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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Pilot-Scale Pelleting Tests on High-Moisture Pine, Switchgrass, and Their Blends: Impact on Pellet Physical Properties, Chemical Composition, and Heating Values

In this study, we evaluated the pelleting characteristics of southern yellow pine (SYP), switchgrass (SG), and their blends for thermochemical conversion processes, such as pyrolysis and gasification. Using a pilot-scale ring-die pellet mill, we specifically assessed the impact of blend moisture, length-to-diameter (L/D) ratio in the pellet die, and ratio of pine to SG on the physico-chemical properties of the resulting pellets. We found that an increase in pine content by 25–50% marginally affected the bulk density; however, it also led to an increase in calorific value by 7% and a decrease in ash content by 72%. A moisture content of 25% (wet basis) and an L/D ratio of 5 resulted in poor pellet durability at <90% and bulk density values of <500 kg/m 3 , but increasing the L/D ratio to 9 and lowering the moisture content to 20% (w.b.) improved the pellet durability to >90% and the bulk density to >500 kg/m 3 . Blends with ≥50% pine content resulted in lower energy consumption, while a lower L/D ratio resulted in higher pelleting energy. Based on these findings, we successfully demonstrated the high-moisture pelleting of 2.5 ton of pine top residues blended with SG at 60:40 and 50:50 ratios. The quality of the pellets was monitored off-line and at-line by near infrared (NIR) spectroscopy. Multivariate models constructed by combining the NIR data and the pelleting process variables could successfully predict the pine content (R 2 = 0.99), higher heating value (R 2 = 0.98), ash (R 2 = 0.95), durability (R 2 = 0.94), and bulk density (R 2 = 0.86) of the pellets. Thus, we established how blending and densification of SYP and SG biomass could improve feedstock specifications and that NIR spectroscopy can effectively monitor the pellet properties during the high-moisture pelleting process.

09 BIOMASS FUELS↗
DOE OSTI2021

Importance of Engineered and Learned Molecular Representations in Predicting Organic Reactivity, Selectivity, and Chemical Properties

Machine-readable chemical structure representations are foundational in all attempts to harness machine learning for the prediction of reactivities, selectivities, and chemical properties directly from molecular structure. The featurization of discrete chemical structures into a continuous vector space is a critical phase undertaken before model selection, and the development of new ways to quantitatively encode molecules is an active area of research. Here, we highlight the application and suitability of different representations, from expert-guided “engineered” descriptors to automatically “learned” features, in different prediction tasks relevant to organic and organometallic chemistry, where differing amounts of training data are available. These tasks include statistical models of stereo- and enantioselectivity, thermochemistry, and kinetics developed using experimental and quantum chemical data. The use of expert-guided molecular descriptors provides an opportunity to incorporate chemical knowledge, domain expertise, and physical constraints into statistical modeling. In applications to stereoselective organic and organometallic catalysis, where data sets may be relatively small and 3D-geometries and conformations play an important role, mechanistically informed features can be used successfully to obtain predictive statistical models that are also chemically interpretable. We provide an overview of several recent applications of this approach to obtain quantitative models for reactivity and selectivity, where topological descriptors, quantum mechanical calculations of electronic and steric properties, along with conformational ensembles, all feature as essential ingredients of the molecular representations used. Alternatively, more flexible, general-purpose molecular representations such as attributed molecular graphs can be used with machine learning approaches to learn the complex relationship between a structure and prediction target. This approach has the potential to out-perform more traditional representation methods such as “hand-crafted” molecular descriptors, particularly as data set sizes grow. One area where this is particularly relevant is in the use of large sets of quantum mechanical data to train quantitative structure–property relationships. A general approach toward curating useful data sets and training highly accurate graph neural network models is discussed in the context of organic bond dissociation enthalpies, where this strategy outperforms regression using precomputed descriptors. Finally, we describe how graph neural network predictions can be incorporated into mechanistically informed statistical models of chemical reactivity and selectivity. Once trained, this approach avoids the expensive computational overhead associated with quantum mechanical calculations, while maintaining chemical interpretability. We illustrate examples for which fast predictions of bond dissociation enthalpy and of the identities of radicals formed through cleavage of a molecule’s weakest bond are used in simple physical models of site-selectivity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗
DOE OSTI2022

S $^{5}$: The Orbital and Chemical Properties of One Dozen Stellar Streams

We report the kinematic, orbital, and chemical properties of 12 stellar streams with no evident progenitors using line-of-sight velocities and metallicities from the Southern Stellar Stream Spectroscopic Survey (S $^{5}$), proper motions from Gaia EDR3, and distances derived from distance tracers or the literature. This data set provides the largest homogeneously analyzed set of streams with full 6D kinematics and metallicities. All streams have heliocentric distances between ∼10 and 50 kpc. The velocity and metallicity dispersions show that half of the stream progenitors were disrupted dwarf galaxies (DGs), while the other half originated from disrupted globular clusters (GCs), hereafter referred to as DG and GC streams. Based on the mean metallicities of the streams and the mass–metallicity relation, the luminosities of the progenitors of the DG streams range between those of Carina and Ursa Major I (−9.5 ≲ M $_{V}$ ≲ −5.5). Four of the six GC streams have mean metallicities of Fe/H < −2, more metal poor than typical Milky Way (MW) GCs at similar distances. Interestingly, the 300S and Jet GC streams are the only streams on retrograde orbits in our dozen-stream sample. Finally, we compare the orbital properties of the streams with known DGs and GCs in the MW, finding several possible associations. Some streams appear to have been accreted with the recently discovered Gaia–Enceladus–Sausage system, and others suggest that GCs were formed in and accreted together with the progenitors of DG streams whose stellar masses are similar to those of Draco to Carina (∼10$^{5}$–10$^{6}$ M $_{⊙}$).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Spectroscopic and Chemical Properties of Ionic Liquids: Computational Study

A brief account is given of highlights of our computational efforts – often in collaboration with experimental groups – to understand spectroscopic and chemical properties of ionic liquids (ILs). Molecular dynamics, including their inhomogeneous character, responsible for key spectral features observed in dielectric absorption, infra-red (IR) and fluorescence correlation spectroscopy (FCS) measurements are elucidated. Mechanisms of chemical processes involving imidazolium-based ILs are illustrated for CO 2 capture and related reactions, transesterification of cellulose, and Au nanocluster-catalyzed Suzuki cross-coupling reaction with attention paid to differing roles of IL ions. A comparison with experiments is also made.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO 2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydrogen bonded trimesic acid networks on Cu(111) reveal how basic chemical properties are imprinted in HR-AFM images

High resolution non-contact atomic force microscopy measurements characterize assemblies of trimesic acid molecules on Cu(111) and the link group interactions, providing the first fingerprints utilizing CO-based probes for this widely studied paradigm for hydrogen bond driven molecular self assembly. The enhanced submolecular resolution offered by this technique uniquely reveals key aspects of the competing interactions. Accurate comparison between full-density-based modeled images and experiment allows to identify key structural elements in the assembly in terms of the electron-withdrawing character of the carboxylic groups, interactions of those groups with Cu atoms in the surface, and the valence electron density in the intermolecular region of the hydrogen bonds. This study of trimesic acid assemblies on Cu(111) combining high resolution atomic force microscopy measurements with theory and simulation forges clear connections between fundamental chemical properties of molecules and key features imprinted in force images with submolecular resolution.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Physico-chemical properties of lignin fractions from acid pretreated corn stover and their effects on enzymatic hydrolysis of microcrystalline cellulose

Lignin has been shown to be a recalcitrance factor in many biomass conversion studies. To better understand the effects of lignin on cellulose conversion, different lignin fractions were extracted from the same dilute acid pretreated corn stover by three sequential isolation methods, namely ethanol extraction, dioxane extraction, and enzyme purification. The physicochemical properties of each lignin fraction including molecular weight distribution, surface area, surface charge, and other structural features varied, depending on the isolation methods. All three lignin fractions had negative surface charges, and ethanol-extracted lignin carried the highest surface charges, followed by dioxane-extracted lignin and cellulase-purified residual lignin. These physicochemical properties of lignin fractions also resulted in different extent of inhibitory effects on enzymatic hydrolysis of microcrystalline cellulose (MCC). Dioxane-extracted lignin exhibited the highest inhibitory effect on glucose release from MCC, followed by the cellulase-purified residual lignin fraction and ethanol-extracted lignin. Furthermore, lignin fractions with higher contents of syringyl (S) substructure and β-O-4 aryl ether interunit linkages showed a stronger negative effect on cellulase hydrolysis of MCC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Role of ripples in altering the electronic and chemical properties of graphene

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure–property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which indicates that the Eley–Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir–Hinshelwood mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Measurements of aerosol microphysical and chemical properties in the central Arctic atmosphere during MOSAiC

The Arctic environment is transforming rapidly due to climate change. Aerosols’ abundance and physicochemical characteristics play a crucial, yet uncertain, role in these changes due to their influence on the surface energy budget through direct interaction with solar radiation and indirectly via cloud formation. Importantly, Arctic aerosol properties are also changing in response to climate change. Despite their importance, year-round measurements of their characteristics are sparse in the Arctic and often confined to lower latitudes at Arctic land-based stations and/or short high-latitude summertime campaigns. Here, we present unique aerosol microphysics and chemical composition datasets collected during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, in the central Arctic. These datasets, which include aerosol particle number concentrations, size distributions, cloud condensation nuclei concentrations, fluorescent aerosol concentrations and properties, and aerosol bulk chemical composition (black carbon, sulfate, nitrate, ammonium, chloride, and organics) will serve to improve our understanding of high-Arctic aerosol processes, with relevance towards improved modelling of the future Arctic (and global) climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The chemical properties of the Milky Way’s on-bar and off-bar regions: evidence for inhomogeneous star formation history in the bulge

ABSTRACT Numerous studies of integrated starlight, stellar counts, and kinematics have confirmed that the Milky Way is a barred galaxy. However, far fewer studies have investigated the bar’s stellar population properties, which carry valuable independent information regarding the bar’s formation history. Here, we conduct a detailed analysis of chemical abundance distributions ([Fe/H] and [Mg/Fe]) in the on-bar and off-bar regions to study the azimuthal variation of star formation history (SFH) in the inner Galaxy. We find that the on-bar and off-bar stars at Galactocentric radii 3 kpc < rGC < 5 kpc have remarkably consistent [Fe/H] and [Mg/Fe] distribution functions and [Mg/Fe]–[Fe/H] relation, suggesting a common SFH shared by the long bar and the disc. In contrast, the bar and disc at smaller radii (2 kpc < rGC < 3 kpc) show noticeable differences, with relatively more very metal-rich ($\rm [Fe/H] \sim 0.4$) stars but fewer solar abundance stars in the bar. Given the three-phase star formation history proposed for the inner Galaxy in Lian et al., these differences could be explained by the off-bar disc having experienced either a faster early quenching process or recent metal-poor gas accretion. Vertical variations of the abundance distributions at small rGC suggest a wider vertical distribution of low-α stars in the bar, which may serve as chemical evidence for vertical heating through the bar buckling process. The lack of such vertical variations outside the bulge may then suggest a lack of vertical heating in the long bar.

Lian, Jianhui↗
DOE OSTI2021

Dynamic Mixing Behaviors of Ionically Tethered Polymer Canopy of Nanoscale Hybrid Materials in Fluids of Varying Physical and Chemical Properties

An emerging area of sustainable energy and environmental research is focused on the development of novel electrolytes that can increase the solubility of target species and improve subsequent reaction performance. Electrolytes with chemical and structural tunability have allowed for significant advancements in flow batteries and CO 2 conversion integrated with CO 2 capture. Liquid-like nanoparticle organic hybrid materials (NOHMs) are nanoscale fluids that are composed of inorganic nanocores and an ionically tethered polymeric canopy. NOHMs have been shown to exhibit enhanced conductivity making them promising for electrolyte applications, though they are often challenged by high viscosity in the neat state. In this study, a series of binary mixtures of NOHM-I-HPE with five different secondary fluids, water, chloroform, toluene, acetonitrile, and ethyl acetate, were prepared to reduce the fluid viscosity and investigate the effects of secondary fluid properties (e.g., hydrogen bonding ability, polarity, and molar volume) on their transport behaviors, including viscosity and diffusivity. We report our results revealed that the molecular ratio of secondary fluid to the ether groups of Jeffamine M2070 ($λ_{\text{SF}}$) was able to describe the effect that secondary fluid has on transport properties. Our findings also suggest that in solution, the Jeffamine M2070 molecules exist in different nanoscale environments, where some are more strongly associated with the nanoparticle surface than others, and the conformation of the polymer canopy was dependent on the secondary fluid. This understanding of the polymer conformation in NOHMs can allow for the better design of an electrolyte capable of capturing and releasing small gaseous or ionic species.

25 ENERGY STORAGE↗
DOE OSTI2025

The role of soil chemical properties and microbial communities on Dendrocalamus brandisii bamboo shoot quality, Yunnan Province, China

Objective To explore the effects of soil nutrients and microbial communities on the quality of Dendrocalamus brandisii shoots in different regions, providing a scientific basis for their development and utilization. Methods Using seven different geographic sources of D. brandisii from Yunnan Province as research subjects, this study employs chemical analysis and high-throughput sequencing to reveal the relationship between soil nutrients, microbial functional groups, and the nutritional quality of bamboo shoots. Results The results indicate that there are significant differences in soil nutrient content among the regions ( p < 0.05), with bamboo shoots from Baoshan Changning (CN) exhibiting the best overall nutritional quality. The key factors influencing bacterial community changes include pH, available phosphorus (AP), and available potassium (AK). In contrast, the main factors affecting fungal community changes are pH, soil organic matter (SOM), available potassium (AK), and total nitrogen (TN). This version maintains clarity and logical flow, making it easier for readers to understand the different factors influencing bacterial and fungal community changes. The diversity indices of soil microbial communities among different sources of Dendrocalamus brandisii show significant differences ( p < 0.05). The dominant groups in the seven regions include Proteobacteria, Acidobacteriota, Actinobacteriota, Chloroflexi, Ascomycota, and Basidiomycota. The soil microbial community in Baoshan Changning (CN) shows significant structural differences compared to the other six regions, with the highest relative abundances of Chloroflexi and Acidobacteriota. In contrast, the highest relative abundance of Proteobacteria is found in Honghe Shiping (SP), while Actinobacteriota has the highest relative abundance in Yuxi Xinping (XP). RDA analysis indicates that soil nutrients (SOM, pH, AP, TN) affect the water content, soluble sugar, and crude fat of bamboo shoots. Additionally, the bacterial communities including Actinobacteriota, Chloroflexi, Patescibacteria, GAL15, and Cyanobacteria influence the water content, soluble sugar, ash content, protein, and lignin of bamboo shoots. Discussion In the fungal community, Basidiomycota, Kickxellomycota, Mucoromycota, unclassified-k-Fungi, and Glomeromycota affect the water content and tannin levels in bamboo shoots. In summary, soil nutrients and soil microorganisms are interconnected and work together to influence the quality of bamboo shoots.

Chen, Qian↗
DOE OSTI2020

Effects of Revegetation on Soil Physical and Chemical Properties in Solar Photovoltaic Infrastructure

Solar photovoltaic (PV) technology is being deployed at an unprecedented rate. However, utility-scale solar energy development is land intensive and its large-scale installation can have negative impacts on the environment. In particular, solar energy infrastructure can require extensive landscape modification that transforms soil ecological functions, thereby impacting hydrologic, vegetative, and carbon dynamics. However, reintroducing native vegetation to solar PV sites may be a means of restoring their soils. To this end, we investigated critical soil physical and chemical parameters at a revegetated photovoltaic array and an adjacent reference grassland in Colorado, United States. Seven years after revegetation, we found that carbon and nitrogen remained lower in the PV soil than in the reference soil and contained a greater fraction of coarse particles. We also found that the PV modules introduced heterogeneity in the soil moisture distribution, with precipitation accumulating along the lower edges of panels. The redistribution of soil moisture by panel arrays could potentially be used in concert with planting strategies to maximize plant growth or minimize soil erosion, and should be considered when evaluating the potential to co-locate vegetation with solar infrastructure.

14 SOLAR ENERGY↗
DOE OSTI2020

Briquetting characteristics of woody and herbaceous biomass blends: Impact on physical properties, chemical composition, and calorific value

Abstract Intercropping (or polyculture) is gaining a lot of interest as it increases yields, allows better utilization of resources (water and nutrients), and provides better land management. The objective of this study is to understand the briquetting characteristics of woody and herbaceous biomass blends, which might result from intercropping. Tests were conducted on blends of lodgepole pine, switchgrass, and corn stover biomass using three hammer mill screen sizes (i.e., 4.8, 12.7, and 19.05 mm), three blend moistures (12%, 15%, and 18%, w.b.), and two‐ and three‐blend ratios (i.e., 1:1 and 1:1:1) using a pilot‐scale hydraulic briquette press. The briquette properties, such as unit and bulk density, durability rating after 5 days of storage (as they tend to attain stable density), and the energy consumption of the process were measured. The results indicate that moisture content of 12% and 15% (w.b.) and smaller hammer mill screen size of 4.8 mm increased the unit and bulk densities to >750 and >430 kg/m 3 and moisture content (15% and 18% (w.b.)) and hammer mill screen size of 12.7 and 19.05 mm produced briquettes with durability rating values of >95%. The higher moisture content of 18% (w.b.) and the hammer mill screen size of 12.7 and 19.05 mm had the highest energy consumption. The proximate and ultimate analysis showed that energy content improved by blending lodgepole pine with both corn stover and switchgrass and also showed increased calorific value and reduced ash content. Scanning electron microscopy micrographs showed interlocking of particles and cracks in the briquettes. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

Tumuluru, Jaya Shankar↗
DOE OSTI2020

Molten Chloride Thermophysical Properties, Chemical Optimization, and Purification

Next-generation concentrating solar power (CSP) technology requires high-temperature heat-transfer fluids and thermal energy storage that can operate in the temperature range of 500°–720°C. This high temperature demands a new chemistry for the heat-transfer fluids that must have high-temperature thermal and chemical stabilities, high energy density, and low corrosion rate on metallic materials used in the heat exchangers, piping, and thermal energy storage tanks. A ternary MgCl 2 -KCl-NaCl chloride-salt system has been proposed to achieve such goals, given its high-temperature thermal stability. The chloride-salt-based systems have been used by the metallurgy industry as the electrolyte to electrolytically extract metallic magnesium. They have also attracted attentions from the nuclear industry for developing the molten salt fast reactors that can operate at close to atmospheric pressure and at higher temperature than traditional light-water reactors. However, the corrosion properties of the ternary salt are not well known. The corrosion mechanism is believed to be correlated to the presence of MgOHCl impurity at the operation temperature. MgOHCl is fundamentally caused by the hygroscopic nature of the MgCl 2 component. Therefore, the first key objective of this project is to understand the nature of the corrosiveness of the ternary chloride-salt system and its prevention by designing new lab-scale purification processes. Because of its importance, a working group called the Chloride Salt Collective across multiple U.S. Department of Energy national laboratories is established to gain experimental agreement on the corrosion behaviors. In addition, water generation during salt dehydration could lead to highly corrosive HCl/water mixture via a hydrolysis process between water and anhydrous MgCl 2 or MgCl 2 hydrates. MgOHCl will eventually be converted to MgO particulates regardless of the chemical path chosen (i.e., by thermal decomposition, chemical purification with an active metal, or electrochemical purification utilizing the reduction power of electron flows). Large MgO particles with high hardness can wear out bearing and bushing and even clog the delicate channels in the primary heat exchanger. Because of this, a second objective is to understand the chemistry behind salt purification and transfer the scientific understanding to a set of engineering know-how for large-scale salt melter design. Because there is limited information on the thermophysical properties and the sensitivity of these properties around the targeted salt composition, a third objective is to measure thermophysical properties relevant to system and component design and support Topic 1 Liquid Pathway development. For example, composition shift due to salt reaction with water can be a potential issue because it can lead to changes of thermophysical properties, such as (1) melting point (or freeze point), which can jeopardize safe operation of the supercritical CO 2 power cycle proposed for next-generation CSP, and (2) heat capacity and density, which can decrease the overall power-generation capability of the plants. The value of the thermal conductivity of the selected salt composition is also a critical criterion for the solar receiver design.

14 SOLAR ENERGY↗
DOE OSTI2020

Mechanical and chemical properties of PVD and cold spray Cr-coatings on Zircaloy-4

In this paper, accident-tolerant fuel (ATF) cladding materials aim to improve fuel reliability and safety during accident scenarios in water-cooled reactors. These ATF cladding should also perform comparable or better than the current zirconium alloy cladding under reactor normal operating conditions. Surface-modified Zircaloy-4 was produced by depositing a protective coating of chromium by two different coating techniques, Physical Vapor Deposition (PVD) and Cold Spray (CS). The coating thickness, structure, composition, and mechanical properties of the coated Zircaloy were assessed with advanced materials characterization techniques. Results showed a strengthening effect of the Cr-coating, along with ~83% higher hardness compared to that of the Zircaloy-4 substrate. Surface topography and surface chemistry of the Cr-coated Zircaloy-4 were assessed with contact profilometry, atomic force microscopy, contact angle goniometry, and X-ray photoelectron spectroscopy. Deposited Cr-coating significantly improved surface wettability compared to the substrate Zircaloy-4. The formation of surface oxides on the coatings by prolonged exposure to ambient air showed a further increase in the hydrophobic behavior. Surface parameters and surface chemistry after flow boiling critical heat flux tests, conducted at atmospheric pressure, evidenced a slight increase in surface roughness with notable changes in wettability associated with the formation of surface oxides.

36 MATERIALS SCIENCE↗