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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 109 records · Page 6

Efficient Dimension Reduction of Complex Three-dimensional CO2 Saturation using Deep Learning Models

In the domain of deep learning (DL), dimension reduction is crucial for enhancing training efficiency and mitigating overfitting, particularly when managing complex data such as three-dimensional (3D) saturation data. The 3D saturation data in the context of geological carbon storage (GCS) presents unique challenges due to its inherent sparsity and the abrupt transitions at plume boundaries, known as shock fronts. To address the challenges, we proposed a novel DL framework that integrates dimension reduction with advanced 3D reconstruction techniques. Our model leveraged latent variables derived from 2D average saturation data, offering a robust and efficient solution tailored to the intricate dynamics of 3D saturation fields. The proposed framework can extract the critical features of the high-dimensional data while reducing the variable numbers, which is more tractable for DL models and enhances the model robustness and accuracy. Therefore, it provides a novel approach for modeling and analyses in complex geological scenarios, which finds great potential applications in environmental monitoring and energy storage.

Wang, Hongsheng↗

Stressful crystal histories recorded around melt inclusions in volcanic quartz

Abstract Magma ascent and eruption are driven by a set of internally and externally generated stresses that act upon the magma. We present microstructural maps around melt inclusions in quartz crystals from six large rhyolitic eruptions using synchrotron Laue X-ray microdiffraction to quantify elastic residual strain and stress. We measure plastic strain using average diffraction peak width and lattice misorientation, highlighting dislocations and subgrain boundaries. Quartz crystals across studied magma systems preserve similar and relatively small magnitudes of elastic residual stress (mean 53–135 MPa, median 46–116 MPa) in comparison to the strength of quartz (~ 10 GPa). However, the distribution of strain in the lattice around inclusions varies between samples. We hypothesize that dislocation and twin systems may be established during compaction of crystal-rich magma, which affects the magnitude and distribution of preserved elastic strains. Given the lack of stress-free haloes around faceted inclusions, we conclude that most residual strain and stress was imparted after inclusion faceting. Fragmentation may be one of the final strain events that superimposes stresses of ~ 100 MPa across all studied crystals. Overall, volcanic quartz crystals preserve complex, overprinted deformation textures indicating that quartz crystals have prolonged deformation histories throughout storage, fragmentation, and eruption.

58 GEOSCIENCES↗

An Efficient Checkpointing System for Large Machine Learning Model Training

As machine learning models increase in size and complexity rapidly, the cost of checkpointing in ML training became a bottleneck in storage and performance (time). For example, the latest GPT-4 model has massive parameters at the scale of 1.76 trillion. It is highly time and storage consuming to frequently writes the model to checkpoints with more than 1 trillion floating point values to storage. This work aims to understand and attempt to mitigate this problem. First, we characterize the checkpointing interface in a collection of representative large machine learning/language models with respect to storage consumption and performance overhead. Second, we propose the two optimizations: i) A periodic cleaning strategy that periodically cleans up outdated checkpoints to reduce the storage burden; ii) A data staging optimization that coordinates checkpoints between local and shared file systems for performance improvement.

machine learning, artificial intelligence↗

Perspective Chapter: Safe Disposal and Storage of Nuclear Waste

The use of nuclear energy inevitably generates nuclear waste as the byproduct of fission reactions. Depending on the initial composition of the fuel that goes into the reactor and the subsequent burn-up level, the chemistry of the resulting nuclear waste can vary substantially. This waste typically exhibits a broad spectrum of radioactivity and half-lives, making effective management one of the most critical challenges for global nuclear energy. This chapter provides a comprehensive overview of the origin and classification of nuclear waste and various strategies for its safe immobilization and disposal. The short- and long-term storage of waste with varying radioactivity is addressed. The significant technical and political complexities involving primarily long-term disposal are also discussed. To ensure the safe and permanent disposal of hazardous waste with extremely long half-lives, future efforts should focus on both technical innovation and public engagement.

36 MATERIALS SCIENCE↗

The Polarity of Co-solvents Regulates the Charge Storage Mechanisms in Supercapacitors with Concentrated Electrolytes

Developing better energy storage devices depends on comprehending the underlying mechanisms involved in charge storage. With the continuous conception of new electrolytes, this task becomes progressively more urgent and complex. An example is the utilization of co-solvated concentrated solutions. While these show promising electrochemical responses, their dynamic properties (especially under confinement) and their relationships with performance are not fully understood. Here, we combined modified step potential electrochemical spectroscopy and quasielastic neutron scattering to investigate systems composed of activated mesoporous carbon (AMC) and concentrated solutions of lithium bis(trifluoromethanesulfonyl)imide in acetonitrile co-solvated with either toluene or acetone. Further, we report that acetone does not impair surface-controlled mechanisms, contrary to the case with toluene, which competes with charged species to populate the AMC’s pores without contributing to charge storage. In turn, toluene promotes a greater overall capacitance owing to Faradaic processes, which may be related to changes in the solvation structures under confinement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing Suitable Geologic Carbon Storage Sites Across Utah

Utah has a wealth of potential geological reservoirs for carbon dioxide storage (CS) and a long history of geologic research resulting in an abundance of available subsurface data to evaluate CS potential. Reservoirs may include sandstone, carbonate, and basalt; these rock types are plentiful in Utah’s subsurface and the complex Phanerozoic history throughout the state requires evaluating each geologic region individually for promising reservoir-seal pairs for CO2 storage. Classifying Utah by geologic provinces (or “geo-regions”) allows for customized thinking about suitable CS reservoir and seal distribution, CO2 point sources, land use, and existing infrastructure. Preliminary results from this study highlight the geologic CS potential across 15 geo-regions. Four regions stand out as having high CS potential: the Uinta Basin, San Rafael Swell, Paradox Basin, and the southern Basin and Range Province. The Uinta Basin and San Rafael Swell geo-regions are well suited for CS and have several projects ongoing to evaluate Cretaceous Frontier and Naturita Formations, Jurassic Navajo Sandstone and Entrada Sandstone, and Permian Weber Sandstone reservoir units that lie beneath robust sealing units like the ~5000-ft-thick Mancos Shale and Carmel Formation. Reservoirs such as the Navajo and Weber Sandstones have been demonstrated to be suitable reservoirs through a long history of oil and gas exploration in Utah. New areas of interest include the southern Basin and Range in southwest Utah, where the Jurassic Navajo Sandstone is overlain by the sealing Carmel Formation at suitable depths (>3000 ft), and has good porosities based on outcrop analogue data. Just to the north (e.g., central Basin and Range), legacy wells and 2D seismic data show possible salt and subsurface basalt flows that may provide additional possible CS reservoirs and seals. This geo-region also has the advantage of being coupled with geothermal energy resources that may be used to power burgeoning direct air capture technologies. In the Paradox Basin of southeastern Utah, the Leadville Limestone is a potential storage reservoir beneath the thick (4000–5000 ft), salt-bearing Pennsylvanian Paradox Formation. Although the northern and western parts of Utah offer CS potential, these areas typically contain less infrastructure and subsurface penetrations, creating geologic uncertainty associated with subsurface seals and reservoirs due to a lack of data. Overall, this statewide assessment and ranking is the first step to aid in evaluating CS potential across Utah and provides a foundation for future research in the most favorable locations.

58 GEOSCIENCES↗

Hydromechanical Modeling of Fault Rupture in Geologic CO 2 Sequestration: A Comparison of Two Failure Criteria

Abstract The large‐scale implementation of geological carbon sequestration has raised concerns about potential fault activation and induced seismicity, which could compromise storage integrity and pose seismic risks. We theoretically compared two failure criteria, Mohr‐Coulomb (MC) and Modified Cam‐Clay criteria (MCC), to assess fault rupture during CO 2 storage. Both criteria characterize fault behavior in a specific stress regime but differ in reducing the complexity of fault rupture to a few key mechanisms. Using a coupled hydromechanical model, we demonstrate that the choice of a failure criterion and the physics of fault weakening associated with these criteria strongly condition fault response to a given fluid injection. MC mainly relates rupture to friction, while MCC relates rupture to fault poro‐plasticity. Our findings highlight that the selection of a failure criterion, being inherently subjective, can significantly alter the predicted fault behavior during CO 2 storage, thereby impacting the reliability of geomechanical risk assessments.

Cao, M. [Energy Geosciences Division Lawrence Berk↗

Beyond Price-Taker: Multiscale Optimization of Wind and Battery Integrated Energy Systems

Integrating renewable energy into the electric grid is challenging due to the intermittency and variability of wind and other non-dispatchable resources. Integrated energy systems (IESs) combine multiple energy technologies (e.g., fossil, nuclear, renewables, storage) to reduce costs and improve flexibility and reliability. However, standard techno-economic analysis (TEA) methods often overestimate the benefits of IESs because they fail to account for energy market adjustments. This paper systematically studies the limitations of the prevailing price-taker assumption for TEA and optimization of hybrid energy systems. As an illustrative case study, we retrofit an existing wind farm in the RTS-GMLC test system (which loosely mimics the Southwest U.S.) with battery energy storage to form an IES. We show that the standard price-taker model overestimates the electricity revenue and the net present value (NPV) of the IES up to 178% and 30.4%, respectively, compared to our more rigorous multiscale optimization. These differences arise because introducing storage creates a more flexible resource that impacts the larger wholesale electricity market. Moreover, this work highlights the impact of the IES has on the market via various strategic bidding, and underscores the importance of moving beyond price-taker for optimal storage sizing and TEA of IESs. We conclude by discussing opportunities to generalize the proposed framework to other IESs, and highlight emerging research questions regarding the complex interactions between IESs and markets.

25 ENERGY STORAGE↗

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗

Quantifying the Reactivity of Isolated Li x Si Domains in Si Anodes Using Operando NMR

The use of Si anodes can greatly improve the energy density of Li-ion batteries. However, understanding and mitigation of calendar aging remains a barrier to commercialization. Here, in this short report, we utilize operando Nuclear Magnetic Resonance (NMR) spectroscopy to detect and quantify lithium silicides (Li x Si) as they form and react within Si anodes in pouch cells during calendar aging. We provide direct experimental evidence of complex aging phenomena in the Si anodes, including both SEI growth and dissolution during storage. Formation of electrochemically isolated Li x Si is also observed, as indicated by the partial persistence of highly lithiated phases after the cell is discharged. Remarkably, we show that these isolated domains can themselves self-discharge over time, suggesting that their detection can be challenging in post-mortem studies. Finally, we show that aging outcomes depend heavily on the type of silicon particles contained within the electrode, and that certain surface coatings can help decrease the reactivity between lithium silicides and the electrolyte.

Li-ion battery↗

Unravelling electro-chemo-mechanical interplay in layered oxide cathode degradation in solid-state batteries

Solid-state batteries (SSBs) hold notable promise for advancing energy storage technologies. However, their commercial viability is limited by the poor cycle stability and complex degradation mechanism. This study underscores the pivotal role of electro-chemo-mechanical interactions in driving the failure of SSBs. Leveraging advanced x-ray imaging and spectroscopy techniques, we analyzed LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes from cycled Li x In||Li 6 PS 5 Cl (LPSC)||NMC811 SSBs, uncovering the interplay between microstructure, chemical heterogeneity, mechanical characteristics, and electrochemical performance. Our results show that revealing electro-chemo-mechanical interactions is essential to develop strategies to suppress the degradation of SSBs. Particularly, we revisit a LiNbO 3 (LNO) coating layer to mitigate electrochemical degradation. The LNO@NMC811 cathode retains 116 milliampere-hours per gram after 200 cycles, showing excellent stability, while the uncoated NMC811 cathode keeps degrading over time, with suppressed chemical heterogeneity and mechanical failure. This work highlights the importance of synergizing advanced material design with coating techniques, ensuring uniform lithium flux and improving mechanical properties to achieve stable, high-performance SSBs.

Zheng, Xueli [SLAC National Accelerator Laboratory↗

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗

Design study of a low emittance complex bend achromat lattice

Light sources worldwide have experienced rapid growth in the last decades, pushing toward higher brightness with lower emittance to meet growing demands from the user community. The quest for higher brightness motivates the development of low-emittance ring lattices. At this point, all fourth-generation storage ring light sources employ variations of the multibend achromat (MBA) lattice. In this paper, we discuss an extension of this approach, known as complex bend achromat lattice in relation to the future NSLS-II upgrade. A detailed approach for the lattice design will be described and the developed lattice will be presented. The advantages of using our complex bend approach are evident in reaching a natural emittance as low as 23 pm at a beam energy of 3 GeV, providing a straight section of 8.4 m for long insertion devices, and acquiring a ratio of about 50% of free space with respect to the ring circumference. The design includes the use of permanent magnets largely reducing the need for power supplies. Our new approach provides an extension to the MBA concept for the next-generation light source lattice design. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Thermodynamic Modeling of Complex Solid Solutions in the Lu-H-N System via Graph Neural Network Accelerated Monte Carlo Simulations

Metal hydrides are important across diverse applications, such as hydrogen storage, batteries, gas sensors, nuclear reactions, and high-temperature superconductivity. Previous computational studies of metal hydrides under extreme pressures, e.g., 𝑂⁡(10 2 ) ⁢GPa, usually treat them as stoichiometric compounds without considering interstitial lattice disorder. As pressures become more moderate in the 𝑂⁡(10 0 ) ⁢GPa and below range, hydrogen disorder at interstitial lattice sites becomes prominent, e.g., in the N-doped Lu hydride that was recently claimed superconducting near 1 GPa. Further adding compositional complexity from alloying and/or multielement interstitial occupation makes elucidating pressure- and temperature-dependent observables intractable by first-principles calculations alone. We therefore propose a lattice graph neural-network surrogate modeling approach to predict configuration- and pressure-dependent equation-of-state properties. Their efficiency permits Monte Carlo simulations to calculate Gibbs energies and pressure-dependent phase diagrams, thereby revealing insights into the synthesis conditions required for achieving desired phase equilibria. We demonstrate this concept for the compositionally complex cubic Lu(H,N,Va) 3 system where three constituents (hydrogen, nitrogen and vacancy) have disordered multielement interstitial occupancies and insights into pressure-dependent phase equilibria are critically needed, e.g., N-doping levels can significantly lower dehydrogenation temperatures and provide a new strategy to optimize hydrogen-storage alloys. This work can improve the thermodynamic understanding of the Lu-H-N system and help rational synthesis of N-doped Lu hydrides, but more generally demonstrates an efficient approach to model pressure-dependent thermodynamics of multicomponent solid solutions.

Monte Carlo methods↗

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗

Soft X-ray Emission Spectroscopy of Phosphorus Compounds for Energy Conversion and Storage

Phosphorus (P) is a ubiquitous component of materials for energy conversion and storage. Despite the effectiveness of soft X-ray emission spectroscopy (XES) to characterize these complex materials, XES studies of P-containing compounds are still largely missing. In this investigation, the electronic structure and XES signatures from the P L 2,3 -edge are probed for nine solid-state P-containing compounds characterized by various oxidation states and chemical environments: GaP (3−) , InP (3−) , red-P (0) , H 3 P (3+) O 3 , Na 2 H 2 P 2 (4+) O 6 , H 3 P (5+) O 4 , KH 2 P (5+) O 4 , Na 2 HP (5+) O 4 , and InP (5+) O 4 . The XES spectrum of each material exhibits distinct spectral fingerprints, which provide a robust basis for the speciation of complex P-containing samples. Density functional theory calculations shed light on the electronic structure of selected materials and particularly on the effect of phosphorus-oxygen hybridization. This study provides a comprehensive understanding of P L 2,3 XES spectral fingerprints across a wide range of oxidation states and chemical environments. These data sets and insights pave the way for dedicated future work, such as in situ and operando investigations of P-containing compounds in energy-related applications, where speciation of P compounds is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-Heating Conductive Ceramic Composites for High Temperature Thermal Energy Storage

The absence of affordable and deployable large-scale energy storage poses a major barrier to providing zero-emission energy on demand for societal decarbonization. High temperature thermal energy storage is one promising option with low cost and high scalability, but it is hindered by the inherent complexity of simultaneously satisfying all of the material requirements. Here we design a class of ceramic–carbon composites based on co-optimizing mechanical, electrical, and thermal properties. Further, these composites demonstrate stability in soak-and-hold tests and direct self-heating up to 1,936 °C and 750 thermal cycles from 500 to 1,630 °C without degradation. This thermal performance derives from their composition and microstructural design as verified by in situ high-temperature transmission electron microscopy and X-ray diffraction. They offer both higher energy density and lower cost than conventional storage technologies with a projected system Levelized Cost of Storage below the U.S. Department of Energy’s 2030 target 5 ¢/kWh (electric).

25 ENERGY STORAGE↗

Soft interface instability and gas flow channeling in low-permeability deformable media

Understanding gas percolation through a clay layer or a shale formation is of great importance for the development of a geologic repository for nuclear waste disposal, a subsurface system for gas storage, and an engineering approach for hydrocarbon extraction from unconventional reservoirs. Gas injection experiments have revealed complex dynamic behaviours of gas percolation through water saturated compacted bentonite, characterized by a high breakthrough pressure, rapid breakthrough, a pressure/stress decay after the breakthrough, a relatively high migration rate, high-frequency periodic/nonperiodic variations in flow rate, stepwise rate reductions during relaxation, and low gas saturation over the whole process, all indicating channelling nature of the processes. Using linear stability analyses, we show that this channelling can autonomously emerge from the instability of the deformable interface between the injected gas and the compacted bentonite matrix driven by local stress concentration, pore dilation, and hydrologic gradient. Channel patterns formed would possess a fractal geometry. We further show that, once a percolating channel is established, the gas injected would percolate through the channel in a chain of gas bubbles, also due to the interface instability, resulting in periodic/chaotic variations in gas flow rate. Our work provides a unified explanation for key features observed for gas percolation in low-permeability deformable media. The work also suggests a possibility of designing an engineered barrier system for a nuclear waste repository that can have controllable gas release while limit water transport.

Bentonite↗