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At least 253 records · Page 14

Sludge Batch 11 Assembly: Tank 15

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 15 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 15 prior to transfer from Tank 15 to Tank 13 (prior to sending to Tank 51) in order to demonstrate that the transfer is "Low Rem" and ensure the sludge concurs with the estimated transfer mass for the SB11 recipe. A total of 3 sets of Tank 15 samples were delivered to SRNL from December 2022 to August 2023. The individual sets of composite samples were analyzed for density, weight percent solids, chemical composition, radionuclides, and/or supernate corrosion control tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Chemical Characterization and Antimicrobial Activity of Green Propolis from the Brazilian Caatinga Biome

Green propolis, particularly from the unique flora of the Brazilian Caatinga biome, has gained significant interest due to its diverse chemical composition and biological activities. This study focuses on the chemical characterization and antimicrobial evaluation of Caatinga green propolis. Twelve compounds were isolated through different chromatographic techniques, including flavanones (naringenin, 7-O-methyleriodictyol, sakuranetin), flavones (hispidulin, cirsimaritin), flavonols (quercetin, quercetin-3-methyl ether, kaempferol, 6-methoxykaempferol, viscosine, penduletin), and one chalcone (kukulkanin B). Using liquid chromatography–quadrupole time-of-flight tandem mass spectrometry (LC-QToF-MS), a total of 55 compounds excluding reference standards were tentatively identified, which include flavonoids, phenolic acids derivatives, and alkaloids, with flavonols, flavanones, and flavones being predominant. Antimicrobial testing against pathogens revealed that the crude extract exhibited low inhibitory activity, against Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE) (IC50: 148.4 and 120.98 µg/mL, respectively). Although the isolated compounds showed limited individual activity, a fraction containing sakuranetin and penduletin (Fraction 8) exhibited moderated activity against Cryptococcus neoformans (IC50: 47.86 µg/mL), while a fraction containing quercetin and hispidulin showed moderated activity against VRE (IC50: 16.99 µg/mL). These findings highlight the potential application of Caatinga green propolis as an antimicrobial agent, particularly against resistant bacterial strains, and underscore the importance of synergistic interactions between compounds in enhancing biological effects.

Aldana-Mejía, Jennyfer A. (ORCID:0000000307361899)↗

Improving ChemCam LIBS long-distance elemental compositions using empirical abundance trends

The ChemCam instrument on the Curiosity rover provides chemical compositions of Martian rocks and soils using remote laser-induced breakdown spectroscopy (LIBS). The elemental calibration is stable as a function of distance for Ti, Fe, Mg, and Ca. The calibration shows small, systematically increasing abundance trends as a function of distance for Al, Na, K, and to some extent, Si. The distance effect is known to be due to a dependence with distance on the relative strengths of atomic transition lines. Emission lines representing transitions from relatively low energy levels remain intense at longer distances while emission lines representing transitions from higher energy levels decrease in intensity more rapidly as a function of distance. The multivariate algorithms used to determine elemental compositions rely on a large number of emission lines in many cases, so rather than trying to correct all emission lines, a study was made of the predicted compositions as a function of distance, in order to determine an empirical correction. Abundance trends can be well approximated by a linear trend with distance within the ranges of abundances and distances observed up to ~6 m. Data from 11 distinct geological members and data groups of the Murray formation in Gale crater, Mars, were used to form the model, selecting the members and data groups yielding the best statistics. The model was tested using data from several targets observed from two different distances, and using data from the Kimberley formation, the composition of which is significantly different from the Murray formation, showing that the model works on other compositions beyond those used to build the model. For long-distance observations up to ~6 m, corrections can be made back to an equivalent composition at the median distance of ChemCam observations (2.6 m). Finally, the model has been validated up to 6.2 m, although ChemCam is able to observe bedrock targets to >7 m, and iron meteorites to distances of >9 m.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular and Topographical Organization: Influence on Cicada Wing Wettability and Bactericidal Properties

Numerous natural surfaces have micro/nanostructures that result in extraordinary functionality, such as superhydrophobicity, self-cleaning, antifogging, and antimicrobial properties. One such example is the cicada wing, where differences in nanopillar geometry and composition among species can impact and influence the degree of exhibited properties. To understand the relationships between surface topography and chemical composition with multifunctionality, the wing properties of Neotibicen pruinosus (superhydrophobic) and Magicicada cassinii (hydrophobic) cicadas are investigated at time points after microwave-assisted extraction of surface molecules to characterize the chemical contribution to nanopillar functionality. Electron microscopy of the wings throughout the extraction process illustrates nanoscale topographical changes, while concomitant changes in hydrophobicity, bacterial fouling, and bactericidal properties are also measured. Extract analysis reveals the major components of the nanostructures to be fatty acids and saturated hydrocarbons ranging from C17 to C44. Effects on the antimicrobial character of a wing surface with respect to the extracted chemicals suggest that the molecular composition of the nanopillars plays both a direct and an indirect role in concert with nanopillar geometry. The data presented not only correlates the nanopillar molecular organization to macroscale functional properties, but it also presents design guidelines to consider during the replication of natural nanostructures onto engineered substrates to induce desired properties.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of biological materials with soft X-ray scattering

The complex structure of biological assemblies is crucial for function yet challenging to discern given the chemical similarities between constituent components. Hard X-ray techniques, for example, rely on small density differences between domains that lead to modest scattering intensities. Resonant soft X-ray scattering (RSoXS) uses X-rays below 2 keV to access absorption edges of low-Z elements. In this way, RSoXS can enhance scattering contrast between domains of different chemical compositions or bonding motifs, thus providing structural information about specific chemical motifs. RSoXS is emerging as a technique applicable for biological systems, having been used to characterize protein structure in solution and polysaccharide organization in plant cell walls. Sample environment instrumentation, however, is challenging in the current state of the art, particularly with liquid samples. Here, this chapter contains a brief introduction to RSoXS and current beamline capabilities, and provides methods to prepare, store, and mount biological samples for RSoXS characterization. Furthermore, key details during RSoXS and X-ray absorption data acquisition are highlighted and some future opportunities in RSoXS instrumentation for biological systems are discussed.

47 OTHER INSTRUMENTATION↗

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗

Tuning the magnetic properties of the CrMnFeCoNi Cantor alloy

Magnetic properties of more than 20 Cantor alloy samples of varying composition were investigated over a temperature range of 5 K to 300 K and in fields of up to 70 kOe using magnetometry and muon spin relaxation. Two transitions are identified: a spin-glass-like transition that appears between 55K and 190K, depending on composition, and a ferrimagnetic transition that occurs at approximately 43K in multiple samples with widely varying compositions. The magnetic signatures at 43K are remarkably insensitive to chemical composition. A modified Curie-Weiss model was used to fit the susceptibility data and to extract the net effective magnetic moment for each sample. The resulting values for the net effective moment were either diminished with increasing Cr or Mn concentrations or enhanced with decreasing Fe, Co, or Ni concentrations. Beyond a sufficiently large effective moment, the magnetic ground state transitions from ferrimagnetism to ferromagnetism. The effective magnetic moments, together with the corresponding compositions, are used in a global linear regression analysis to extract element-specific effective magnetic moments, which are compared to the values obtained by ab initio based density functional theory calculations. Finally, these moments provide the information necessary to controllably tune the magnetic properties of Cantor alloy variants.

36 MATERIALS SCIENCE↗

Investigating the contribution of grown new particles to cloud condensation nuclei with largely varying preexisting particles – Part 1: Observational data analysis

This study employed multiple techniques to investigate the contribution of grown new particles to the number concentration of cloud condensation nuclei (CCN) at various supersaturation (SS) levels at a rural mountain site in the North China Plain from 29 June to 14 July 2019. On 8 new particle formation (NPF) days, the total particle number concentrations (N cn ) were 8.4 ± 6.1×10 3 cm -3 , which was substantially higher compared to 4.7 ± 2.6×10 3 cm -3 on non-NPF days. However, the CCN concentration (Nccn) at 0.2 % SS and 0.4 % SS on the NPF days was significantly lower than those observed on non-NPF days (p<0.05). This was due to the lower cloud activation efficiency of preexisting particles resulting from organic vapor condensation and smaller number concentrations of preexisting particles on NPF days. A case-by-case examination showed that the grown new particles only yielded a detectable contribution to N ccn at 0.4 % SS and 1.0 % SS during the NPF event on 1 July 2019, accounting for 12 % ± 11 % and 23 % ± 12 % of N ccn , respectively. The increased N ccn during two other NPF events and at 0.2 % SS on 1 July 2019 were detectable but determined mainly by varying preexisting particles rather than grown new particles. In addition, the hygroscopicity parameter values, concentrations of inorganic and organic particulate components, and surface chemical composition of different sized particles were analyzed in terms of chemical drivers to grow new particles. The results showed that the grown new particles via organic vapor condensation generally had no detectable contribution to N ccn but incidentally did. However, this conclusion was drawn from a small size of observational data, leaving more observations, particularly long-term observations and the growth of preexisting particles to the CCN required size, needed for further investigation.

54 ENVIRONMENTAL SCIENCES↗

A thermochemical database from high-throughput first-principles calculations and its application to analyzing phase evolution in AM-fabricated IN718

A comprehensive thermochemical database is constructed based on high–throughput first-principles phonon calculations of over 3000 atomic structures in limited concentrations in Ni, Fe, and Co alloys involving a total of 26 elements including Al, B, C, Cr, Cu, Hf, La, Mn, Mo, N, Nb, O, P, Re, Ru, S, Si, Ta, Ti, V, W, Y, and Zr, providing thermochemical data largely unavailable from existing experiments. Here, the database can be employed to predict the equilibrium phase compositions and fractions directly from first-principles by minimizing the chemical potential of a multicomponent system with a fixed overall chemical composition and a fixed temperature. It is applied to the additively manufactured nickel-based IN718 superalloy to analyze the phase evolution with temperature. IN718 is known for its great performance in tensile, fatigue, creep, and rupture strength, combined with easy fabrication and corrosion resistance. In particular, we successfully predicted the formation of L1 0 -FeNi, γ’-Ni 3 (Fe,Al), α-Cr, δ-Ni 3 (Nb,Mo), γ”-Ni 3 Nb, and η-Ni 3 Ti at low temperatures (below 680 K), γ’-Ni 3 Al, δ-Ni 3 Nb, γ”-Ni 3 Nb, α-Cr, and γ-Ni(Fe,Cr,Mo) at intermediate temperatures (between 680 and 1140 K), and δ-Ni 3 Nb and γ-Ni(Fe,Cr,Mo) at high temperatures (above 1140 K) in IN718. These predictions are validated by EDS mapping of compositional distributions and corresponding identifications of phase distributions. The database is expected to be a valuable source for future thermodynamic analysis and microstructure prediction of alloys involving the 26 elements.

36 MATERIALS SCIENCE↗

Critical role of structural order in bipolar redox-active molecules for organic redox flow batteries

Bipolar redox-active molecules (BRMs) have been suggested as a means to address crossover related issues in all-organic redox flow batteries (RFBs). In such species, electron donors (anolytes) and electron acceptors (catholytes) are linked by a chain, and the same chemical composition is used in both anode and cathode compartments to reduce chemical gradients and unbalanced ion transport. The resultant RFBs resemble the aqueous vanadium RFBs, but offer greater design flexibility and potentially more favorable electrochemical and physicochemical properties. Yet the complex trade-offs in these properties have been a complication. Here we developed a fundamental rubric to uncover the likely origins in the performance metrics of these BRMs that are salient for their use in RFBs. Methylene linked phenothiazine and phthalimide moieties were employed as model BRMs and variations in their properties and molecular conformations were evaluated by systematically varying the methylene linker. Our results revealed that even minimalistic changes in the linker length resulted in dramatic oscillations in the solubility and stability. Using crystallography, quantum chemistry, and molecular dynamics, we clarify that the seemingly fluctuating behavior is due to (1) the inter- and intra-molecular charge transfer between the donor and acceptor through bond or/and through space; (2) the formation of distinctive packing/clustering motifs. Both interactions are strongly dependent on the molecular conformation. As these structural factors modify the electronic structure of both electroactive functional groups and do not change monotonically, the structure–property response in BRMs is often complex. Finally, accordingly, these behaviors need to be taken into account in developing BRMs and knowledge of these structural factors will allow the more rational design of BRMs for grid-scale energy storage.

25 ENERGY STORAGE↗

Sludge Batch 11 Assembly: Tank 35

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 35 characterization analyses in support of Sludge Batch 11 (SB11) assembly. Two Tank 35 samples were delivered to SRNL and composited into a single sample in April 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sludge Batch 11 Assembly: Tank 26

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 26 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 26 prior to transfer from Tank 26 to Tank 51 that confirms the transfer is "Low Rem" and ensures the sludge concurs with the estimated transfer mass for the SB11 recipe. Two Tank 26 samples were delivered to SRNL and composited into a single sample in September 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite. The slurry was also evaluated for sulfate washing behavior in order to provide knowledge on insoluble sulfate dissolution during Tank 51 sludge washing similar to a previous washing study performed in 2019. The Tank 26 sample results are consistent with and representative of PUREX sludge and the prior usage of Tank 26 as a feed tank for the 1F and 2F Evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sludge Batch 11 Assembly: Tank 35

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 35 characterization analyses in support of Sludge Batch 11 (SB11) assembly. Two Tank 35 samples were delivered to SRNL and composited into a single sample in April 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sludge Batch 11 Assembly: Tank 26 (Rev.1)

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 26 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 26 prior to transfer from Tank 26 to Tank 51 that confirms the transfer is "Low Rem" and ensures the sludge concurs with the estimated transfer mass for the SB11 recipe. Two Tank 26 samples were delivered to SRNL and composited into a single sample in September 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite. The slurry was also evaluated for sulfate washing behavior in order to provide knowledge on insoluble sulfate dissolution during Tank 51 sludge washing similar to a previous washing study performed in 2019. The Tank 26 sample results are consistent with and representative of PUREX sludge and the prior usage of Tank 26 as a feed tank for the 1F and 2F Evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sludge Batch 11 Assembly: Tank 51

Savannah River Mission Completion (SRMC) Nuclear Safety and Engineering Integration has requested that Savannah River National Laboratory (SRNL) perform Tank 51 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 51 after transfers from Tank 22, Tank 35, and Tank 13 (post Tank 15 to Tank 13 transfer) to Tank 51 that demonstrates the sludge concurs with the estimated transfer mass for the SB11 recipe. A total of 3 sets of Tank 51 samples were delivered to SRNL from March 2023 to February 2024. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, and supernate corrosion control analyses. The results of the Tank 51 samples are consistent with and representative of expected sludge projections for Sludge Batch 11.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Magnetic Sorbent for the Removal of Selenium(IV) from Simulated Industrial Wastewaters: Determination of Column Kinetic Parameters

A novel meso- and microporous tire-derived-carbon support with magnetic iron oxide nanoparticle adsorbents that selectively adsorbs Se(IV) ions from simulated contaminated water has been developed. In this work, the physicochemical characteristics of the composite adsorbent are characterized with respect to porosity and surface area, chemical composition, and microstructure morphology. The kinetics of this composite adsorbent in a fixed-bed setting has been determined. Several column runs were conducted and analyzed by inductively coupled plasma-optical emission spectroscopy (ICP-OES) to determine the concentration gradient vs time. These results were then fit to a pseudo-second order rate law to obtain equilibrium values. Combining calculated equilibrium values with effluent concentration data, enabled the application of the Adams–Bohart model to determine reaction constants and column coefficients. Column parameters obtained from different flow rates and fittings of the Adams–Bohart model were remarkably consistent. These findings enable the application of this sorbent to fixed-bed column systems and opens up further research into mixed pollutants tests with real wastewater and scaling of selenium pollutant removal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven prediction of the output composition of an atmospheric pressure plasma jet

Cold atmospheric plasma (CAP) in open air hosts numerous chemical species engaged in thousands of chemical reactions. Comprehensive diagnosis of its chemical composition is important across various fields from medicine, where reactive oxygen and nitrogen play key roles, to surface modification. In applications, a centimeter-scale helium–air jet operates for minutes, featuring micrometer-sized streamers and an atmospheric pressure-induced collision frequency in the hundreds of GHz range. To address this intricate multi-scale issue, we introduce a machine learning approach: using a physics-informed neural network (PINN) to tackle the multi-scale complexities inherent in predicting the complete list of species concentrations, gas temperature, and electron temperature of a CAP jet supplied with a mixture of helium and air. Experimental measurements of O 3 , N 2 O, and NO 2 concentrations downstream of the plasma jet, combined with fundamental physics laws, the conservation of mass and charge, constrain the PINN, enabling it to predict the concentrations of all species that are not available from the experiment, along with gas and electron temperatures. The results, therefore, obey all the physical laws we provided and can have a chemical balance with the measured concentrations. In conclusion, this methodology holds promise for describing and potentially regulating complex systems with limited experimental datasets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Plant versus local soil inorganic ionic composition: The relationship to biomass smoke

Here, we examine the relationship between soil and plant inorganic chemical composition as a precursor to biomass smoke aerosol particle (PM 2.5 ) properties in desert landscapes of the Southwestern United States. Past work underscored the importance of plant species and in particular the dependence of smoke PM 2.5 water uptake on the water-soluble inorganics important in select plant species (e.g., halophytes) versus absent in other species (e.g., conifers). This study extends this work by looking at a range of soil types and salinity in examining native and invasive species in the Desert Southwest US region. Eighteen plant samples and surrounding soils were taken from four ecosystems in New Mexico, USA. Results here support the conclusion that plant species are the primary controller over the inorganic plant composition that is relevant to biomass smoke and controls its hygroscopicity. The role of soil type is secondary to plant inorganic composition but is found to be important on the ecosystem level in determining what plant species are viable in a given ecosystem. This ultimately affects the smoke properties, including PM 2.5 hygroscopicity (water uptake), produced in landscape fires. Knowledge of ecosystem features including plant species distribution and soil salinity may be combined as a first-order predictor of PM 2.5 hygroscopicity of the primary smoke emissions. This can be particularly useful when combined with knowledge of burn characteristics such as flame temperature, which also plays a key role in determining PM 2.5 water uptake response.

54 ENVIRONMENTAL SCIENCES↗