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DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data: Preprint

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data input to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

Measuring Critical Fuel Properties for Simulations to Accelerate Fuel Qualification

NREL's sustainable aviation fuel (SAF) research in the area of fuel properties and end use is focused on accelerating SAF development and deployment. This will be achieved by close collaboration with BETO program researchers on fuel property measurement and development of structure-property relationships. Additionally, fuel properties measured at often extreme engine operating conditions will be measured, and will be used as inputs to exascale ready simulations of aviation combustion turbines to reveal impacts of properties on turbine operation. This research will potentially lead to a widening of the allowable fuel property range for SAF, expanding SAF production process options and production volumes.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2013

The Property Value Protection Program - How the Compensation Plan is Working and Evolving to Meet Changing Needs - 13149

The Property Value Protection (PVP) Program offers an innovative approach to address the risk of individual property value loss resulting from the cleanup and long-term management of historic low level radioactive waste in the Port Hope area in Southern Ontario, Canada. This cleanup is taking place through the Port Hope Area Initiative (PHAI), a federally sponsored waste remediation project. The PVP Program came into effect on October 1, 2000, having been established as a key element of the PHAI Legal Agreement between the Government of Canada and the municipalities of Port Hope and Clarington. The PVP Program was designed in direct response to the concern expressed by the agreement's two municipal signatories that protection of local property owners from the risk of property value loss was critical to their acceptance of the Port Hope and Port Granby projects. The PVP Program compensates owners of residential, commercial or industrial properties for a loss in fair market value on the sale or rental of their properties. Increased mortgage refinancing costs and expenses incurred as a result of delayed sales that can be attributed to the Port Hope Area Initiative are also compensated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Tailored Microstructure and Properties in UO{sub 2}

Advanced fuels with enhanced safety margin and accident tolerance are of vital importance for safe operation of current light water reactor fleet and the development of future reactor systems. The current UO{sub 2} fuel for LWRs has low thermal conductivity, which will be further reduced upon burn-up. The intrinsically low thermal transfer efficiency of the oxide fuels results in a large temperature gradient within the fuel pellet and high center-line temperature. Thermal swelling of the pellets and fission product accommodation and retention limit the lifetime of UO{sub 2} fuel in the reactor, presenting the great challenges for extending burn-up, effective utilization of nuclear resources and minimization of nuclear waste accumulation. Critical needs also exist in developing accident tolerant fuels that can tolerate loss of coolant accident or improve fuel performance under regular operation or beyond design scenario. Key properties of advanced fuels include high thermal conductivity, oxidation resistance, high temperature mechanical properties, fission gas retention capability and thus improved accident tolerance. The US Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is developing science-based next generation fuel performance modeling capability as part its Fuel Product Line in order to facilitate the predictive capability of nuclear fuel performance and assist the design and analysis of reactor systems. Critical experimental data are needed to validate MARMOT models, particularly on effective thermal transport, fracture mechanisms, grain growth kinetics and fission gas behavior. The fabrication of sintered fuel pellets with well-controlled microstructure is prerequisite to establish the correlation of the microstructure features and fuel behavior in order to develop high fidelity fuel performance models. In this talk, recent advancements on developing advanced UO{sub 2} fuels and properties improvement are overviewed with the emphasis on different accident tolerant fuel (ATF) concepts and tailoring microstructures for MARMOT validation. Current efforts on ATFs include composite fuels and high-density fuels to improve thermal-mechanical properties and fission gas retention capabilities. Different composite UO{sub 2} fuels are fabricated with heterogeneous phases as sintering additives for microstructure and property control, and the potential application of the composites as advanced fuels with enhanced accident tolerance will be discussed. In addition, recent progresses of using field-assisted sintering technologies, specifically spark plasma sintering (SPS), in tailoring and engineering fuel matrix as the target systems for validating MARMOT physics models will be highlighted. Particularly, monolithic UO{sub 2} with tailored microstructure including grain size across multiple length scales from nano-metered to micron-sizes, porosity and stoichiometry can be sintered. The impacts of tailored microstructure on thermal-mechanical properties and grain growth kinetics are discussed within the context of the MARMOT modeling. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Tabulated Fluid Properties Research Report

The Multiphysics Object-Oriented Simulation Environment (MOOSE) enables a wide range of advanced nuclear reactor simulations.[6] Under the guidance of MOOSE’s Thermal Hydraulics Team,I worked to expand the capabilities of Tabulated Fluid Properties (TFP) in the fluid properties module. The fluid properties module allows the user to determine a variety of fluid properties by interpolating points between tabulated data. I implemented the ability to use bilinear interpolation instead of bicubic interpolation for interpolating tabulated data. I also changed the method of variable set inversions to use a 2-dimensional Newton’s Method utility that I created. Variable set inversions are often done from (v,e) to (p,T), where v is specific volume, e is specific internal energy, p is pressure and T is temperature. New routines have also been added into TFP such that it can be used with more applications, such as the Navier Stokes and Thermal Hydraulics modules in MOOSE for Pronghorn[5] and RELAP-7[1] respectively. This work was spurred by interest from NASA in testing a Nuclear Thermal Propulsion (NTP) engine system. NTP engines have drastically different fluid properties throughout the engine and Tabulated Fluid Properties provides the flexibility needed to properly simulate and test these engines.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Temperature-Dependent Mechanical Properties of Ni-Based Concentrated Alloys: Insights from First-Principles Calculations

The present work focuses on predicting temperature-dependent mechanical properties of Ni-based concentrated alloys Ni 18 Cr 10 Co 10 Fe 6 M 4 (abbreviated by X 44 M 4 , with M = Al, V, Mn, Fe, Nb, Mo, and W) using density functional theory (DFT). These predictions are based on shear (plastic) and elastic deformations, utilizing the special quasirandom structure (SQS), the phonon-based quasiharmonic approach (QHA), and the quasistatic approach. The resulting properties include coefficient of thermal expansion via QHA, ideal shear strength (τ IS ), and stable and unstable stacking fault energies (γ SF and γ US ) through pure alias shear deformation, and elastic constants (c ij ), bulk modulus (B 0 ), and shear modules (G 0 ) via elastic deformation. Notably, predicting accurate γ SF is challenging due to uncertainties that can exceed the γ SF values. τ IS and γ US exhibit a strong linear relationship, enabling the accurate prediction of γ US based on the precisely determined τ IS . All mechanical properties of X 44 M 4 decrease with increasing temperature, except for some γ SF cases such as X 44 M 4 with M = V, Mn, Fe, Mo, and W. Among the X 44 M 4 alloys, X 44 Nb 4 exhibits the lowest τ IS , γ US , and G 0 values, and the highest B 0 /G 0 ratio, while X 44 Mn 4 has the lowest B 0 and B 0 /G 0 ratio. We found that volume is a crucial descriptor for understanding and modeling mechanical properties (except B0 and maybe also γ SF ) affected by alloying elements and temperature. Ni-based dilute alloys (e.g., Ni 11 M 1 and Ni 31 M 1 ) and concentrated alloys (e.g., X 44 M 4 ) show similar trends in mechanical properties influenced by alloying elements and temperature, simplifying the analysis and design of Ni-based alloys.

Elastic properties↗

DOE OSTI2023

Finite temperature properties of uranium mononitride

Uranium mononitride (UN) is a promising nuclear fuel that combines the advantageous properties of readily used UO 2 and uranium alloys, such as high melting temperature and high uranium density, and thermal conductivity, respectively. A better understanding of UN behavior at operating temperatures can be obtained from finite temperature data, such as elastic properties. To get this information, ab initio molecular dynamics (AIMD) simulations were performed at five different temperatures using constant volume (NVT) and constant pressure (NPT) ensembles. Initially, the performance of PBE functional in reproducing experimental crystallographic properties and magnetic ordering is assessed. The finite temperature phonon dispersions are calculated using NVT simulation results, which show a softening of the phonon modes with increasing temperature. The NPT results are used to obtain the thermal expansion of UN and finite temperature electronic properties. The calculated thermal expansion is compared with our measurements using neutron diffraction. Additionally, the temperature dependent elastic properties of UN are evaluated using the strain-stress method in AIMD simulations, indicating that UN becomes softer and more compressible with increasing temperature. Also, the calculated Young’s modulus slope is in very good agreement with the experiment. The finite temperature heat capacity and electronic thermal conductivity are calculated from AIMD simulations, which are in better agreement with the experiment than the heat capacity and thermal conductivity calculated using the structures relaxed at 0K. Finally, the thermal diffusivity from AIMD has opposite temperature dependence compared to experimental results, which we argued comes from the underestimated electronic thermal conductivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

Electronic band structure and optical properties of titanium oxyphosphates Li{sub 0.50}Co{sub 0.25}TiO(PO{sub 4}) single crystals: An ab-initio calculations

From the refined atomic positions obtained by Belmal et al. (2004) using X-ray diffraction for Li{sub 0.50}Co{sub 0.25}TiO(PO{sub 4}), we have performed a structural optimization by minimizing the forces acting on the atoms keeping the lattice parameters fixed at the experimental values. With this relaxed (optimized) geometry we have performed a comprehensive theoretical study of electronic properties and dispersion of the linear optical susceptibilities using the full potential linear augmented plane wave (FP-LAPW) method. The generalized gradient approximation (GGA) exchange-correlation potential was applied. In addition, the Engel-Vosko generalized gradient approximation (EVGGA) was used for comparison with GGA because it is known that EVGGA approach yields better band splitting compared to the GGA. We have calculated the band structure, and the total and partial densities of states. The electron charge densities and the bonding properties were analyzed and discussed. The complex dielectric optical susceptibilities were discussed in detail. - Graphical abstract: It is shown that P is tetrahedrally coordinated by four O ions. Highlights: > Comprehensive theoretical study of electronic and optical properties was performed. > Using X-ray diffraction data we have performed a structural optimization. > The electron charge densities and the bonding properties were analyzed and discussed. > Fermi surface was analyzed since it is useful for predicting thermal, magnetic, and optical properties. > The density of states at E{sub F} and the electronic specific heat coefficient were calculated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Study of structural, elastic, electronic and optical properties of seven SrZrO{sub 3} phases: First-principles calculations

On the plane-wave ultrasoft pseudopotential technique based on the first-principles density functional theory (DFT), we calculated the structural, elastic, electronic and optical properties of the seven different phases of SrZrO{sub 3}. The obtained ground-state properties are in good agreement with previous experiments and calculations, which indicate that the most stable phase is orthorhombic Pnma structure. Seven phases of SrZrO{sub 3} are mechanically stable with cubic, tetragonal and orthorhombic structures. The mechanical and thermodynamic properties have been obtained by using the Voigt-Reuss-Hill approach and Debye-Grueneisen model. The electronic structures and optical properties are obtained and compared with the available experimental and theoretical data. - Graphical abstract: Energy versus volume of seven phases SrZrO{sub 3} shows the Pnma phase has the minimum ground-state energy. Highlights: Black-Right-Pointing-Pointer We calculated the physical and chemical properties of seven SrZrO{sub 3} polymorphs. Black-Right-Pointing-Pointer The order of stability is Pnma>Imma>Cmcm>I4/mcm>P4/mbm>P4mm>Pm3-bar m. Black-Right-Pointing-Pointer The most stable phase is orthorhombic Pnma structure. Black-Right-Pointing-Pointer Seven phases of SrZrO{sub 3} are mechanically stable. Black-Right-Pointing-Pointer The relationship between n and {rho}{sub m} is n=1+0.18{rho}{sub m}.

36 MATERIALS SCIENCE↗

DOE OSTI2020

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↗

DOE OSTI2020

Thiolate‐Protected Single‐Atom Alloy Nanoclusters: Correlation between Electronic Properties and Catalytic Activities

Abstract Due to their interesting chemical and optical properties, metal nanoclusters are used in various catalytic reactions and in energy conversion. By incorporating thiolate‐protecting ligands, their size and composition can be tuned. Doping these nanoclusters to form single‐atom alloy (SAA) nanoclusters is shown to further enhance these properties as a result from the synergy between the dopant and host atoms. In addition to their optical and chemical properties, SAA nanoclusters also have interesting electronic properties. However, these properties are often underdiscussed when studying SAA nanoclusters. This review provides an overview of representative studies done on the in‐depth understanding of the electronic properties and catalytic activities of Ag‐based and Au‐based thiolate‐protected SAA nanoclusters. The use of density functional theory (DFT), X‐ray absorption spectroscopy, and X‐ray photoelectron spectroscopy are employed to correlate the changes in charge states of thiolate‐protected SAA nanoclusters with their superior catalytic activity versus monometallic nanoclusters. DFT, UV–vis spectroscopy, and voltammetric methods link the changes in molecular energy levels of thiolate‐protected SAA nanoclusters to their enhanced catalytic performance over monometallic nanoclusters.

Walsh, Andrew G.↗

DOE OSTI2023

Hybrid Monomer Design Synergizing Property Trade‐offs in Developing Polymers for Circularity and Performance

Abstract Current search for more sustainable plastics seeks to redesign polymers possessing both chemical recyclability to monomer for a circular plastics economy and desirable performance that can rival or even exceed today's non‐recyclable or hard‐to‐recycle petroleum‐based incumbents. However, within a traditional monomer framework it is challenging to optimize, concurrently , contrasting polymerizability/depolymerizability and recyclability/performance properties. Here, we highlight the emerging hybrid monomer design strategy to develop intrinsically circular polymers with tunable performance properties, aiming to unify desired, but otherwise conflicting, properties in a single monomer. Conceptually, this design hybridizes parent monomer pairs of contrasting, mismatching, or matching properties into offspring monomers that not only unify the above‐described conflicting properties but also radically alter the resultant polymer properties far beyond the limits of what either parent homopolymers or their copolymers can achieve.

Shi, Changxia↗

DOE OSTI2018

Machine learning properties of binary wurtzite superlattices

The burgeoning paradigm of high-throughput computations and materials informatics brings new opportunities in terms of targeted materials design and discovery. The discovery process can be significantly accelerated and streamlined if one can learn effectively from available knowledge and past data to predict materials properties efficiently. Indeed, a very active area in materials science research is to develop machine learning based methods that can deliver automated and cross-validated predictive models using either already available materials data or new data generated in a targeted manner. In the present paper, we show that fast and accurate predictions of a wide range of properties of binary wurtzite superlattices, formed by a diverse set of chemistries, can be made by employing state-of-the-art statistical learning methods trained on quantum mechanical computations in combination with a judiciously chosen numerical representation to encode materials’ similarity. These surrogate learning models then allow for efficient screening of vast chemical spaces by providing instant predictions of the targeted properties. Moreover, the models can be systematically improved in an adaptive manner, incorporate properties computed at different levels of fidelities and are naturally amenable to inverse materials design strategies. Finally, while the learning approach to make predictions for a wide range of properties (including structural, elastic and electronic properties) is demonstrated here for a specific example set containing more than 1200 binary wurtzite superlattices, the adopted framework is equally applicable to other classes of materials as well.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Characterizing mechanical and microstructural properties of novel montmorillonite-rich polyethylene composites

Montmorillonite (MMT) clays are important industrial materials used as catalysts, chemical sorbents and fillers in polymer–clay nanocomposites. The layered structure of these clays has motivated research into further applications of these low-cost materials, including use as ion exchange media and solid-state ionic conductors. In these applications, the mechanical properties of MMT are key when considering long-term, reliable performance. Previous studies have focused on the mechanical properties of nanocomposites with MMT as the minority component or pure MMT thin films. In this work, the microstructure and mechanical properties of pure MMT and majority MMT/polyethylene composites pressed into dense pellets are examined. Characterization methods such as X-ray diffraction, atomic force microscopy and scanning electron microscopy together with nanoindentation reveal important structure–property relationships in the clay-based materials. Here, utilizing these techniques, we have discovered that MMT processing impacts the layered microstructure, chemical stability and, critically, the elastic modulus and hardness of bulk MMT samples. Particularly, the density of the pellets and the ordering of the clay platelets within them strongly influence the elastic modulus and hardness of the pellets. By increasing pressing force or by incorporating secondary components, the density, and therefore mechanical properties, can be increased. If the layered structure of the clay is destroyed by exfoliation, the mechanical properties will be compromised. Understanding these relationships will help guide new studies to engineer mechanically stable MMT-based materials for industrial applications.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Interactive Influence of Biofiber Composition and Elastomer on Physico-Mechanical Properties of PLA Green Composites

The objective of this work was to improve the impact and thermal properties of polylactic acid (PLA)-based biocomposite by appropriate application of cellulosic fiber and a bioelastomer. Biocomposites formulations with fiber contents of up to 20% in combination with a bioelastomer were extrusion-compounded in a twin-screw extruder followed by molding in an injection molding system. Fibers used in the formulations included three types of cellulosic fiber; namely, raw fiber from oat hull biomass (RF), hydrolysis byproduct (ATF) which was the solid fraction obtained from an acid-catalyzed hydrolysis of RF, and delignified fibers (AD30, AD65, AD100) which were the products of delignification of ATF. Formulated biocomposites were characterized for thermal (glass transition and melting temperatures, and enthalpy of melting) and physico-mechanical (tensile and bending strengths, stiffness, impact energy, and water absorption) properties. Among all types of biofibers, RF resulted in poor properties in the biocomposites due to the high hemicellulose content in the structure. On the other hand, the ratio of lignin to cellulose (in the absence of hemicellulose) in the modified fibers did not significantly affect the physico-mechanical and thermal properties of the biocomposites. The elastomer applied in the formulations improved the impact energy, thermal properties, and elongation at break of the composites. However, it adversely affected the strength and water resistance of biocomposites, especially in the presence of hemicellulose. The results indicated that, depending on the application, a wide range of PLA green composites with different physico-mechanical properties can be achieved.

09 BIOMASS FUELS↗

DOE OSTI2018

On the Size Dependence of Molar and Specific Properties of Independent Nano-phases and Those in Contact with Other Phases

Nano-materials are materials with at least one nano-phase. A nano-phase is a phase with at least one of its dimensions below 100 nm. It is shown here that nano-phases have at least 1% of their atoms along their surface layer. The ratio of surface atoms is proportional to the specific surface area of the phase, defined as the ratio of its surface area to its volume. Each specific/molar property has its bulk value and its surface value for the given phase, being always different, as the energetic states of the atoms in the bulk and in the surface layer of a phase are different. The average specific/molar property of a nano-phase is modeled here as a linear combination of the bulk and surface values of the same property, scaled with the ratio of the surface atoms. That makes the performance of all nano-phases proportional to their specific surface area. As the characteristic size of the nano-phase is inversely proportional to its specific surface area, all specific/molar properties of nano-phases are inversely proportional to the characteristic size of the phase. This is applied to the size dependence of the molar Gibbs energy of the nano-phase, which appears to be in agreement with the thermodynamics of Gibbs. This agreement proves the general validity of the present model on the size dependence of the specific/molar properties of independent nano-phases. It is shown that the properties of nano-phases are different for independent nano-phases (surrounded only by their equilibrium vapor phase) and for nano-phases in multi-phase situations, such as a liquid nano-droplet in the sessile drop configuration.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2016

Effects of the microstructure and porosity on properties of Ti-6Al-4V ELI alloy fabricated by electron beam melting (EBM)

Electron Beam Melting (EBM) is a metal powder bed-based Additive Manufacturing (AM) technology that makes possible the fabrication of three dimensional near-net-shaped parts directly from computer models. EBM technology has been in continuously updating, obtaining optimized properties of the processed alloys. Ti-6Al-4V titanium alloy is the most widely used and studied alloy for this technology and is the focus of this work. Several research works have been completed to study the mechanisms of microstructure formation as well as its influence on mechanical properties. However, the relationship is not completely understood, and more systematic research work is necessary in order to attain a better understanding of these features. In this work, samples fabricated at different locations, orientations, and distances from the build platform have been characterized, studying the relationship of these variables with the resulting material intrinsic characteristics and properties (surface topography, microstructure, porosity, micro-hardness and static mechanical properties). This study has revealed that porosity is the main factor controlling mechanical properties relative to the other studied variables. Therefore, in future process developments, decreasing of the porosity should be considered as the primary goal in order to improve mechanical properties.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Evolution of AISI 304L stainless steel part properties due to powder recycling in laser powder-bed fusion

Selective laser melting (SLM) is a powder-bed fusion process in Additive Manufacturing (AM) that uses a laser beam to selectively fuse layers of powder into near net-shape components with little porosity. However, inconsistencies in the part properties due to the presence of defects in as-built components has hindered the widespread adoption of SLM for industrial applications forcing researchers to study the sources of variation for quality control purposes. A critical area suspected of creating variation in the part properties is the feedstock, where batch-to-batch differences as well as changes in the powder properties with reuse have the potential to affect performance. During processing, laser spatter and condensate eject from the melt pool and deposit into the powder-bed surrounding the parts. These particulates, more commonly known as ejecta, differ morphologically and chemically from the virgin powder compromising its reusability. In this study, 304L stainless steel powder was recycled for a total of 5 times through a systematic approach aimed at accelerating powder degradation to reveal the influence on both the tensile and impact toughness properties. Through analysis of variance (ANOVA), it was found that tensile properties did not change with reuse, while the impact toughness showed a steady decline illustrating the differences in static and dynamic part properties due to powder recycling.

36 MATERIALS SCIENCE↗