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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 109 records · Page 6

Investigation of Proton Beam-Driven Fusion Reactions Generated by an Ultra-Short Petawatt-Scale Laser Pulse

We present results from a pitcher-catcher experiment utilizing a proton beam generated with nanostructured targets at a petawatt-class, short-pulse laser facility to induce proton-boron fusion reactions in a secondary target. A 45-fs laser pulse with either 400 nm wavelength and 7 J energy, or 800 nm and 14 J, and an intensity of up to 5 × 10 21 W/cm 2 was used to irradiate either thin foil targets or near-solid density, nanostructured targets made of boron nitride (BN) nanotubes. In particular, for 800 nm wavelength irradiation, a BN nanotube target created a proton beam with about five times higher maximum energy and about ten times more protons than a foil target. This proton beam was used to irradiate a thick plate made of boron nitride placed in close proximity to trigger 11 B (p, α) 2α fusion reactions. A suite of diagnostics consisting of Thomson parabola ion spectrometers, postshot nuclear activation measurements, neutron time-of-flight detectors, and differentially filtered solid-state nuclear track detectors were used to measure both the primary proton spectrum and the fusion products. From the primary proton spectrum, we calculated (p, n) and (α,n) reactions in the catcher and compare with our measurements. The nuclear activation results agree quantitatively and neutron signals agree qualitatively with the calculations, giving confidence that primary particle distributions can be obtained from such measurements. These results provide new insights for measuring the ion distributions inside of proton-boron fusion targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Microwave heated chemical looping ammonia synthesis over Fe and CoMo particles

Chemical looping ammonia synthesis (CLAS) materials were subjected to a three cycle ammonia synthesis test under both conventional thermal heating and microwave heating. Microwave heating was found to outperform conventional heating for the first cycle on both Fe and CoMo materials. Principles of microwave catalysis and the heating of metallic particles may be generalized from this study; the dielectric loss tangent for optimum heating must fall within a realtively small range, ~0.8–1.4, and the penetration depth of the microwave into the particle must be considered and optimized for efficient heating, penetration depth should be on the same order as the particle size. The active phases of both catalysts, Fe 4 N and Co 3 Mo 3 N, were found to be responsive to microwave irradiation. Lastly, the deactivation and regeneration of the materials was studied by examining the BET surface areas by reforming surfaces with a low concentration gas phase oxidation reaction. This study sheds light on more general principles of microwave catalysis and on the scale-up of CLAS reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Regulating the Third Metal to Design and Engineer Multilayered NiFeM (M: Co, Mn, and Cu) Nanofoam Anode Catalysts for Anion-Exchange Membrane Water Electrolyzers

In this study, alkaline anion-exchange membrane water electrolyzers (AEMWEs) for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant platinum group metal (PGM)-free catalysts. Herein, the third metal is incorporated into NiFe-based catalysts to regulate their electronic structures and morphologies, aiming to achieve sufficient oxygen evolution reaction (OER) activity and performance in AEMWEs. The ternary NiFeM (M: Cu, Co, or Mn) catalysts are featured with multiple layered structures and nanofoam network morphologies, consisting of highly OER-active amorphous Ni-rich oxide shells and electrically conductive metallic alloy cores. The physical and electronic perturbations to the NiFe induced by a third element lead to a fine-tuning of the redox ability of the metal sites at the reaction centers, which breaks the scaling relationship between OH* and O* intermediates at the reaction centers. Thus, the unique structural configuration and electronic regulation simultaneously benefit catalytic activity and performance improvements. These NiFeM nanofoam catalysts demonstrated promising anode performance in actual AEMWEs, comparable to the IrO 2 reference, especially at high current densities. Notably, using various electrolytes (e.g., KOH solution or pure water) for AEMWEs exhibited a different performance trend among studied NiFeM catalysts, likely due to dynamic changes of catalysts under various OER environments.

25 ENERGY STORAGE↗

Steric effects of central dogma processes on the compaction and segregation of bacterial nucleoids

The bacterial cytoplasm is characterized by a distinctive membrane-less organelle, the nucleoid, which harbors the chromosomal DNA. Here, we investigate the steric effects of dynamic processes associated with transcription and translation on the structure of this organelle using coarse-grained molecular dynamics simulations that incorporate out-of-equilibrium reactions. Our model captures the scale of the entire cell and incorporates a reaction-diffusion system for ribosomes and polyribosomes, coupling their nonequilibrium kinetics to DNA excluded volume interactions. Our findings demonstrate that out-of-equilibrium reactions increase the size of the nucleoid and the number of ribosomes in this subcellular region. In addition, we show that nucleoid size is proportional to transcriptional activity. Our model reproduces the time-dependent change in nucleoid size observed in rifampicin treatment experiments, where the pool of polyribosomes is depleted. Furthermore, we find that these active processes are essential for complete sister chromosome separation and correct nucleoid positioning within the cell. Overall, our study reveals the effects of the central dogma processes on the internal organization and localization of bacterial nucleoids.

Chang, Mu-Hung [Univ. of Tennessee, Knoxville, TN ↗

New scaling and nuclear structure aspects in heavy-ion fusion reactions

Three new behaviors have been found in comparisons of fusion cross sections for different collision systems. root (1) Replacing the energy E with a scaling one, E scal = (E-V g )/($\sqrt{2}$W g ), is successful for washing out the Coulomb interaction in the spectra of fusion cross sections, where V g and W g are barrier height and width of the single-Gaussian barrier distribution model. (2) In a representation of σE vs the scaling energy, E scal , all data sets display in parallel. Here, the ratio for sigma E from any two fusion systems over the whole range is a constant value. That behavior is also studied in another representation, in which the data sets display as parallel horizontal lines for any heavy-ion fusion system. (3) The constant ratio value is the ratio of parameter products, $R^2_gW_g$, of the two systems; where R g is the barrier radius obtained in the single-Gaussian barrier distribution model. Moreover, when comparing neighboring collision systems at the same E scal , the ratio of sigma is near a constant value within a few percent over the whole range. Thus a quantitative comparison for the fusion enhancement for neighboring systems is developed. The present finding could be beneficial for predicting unmeasured fusion cross sections.

Jiang, C. L. [Argonne National Laboratory (ANL), A↗

MEMOTE for standardized genome-scale metabolic model testing

Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

59 BASIC BIOLOGICAL SCIENCES↗

Interplay of intercalation dynamics and lithium plating in monolithic and architectured graphite anodes during fast charging

Fast charging of high-capacity anodes is challenging due to lithium plating reactions, which lead to poor cycling performance and safety concerns. Thus, accurate predictions of plating onset and an understanding of this electrochemical process are crucial for robust battery design. However, the most commonly used models, based on porous electrode theory (e.g., the pseudo-2D model), are notoriously difficult to calibrate due to their complexity, limiting their predictive power. This work studies the process of lithium plating during fast charging of (small-particle) graphite half-cells by measuring local reaction progression and plating behavior using optical operando techniques. These experiments employ a realistic 1D graphite electrode geometry with commercially-relevant mass loading charged at fast charge rates. It is demonstrated that the local reaction progression and plating onset can not only be predicted accurately with a p2D numerical model, but that these processes follow a simple scaling law. Remarkably, the entire reaction histories of different electrodes charged at different rates (e.g., 160 μm thickness at 0.5C, 111 μm at 1C or 66 μm at 4C) were observed to have self-similar intercalation profiles. It is demonstrated that plating onset is in turn governed by the reaction profile which explains why both processes exhibit the same scaling behavior. Finally, operando measurements of local reaction dynamics are conducted for the first time in electrodes with channeled architectures, quantitatively determining how channels affect reaction uniformity and plating onset. Together, these results reveal underlying simplicity in the complex electrochemical environment of fast charging and lithium plating, improving understanding of this process. These fundamental insights are broadly applicable for design processes, modeling and experimental evaluation of lithium ion batteries.

25 ENERGY STORAGE↗

Toward sustainable, cell-free biomanufacturing

Industrial biotechnology is an attractive approach to address the need for low-cost fuels and products from sustainable resources. Unfortunately, cells impose inherent limitations on the effective synthesis and release of target products. One key constraint is that cellular survival objectives often work against the production objectives of biochemical engineers. Additionally, industrial strains release CO2 and struggle to utilize sustainable, potentially profitable feedstocks. Cell-free biotechnology, which uses biological machinery harvested from cells, can address these challenges with advantages including: (i) shorter development times, (ii) higher volumetric production rates, and (iii) tolerance to otherwise toxic molecules. In this review, we highlight recent advances in cell-free technologies toward the production of non-protein products beyond lab-scale demonstrations and describe guiding principles for designing cell-free systems. Specifically, we discuss carbon and energy sources, reaction homeostasis, and scale-up. Expanding the scope of cell-free biomanufacturing practice could enable innovative approaches for the industrial production of green chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Computational fluid dynamics analysis of char conversion in Sandia’s pressurized entrained flow reactor

Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia’s pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

47 OTHER INSTRUMENTATION↗

Emergence of local scaling relations in adsorption energies on high-entropy alloys

Alloying has been proposed to circumvent scaling relations between the adsorption energies thus allowing for the complete optimization of multistep reactions. Herein the fidelity of scaling rules on high-entropy alloy (HEA) surfaces is assessed focusing on hydrogen-containing molecules, *AH x for A = C and N (x = 0, 1, 2, 3), A = S (x = 0, 1, 2) and A = O (x = 0, 1). Using an adsorbate- and site-specific deep learning model to rapidly compute the adsorption energies on CoMoFeNiCu HEA surfaces, the energies of *AH x and *A are shown to be linearly correlated if *A and *AH x have identical adsorption site symmetry. However, a local linear dependence emerges between the configuration-averaged adsorption energies irrespective of the site symmetry. Although these correlations represent a weaker form of the scaling relationships, they are sufficient to prohibit the optimization of multistep reactions. The underpinning of this behavior is twofold (1) the nearsightedness principle and (2) the narrow distribution of the adsorption energies around the mean-field value. While the nearsightedness is general for all electronic systems, the second criterion applies in HEAs with relatively strong reactive elements. The present findings strongly suggest that alloys may not generally enable the breaking of scaling relationships.

36 MATERIALS SCIENCE↗

Machine Intelligence to Detect, Characterise, and Defend against Influence Operations in the Information Environment

Social media has enabled a new era of manipulation in the information and cognitive domains. Deceptive content—misleading, falsified, and fabricated—is routinely created and spread in the modern social media environment with the intent to create confusion and widen political and social divides, and exploit the societal conflict exacerbated by these divides in the real-world (aka physical domain). Such disinformation campaigns demonstrate a threat to the integrity of economic, political, cultural, public health, and national security institutions around the world. In this work we overview our artificial intelligence (AI) capabilities to detect, describe, and defend against information operations on Twitter as an example social platform to understand the influence of misleading and falsified content diffusion and better enable those charged with defending against such manipulation to enable responsive parties to counter it. We first present novel linguistically-informed deep learning (DL) models for misinformation and disinformation detection, and present an in-depth linguistic analysis of psycho-linguistic markers across broad deception categories. We then demonstrate how our models perform in the multilingual and multimodal setting and categorize falsified and misleading content based on the intent to deceive. We also provide a large-scale analysis to describe user behavior and spread patterns while engaging with deceptive content and report novel findings about the immediate diffusion of deceptive content by characterizing the vulnerable sub-populations and their demographics, and explicitly measuring speed and scale of deception spread to uncover who shares deceptive content, how quickly, how much, and how evenly. In addition, we measure audience reactions to misinformation and disinformation at scale, distinguishing the reactions of users identified as bots versus humans. Finally, we take advantage of deep translation and generation models to create unique solutions for real-time defense against digital deception and discuss how to apply causal inference to prescribe and intervene into strategic communications jointly across information, cognitive, and physical domains.

artificial intelligence, deep learning, neural lan↗

Effective kinetics driven by dynamic concentration gradients under coupled transport and reaction

Biogeochemical reaction kinetics are generally established from batch reactors where concentrations are uniform. In natural systems, many biogeochemical processes are characterized by spatially and temporally variable concentration gradients that often occur at scales which are not resolved by field measurements or biogeochemical and reactive transport models. Yet, it is not clear how these sub-scale chemical gradients affect reaction kinetics compared to batch kinetics. Here we investigate this question by studying the paradigmatic case of localized pulses of solute reacting with a solid or a dissolved species in excess. Additionally, we consider non-linear biogeochemical reactions, representative of mineral dissolution, adsorption and redox reactions, which we quantify using simplified power-law kinetics. The combined effect of diffusion and reaction leads to effective kinetics that differ quantitatively and qualitatively from the batch kinetics. Depending on the nonlinearity (reaction order) of the local kinetics, these effects lead to either enhancement or decrease of the overall reaction rate, and result in a rich variety of reaction dynamics. We derive analytical results for the effective kinetics, which are validated by comparison to direct numerical simulations for a broad range of Damköhler numbers and reaction order. Our findings provide new insights into the interpretation of imperfectly mixed lab experiments, the effective kinetics of field systems characterized by intermittent reactant release and the integration of sub-scale concentration gradients in reactive transport models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗

Complete integration of carbene-transfer chemistry into biosynthesis

Biosynthesis is an environmentally benign and renewable approach that can be used to produce a broad range of natural and, in some cases, new-to-nature products. However, biology lacks many of the reactions that are available to synthetic chemists, resulting in a narrower scope of accessible products when using biosynthesis rather than synthetic chemistry. A prime example of such chemistry is carbene-transfer reactions. Although it was recently shown that carbene-transfer reactions can be performed in a cell and used for biosynthesis, carbene donors and unnatural cofactors needed to be added exogenously and transported into cells to effect the desired reactions, precluding cost-effective scale-up of the biosynthesis process with these reactions. Here, in this paper, we report the access to a diazo ester carbene precursor by cellular metabolism and a microbial platform for introducing unnatural carbene-transfer reactions into biosynthesis. The α-diazoester azaserine was produced by expressing a biosynthetic gene cluster in Streptomyces albus. The intracellularly produced azaserine was used as a carbene donor to cyclopropanate another intracellularly produced molecule—styrene. The reaction was catalysed by engineered P450 mutants containing a native cofactor with excellent diastereoselectivity and a moderate yield. Our study establishes a scalable, microbial platform for conducting intracellular abiological carbene-transfer reactions to functionalize a range of natural and new-to-nature products and expands the scope of organic products that can be produced by cellular metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

Structural features of xylan dictate reactivity and functionalization potential for bio-based materials

Plant-based materials have the potential to replace some petroleum-based products, offering compostability and biodegradability as critical advantages. Xylan-rich biomass sources are gaining recognition due to their abundance and underutilization in current industrial applications. Research of potential xylan applications has been complicated by the complex and heterogeneous structure that varies for different xylan feedstocks. Acylation is a broadly used reaction in functionalization of polysaccharides at an industrial scale. However, the efficiency of this reaction varies with the xylan source. To optimize xylan valorization, a systematic understanding of structure–reactivity relationships is essential. This study explores, characterizes, and compares various xylan feedstocks in the acylation process. Xylan feedstocks were analyzed for their chemical composition, degree of polymerization, branching, solubility, and presence of impurities. These features were correlated with xylan glycotypes’ reactivity toward functionalization with succinic anhydride in an optimized DMSO/KOH condition, achieving carboxyl contents of up to 1.46. We used principal component analysis and hierarchical clustering to identify key structural features of xylan that promote its reactivity. Our findings reveal that xylans with higher xylose content and lower degrees of branching exhibit enhanced reactivity, achieving higher carboxyl content and yields. Structural analyses confirmed successful modification, and light scattering analyses showed dramatic changes in the solution properties. Succinylation improves the solubility and film-forming properties of native xylans. This study shows key structure–reactivity relationships in xylan succinylation, establishing that low branching, high xylose content, and reduced lignin impurity enhance chemical functionalization. The results offer a framework for selecting optimal biomass feedstocks and support future efforts in genetic and synthetic biology to design plants with tunable xylan architectures. These findings advance the hemicellulose valorization for applications in coatings and packaging.

Acylation↗

Multi-group Examination of Nickel-Reflected HEU System [Slides]

Researchers noted an unusually large bias for 8-in. nickel reflected HEU sphere in HMF-003 between the 252- group library and the CE library in SCALE 6.2.4. The bias was investigated by reviewing reactions that $k_{eff}$ is sensitive to using TSUNAMI and collecting reaction rate data using tools within SCALE. For this system, bias is primarily due to the elastic scattering in nickel. Researchers compared new multigroup structures in SCALE 6.3. For this system, reduction in CE-to-MG bias seen in the 302-group and further improved in the 1597-group structure. When researchers compared ENDF/B-VIII.0 in SCALE 6.3, library showed improved results with new nickel evaluation. However, the MG-to-CE bias can still be large as large biases can occur in any system. This example highlights the importance of validating results with measured systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Pore‐Scale Investigation of Mineral Precipitation Driven Diffusivity Change at the Column‐Scale

Abstract Mineral precipitation affects the pore structure and thus transport properties of porous media. In this study, we investigated the pore‐scale dynamics of precipitation in diffusion controlled systems and the resulting impacts on the effective diffusivity, using a micro‐continuum reactive transport model. Forty two‐dimensional pore structures representing both idealized and realistic geometries were simulated with consideration of different precipitation scenarios and rates. A homogeneous nucleation scenario reproduced patterns observed in previous experimental study showing mixing‐induced precipitation, and a surface growth scenario captured the pattern for mineral precipitation on a substrate with the same or similar mineral structures. In all cases, local precipitation resulted in the reduction in the average porosity of the domain ( Φ ) until the cessation of diffusive transport and the termination of precipitation. The minimum porosity reached was referred to as the critical porosity ( Φ c ). The effective diffusivity ( D eff ) decreased with Φ and dropped sharply to effectively zero, that is, the critical effective diffusivity ( D eff c ), as Φ c was reached. These pore‐scale dynamics can be captured by a revised relationship that explicitly considers the critical porosity and the corresponding effective diffusivity, and the pre‐exponential coefficient and the exponent of the relationship varied with initial pore structure and the precipitation kinetics. Overall, the homogeneous nucleation scenario results in systematically larger Φ c and coefficients that give rise to a sharper decrease in diffusivity as Φ c is approached, compared to the surface growth scenario. The revised relationship was also implemented at continuum scale and used to examine column scale diffusivity change and reactions.

58 GEOSCIENCES↗