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At least 379 records · Page 21

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DOE OSTI2025

Implementing Large-Scale CCS in Complex Geologic Reservoirs: Insights from Three Appalachian Basin Case Studies

This paper presents three design case studies for implementing large-scale geologic carbon storage in the Appalachian Basin region of the midwestern United States. While the Appalachian Basin has a challenging setting for carbon storage, the three case studies detailed in this article demonstrate that there are realistic options for implementing carbon storage in the basin. Carbonate rock formations, depleted hydrocarbon reservoirs, and moderate-porosity sandstones can be utilized as carbon-storage reservoirs in the Appalachian Basin. While these are not typical concepts for CO2 storage, the storage zones have advantages such as defined trapping mechanisms, multiple caprocks, and defined boundaries that are not always present in thick, permeable sandstones being targeted for many carbon-storage projects. The geologic setting, geotechnical parameters, and hydrologic setting for the three case studies are provided, along with the results of reservoir simulations of the CO2 injection-deployment strategies. The geological rock formations available for CO2 storage in the Appalachian Basin are more localized reservoirs with defined boundaries and finite storage capacities. Simulation results showed that accessing carbon-storage resources in these fields may require wellfields with 2–10 injection wells. However, these fields would have the capacity to inject 1–3 million metric tons of CO2 per year and up to 90 million metric tons of CO2 in total. The CO2 storage resources would fulfill decarbonization goals for many of the natural-gas power plants, cement plants, hydrogen plants, and refineries in the Appalachian Basin region.

Sminchak, Joel↗

DOE OSTI2024

Adoption of ROOT RNTuple for the next main event data storage technology in the ATLAS production framework Athena

Since the start of LHC in 2008, the ATLAS experiment has relied on ROOT to provide storage technology for all its processed event data. Internally, ROOT files are organized around TTree structures that are capable of storing complex C++ objects. The capabilities of TTrees developed over the years and are now offering support for advanced concepts like polymorphism, schema evolution and user defined collections and ATLAS makes use of these features to handle its EDM. But some original TTrees concepts, like the POSIX file model and sequential writing, remain unchanged since the beginning and could be an obstacle to achieving the performance required for High Luminosity LHC. With the HL-LHC performance goals in mind, the ROOT project developed a new storage format - the RNTuple. RNTuple, with its accompanying user API, is now in the final development stage and is planned to be production-ready at the end of 2024. Soon after that, the TTree will become a legacy format. ATLAS intends to have its main Event processing framework Athena ready to use RNTuple in the production environment as early as possible. The work on adopting RNTuple as another ROOT storage technology in Athena started already in 2021 and is now nearly complete. Although the initial goal was to focus on derived-AOD products (PHYS and PHYSLITE), with a little added effort all ATLAS data products: RDO, HITS, ESD, AOD and DAOD can be now stored in RNTuple format and transparently read back. In this paper we will describe the current state of RNTuple adoption in the Athena framework and explain the ATLAS EDM requirements that had to be met on the ROOT side to successfully integrate both environments. We will demonstrate the ability to run standard ATLAS production workflows, based on RNTuple as the Event data storage technology, and point out key advantages of the new format.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Quantum computing and quantum information storage

Quantum storage, transmission, and processing is the future of information technology. Here, the promise of quantum hardware stems from the inherent complexity of an entangled quantum system—the size of the wave-function scales exponentially with the number of particles, whether represented in real space or in a parameter space. In contrast, a classical N-body system can be completely represented by only 6N variables (positions and momenta of all particles). This complexity of quantum systems creates a yet-unsolved challenge of modeling quantum systems by means of classical computing—the curse of dimensionality. Indeed, although we can easily write the Schrödinger equation for any system of interacting nuclei and electrons, we can only solve it exactly on classical computers for very small systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Subvoxel Control of Fiber Orientation via Multidirectional Shearing in 3D Printing

Anisotropy, the characteristic of materials exhibiting different properties based on their direction, is widespread in nature. Conventional manufacturing techniques often fall short in recreating such complex anisotropy. While 3D printing allows for precise fiber deposition in anisotropic composites, previous studies have only achieved bulk reorientation of fibers at the voxel level in two dimensions. This limits the replication of localized 3D anisotropies found in natural materials. To address this, a novel 3D printing technique is presented that enables subvoxel control of fiber orientation in all three directions using multidirectional shearing via nozzle rotation and inclination. The fiber orientation control in these experimental tests is driven by a numerical model, enabling a fully digital approach to program microstructures within a strand. This programmability is demonstrated through mechanical and thermal tests, illustrating a localized and controllable response to external stimuli. Achieving such complex anisotropy holds potential across several fields, including wearables and biomedical implants, lightweight composite structures, and energy storage technologies such as batteries and supercapacitors.

3D printing↗

DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

United States Nuclear Power Reactor Used Nuclear Fuel Database and Applications

The Unified Database (UDB) within STANDARDS serves as the foundational data infrastructure for managing the United States' spent nuclear fuel inventory of 315,111 discharged assemblies totaling 91,036 metric tons of heavy metal. The database organizes this complex inventory through over 200 interconnected tables structured into eight primary attribute categories, supporting integrated analyses across storage, transportation, and disposal domains. Data enters the UDB through the GC-859 Nuclear Fuel Data Survey, which transitioned to web-based collection in 2023, improving data quality through real-time validation. The UDB enables automated generation of input files for nuclear safety analyses, reducing preparation time from weeks to hours while maintaining traceability. Applications include national inventory reporting, Certificate of Compliance assessments, and facility optimization. The three-tier distribution model balances accessibility with security requirements for federal agencies, national laboratories, and research organizations. The UDB provides essential data infrastructure as spent fuel management transitions from site-specific to integrated national campaigns.

Stefanovic, Peter↗

DOE OSTI2023

Progress Report on Model Development for Aerosol Transport through Divergent Cracks Paths

This report summarizes the progress in developing a phenomenological model of aerosol transport, deposition, and plugging through microchannels. The purpose of this effort is to introduce to a user community—involving researchers, regulators, and industry—a generic, reliable numerical model for the prediction of aerosol transport while accounting for potential deposition and plugging of the leak paths to model spent nuclear fuel (SNF) release from postulated Stress Corrosion Cracks in canisters under storage or transportation. Current work focuses on expanding the model to predict aerosol (and gas) flow through complex microchannel (nozzle) geometries in addition to the rectangular and cylindrical geometries, as we approach more realistic Stress Corrosion Crack conditions. In this regard, a divergent nozzle geometry, used at Sandia National Laboratories (SNL) for testing aerosol release and retention (Durbin et al. 2021), was added to the model. The model was then validated with blowdown data for the particular microchannel, from experiments conducted at SNL. The report also presents preliminary non-benchmarked aerosol penetration fraction and mass flow rate for a monodisperse 10-micron (AED) particle concentration of 1.7e-08 kg/m 3 being released through the divergent microchannel geometry from the SNL’s aerosol experimental tank setup.Future work will involve validating the aerosol model and updating the model’s Graphical User Interface (GUI) to include the divergent nozzle geometry. This is expected to help stakeholders perform quick and easy first principles calculations without needing to understand the underlying MATLAB script.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Additive manufacturing of LiNi 1/3 Mn 1/3 Co 1/3 O 2 battery electrode material via vat photopolymerization precursor approach

Additive manufacturing, also called 3D printing, has the potential to enable the development of flexible, wearable and customizable batteries of any shape, maximizing energy storage while also reducing dead-weight and volume. In this work, for the first time, three-dimensional complex electrode structures of high-energy density LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC 111) material are developed by means of a vat photopolymerization (VPP) process combined with an innovative precursor approach. This innovative approach involves the solubilization of metal precursor salts into a UV-photopolymerizable resin, so that detrimental light scattering and increased viscosity are minimized, followed by the in-situ synthesis of NMC 111 during thermal post-processing of the printed item. The absence of solid particles within the initial resin allows the production of smaller printed features that are crucial for 3D battery design. The formulation of the UV-photopolymerizable composite resin and 3D printing of complex structures, followed by an optimization of the thermal post-processing yielding NMC 111 is thoroughly described in this study. Based on these results, this work addresses one of the key aspects for 3D printed batteries via a precursor approach: the need for a compromise between electrochemical and mechanical performance in order to obtain fully functional 3D printed electrodes. In addition, it discusses the gaps that limit the multi-material 3D printing of batteries via the VPP process.

25 ENERGY STORAGE↗

DOE OSTI2024

Nuclear Fuel and Pu Redox Studies from The Glenn T. Seaborg Institute at Idaho National Laboratory

The Glenn T. Seaborg Institute at Idaho National Laboratory (INL-GTSI) focuses on advancing fundamental research in the actinide sciences by providing unique opportunities to early career scientists and engineers to gain experience studying the actinide elements and their associated systems. The INL-GTSI is built from three focus areas that are based on the expertise and supporting infrastructure at INL and include solid state chemistry and physics, solution phase chemistry and physics, and forensic and isotope science. INL is the lead Laboratory for nuclear energy research and development in the U. S. and the research on nuclear fuels performed under the INL-GTSI gives good examples of solid state studies. Uranium-Molybdenum (U-Mo) alloys are leading fuel candidates for conversion of high performance research and test reactors to low-enriched fuels. During irradiation, generated fission gas accumulates into bubbles and self-organizes into a gas bubble superlattice (GBS) that effectively stores fission gases and inhibits fuel swelling. A study on the early self- organizing behavior of the GBS shows that not only grain boundaries but the interfaces between the U-Mo matrix and uranium carbide (UC) impurities are important to GBS formation.[1] In solution, understanding the complex redox behavior of plutonium in aqueous environments is critical for establishing optimized nuclear waste reprocessing solvent systems and storage tank environments. INL-GTSI researchers have produced an experimentally validated multi-scale model of the gamma radiation induced behavior of plutonium ions in concentrated aqueous HNO3 solutions.[2] Here, gamma radiation effected only minimal steady state changes in the redox distribution of the plutonium oxidation states. The redox cycling between Pu(IV) and Pu(III) is demonstrated to be mediated by the •OH/NO3• radical oxidation of Pu(III) and the H2O2/HNO3 driven reduction of Pu(IV). The INL-GTSI offers young researchers the unique chance to work directly with actinide bearing materials in a U. S. National Laboratory environment. Further topical areas of interest to the INL-GTSI include, but are not limited to, fundamental actinide properties, structure/property (electronic, magnetic, thermal) relations, actinide quantum criticality, f- electron interactions, electron correlations, computational studies, new phases, defect effects, interface interactions, isotope production and separation, forensic analytical chemistry, structure and dynamic properties of actinides in non-aqueous media, separations chemistry and kinetics for advanced nuclear fuel cycles, radiation effects, and innovative and advanced ligand design for complexation of the actinides.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

A History of Hanford Tank Waste, Implications for Waste Treatment and Disposal

More than 40 years of plutonium processing have left almost 56 million gallons of mixed radioactive waste sequestered in 177 underground tanks on the Hanford Site. Three different processing technologies were employed for plutonium purification in addition to uranium scavenging and fission product removal from the tank waste. All of these chemical processes have contributed to a complex waste stream that varies from tank to tank that presents downstream processing challenges to render the waste into a safe form for long-term storage. The current disposition pathway for Hanford tank waste is vitrification. To maximize waste loading and minimize the number of high-level waste canisters stored in a geologic repository, pretreatment of the waste is required. Both pretreatment and vitrification operations are impacted by the waste composition.

Separations, filtration, ion exchange↗

DOE OSTI2025

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format

Advances in mass spectrometry (MS) instrumentation, such as higher resolution, faster scan speeds, and improved sensitivity, have significantly increased the volume and complexity of data. The growing adoption of imaging and ion mobility further amplifies these challenges across MS-based omics fields, including proteomics, metabolomics, and lipidomics. While these technologies unlock new possibilities, they also present significant challenges in data management, storage, and accessibility. Existing open formats, such as the XML-based community standards mzML and imzML, struggle to meet the demands of modern MS workflows due to their large file sizes, slow data access, and limited metadata support. Vendor-specific formats, while optimized for proprietary instruments, lack interoperability, comprehensive metadata support and long-term archival reliability. This white paper lays the groundwork for mzPeak, a next-generation community data format designed to address these challenges and support high-throughput, multi-dimensional MS workflows. By adopting a hybrid model that combines efficient binary storage for numerical data and both human and machine-readable metadata storage, mzPeak will reduce file sizes, accelerate data access, and offer a scalable, adaptable solution for evolving MS technologies. For researchers, mzPeak will enable enhanced interoperability across platforms, seamless support for complex workflows including ion mobility and MS imaging, and faster data access compared to existing community formats such as mzML. Its design will ensure data is managed in compliance with regulatory standards, essential for applications such as precision medicine and chemical safety, where long-term data integrity and accessibility are critical. For vendors, mzPeak provides a streamlined, open alternative to proprietary formats, reducing the burden of regulatory compliance while aligning with the industry's push for transparency and standardization. By offering a high-performance, interoperable solution, mzPeak positions vendors to meet customer demands for sustainable data management tools which will be able to handle emerging and future data types and workflows. mzPeak aspires to become the cornerstone of MS data management, empowering researchers, vendors, and developers to innovate and collaborate more effectively.

data formats↗

DOE OSTI2023

Annual report for DOE VTO

Carbon fiber (CF)/polymer composites are a transformative class of high-performance, lightweight material, where high aspect-ratio CFs reinforce a polymer matrix and exceed the strength of steel alloys at a fraction of the density. Despite the advantages of such a class of material, the broader implementation of CF composites in a range of automotive, aerospace, and energy applications is hindered by limitations of current manufacturing methods. These current techniques (e.g., hand lay-up, wet filament winding) are costly and impose severe limitations on fiber placement, orientation, and angle, and thus a composite’s ultimate properties. Today’s CF composites are expensive to manufacture, limited in form factor, and utilize costly and sub-optimal continuous filament CF. Advanced additive manufacturing (AM) processes, combined with computational design optimization and new approaches to resin development, offer alternative design and manufacturing paradigms that have the realistic potential to lift these constraints. Such integrated AM approaches could thus help to realize the full potential of CF composite materials. One relevant application of CF composite materials where manufacturing constraints limit the cost-benefit ratio is in the manufacture of high-performance composite pressure vessels for onboard compressed natural gas (CNG) storage. Current CNG storage vessels (Types 3–5) are made from load-bearing filament-wound carbon-fiber composite and are ~3.5 times as expensive as an all-metallic Type-1 vessel. This cost is invariably tied to the complex and labor-intensive nature of conventional filament winding processes and the large volumes of expensive high tensile-strength CF tow feedstock required in manufacture. Our proposed approach to CNG storage vessel manufacture is based on a combination of AM technologies for CF composite printing and design optimization tools that were pioneered at Lawrence Livermore National Laboratory (LLNL), with advances in resin/composite formulation enabled by chemical and nano-material modification. Through the successful development of this technology, LLNL seeks to demonstrate the capability for advanced CNG storage vessel manufacture at reduced cost with no reduction in performance versus the most advanced, extant Type-5 designs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Microwave-Assisted Preparation of Luminescent Inorganic Materials: A Fast Route to Light Conversion and Storage Phosphors

Luminescent inorganic materials are used in several technological applications such as light-emitting displays, white LEDs for illumination, bioimaging, and photodynamic therapy. Usually, inorganic phosphors (e.g., complex oxides, silicates) need high temperatures and, in some cases, specific atmospheres to be formed or to obtain a homogeneous composition. Low ionic diffusion and high melting points of the precursors lead to long processing times in these solid-state syntheses with a cost in energy consumption when conventional heating methods are applied. Microwave-assisted synthesis relies on selective, volumetric heating attributed to the electromagnetic radiation interaction with the matter. The microwave heating allows for rapid heating rates and small temperature gradients yielding homogeneous, well-formed materials swiftly. Luminescent inorganic materials can benefit significantly from the microwave-assisted synthesis for high homogeneity, diverse morphology, and rapid screening of different compositions. The rapid screening allows for fast material investigation, whereas the benefits of enhanced homogeneity include improvement in the optical properties such as quantum yields and storage capacity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Tailoring the Mass Transport to Achieve High-Performing Unitized Regenerative Fuel Cells Considering Practical Operating Conditions

Unitized regenerative fuel cells (URFCs) convert electrical energy to chemical bonds in hydrogen during charge and convert chemical energy to output electricity during discharge, offering a promising solution to long-term energy storage. Recent studies indicate that the round-trip-voltaic efficiency (RTE) and longevity of URFCs are limited by complex mass transport during charging and discharging. Here, we first investigate how different porous transport layer (PTL) structures can impact URFC performance. The preferred PTL has a low tortuosity and high porosity, leading to a high RTE above 50% at 1 A cm −2 using Nafion 212. Moreover, thicker membranes, such as Solvay 90, are required to ensure mechanical stability and minimize H 2 crossover when operating under high differential pressure. Although this assembly inevitably leads to a higher ohmic loss, the RTE can be improved by further tailoring the electrode structures to facilitate mass transport by using supported catalyst, which still achieves over 50% RTEs at 1 A cm −2 . Optimization of porous structure to mitigate mass transport resistance with appropriate materials down selection considering practical application requirements can be a key design principle for achieving high-performing URFCs.

25 ENERGY STORAGE↗

DOE OSTI2020

Dual Purpose Canister Reactivity and Groundwater Absorption Analyses

The current spent nuclear fuel (SNF) management strategy includes reliance on dry storage. Utilities are meeting their interim storage needs on an individual basis with use of large-capacity dry storage casks, with a current focus on meeting existing storage and transportation requirements, as disposal requirements are not currently available. These casks are commonly known as dual-purpose (i.e., storage and transportation) canisters (DPCs). However, a small percentage of single-purpose (storage only) systems is also being used to meet storage needs. These are included under the “DPC” heading. This report investigates the postclosure criticality safety aspects of DPCs. Placing large, heavy waste packages containing DPCs into a repository for direct disposal has not yet been implemented domestically or internationally. Therefore, direct disposal of DPCs represents new engineering and scientific challenges. Some of the engineering challenges that have already been addressed include handling and placement, use of ramps vs. shafts, use of hoists, use of transport equipment, and thermal management. Additionally, some studies have been conducted in the past regarding the feasibility of direct disposal from a criticality analysis perspective and have concluded that while possible, demonstrating subcriticality over the disposal time period is a challenge. The alternative to direct disposal of DPCs into a repository is to repackage the SNF into different canisters. The direct disposal of DPCs without cutting them open and repackaging is appealing because it could be more cost-effective, reduce the complexity of fuel management operations both in and outside reactor facilities, and result in less cumulative worker dose during interim storage and handling before eventual disposal in a deep geologic repository.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Dual Purpose Canister Reactivity and Groundwater Absorption Analyses

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Fetch-trap Pairs: Exploring definition of carbon storage prospects to increase capacity and flexibility in areas with competing uses

As CCS grows beyond isolated first-mover projects, the question of how to identify potential storage sites (prospects) is key to siting projects amidst the constraints of neighboring storage projects, hydrocarbon fields and other considerations. To date, prospects have been defined either by the extent of a buoyant trap or by the predicted maximum extent of the CO 2 or pressure plume. Both approaches have worked, but they may struggle in places like the Gulf of Mexico where complex geologic structure can invalidate simple assumptions of radial plume spread and buoyant traps are commonly unattractive due to numerous legacy well penetrations. Here, we propose identifying prospective storage sites by fetch area (drainage cell) rather than by buoyant closure alone. Doing so offers 1) greater freedom in siting injectors to avoid surface and subsurface constraints, including legacy wells that tend to cluster on structural high; and 2) a coherent flow regime in which buoyancy drives all injected CO 2 toward a common high. This strategy gives space to dissipate injection pressure and minimize the number of legacy wells needing review. It may also offer 1) better injectivity by bringing synclines and associated channel axes into play; and 2) potentially improved capacity by tapping a larger rock volume and taking advantage of migration losses.

58 GEOSCIENCES↗

DOE OSTI2022

Battery calendar aging and machine learning

Batteries continue to attract immense attention due to the critical need for new energy technologies that can help humankind transition to a net-zero future. To meet global goals for implementation of new batteries, the research community needs to more coherently consider how to go about the process of innovation, development, and validation of new technologies. Current practices for bringing a new battery technology from the benchtop to deployment can be very time consuming and complex, given that batteries can have distinct aging pathways based on both how they are cycled and their storage conditions. In nearly all use cases, batteries experience periods of active cycling and also extended periods of rest. Thus, calendar time often occurs when a battery is close to fully charged. Currently, the combined cycle and calendar life aspects receive inconsistent attention during most stages of research and development. For batteries to fulfill the critical role envisioned to meet global energy demands, greater uniformity in practice is needed to alleviate potential delays caused by the inconsistent acquisition of aging data. In this study, we present our thoughts and recommendations on the need to further advance commonality and availability of calendar aging data for emerging high-energy and long-duration batteries. While there is a broad need to adopt best practices for both calendar and cycle life assessment, a push to greater uniformity in approach and reporting is sorely needed to allow calendar life predictions to harness many of the advances that have recently been seen for cycle life prediction using machine learning (ML) and other techniques.

25 ENERGY STORAGE↗