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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 523 records · Page 29

Irradiation of an enriched uranium (NaCl-UCl 3 ) fuel salt capsule, summary of nondestructive post-irradiation examinations, and solidification modeling

Molten salt reactors (MSRs) are gaining attention due to their potential for safe, carbon-free nuclear energy with reduced waste. However, licensing these reactors is hindered by limited experimental data on fueled salts, both pre- and post-irradiation. Here, the novel Molten-salt Research Temperature-controlled Irradiation (MRTI) vehicle was designed to address knowledge gaps in irradiating enriched‑uranium-bearing salts. The MRTI experiment irradiated 13 cm 3 of UCl₃-NaCl (93 % U-235) salt in the Neutron Radiography (NRAD) Reactor, achieving a burnup of 0.196 GWd/MTU over 390 h. Despite a heater failure, the thermocouple data suggested fission heat kept the salt molten. The MRTI assembly was remotely disassembled for nondestructive post-irradiation examination (PIE), which included precision gamma-ray scanning (PGS) and neutron radiography. Radiograph images showed the location of the salt and the solidification pattern. PGS results provided an early indication that activated materials of construction did not increase in relative intensity in the region of the capsule where the salt was in contact with the material of construction. Additionally, PGS data showed the presence of several gamma emitting fission products, such as Nb-95, Zr-95, Ru-103, Ce-141, and La-140, where Ru-103 had the highest counts at the bottom of the capsule. Computational fluid dynamics modeling supported observations of salt solidification patterns and proved to be a valuable tool to inform PIE activities. The MRTI experiment has thus far provided critical data and lessons learned for fuel salt PIE activities, essential for advancing the technical readiness of MSRs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computational modeling of graphite degradation in molten salt reactors: Role of infiltration

Molten salt reactors (MSRs) often employ graphite as a moderator and reflector. An important challenge for deploying graphite in these reactors is that, due to limited experimental data, our understanding of graphite’s structural integrity in molten salt environments remains incomplete. Here, this study addresses heat generation from fuel-bearing salt that has infiltrated open pores in the graphite, driven primarily by pressure differentials. This is one of multiple identified physical and chemical mechanisms through which molten salt could potentially degrade graphite. Thermally driven stresses are quantified using the Molten-Salt Reactor Experiment (MSRE) graphite moderator elements as a case study. Finite element simulations predict stress distributions at varying infiltration levels, indicating that thermal stresses increase with higher infiltration. Rare-event simulations using the parallel subset simulation framework identify the combinations and corresponding ranges of input parameters that lead to stresses above a specified threshold. In particular, combinations involving high infiltration amounts, high power density, and low thermal conductivity tend to induce the highest stresses. Under the inputs and assumptions considered in this work, the magnitudes of the thermally driven stresses are quite low, with a very low likelihood of causing failure due to exceeding the graphite’s tensile strength. Additionally, rare-event simulations were performed for two more scenarios: a scaled-up moderator geometry and a localized hotspot in the original geometry. Both cases resulted in increased susceptibility to failure, though not to a detrimental extent. Furthermore, the combined effects of irradiation and infiltration-induced thermal stresses were evaluated. The results showed that thermal stresses from infiltration were negligible compared to those caused by irradiation. The findings of such a study are inherently component-specific, but the methodology presented here could be used for similar assessments of salt-infiltration effects in other graphite components.

36 - MATERIALS SCIENCE↗

Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models

To ensure optimal utilization and bioavailability, iron uptake, transport, subcellular localization, and assimilation are tightly regulated in plants. In this work, we examine recent advances in our understanding of cellular responses to Fe deficiency. We then use intracellular mechanisms of Fe homeostasis to discuss how formalizing cell biology knowledge via a mathematical model can advance discovery even when quantitative data is limited. Using simulation-based inference to identify plausible systems mechanisms that conform to known emergent phenotypes can yield novel, testable hypotheses to guide targeted experiments. However, this approach relies on the accurate encoding of domain-expert knowledge in exploratory mathematical models. We argue that this would be facilitated by fostering more “systems thinking” life scientists and that diversifying your research team may be a practical path to achieve that goal.

59 BASIC BIOLOGICAL SCIENCES↗

First measurement in the Gamow window of a reaction for the γ-process in inverse kinematics: 76 Se(α,γ) 80 Kr

The p-nuclei are the few stable nuclei heavier than iron on the neutron-deficient side of the valley of stability that cannot be produced through astrophysical neutron-capture reactions. The limited experimental data on reactions through which the p-nuclei might be produced leaves the origin of their production largely unknown. This work presents the first cross section measurements of the 76 Se(α,γ) 80 Kr reaction. The rate of the time reversed reaction, 80 Kr(γ,α) 76 Se, is one of the most uncertain of possible reactions which can occur at the 80 Kr branching point on the ,-process photo-disintegration pathway. The reaction flow through 80 Kr will directly affect the final abundance of the p nuclide 78 Kr. Experimental cross sections at two astrophysically relevant energies are reported and compared to cross sections calculated using Hauser-Feshbach codes TALYS, NON-SMOKER, and SMARAGD. The success of these first (α,γ) cross section measurements performed in inverse kinematics in the energy region of the γ-process opens the door for future studies of reactions on radioactive γ-process nuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Combining organic amendments with enhanced rock weathering shifts soil carbon storage in croplands

Enhanced rock weathering (ERW) involves applying crushed silicate minerals to cropland soils to remove carbon dioxide and stabilize the global climate. If practiced widely, ERW has the potential to mitigate climate change and improve soil health and crop productivity. However, most ERW studies emphasize inorganic carbon (IC) chemistry, using model-based estimates and short-term mesocosms. Limited field data exist on how ERW interacts with organic amendments to affect organic carbon (C) cycling in soils. In a three-year field study in conventionally managed, irrigated maize fields, we monitored how key soil variables responded to crushed rock-alone, and in combination with compost and/or biochar. We measured weathering indicators (pH, major cations, and IC contents) and organic fractions, including particulate organic matter (POM), mineral-associated organic matter (MAOM), microbial biomass C, and water-extractable organic C. Rock-alone treatments increased weathering proxies (pH and IC) and showed an increasing trend in POM and MAOM, relative to control. In contrast, combining crushed rock with organic amendments resulted in lower soil organic C and nitrogen (N) concentrations (in both POM and MAOM) compared to organic amendments alone, though IC increased in the rock+compost treatment. Combining rock with both compost and biochar (compost/biochar) significantly lowered MAOM-N compared to compost/biochar alone. Overall, co-applying rock with organic inputs may promote weathering and C accrual but slow the accrual rate of organic C and N relative to organic amendments alone. Quantifying these trade-offs over multiple years and scales is critical to integrating ERW with existing soil health practices and climate mitigation strategies.

Biological and medical sciences↗

Entropy-driven melting point depression in fcc HEAs

High Entropy Alloys (HEAs) are an increasingly dominant alloy design paradigm. The premise of entropic stabilization of single-phase alloys has motivated much of the research on HEAs. Chemical complexity may indeed help stabilize single alloy phases relative to other lower-entropy competing solid phases. Paradoxically, this complexity may de-stabilize these alloys against the liquid phase, potentially limiting the application space of HEAs at elevated temperatures. In this work, we carry out a comprehensive investigation of the phase stability in the fcc CoCrFeMnNiV-Al HEA space using a state of the art CALPHAD database. By using modern visualization techniques and statistical analysis we examine the trade-off between chemical complexity and stability against the liquid state and identify a potentially difficult to overcome barrier for development of high temperature alloys, at least within the conventional fcc HEA space. Here, limited experimental data seem to be consistent with this analysis.

36 MATERIALS SCIENCE↗

Temperature-dependent diffuse reflectance measurements of ceramic powders in the near- and mid-infrared spectra

Radiative properties are critical to quantify radiative energy fluxes between surfaces and in participating media. However, there is limited experimental data on temperature-dependent radiative properties of materials. Herein, this work focuses on experimentally measuring temperature-dependent diffuse reflectance in the near- and mid-infrared spectra (1–20 μm) for ceramic particles with applications as heat-transfer and thermal-storage media in concentrated solar power (CSP) plants. Specifically, a commercially available sintered bauxite proppant, ACCUCAST ID80, and its primary chemical constituents—alumina (Al 2 O 3 ) and silica (SiO 2 )—are measured in powder form using a Fourier transform infrared spectrometer (FTIR) coupled with a specialized diffuse reflectance accessory and a heated stage. Room-temperature diffuse reflectance measurements show increased absorption in tests with greater mass fractions of the ceramic samples. There is a strong correlation in the measured reflectance spectra of ACCUCAST with alumina and silica in the spectral range 2000–500 cm –1 (5–20 μm). Whereas, for shorter wavelengths (< 5 μm), the absorptance for ACCUCAST is greater than the absorptance for alumina and silica, indicating contributions from other chemical species present in the composite material. For the first time, temperature-dependent diffuse reflectance measurements are reported for ACCUCAST up to 1000 °C. These results are compared against those of alumina and silica through the calculation of a thermal emittance. All three materials exhibit a calculated emittance of ~0.9 at room temperature. However, this value decreases to ~0.6 for ACCUCAST and drops to less than 0.4 for alumina and silica at 1000 °C. Thermal cycling in air at 1000 °C resulted in a visible color change from dark grey to light orange for ACCUCAST and a subsequent larger increase in reflectance for wavelengths less than 5 μm as compared to ACCUCAST thermally cycled at 1000 °C in vacuum. Alumina and silica spectra proved to be largely unaffected by thermal cycling under atmospheric conditions. Overall, this study establishes a powerful technique for the characterization of radiative properties of particulate materials as a function of temperature and presents a detailed case study of ACCUCAST, a candidate for next-generation particle-based CSP.

14 SOLAR ENERGY↗

High-resolution lithospheric structure of continental China from joint inversion of surface wave and gravity data

The lithospheric structure of continental China has been previously determined by seismic travel time tomography, surface wave tomography, and joint inversion of body wave and surface wave data. However, due to the inherent limitations of seismic data, the lithospheric structure of continental China is still not well resolved in the shallow part and in some regions where the station coverage is relatively sparse. In this study, we aim at improving the lithospheric structure by joint inversion of seismic surface wave data and satellite gravity data to take advantage of the uniform distribution and complementary strength of the gravity data. Here, the empirical relationship between velocity and density is used as a bridge for joint inversion of surface wave and gravity data. The joint inversion shear-wave velocity Vs (density) model, named as USTClitho1.0g, can fit both surface wave and gravity data well. This high-resolution Vs model can better fit the active airgun source seismic arrival times and better delineate some features in continental China, such as the velocity contrast across the north–south gravity lineament (NSGL), the lithosphere thinning in eastern China, the crustal footprint of the Hainan mantle plume, the likely magma chamber beneath volcanos in northeast China, the middle-lower crust low velocity layer beneath the Tibetan plateau, and the tearing of subducted Indian mantle lithosphere. Our joint inversion Vs model can provide a reference model for geosciences in continental China and surrounding areas.

58 GEOSCIENCES↗

Assessing Melting and Solid–Solid Transition Properties of Choline Chloride via Molecular Dynamics Simulations

Choline chloride (ChCl) is used extensively as a hydrogen bond donor in deep eutectic solvents (DESs). However, determining its melting properties experimentally is challenging due to decomposition upon melting, leading to widely varying literature values. Accurate melting properties are crucial for understanding the solid–liquid phase behavior of ChCl-containing DESs. Here, we employ molecular dynamics simulations to compute the phase transitions of ChCl, testing a variety of atomistic force fields. We find that the results are sensitive to the choice of force field, but a melting temperature of 627 K and a melting enthalpy of 7.8 kJ/mol seem most reasonable, in good agreement with some literature values. Furthermore, we suggest these as the likely melting properties of ChCl, though the results are tentative due to limited experimental data for the liquid ChCl phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantitative Simulations of Siloxane Adsorption in Metal–Organic Frameworks

We present a transferable force field (FF) for simulating the bulk properties of linear and cyclic siloxanes and the adsorption of these species in metal–organic frameworks (MOFs). Unlike previous FFs for siloxanes, our FF accurately reproduces the vapor–liquid equilibria of each species in the bulk phase. The quality of our FF combined with the Universal Force Field using standard Lorentz–Berthelot combining rules for MOF atoms was assessed in a wide range of MOFs without open metal sites, showing good agreement with dispersion-corrected density functional theory calculations. Predictions with this FF show good agreement with the limited experimental data for siloxane adsorption in MOFs that is available. As an example of using the FF to predict adsorption properties in MOFs, we present simulations examining entropy effects in binary linear and cyclic siloxane mixture coadsorption in the large-pore MOF with structure code FOTNIN.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Stability of Nd Hydroxyl Complexes at Near Neutral to Alkaline pH from 25 to 75 °C: Implications for Monazite Solubility in Hydrothermal Aqueous Fluids

Speciation of rare earth elements (REE) in aqueous fluids controls their mobilization during fluid-rock interaction. Thermodynamic modeling provides important insights into the factors controlling REE mobility and fractionation in aqueous fluids, in which aqueous REE hydroxyl complexes are particularly important across a broad pH range. However, the stability of these REE hydroxyl complexes remains poorly determined due to limited experimental data above ambient temperature. In this work, UV–vis spectrophotometry experiments were conducted to determine the cumulative hydrolysis constants for neodymium (Nd) from 25 to 75 °C in near-neutral to alkaline solutions. The color indicator m -cresol purple was used to determine in situ pH. Alkaline NaOH-bearing aqueous solutions were doped with varying initial Nd concentrations (0 to ∼0.155 mmol/kg), which resulted in the release of protons (H + ) and pH decrease during hydrolysis of Nd 3+ according to Nd 3+ + n H 2 O = Nd(OH) n 3– n + H + . The average OH – ligand number coordinated to Nd 3+ was found to increase from 1.0 to 1.6 at 25 °C and from 1.2 to 2.8 at 75 °C over a pH range from 6.3 to 9.0. The measured speciation shows an increased predominance of Nd(OH) 3 0 over the Nd(OH) 2 + and Nd(OH) 2+ species with increased temperature and pH. The increasing cumulative formation constants (log*β° n , n = 1 to 3) retrieved from 25 to 75 °C differ by 0.1 to 1.9 logarithmic units in comparison to existing thermodynamic databases. These updated thermodynamic data have important implications for geochemical modeling of the speciation of Nd hydroxyl complexes and the solubility of monazite as a function of pH.

58 GEOSCIENCES↗

Characterizing uncertainties in ground “truth” of precipitation over complex terrain through high-resolution numerical modeling

Ground observation of precipitation over complex terrain is subject to large uncertainties due to inadequate sampling. This study explores a method that combines limited gauge data and a high-resolution numerical simulation to quantify the precipitation uncertainties in central Himalaya. Specifically, the Coefficient of spatial Variability (CV) of precipitation and the minimum Number of Required Stations (NRS) to obtain areal-mean precipitation ground truth values within a 0.25-degree area are investigated using fine-scale meteorological simulation at 1.5 km grid spacing. Evaluation over a densely-gauged area demonstrates comparable CV and NRS values between station observations and simulations. The simulated CV and NRS values in a larger area show a strong and positive dependence on each other and an expected positive (negative) correlation with topographic complexity (temporal scale). The proposed method sheds lights on evaluating precipitation products and holds promise for informing the layout of rain gauge networks in complex terrain.

Ouyang, Lin↗

Future Projections of the El Niño—Southern Oscillation and Tropical Pacific Mean State in CMIP6

Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.

54 ENVIRONMENTAL SCIENCES↗

Regularization via f -Divergence: An Application to Multi-Oxide Spectroscopic Analysis

In this paper, we explore the application of convolutional neural networks (CNNs) for predicting the chemical composition of complex geologic samples in a simulated Martian atmospheric environment. Specifically, we aim to characterize oxide weight percentages (wt.%) of rock samples analyzed by remote Laser-Induced Breakdown Spectroscopy (LIBS), framing the problem as a multi-target regression task . Neural networks trained on LIBS spectra are prone to overfitting due to high spectral complexity, limited labeled data, and measurement noise. While regularization is critical for improving generalization, common methods (e.g., ℓ 2 regularization) impose constraints not directly tied to data distribution properties. We propose a novel regularization method based on a specific ƒ-divergence induced by a graph-based estimator, designed to constrain the distributional discrepancy between predictions and targets. This regularizer serves a dual purpose: (a) mitigating overfitting by enforcing a constraint on the distributional difference between predictions and noisy targets, and (b) acting as an auxiliary loss that penalizes large divergences. To enable backpropagation, we develop a differentiable approximation of this particular ƒ-divergence, making the method feasible for neural networks. Experiments on ChemCam and SuperCam LIBS calibration spectra show that mathematical equation-divergence regularization outperforms or matches standard regularization methods (ℓ 1 , ℓ 2 , dropout) and the classical baseline, partial least squares (PLS). Combining ƒ-divergence regularization with standard regularization yields further performance gains, indicating that distributional regularization is useful in this context giving a promising direction for robust model training in planetary science applications. Source code is publicly available at Klein and Li (2025), https://doi.org/10.11578/dc.20250530.7.

58 GEOSCIENCES↗

Inferring protein expression changes from mRNA in Alzheimer’s dementia using deep neural networks

Identifying the molecular systems and proteins that modify the progression of Alzheimer’s disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic data, has limited our ability to advance candidate targets that are mainly based on gene expression. Therefore, by using a deep neural network that predicts protein abundance from mRNA expression, here we attempt to track the early protein drivers of ADRD. Specifically, by applying the clei2block deep learning model to 1192 brain RNA-seq samples, we identify protein modules and disease-associated expression changes that were not directly observed at the mRNA level. Moreover, pseudo-temporal trajectory inference based on the predicted proteome became more closely correlated with cognitive decline and hippocampal atrophy compared to RNA-based trajectories. This suggests that the predicted changes in protein expression could provide a better molecular representation of ADRD progression. Furthermore, overlaying clinical traits on protein pseudotime trajectory identifies protein modules altered before cognitive impairment. These results demonstrate how our method can be used to identify potential early protein drivers and possible drug targets for treating and/or preventing ADRD.

60 APPLIED LIFE SCIENCES↗

Spatio-temporal dynamics of Hendra virus in Australia reveal stable maintenance of diverse viral clades among Pteropus bats

Hendra virus (HeV) was discovered in 1994 in Australia. Limited genomic data have hindered comprehensive understanding of HeV’s evolutionary dynamics. Here, in this work, we recovered 48 HeV genomes from bats and 9 from horses from Australia between 2016 and 2020, revealing four distinct clades. Each clade was distributed over a large spatial area with multiple clades co-circulating within a single bat roost on the same day and over consecutive years. The diversity and temporal stability of co-circulating clades suggest that viral dynamics are driven by episodic shedding of existing lineages maintained at the population level, rather than immune-driven strain-replacement dynamics. HeV isolates of different clades displayed variation in phenotypic properties but minimal antigenic differences. We provide an overview of evolutionary dynamics, phenotypic properties and assessment of countermeasures for HeV, and provide insights into the processes that maintain virus diversity in bats and influence the potential for viral emergence.

genetic variation↗

Geochemical constraints on bacteriophage infectivity in terrestrial environments

Abstract Lytic phages can be potent and selective inhibitors of microbial growth and can have profound impacts on microbiome composition and function. However, there is uncertainty about the biogeochemical conditions under which phage predation modulates microbial ecosystem function, particularly in terrestrial systems. Ionic strength is critical for infection of bacteria by many phages, but quantitative data is limited on the ion thresholds for phage infection that can be compared with environmental ion concentrations. Similarly, while carbon composition varies in the environment, we do not know how this variability influences the impact of phage predation on microbiome function. Here, we measured the half-maximal effective concentrations (EC50) of 80 different inorganic ions for the infection of E. coli with two canonical dsDNA and ssRNA phages, T4 and MS2, respectively. Many alkaline earth metals and alkali metals enabled lytic infection but the ionic strength thresholds varied for different ions between phages. Additionally, using a freshwater nitrate-reducing microbiome, we found that the ability of lytic phages to influence nitrate reduction end-products depended upon the carbon source as well as ionic strength. For all phage:host pairs, the ion EC50s for phage infection exceeded the ion concentrations found in many terrestrial freshwater systems. Thus, our findings support a model where phages most influence terrestrial microbial functional ecology in hot spots and hot moments such as metazoan guts, drought influenced soils, or biofilms where ion concentration is locally or transiently elevated and nutrients are available to support the growth of specific phage hosts.

Carlson, Hans K. (ORCID:0000000215835313)↗

Thermodynamic consequences of Tyr to Trp mutations in the cation–π-mediated binding of trimethyllysine by the HP1 chromodomain

Evolution has converged on cation–p interactions for recognition of quaternary alkyl ammonium groups such as trimethyllysine (Kme3). While computational modelling indicates that Trp provides the strongest cation–p interaction of the native aromatic amino acids, there is limited corroborative data from measurements within proteins. Herein we investigate a Tyr to Trp mutation in the binding pocket of the HP1 chromodomain, a reader protein that recognizes Kme3. Binding studies demonstrate that the Trpmediated cation–p interaction is about -5 kcal mol -1 stronger, and the Y24W crystal structure shows that the mutation is not perturbing. Quantum mechanical calculations indicate that greater enthalpic binding is predominantly due to increased cation–π interactions. NMR studies indicate that differences in the unbound state of the Y24W mutation lead to enthalpy–entropy compensation. These results provide direct experimental quantification of Trp versus Tyr in a cation–π interaction and afford insight into the conservation of aromatic cage residues in Kme3 reader domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗