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At least 109 records · Page 6

First Principles Modeling of Cluster-Based Solid Electrolytes (Final Technical Report)

Given the trend of global warming and the urgent need to transition from fossil fuels to green energy, lithium-ion batteries continue to be an integral part of our lives. Design, development, and understanding of novel solid-state electrolyte materials play the key role for achieving next-generation all-solid-state batteries with high energy and great safety. The current modeling schemes to develop advanced solid electrolytes are focusing on materials in which the building blocks are individual atoms. Our theoretical approach is a paradigm shift in solid-state electrolyte design. Instead of atoms, we focus on clusters as the building blocks and model these solid electrolytes and their interfaces with electrodes, especially Li-metal anode, for their successful implementation in solid-state batteries. The advantage of using the cluster ions to replace elemental ions is that the size, composition, and shape of the former can be tailored to achieve higher ionic conductivity at room temperature, electrochemical stability, and charge transfer across solid-solid interfaces than conventional materials. Specifically, the project includes: (1) Developing cluster-based solid electrolytes, where the halogen components are replaced by cluster ions that mimic the chemistry of halogens but are characterized by additional degrees of freedom, including the size, shape, composition, and motional dynamics under excitation. (2) Providing a fundamental understanding of the ion conduction mechanism in the developed cluster-based solid electrolytes; (3) Modeling the interfacial properties (i.e., structural, chemical, and transport properties) between the cluster-based solid electrolytes and electrodes at the atomic level. For the cluster-based solid electrolytes incompatible with the Li-metal anode or cathode materials, potential candidates for interfacial coatings are identified and studied. (4) Providing a theoretical framework towards optimizing critical parameters of the solid-state electrolytes that guides experimentalists to attain desired cathode-electrode interface for cluster-based solid-state electrolytes.

25 ENERGY STORAGE↗

Deterministic Calibration of MFiX-PIC, Part 1: Settling Bed

The Particle-in-cell (PIC) numerical approach for modeling granular solids in fluid flow has gained significant interest in recent years. Valued for its often shorter time-to-solution, the PIC formulation relies on modeling statistical groupings of particles called parcels in cooperation with a solids stress model to affect local solids velocity. This is in contrast to the discrete element model (DEM) where every particle in a system is modelled individually and directly coupled to local solids velocity through Newtonian mechanics. The U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) develops and maintains Multiphase Flow with Interphase eXchanges (MFiX), a collection of open-source computational fluid dynamics (CFD) solvers. Included in the MFiX suite are traditional two-fluid model (TFM) and DEM solvers, and a recently added PIC solver (NETL, 2021). In general, PIC methodologies offer an accuracy trade-off in lieu of computational speed; and therefore, it is important to assess the credibility of MFiX-PIC simulations. For this purpose, a systematic verification, validation and uncertainty quantification (VVUQ) effort was initiated at NETL to assess the new PIC solver

42 ENGINEERING↗

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗

Improved modeling of the solid-to-plasma transition of polystyrene ablator for laser direct-drive inertial confinement fusion hydrocodes

We report that the target performance of laser direct-drive inertial confinement fusion (ICF) can be limited by the development of hydrodynamic instabilities resulting from the nonhomegeneous laser absorption at the target surface, i.e., the laser imprint on the ablator. To understand and describe the formation of these instabilities, the early ablator evolution during the laser irradiation should be considered. In this work, an improved modeling of the solid-to-plasma transition of a polystyrene ablator for laser direct-drive ICF is proposed. This model is devoted to be implemented in hydrocodes dedicated to ICF which generally assume an initial plasma state. The present approach consists of the two-temperature model coupled to the electron, ion and neutral dynamics including the chemical fragmentation of polystyrene. The solid-to-plasma transition is shown to significantly influence the temporal evolution of both free electron density and temperatures, which can lead to different shock formation and propagation compared with an initial plasma state. The influence of the solid-to-plasma transition on the shock dynamics is evidenced by considering the scaling law of the pressure with respect to the laser intensity. The ablator transition is shown to modify the scaling law exponent compared with an initial plasma state.

36 MATERIALS SCIENCE↗

Comparison and multi-model inference of excess risks models for radiation-related solid cancer

In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose–response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Modeling Electrokinetics of Oxygen Electrodes in Solid Oxide Electrolyzer Cells

A microscale model is presented in this study to simulate electrode kinetics of the oxygen electrode in a solid oxide electrolyzer cell (SOEC). Two mixed ionic/electronic conducting structures are examined for the oxygen producing electrode in this work: single layer porous lanthanum strontium cobalt ferrite (LSCF), and bilayer LSCF/SCT (strontium cobalt tantalum oxide) structures. A yttrium-stabilized zirconia (YSZ) electrolyte separates the hydrogen and oxygen electrodes, as well as a gadolinium doped-ceria (GDC) buffer layer on the oxygen electrode side. Electrochemical reactions occurring at the two-phase boundaries (2PBs) and three-phase boundaries (3PBs) of single-layer LSCF and bilayer LSCF/SCT oxygen electrodes are modeled under various SOEC voltages with lattice oxygen stoichiometry as the key output. The results reveal that there exists a competition in electrode kinetics between 2PBs and 3PBs, but 3PBs are the primary reactive sites for single-layer LSCF oxygen electrode under high voltages. These locations experience the greatest oxygen stoichiometry variations and are therefore the most likely locations for dimensional changes. By applying an active SCT layer over LSCF, the 2PBs become activated to compete with the 3PBs, thus alleviating oxygen stoichiometry variations and reducing the likelihood of dimensional change. This strategy could reduce lattice structural expansion, proving to be valuable for electrode-electrolyte delamination prevention and will be the focus of future work.

30 DIRECT ENERGY CONVERSION↗

Development of chemometric models to classify solid-state U materials by micro-Raman spectroscopy

Discerning uranium (U) particles found in environmental sampling is of interest for monitoring the peaceful use of nuclear material. In this study, a soft independent modeling of class analogy (SIMCA) library was successfully developed for the classification of a four-class system consisting of α-U 3 O 8 , UO 2 , UO 2 (NO 3 ) 2 ·6H 2 O (UNH), and UO 2 O 2 ·4H 2 O (studtite) by Raman spectroscopy in the presence of matrix particulates and additional outliers. Spectral variability between numerous particles of each type revealed appreciable differences as a function of particle size with respect to hydration state and potential oxide phase within each class. Interclass variability was accounted for using both unsupervised and supervised chemometric models. The supervised SIMCA model displayed reasonable sensitivity for each U class and a high degree of specificity by returning whether a spectrum belonged to one class or not. This work demonstrates how Raman spectral features and chemometrics can be used to distinguish U materials from one another and from matrix materials such as flint clay. Combining the outlined chemometric approach with Raman mapping sequences could provide a rapid, nondestructive technique to characterize the chemical composition of a diverse collection of U compounds amid background samples for environmental sampling, nuclear forensics, and industrial applications.

Actinide↗

Layered CAD/CSG geometry for spatially complex radiation transport scenarios

Many spatially complex fission, fusion, and national security Monte Carlo (MC) radiation transport scenarios involve combining computer-aided design (CAD) models with constructive solid geometry (CSG) models. A layered geometry method has been implemented in the Shift MC code to address this need. With layered geometry, multiple CAD and/or CSG models can be clipped, translated, rotated, and placed in overlapping layers to form transport-ready geometries. Here, the utility of this method is demonstrated with two problems: (1) a fixed-source simulation with a layered geometry consisting of a LiDAR-generated CAD model of the Combined Arms Collective Training Facility urban environment overlaid with CSG models of a mock hotel and a detector apparatus, and (2) a k-eigenvalue calculation using a layered geometry model of the Transformational Challenge Reactor consisting of CAD fuel elements placed in a CSG core. Tallied particle flux distributions match expectations, but tracking robustness must be improved prior to general-purpose use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Solid and gas thermal conductivity models improvement and validation in various porous insulation materials

In the past few decades, significant efforts have been made to improve the theoretical understanding of thermal transport mechanisms in thermal insulation materials and push the thermal conductivity's lower limits. However, most works focused singularly on specific types of materials, and the models used for thermal conductivity predictions are diverse - a model that fits one material might not fit others. Here, we improve and unify the gas and solid thermal conductivity models for porous materials. Through experimental characterization of several different materials as well as literature data for other materials, these models are validated. Further, we have also found that the pressure-dependent gas thermal conductivity of most materials can be well fitted by using one or two pore sizes without using a complex pore size distribution. With the refined models, we decompose the effective thermal conductivity of several thermal insulation materials into gas, solid, and radiation contributions. For cellular (polystyrene and polyurethane) foams, the relative contributions from air, solid, and radiation are 58–75%, 3–11%, 16–38%, respectively. For granular porous materials (polyurethane and silica in this work), the contributions from air, solid, and radiation are 45–66%, 34–46%, and 0–8%, respectively. This work is expected to provide guidance on the design and optimization of the next generation of thermal insulation materials, for example, through the effort of reducing gas conduction and radiation in foams and suppressing gas and solid conduction in aerogels.

36 MATERIALS SCIENCE↗

A real-time multiphysics model of a pressurized solid oxide electrolysis cell (SOEC) for cyber-physical simulation

Solid oxide electrolysis cells (SOEC) can play important roles in integrated energy systems (IES) as the hydrogen production hub and the resilience energy hub. When tied to a microgrid with high renewable penetration, the SOEC is subjected to rapid load transitions in response to the intermittent renewable generations that occur not only in diurnal cycles but also in short timeframes (e.g., sub-minute). The cyber-physical simulation approach can derisk operability research but requires a real-time dynamic SOEC model. In the present work, a real-time multiphysics model for pressurized SOEC is developed and validated in the pressure range from 1.4 to 8bar. Further, the accuracy of the single repeating unit (SRU) assumption in SOEC stack simulation is quantified. A guidance of more than 45 cells in one SOEC stack is recommended to safely apply the SRU assumption. Modeling results suggest that at a given current density, more power is consumed by SOEC at elevated operating pressures. The anode air and cathode stream have major impacts on thermal management, highlighting the potential benefit of integrating SOEC with other thermal processes in IES. To achieve high hydrogen production efficiency, the SOEC could operate at the maximum endothermic point to maximize the use of thermal energy. The real-time execution of the developed SOEC model is also demonstrated, which only takes 0.1% of the fixed time step of 5ms. The developed model establishes the basis for cyber-physical simulation of SOEC hybrid systems.

25 ENERGY STORAGE↗

Ni coarsening under humid atmosphere in the electrode of solid oxide cells: A combined study of density-functional theory and phase-field modeling

Ni coarsening in solid oxide cell (SOC) electrodes is known to be significantly faster under a humid atmosphere. The underlying mechanisms, though, have not been fully understood. In this work, we examine the surface diffusion of Ni(OH) x by a combination of density-functional theory and phase-field modeling. Here, density-functional theory is used to evaluate the adsorption and diffusion of the Ni(OH) x species on Ni (111) surface, and the results are used to obtain the effective surface diffusivity of Ni versus steam and hydrogen gas partial pressures. This diffusivity is used as an input for a phase-field model to investigate the Ni coarsening in SOC electrodes. It is found that Ni(OH) x formed through chemical reaction cannot accelerate coarsening unless an extremely high steam to hydrogen ratio is reached. However, if Ni(OH) x is formed through electrochemical reactions near triple phase boundaries (TPBs), surface diffusion of Ni(OH) x may cause faster Ni coarsening in fuel cell mode under a large overpotential. Specifically, surface diffusion of Ni(OH) may be comparable to or faster than that of Ni under an overpotential that is large but still possible under fuel cell operating conditions.

25 ENERGY STORAGE↗

Composite Analysis Solid Waste Release Data Reduction of Activity Flux from Waste Sites to the Vadose Zone for Baseline Assessment

This environmental calculation file (ECF) describes the data reduction methodology for the solid waste release datasets generated by the Composite Analysis Solid Waste Release (CASWR) model (CP-62766, Model Package Report: Composite Analysis Solid Waste Release Model [CASWR Model]) and documents the resulting reduced datasets for the updated Composite Analysis (CA) baseline assessment. This ECF is in support of the updated Hanford Site CA. The purpose of the updated Hanford Site CA is to provide an estimate of the cumulative radiological impacts from active and planned low-level radioactive waste disposals and other potentially interacting radioactive waste disposal sources that will remain following Hanford Site closure. The vadose zone modeling activities associated with the CA includes solid waste forms as contaminant sources. To support the modeling of solid waste transport from the vadose zone to the groundwater at the Hanford Site, the CASWR model was designed to generate deterministic radionuclide release rates for the Hanford Site Central Plateau solid waste disposal sites. The complete CASWR model-generated dataset for the CA Baseline Assessment consists of 2,378,831 sets of time and release rates (1,073,869 sets for the 200 East Area and 1,304,962 sets for the 200 West Area), representing a course of the simulation from year 1953 to year 12,069, 16 radiological contaminants of potential concern (COPCs), and 237 solid waste sources as documented in ECFHANFORD- 19-0112, Solid Waste Release Calculations for the Composite Analysis Baseline Assessment. For several of the STOMP vadose zone models, the number of release rate data pairs required for release at all waste sites would exceed the limitations imposed by the STOMP modelling software package used to simulate contaminant transport through the vadose zone. As a result, a data reduction of the CASWR dataset is required prior to its use as a source input for the CA vadose zone modeling activities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A new model for the effective thermal conductivity of polycrystalline solids

We introduce a novel model for the effective thermal conductivity of polycrystalline solids based on the thin-interface description of grain boundaries (GBs). In contrast to existing models, our new model treats a GB as an autonomous “phase” with its own thermal conductivity. The Kapitza resistance/conductance of a thin interface is then derived in terms of the interface thermal conductivity and width. In turn, the effective thermal conductivity of polycrystals is derived in terms of grain size, grain and GB conductivities, and GB width. This treatment allows the model to simulate the change of the Kapitza resistance/conductance with segregation/doping, GB structure/phase transition, or GB decohesion. Moreover, since the model assumes a finite width for GBs, it is expected to give better predictions than its sharp-interface-based counterparts for nanoscale grains. The predictions of the new model deviate from the corresponding ones from existing models by 1%–100% as the grain size approaches the GB width. High-fidelity finite-element simulations were conducted to validate the predictions of the new model. These simulations proved the higher accuracy of the new model. We also discuss how to generalize this treatment to other types of interfaces in heterogeneous materials. The advantages and limitations of the new model are summarized, and some future directions are highlighted.

36 MATERIALS SCIENCE↗

The Effect of Mechanical State on the Equilibrium Potential of Alkali Metal/Ceramic Single–Ion Conductor Systems

The relationship between mechanical stress states and interfacial electrochemical thermodynamics of Li metal/Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 and Na metal/ Na-β”-Al 2 O 3 systems are examined in two experimental configurations with an applied uniaxial load; the solid electrolytes are pellets and the metal electrodes high-aspect-ratio electrodes. The experimental results demonstrate that 1) the change in equilibrium potential at the metal/electrolyte interface, when stress is applied to the metal electrode, is linearly proportional to the molar volume of the metal electrode, and 2) the mechanical stress in the electrolyte has a negligible effect on the equilibrium potential for an experimental setup in which the electrolyte is stressed and the electrode is left unstressed. Solid mechanics modeling of a metal electrode on a solid electrolyte pellet indicates that pressure and normal stress are within ≈0.5 MPa of each other for the high aspect ratio (≈1:100 thickness:diameter in our study) Li metal electrodes under loads that exceed yield conditions. Furthermore, this work should aid in advancing the quantitative understanding of alkali metal dendrite formation within incipient cracks and their subsequent growth, and pore formation upon stripping, both situations where properly accounting for the impact of mechanical state on the equilibrium potential is of critical importance for calculating the current distribution.

25 ENERGY STORAGE↗

Vickers hardness prediction from machine learning methods

Abstract The search for new superhard materials is of great interest for extreme industrial applications. However, the theoretical prediction of hardness is still a challenge for the scientific community, given the difficulty of modeling plastic behavior of solids. Different hardness models have been proposed over the years. Still, they are either too complicated to use, inaccurate when extrapolating to a wide variety of solids or require coding knowledge. In this investigation, we built a successful machine learning model that implements Gradient Boosting Regressor (GBR) to predict hardness and uses the mechanical properties of a solid (bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio) as input variables. The model was trained with an experimental Vickers hardness database of 143 materials, assuring various kinds of compounds. The input properties were calculated from the theoretical elastic tensor. The Materials Project’s database was explored to search for new superhard materials, and our results are in good agreement with the experimental data available. Other alternative models to compute hardness from mechanical properties are also discussed in this work. Our results are available in a free-access easy to use online application to be further used in future studies of new materials at www.hardnesscalculator.com .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spontaneous Lithiation of Binary Oxides during Epitaxial Growth on LiCoO 2

Epitaxial growth is a powerful tool for synthesizing heterostructures and integrating multiple functionalities. Interfacial mixing can readily occur at temperatures required for complete film crystallization and can significantly modify the properties of layered structures, particularly for those containing energy storage materials with smaller cations. Here we show a two-step sequence involving the growth of an epitaxial LiCoO 2 cathode layer followed by the deposition of a binary transition metal oxide (WO 3 , TiO 2 , and others) in which controlled lithiation of the binary oxide occurs. Orientation-controlled epitaxial synthesis of the model solid-state-electrolyte Li 2 WO 4 and model anode material Li 4 Ti 5 O 12 occurs as WO 3 and TiO 2 nucleate their respective host lattices and attract Li ions from the underlying cathode. The cathode layer readily provides a tunable amount of Li ions for the controlled lithiation of the subsequent layer. We demonstrate that this approach can be used for energy materials discovery and exploring different combinations of epitaxial interfaces that can serve as well-defined model systems for mechanistic studies of energy storage and conversion processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando neutron radiography validates a parameter-free transport–kinetics model for thick solid-state battery cathodes

Tortuosity-weighted interfacial flux for lithium (TWIF-Li) predicts through-thickness Li gradients in thick composite all-solid-state cathodes without fitted parameters. Image-derived microstructures, GITT-derived concentration-dependent solid diffusion, and tortuosity-weighted interfacial kinetics reproduce operando neutron radiography across practical rates, delivering transferable design rules to suppress transport-limited reaction fronts.

Adam, Andre [ORNL] (ORCID:0000000245023033)↗