent one way of reinforcing a research community's actions, attitudes, and behavior toward safety. For goals of improving chemical safety education with nonformal endeavors, safety moments are similar to 1-2 slides that focus on raising awareness and knowledge for routine safety issues in research laboratories. Intended to catalyze brief discussions at the beginning of meetings and presentations, these materials provide a proactive way for students and faculty to engage in open communication on diverse research safety topics across science and engineering. This commentary provides an overview of designing effective safety moments and tailoring them to highlight practical safety needs and considerations. Key components of model safety moment slides are presented, alongside centralized resources assembled by student-led laboratory safety teams, which can also be extended to posters, social media platforms, online videos, and other forms of scientific communication. Combined with both top-down backing from institution leaders and bottom-up support from student researchers, safety moments remain a low-barrier risk reduction strategy that is easy to implement, encourages local dialogue on safety, combats complacency, and holds potential for facilitating long-term improvements to academic lab safety culture.

Communication/Writing↗