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At least 1,081 records · Page 60

Oxygen redox chemistry in P2-Na 0.6 Li 0.11 Fe 0.27 Mn 0.62 O 2 cathode for high-energy Na-ion batteries

Owing to the abundance of raw material reserves and low cost, Na-ion batteries (NIBs) have successfully gained widespread attention from academic and industrial communities in the past few decades. However, the insufficient cathode energy density is still one of the critical bottlenecks restricting the development of NIBs. Following a strategy of introducing Li+ into the transition-metal (TM) layer to enhance the oxygen redox reaction, a novel layered cathode material P2-Na 0.6 Li 0.11 Fe 0.27 Mn 0.62 O 2 (NLFMO) was designed and successfully synthesized. This NLFMO cathode not only delivers a large initial reversible capacity of 207.3 mA h g -1 , but also shows a good cycling performance (104.2 mA h g -1 after 80 cycles) and rate capability (126.2 mA h g -1 at 1C). The ultrahigh capacity is contributed by both cationic (Fe 3+ /Fe 4+ and Mn 3+ /Mn 4+ ) and partially reversible anionic redox (O 2- /O n- ) reactions, revealed by in situ X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS) techniques. Moreover, no detrimental P2–O2 phase transition was observed in ex situ X-ray diffraction (XRD) patterns, confirming the high structural stability during Na + deintercalation/intercalation processes. These results provide valuable information about the high-energy density layered cathode materials based on anionic redox reactions for NIBs.

25 ENERGY STORAGE↗

OPFLearnData: Dataset for Learning AC Optimal Power Flow

The datasets are resulting from OPFLearn.jl, a Julia package for creating AC OPF datasets. The package was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. The dataset contains load profiles and their respective optimal primal and dual solutions. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets" and in the package website: https://github.com/NREL/OPFLearn.jl.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Lifespan Impacts to Infrastructure, Renewable Energy Components and Energy Storage Components Related to Fluoropolymer Use

This report focuses on the use of fluoropolymers in infrastructure materials (building construction materials, transportation, and electrical transmission and distribution); renewable energy generation components (specifically wind and solar); and energy storage components (lithium-ion batteries and fuel cells) and product lifespan impacts if fluoropolymers were no longer available or allowed in commerce. Additionally, environmental considerations for fluoropolymer manufacture, use, and end-of-life disposal are discussed. This document is the second of two companion reports. The first report, Assessment of Fluoropolymer Production and Use With Analysis of Alternative Replacement Materials, contained an analysis of use of fluoropolymers and their potential replacement technologies in aerospace, automotive, battery, building construction, chemical processing, electronics, infrastructure, semiconductor, solar panel, and wind energy industries sectors, along with qualitative life cycle assessment (LCA) and cost-benefit analysis of replacing fluoropolymers. This report does not focus on the lifecycle aspects of use of fluoropolymer or alternatives in the designated applications. For more information on those topics, see aforementioned report.

25 ENERGY STORAGE↗

An autoencoder compression approach for accelerating large-scale inverse problems

Abstract Partial differential equation (PDE)-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes required to accurately compute the PDE solution introduce an enormous number of parameters and require large-scale computing resources such as more processors and more memory to solve such systems in a reasonable time. For inverse problems constrained by time-dependent PDEs, the adjoint method often employed to compute gradients and higher order derivatives efficiently requires solving a time-reversed, so-called adjoint PDE that depends on the forward PDE solution at each timestep. This necessitates the storage of a high-dimensional forward solution vector at every timestep. Such a procedure quickly exhausts the available memory resources. Several approaches that trade additional computation for reduced memory footprint have been proposed to mitigate the memory bottleneck, including checkpointing and compression strategies. In this work, we propose a close-to-ideal scalable compression approach using autoencoders to eliminate the need for checkpointing and substantial memory storage, thereby reducing the time-to-solution and memory requirements. We compare our approach with checkpointing and an off-the-shelf compression approach on an earth-scale ill-posed seismic inverse problem. The results verify the expected close-to-ideal speedup for the gradient and Hessian-vector product using the proposed autoencoder compression approach. To highlight the usefulness of the proposed approach, we combine the autoencoder compression with the data-informed active subspace (DIAS) prior showing how the DIAS method can be affordably extended to large-scale problems without the need for checkpointing and large memory.

Mathematics↗

Community Sentiment Analysis with Focus on CCS

This research assesses community sentiment towards Carbon Capture and Storage (CCS) as depicted in digital media, focusing on themes such as emissions, transport, and storage. Utilizing the VADER sentiment analysis model, the study analyzed titles and descriptions from online news articles to capture immediate impressions and sentiments. Results indicate a predominantly positive sentiment towards CCS, with significant regional variations. States like Alabama and Texas exhibit high positive sentiment, likely due to economic ties to the energy industry, while states like Delaware and Utah show negative sentiment, potentially driven by environmental concerns. The significance of this study lies in its potential to inform policy and communication strategies for CCS implementation. Understanding public sentiment is crucial for the success of CCS projects as it helps to identify and address community concerns. Media influence plays a significant role in shaping public opinion, and this study highlights the need for effective communication strategies to promote the benefits of CCS while addressing any misconceptions. By providing insights into regional differences in sentiment, this research supports the development of tailored interventions that can enhance public acceptance and support for CCS initiatives, ultimately contributing to the success of efforts to mitigate climate change through reduced greenhouse gas emissions.

White, Casey↗

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗

Review of Mercury in the SRS Tank Waste Storage and Treatment Processes for Applicability to Hanford Waste Processing

The Savannah River Site (SRS) and Hanford produced large quantities of plutonium and other radioisotopes. The separations processes recovered plutonium and produced large quantities of High- Level Waste (HLW) that accumulated at each site in large, underground storage tanks. SRS has been retrieving the stored HLW, pretreating the waste for immobilization, and immobilizing the waste in glass or grout waste forms since the mid-1990s. Treatment of the waste at Hanford is expected to start in the early 2020s. Mercury is present in both the SRS and Hanford tank waste. SRS has recently completed an evaluation of mercury speciation throughout the tank waste treatment and immobilization flowsheet. This study was reviewed to determine what information from the study can be applied to the Hanford tank waste treatment program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Risk-informed Hierarchical Control of Behind-the-Meter DERs with AMI Data Integration (Final Technical Report)

This project addresses several key barriers to implement the next generation demand response applications and provides a clear understanding of implementing hierarchical and standalone control using AMI data. Through this program, Eaton has developed and tested a meter-as-a-controller prototype with the help of other partners--- National Renewable Energy Laboratory (NREL), Electric Power Research Institute (EPRI), Pecan St Inc. (PSI), and Delaware Electric Cooperative (DEC). The controller can utilize residential controllable loads such as heating, ventilation, and air conditioner (HVAC), electric water heater and distributed energy resources like solar PV and battery energy storage systems for off-setting the demand that is required from the grid, thus providing reliable grid-services for demand reduction or peak shaving. The controller is also capable of coordinating the resources of the premises for better management and energy efficiency while meeting the comfort bound of the premises owner as quality-of-service. The development has been demonstrated in a three virtual-home setup at system performance lab of NREL with real appliances (HVAC, electric water heater, solar PV, and battery). The technology has also been proved through laboratory and field demonstration with successful interconnectivity (e.g., end-to-end communication and data exchange) between the residential appliances and utility through the RF network at Delaware Electric Co-op (DEC) in Delaware.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Recent developments in catalyst-related PEM fuel cell durability

Cost and durability remain the two major barriers to the widespread commercialization of polymer electrolyte membrane fuel cell (PEMFC)-based power systems, especially for the most impactful but challenging fuel cell electric vehicle (FCEV) application. Commercial FCEVs are now on the road; however, their PEMFC systems do not meet the cost targets established by the U.S. Department of Energy, primarily due to the high platinum loading needed on the cathode to achieve the requisite performance and lifetime. Furthermore, while the activities of a number of commercial Pt-based alloy cathode catalysts exceed the beginning-of-life (BOL) targets, these activities, and the overall cathode performance, degrade via a variety of mechanisms described herein. Degradation is mitigated in current FCEVs by utilizing a cathode catalyst with a lower BOL activity (e.g., much lower transition metal alloy content and larger BOL nanoparticle size), necessitating higher catalyst loadings, and through the utilization of system controls that avoid conditions known to exacerbate degradation processes, such as limiting the fuel cell stack voltage range. The design and development of active and robust materials and eliminating the need for vehicle mitigation strategies would greatly simplify the operating system, allowing for greater transient operation, avoiding large hybridization, and curtailing of fuel cell power. Although system mitigation strategies have provided the near-term pathway for FCEV commercialization, material-specific solutions are required to further reduce costs and improve operability and efficiency. Future material developments should focus on stabilization of the electrode structure and minimization of the catalyst particle susceptibility to dissolution caused by oxide formation and reduction over PEMFC cathode-relevant operating potentials plus minimization of support corrosion. Ex situ accelerated stress tests have provided insight into the processes responsible for material and performance degradation and will continue to provide useful information on the relative stability of materials and benchmarks for robust and stable materials-based solutions not requiring system mitigation strategies to achieve adequate lifetime.

25 ENERGY STORAGE↗

Dual-shell silicate and alumina coating for long lasting and high capacity lithium ion batteries

In this work we demonstrate a theory-driven, novel dual-shell coating system of Li 2 SrSiO 4 and Al 2 O 3 , achieved via a facile and scalable sol-gel technique on LiCoO 2 electrode particles. The optimal thickness of each coating can lead to increased specific capacity (~185 mAh/g at 0.5 C-rate) at a cut-off potential of 4.5 V, and greater cycling stability at very high C rates (up to 10 C) in half-cells with lithium metal. The mechanism of this superior performance was investigated using a combination of X-ray and electron characterization methods. It shows that the results of this investigation can inform future studies to identify still better dual-shell coating schemes, achieved by such industrially feasible techniques, for application on similar, nickel-rich cathode materials.

25 ENERGY STORAGE↗

Controlling single rare earth ion emission in an electro-optical nanocavity

Abstract Rare earth emitters enable critical quantum resources including spin qubits, single photon sources, and quantum memories. Yet, probing of single ions remains challenging due to low emission rate of their intra-4 f optical transitions. One feasible approach is through Purcell-enhanced emission in optical cavities. The ability to modulate cavity-ion coupling in real-time will further elevate the capacity of such systems. Here, we demonstrate direct control of single ion emission by embedding erbium dopants in an electro-optically active photonic crystal cavity patterned from thin-film lithium niobate. Purcell factor over 170 enables single ion detection, which is verified by second-order autocorrelation measurement. Dynamic control of emission rate is realized by leveraging electro-optic tuning of resonance frequency. Using this feature, storage, and retrieval of single ion excitation is further demonstrated, without perturbing the emission characteristics. These results promise new opportunities for controllable single-photon sources and efficient spin-photon interfaces.

42 ENGINEERING↗

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗

Elucidating and Mitigating High-Voltage Degradation Cascades in Cobalt-Free LiNiO 2 Lithium-Ion Battery Cathodes

LiNiO 2 (LNO) is a promising cathode material for next-generation Li-ion batteries due to its exceptionally high capacity and cobalt-free composition that enables more sustainable and ethical large-scale manufacturing. However, its poor cycle life at high operating voltages over 4.1 V impedes its practical use, thus motivating efforts to elucidate and mitigate LiNiO 2 degradation mechanisms at high states of charge. Here, a multiscale exploration of high-voltage degradation cascades associated with oxygen stacking chemistry in cobalt-free LiNiO 2 , is presented. In this work, lattice oxygen loss is found to play a critical role in the local O3–O1 stacking transition at high states of charge, which subsequently leads to Ni-ion migration and irreversible stacking faults during cycling. This undesirable atomic-scale structural evolution accelerates microscale electrochemical creep, cracking, and even bending of layers, ultimately resulting in macroscopic mechanical degradation of LNO particles. By employing a graphene-based hermetic surface coating, oxygen loss is attenuated in LNO at high states of charge, which suppresses the initiation of the degradation cascade and thus substantially improves the high-voltage capacity retention of LNO. Overall, this study provides mechanistic insight into the high-voltage degradation of LNO, which will inform ongoing efforts to employ cobalt-free cathodes in Li-ion battery technology.

25 ENERGY STORAGE↗

Spatial patterns of historical crop yields reveal soil health attributes in US Midwest fields

Abstract Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers’ fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ.

Fowler, Ames↗

Modeling Electrochemical and Rheological Characteristics of Suspension-Based Electrodes for Redox Flow Cells

Flowable suspension-based electrodes (FSEs) have gained attention in recent years, as the integration of solid materials into electrochemical flow cells can offer improved performance and flexible operation. However, under conditions that engender favorable electrochemical properties (e.g., high particle loading, high conductivity, high surface area), FSEs can exhibit non-Newtonian characteristics that impose large pumping losses and flow-dependent transport rates. These multifaceted trade-offs motivate the use of models to broadly explore scaling relationships and better understand design rules for electrochemical devices. To this end, we present a one-dimensional model, integrating porous electrode theory with FSE rheology as well as flow-dependent electron and mass transport under pressure-driven flow. We study FSE behavior as a function of material properties and operating conditions, identifying key dimensionless groups that describe the underlying physical processes. We assess flow cell performance by quantifying electrode polarization and relative pumping losses, establishing generalized property-performance relationships for FSEs. Importantly, we expound relevant operating regimes—based on a subset of dimensionless groups—that inform practical operating envelopes, ultimately helping to guide FSE and cell engineering for electrochemical systems.

25 ENERGY STORAGE↗

U.S. Department of Energy Free-Air CO 2 Enrichment Experiments: FACE Results, Lessons, and Legacy

In the 1970s, growing concern about potential long-range consequences of carbon dioxide (CO 2 ) emissions from the combustion of fossil fuels prompted the U.S. Department of Energy (DOE) to begin developing a CO 2 research program. The goal was to obtain the scientific information needed to reduce uncertainty and develop a knowledgebase for decision-making. At its start in 1980, this program had three components: the global carbon cycle, climate effects, and vegetation effects. The vegetation effects component recognized that increased atmospheric CO 2 could be a potential benefit to vegetation and crops because CO 2 is an essential resource for plant growth. In addition to increasing crop yield, program developers and researchers recognized that this fertilizer effect could also result in greater storage of fossil fuel CO 2 by forests. Initial experiments were small in scale and scope and focused on the photosynthesis, physiology, and water use of crop plants, but the focus shifted toward responses of plants in natural systems, as needed for connections to the global carbon cycle. Program research investigated CO 2 interactions with other environmental variables, emphasizing field research whenever possible and recognizing that exposure to elevated CO 2 concentrations under realistic field conditions should lead to better predictions of plant response. Whole-ecosystem field experiments were instituted in low-stature ecosystems, but experiments to address forest responses necessarily relied on tree seedlings or saplings in open-top chambers (OTCs) and not within intact forest ecosystems. The need for larger-scale, longer-duration experiments in each of the world’s six major biomes (tundra, boreal forest, temperate forest, tropical forest, grassland, and desert) became clear, and for these experiments, free-air CO 2 exposure facilities were necessary. This report summarizes the objectives and main results of DOE-sponsored experiments employing such facilities, along with the outcomes from research on ecosystem responses using field chambers (see Fig. ES.1, p. x). Additionally, this report highlights the many successes of DOE CO 2 enrichment studies and considers the lessons learned that can be used to guide future initiatives.

54 ENVIRONMENTAL SCIENCES↗

Los Alamos National Laboratory High Performance Computing Overview [Slides]

We need such big computers because without testing, we don't understand the health of the AGING stockpile. Our big computers store a wealth of test data. We model weapons as they were tested and see if we can match the results to validate models, and we then use validated models along with dismantlement information on aging to certify the stockpile. Sometimes the results of tests can’t be explained well, so even that part requires massive computations, but applying the model to future use is an astonishing amount of computing.

97 MATHEMATICS AND COMPUTING↗