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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 127 records · Page 7

Metal-Supported Solid Oxide Fuel Cells for Natural Gas

Solid oxide fuel cells (SOFCs) are high temperature energy conversion devices that produce electricity efficiently and sustainably. High operating temperatures required for SOFC function endow these devices with many advantages including fuel flexibility and high conversion efficiencies. Fuel flexibility, in particular, distinguishes SOFCs from other types of fuel cells that operate with clean H 2 only, and enables operation with natural gas (NG). LBNL has developed metal supported SOFCs (MS-SOFCs) with unique symmetrical architecture that offer several advantages over state of the art (SoA) ceramic SOFC models including inexpensive materials, rapid start up capability, increased mechanical strength and high tolerance to thermal cycling, Fig 1. These advantages make LBNL MS-SOFCs uniquely suited for fast start-up, portable, and mobile backup generator applications. Specifically motivating this work was a scenario of backup generators fueled by pipeline natural gas delivered from SoCalGas in the event of an electric grid shut down. This project investigates the feasibility of using MS-SOFCs with pre-reformed natural gas as well as direct on-cell reforming of simulated natural gas both with and without sulfur.

03 NATURAL GAS↗

2023 Sandia Day at UT Austin

On Wednesday, March 8 th and Thursday, March 9 th , 2023, the University of Texas at Austin hosted Sandia National Laboratories (Sandia) for “Sandia Day 2023 at UT Austin” with the intention of reviewing, planning and shaping ongoing and future collaborations in key areas that reflect each organization’s priorities and strengths. The event brought together nearly 100 UT and Sandia participants including executive leadership, researchers, faculty, staff, and students. The primary sessions of Sandia Day consisted of a half-day tour of select J.J. Pickle Research Campus facilities, a networking happy hour, leadership meetings, presentations by both Sandia and UT Austin representatives in areas of research strategic priorities: Grid Resiliency, Examining Climate Change, and Microelectronics, and a research poster session with lunch. The group also discussed growth opportunities in the following research areas: nuclear and radiation engineering, pulsed power and fusion physics, and digital engineering, specifically as it related to materials discovery and advanced manufacturing. Appendix A contains the full Sandia Day agenda.

99 GENERAL AND MISCELLANEOUS↗

Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations

The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.

Bogenschutz, Peter A. [Lawrence Livermore National↗

A metric framework for evaluating the resilience contribution of hydropower to the grid

This paper will describe a proposed framework for expressing the resilience of hydropower generation and provide initial case studies for three classes of hydropower, run-of-river hydropower, hydropower with reservoirs, and pumped storage hydropower. Hydropower has great flexibility to provide support during and after natural and man-made events that can disrupt critical infrastructure functionality. The concept of the framework provides for consideration of policy and rules, constraints of the water shed and other allocations of water, storage and plant capabilities to produce real and reactive power, and the strength of the delivery network. The paper details a resilience response metric that has inputs of state of storage and plant level constraints on real and reactive power production. Using the definition of resilience, based on maintaining a minimally normal operations, we provide a qualitative assessment of hydropower’s ability to address the various time scales comprising the “R”s of resilience.

13 HYDRO ENERGY↗

Conversion Kinetics and Ionic Conductivity in Na-β”-Alumina + YSZ (Naβ”AY) Sodium Solid Electrolyte via Vapor Phase Conversion Process

Sodium ion batteries have been receiving increasing attention and may see potential revival in the near future, particularly in large-scale grid energy storage coupling with wind and solar power generation, due to the abundant sodium resources, low cost, and sufficiently high energy density. Among the known sodium ion conductors, the Na-β”-alumina electrolyte remains highly attractive because of its high ionic conductivity. This study focuses on the vapor phase synthesis of a Na-β”-Alumina + YSZ (Naβ”AY) composite sodium electrolyte, which has higher mechanical strength and stability than conventional single phase β”-Alumina. The objectives are the measurement of conversion kinetics through a newly developed weight-gain based model and the determination of sodium ionic conductivity in the composite electrolyte. Starting samples contained ~70 vol% α-Alumina and ~30 vol% YSZ (3 mol% Y 2 O 3 stabilized Zirconia) with and without a thin alumina surface layer made by sintering in air at 1600 °C. The sintered samples were placed in a powder of Na-β”-alumina and heat-treated at 1250 °C for various periods. Sample dimensions and weight were measured as a function of heat treatment time. The conversion of α-Alumina in the α-Alumina + YSZ composite into Naβ”AY occurred by coupled diffusion of sodium ions through Na-β”-alumina and of oxygen ions through YSZ, effectively diffusing Na2O. From the analysis of the time dependence of sample mass and dimensions, the effective diffusion coefficient of Na 2 O through the sample, D eff , was estimated to be 1.74 x 10 -7 cm2 s -1 , and the effective interface transfer parameter, k eff , was estimated as 2.33 x 10 -6 cm s -1 . By depositing a thin alumina coating layer on top of the bulk composite, the chemical diffusion coefficient of oxygen through single phase Na-β”-alumina was estimated as 4.35 x 10 -10 cm 2 s -1 . An AC impedance measurement was performed on a fully converted Naβ”AY composite, and the conductivity of the composite electrolyte was 1.3 x 10 -1 S cm -1 at 300 °C and 1.6 x 10 -3 S cm -1 at 25 °C, indicating promising applications in solid state or molten salt batteries at low to intermediate temperatures.

36 MATERIALS SCIENCE↗

Assessment of diffuse-interface methods for compressible multiphase fluid flows and elastic-plastic deformation in solids

This work describes three diffuse-interface methods for the simulation of immiscible, compressible multiphase fluid flows and elastic-plastic deformation in solids. The first method is the localized-artificial-diffusivity approach of Cook, Subramaniam et al., and Adler and Lele, in which artificial diffusion terms are added to the individual phase mass fraction transport equations and are coupled with the other conservation equations. The second method is the gradient-form approach that is based on the quasi-conservative method of Shukla et al., in which the diffusion and sharpening terms (together called regularization terms) are added to the individual phase volume fraction transport equations and are coupled with the other conservation equations. The third approach is the divergence-form approach that is based on the fully conservative method of Jain et al., in which the regularization terms are added to the individual phase volume fraction transport equations and are coupled with the other conservation equations. In the present study, all three diffuse-interface methods are used in conjunction with a four-equation, multicomponent mixture model, in which pressure and temperature equilibria are assumed among the various phases. The primary objective of this work is to compare these three methods in terms of their ability to: maintain constant interface thickness throughout the simulation; conserve mass, momentum, and energy; and maintain accurate interface shape for long-time integration. The second objective of this work is to consistently extend these methods to model interfaces between solid materials with strength. To assess and compare the methods, they are used to simulate a wide variety of problems, including (1) advection of an air bubble in water, (2) shock interaction with a helium bubble in air, (3) shock interaction and the collapse of an air bubble in water, and (4) Richtmyer–Meshkov instability of a copper–aluminum interface. The current work focuses on comparing these methods in the limit of relatively coarse grid resolution, which illustrates the true performance of these methods. In conclusion, this is because it is rarely practical to use hundreds of grid points to resolve a single bubble or drop in large-scale simulations of engineering interest.

97 MATHEMATICS AND COMPUTING↗

Cooperative Research and Development Agreement between National Energy Technology Laboratory and VariGrid Explorations Inc. [Final Report]

The scope of this project is to advance the National Energy Technology Laboratory’s (NETL) Variable Grid Method (VGM) technology to commercial status thought enhancements upon prior work to produce a VGM application that can rapidly quantify multiple types of data and uncertainty commonly encountered by the subsurface energy industry. Along with development, the project will also include technology demonstrations, through applications using common industry data types and uncertainty metrics, to stress the value the VGM can offer the subsurface energy industry by providing an improved understanding of the strengths and limitations of their data, models, and analytical results. The resulting commercially ready VGM will offer interoperability with common industry software applications to ensure broad ‘plug and play’ functionality that will help keep costs relatively low and foster more rapid industry adoption.

97 MATHEMATICS AND COMPUTING↗

When should PIC simulations be applied to atmospheric pressure plasmas? Impact of correlation heating

Abstract Molecular dynamics simulations are used to test when the particle-in-cell (PIC) method applies to atmospheric pressure plasmas. It is found that PIC applies only when the plasma density and macroparticle weight are sufficiently small because of two effects associated with correlation heating. The first is the physical effect of disorder-induced heating (DIH). This occurs if the plasma density is large enough that a species (typically ions) is strongly correlated in the sense that the Coulomb coupling parameter exceeds one. In this situation, DIH causes ions to rapidly heat following ionization. PIC is not well suited to capture DIH because doing so requires using a macroparticle weight of one and a grid that well resolves the physical interparticle spacing. These criteria render PIC intractable for macroscale domains. The second effect is a numerical error due to artificial correlation heating (ACH). ACH is like DIH in that it is caused by the Coulomb repulsion between particles, but differs in that it is a numerical effect caused by a macroparticle weight larger than one. Like DIH, it is associated with strong correlations. However, here the macroparticle coupling strength is found to scale as Γ w 2 / 3 , where Γ is the physical coupling strength and w is the macroparticle weight. So even if the physical coupling strength of a species is small, as is expected for electrons in atmospheric pressure plasmas, a sufficiently large macroparticle weight can cause the macroparticles to be strongly coupled and therefore heat due to ACH. Furthermore, it is shown that simulations in reduced dimensions exacerbate these issues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Recent Developments at the U.S. Navy Wave Energy Test Site.

The U.S. Navy’s Wave Energy Test Site (WETS) in Hawaii has hosted two wave energy conversion (WEC) devices since its June 2015 commissioning – the Fred. Olsen BOLT Lifesaver and the Northwest Energy Innovations (NWEI) Azura – each for two deployments. Several additional devices will be tested in the coming years, beginning with the Ocean Energy device in summer 2019. The Hawaii Natural Energy Institute (HNEI) provides research and logistics support to WETS. We will provide an overview of three major activities that we have recently undertaken in this capacity. First, we will discuss results from a project in which modifications were made to the hull and float of the Azura, aimed at improving power performance for a second WETS deployment. Second, HNEI undertook a redeployment of Lifesaver beginning in October 2018, with the dual intent of achieving improvements in reliability and power performance, while also conducting an important demonstration of the use of wave power for non-grid applications. HNEI partnered with the University of Washington to integrate their Adaptable Monitoring Package (AMP) into the hull of BOLT Lifesaver. Included for this deployment was a subsea inductive charging capability from WiBotic, Inc.. These systems are powered entirely by electricity generated by the Lifesaver itself. Finally, HNEI has undertaken design improvements for the deeper berth moorings at WETS, with principal engineering guidance from DNV GL. This has included extensive numerical analysis of strength and fatigue aimed at establishing moorings that can persist for as long as possible. The resulting design will be discussed.

Wave energy conversion devices, Alternative market↗

Assessment and Coordination of EVSE Cybersecurity Standards

Cybersecurity certification programs for Electric Vehicle Supply Equipment (EVSE) are fragmented due to no single certification covering all aspects of the device and additionally the existence of multiple programs and under different levels of regulation. These devices are also confronted by the intricate assembly of product software, firmware, and hardware. Devices contain both logical and physical interfaces. These multifaceted devices have vulnerabilities at many levels and interconnect with other potentially vulnerable systems including the electric vehicle, the cloud where data and payment information are stored, and the electric grid and electric grid equipment including utilities. Of the EVSE certification programs that are found, none are directly for the cybersecurity of EVSE. Many standards are for safety, specifically battery safety, some are cybersecurity standards for other types of equipment and can be modeled for EVSE. In specific, ISA/IEC 62443 is found to be significantly in line with EVSE security needs and will be used in future testing to certify EVSE and help guide the project to demonstrate where gaps exist, where strengths lie in the standard and how this can be used to lead the certification efforts in harmonizing EVSE cybersecurity standards. In addition, there are multiple efforts that are currently seeking to build EVSE standards or revise existing standards to address gaps. This effort is seeking to establish a cybersecurity program for EVSE that will inform customers and help increase the level of security across products and state EVSE procurements to achieve consistency across different jurisdictions.

33 ADVANCED PROPULSION SYSTEMS↗

Designing Ti-6Al-4V microstructure for strain delocalization using neural networks

Abstract The deformation behavior of Ti-6Al-4V titanium alloy is significantly influenced by slip localized within crystallographic slip bands. Experimental observations reveal that intense slip bands in Ti-6Al-4V form at strains well below the macroscopic yield strain and may serially propagate across grain boundaries, resulting in long-range localization that percolates through the microstructure. These connected, localized slip bands serve as potential sites for crack initiation. Although slip localization in Ti-6Al-4V is known to be influenced by various factors, an investigation of optimal microstructures that limit localization remains lacking. In this work, we develop a novel strategy that integrates an explicit slip band crystal plasticity technique, graph networks, and neural network models to identify Ti-6Al-4V microstructures that reduce the propensity for strain localization. Simulations are conducted on a dataset of 3D polycrystals, each represented as a graph to account for grain neighborhood and connectivity. The results are then used to train neural network surrogate models that accurately predict localization-based properties of a polycrystal, given its microstructure. These properties include the ratio of slip accumulated in the band to that in the matrix, fraction of total applied strain accommodated by slip bands, and spatial connectivity of slip bands throughout the microstructure. The initial dataset is enriched by synthetic data generated by the surrogate models, and a grid search optimization is subsequently performed to find optimal microstructures. Describing a 3D polycrystal with only a few features and a combination of graph and neural network models offer robustness compared to the alternative approaches without compromising accuracy. We show that while each material property is optimized through a unique microstructure solution, elongated grain shape emerges as a recurring feature among all optimal microstructures. This finding suggests that designing microstructures with elongated grains could potentially mitigate strain localization without compromising strength.

Ahmadikia, Behnam↗

Simultaneously improved electrical and mechanical performance of hot-extruded bulk scale aluminum-graphene wires

Aluminum-based alloys are highly sought after as lightweight alternatives in electric grid applications. Improving the electrical conductivity of aluminum alloys has the potential to increase the energy efficiency of power transport. Here we used a hot extrusion process to synthesize AA1100 alloy with low-cost reduced graphene oxide nanoparticles to manufacture ultra-conductive aluminum composites in this study. The effects of graphene content on the electrical and mechanical performance of the composites were evaluated. The macroscale AA1100/graphene wires demonstrated a 2.1% enhancement in electrical conductivity at 20 °C, while the ultimate tensile strength increased by 6.1%. A Zener-Hollomon model was used to confirm the in-process exfoliation of the agglomerated graphene nanoparticle feedstock into high electrical conductivity graphene-like flakes during extrusion. They may have provided high-velocity carrier pathways leading to the enhanced electrical performance of the alloy. Transmission electron microscopy at aluminum-graphene interfaces ensures the preclusion of detrimental carbide formation during composite synthesis while confirming the structure graphene-like flakes. The in-process exfoliation provides an economically viable technique to produce bulk scale graphinated aluminum composites for advanced application and can be applied more generally to other alloy systems.

36 MATERIALS SCIENCE↗

North American Lithium-Ion Battery Supply Chain Database Development - Phase II

Lithium-ion batteries (LIBs) are used in a wide range of applications, including cell phones, laptops, power tools, electric vehicles, and grid storage, and are essential for economic growth and addressing climate change. However, the significant demand for LIBs has led to supply chain issues for the United States, as China dominates the processing of battery materials and battery production. To address this concern, NAATBatt International, a trade association of North American battery companies, supported the National Renewable Energy Laboratory in developing a database of companies that mine, process, manufacture, reuse, and recycle batteries in North America. The purpose of this database was to identify strengths and gaps in the supply chain, so that private-government partnerships could develop strategies to create a competitive LIB supply chain in the US. NREL published the first version of this database in 2021 and the second version in 2022. The database includes companies that have a manufacturing facility in North America and are engaged in materials, cells, packs, end-of-life management, as well as those involved in LIB battery modeling, distribution, service and repair, and R&D. In this presentation, we will discuss our approach to collecting data and categorizing various segments and products. We will also provide a summary of the data and present various maps to illustrate the distribution of companies in the database.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

Optimizing Nonaqueous Sodium–Polysulfide Redox-Flow Batteries: The Role of Solvation Effects with Glyme Solvents

Nonaqueous redox-flow batteries (NARFBs) that use economical alkali metals and the corresponding metal polysulfides are highly attractive for grid-scale energy storage. Although sodium–sulfur systems have been recognized as promising candidates and have been the focus of many studies due to their high earth abundance and energy density, an understanding of the role of the solvation chemistry of commonly used glyme solvents is missing. Herein, we report a systematic investigation into the solvation effects of glyme-based Na-S electrolytes through comprehensive physiochemical experiments and Density Functional Theory (DFT) simulations. Our findings revealed, on one hand, that an optimal coordination strength between glymes and Na + could maintain a relatively smooth Na + diffusion. On the other hand, glyme solvents with extended chain lengths shift the reduction potential of S 8 2– negatively to elevate the formation barrier of undesirable short-chain polysulfides (S n 2– , n ≤ 4) that have high membrane permeability. This solvation phenomenon not only mitigates capacity fading but also extends the operational longevity of the Na-S NARFBs. In conclusion, the results underscore the critical roles of balanced solvent–cation interactions and controlled redox potentials in improving the stability and efficiency of Na-S NARFB systems, marking a significant advancement in the development of sustainable energy storage solutions.

25 ENERGY STORAGE↗

Towards a Unified Setup to Simulate Mid‐Latitude and Tropical Mesoscale Convective Systems at Kilometer‐Scales

Abstract Mesoscale convective systems (MCSs) are the main source of precipitation in the tropics and parts of the mid‐latitudes and are responsible for high‐impact weather worldwide. Studies showed that deficiencies in simulating mid‐latitude MCSs in state‐of‐the‐art climate models can be alleviated by kilometer‐scale models. However, whether these models can also improve tropical MCSs and whether we can find model settings that perform well in both regions is understudied. We take advantage of high‐quality MCS observations collected over the Atmospheric Radiation Measurement (ARM) facilities in the US Southern Great Plains (SGP) and the Amazon basin near Manaus (MAO) to evaluate a perturbed physics ensemble of simulated MCSs with 4 km horizontal grid spacing. A new model evaluation method is developed that enables to distinguish biases stemming from spatiotemporal displacements of MCSs from biases in their reflectivity and cloud shield. Amazon MCSs are similarly well simulated across these evaluation metrics than SGP MCSs despite the challenges anticipated from weaker large‐scale forcing in the tropics. Generally, SGP MCSs are more sensitive to the choice of model microphysics, while Amazon cases are more sensitive to the planetary boundary layer (PBL) scheme. Although our tested model physics combinations had strengths and weaknesses, combinations that performed well for SGP simulations result in worse results in the Amazon basin and vice versa. However, we identified model settings that perform well at both locations, which include the Thompson and Morrison microphysics coupled with the Yonsei University (YSU) PBL scheme and the Thompson scheme coupled with the Mellor‐Yamada‐Janjic PBL scheme.

54 ENVIRONMENTAL SCIENCES↗

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.

59 BASIC BIOLOGICAL SCIENCES↗

Shorting at Long Duration: Impact of Extended Discharge Capacity on Battery Solid Electrolytes

Long-duration energy storage (LDES) is critical to a stable, resilient, and decarbonized electric grid. While batteries are emerging as important LDES devices, extended, high-power discharges necessary for cost-competitive LDES present new materials challenges. Here, focusing on a new generation of low-temperature molten sodium batteries, we explore here unique phenomena related to long-duration discharge through a well-known solid electrolyte, NaSICON. Specifically, molten sodium symmetric cells at 110°C were cycled at 0.1 A cm -2 for 1-23 h discharges. Longer discharges led to unstable overpotentials, reduced resistances, and decreased electrolyte strength, caused by massive sodium penetration not observed in shorter duration discharges. Scanning electron microscopy informed mechanisms of sodium penetration and even “healing” during shorter-duration cycling. Importantly, these findings show that traditional, low-capacity, shorter-duration tests may not sufficiently inform fundamental materials phenomena that will impact LDES battery performance. This case highlights the importance that candidate LDES batteries be tested under pertinent long-duration conditions.

25 ENERGY STORAGE↗

The 2025 Evaluation of Experimental Thermonuclear Reaction Rates (ETR25)

This work describes the formalism for estimating thermonuclear reaction rates for astrophysical applications, emphasizing modern statistical approaches such as Monte Carlo sampling and Bayesian models. We discuss related topics including the calculation of resonance energies from nuclear Q values, indirect estimates of particle partial widths, and matching of reaction rates at elevated temperatures to statistical model results. We have evaluated available experimental data on cross sections, resonance energies and strengths, partial widths, lifetimes, spin-parities, and spectroscopic factors. Based on these results, we have estimated numerical values of 78 experimental charged-particle thermonuclear reaction rates for target nuclei in the A = 2–40 mass region, for temperatures ranging from 1 MK to 10 GK. For each reaction, three rate values are provided: low, median, and high, corresponding to the 16th, 50th, and 84th percentiles, respectively, of the cumulative reaction rate probability density distribution. Additionally, we present the factor uncertainty of each rate at each temperature grid point. These results enable users to sample the reaction rate probability density in nucleosynthesis calculations, facilitating uncertainty estimates of nuclidic abundances. The rates presented here refer to their laboratory values. For use in stellar model simulations, these values need to be corrected for the effects of thermal excitations of the interacting nuclei. For each reaction, we include graphs that illustrate the fractional contributions to the overall reaction rate along with the associated uncertainty. These visuals are designed to assist both stellar modelers and nuclear experimentalists by identifying the primary sources of rate uncertain=^texttx);ty at specific stellar temperatures. A graphical comparison with earlier Monte Carlo rates is also provided.

Nuclear astrophysics↗