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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evaluation of Material Balance Approaches for Hanford Direct-Feed Low Activity Waste Processing - 20022

The Hanford Site has accumulated millions of gallons of tank waste from reprocessing spent fuel to recover plutonium, uranium, cesium, and strontium. The supernatant from the accumulated tank waste will be treated using a Direct Feed Low-Activity Waste approach. The supernatant will be treated to remove solids and cesium in the Tank-Side Cesium Removal process in the Hanford tank farm, then vitrified in a semi-batch process in the Hanford Waste Treatment and Immobilization Plant (WTP). Currently, each batch of feed is sampled at three locations prior to being fed to the melter: the feed qualification tank in the Hanford tank farm as well as the concentrate receipt vessel (CRV) and melter feed preparation vessel (MFPV) in the WTP. The feed qualification sample is taken from a large batch of accumulated feed, only two to three samples are expected each year. Approximately 275 samples from the CRVs and 1100 samples from the MFPV are expected each year. An evaluation was performed to determine if a material balance based on the feed qualification sample could replace most of the sampling in the CRVs and MFPVs. The evaluation consisted of three elements: (1) determination of the practicality of using a material balance to estimate the stream composition of the CRV and MFPV contents, (2) evaluation of whether the material balance could be automated using the existing process control system, and (3) determination of the uncertainty in glass composition using the material balance approach. It is assumed that periodic sampling at the CRV and MFPV would be performed periodically to re-baseline the material balance, evaluations are in progress to determine the frequency of this periodic sampling. Process sample locations downstream of the melter were reviewed as well, but the partitioning of semi-volatile species in the melter was determined to preclude extending the material balance approach past the melter. It was determined that replacement of the CRV sample location was feasible and did not increase process uncertainty or significantly impact waste loading. Replacement of the MFPV sample was also determined to be feasible, but that measurement of the glass former chemical addition may be needed prior to addition of these chemicals to the MFPV. This measurement could be performed by an in situ laser-induced breakdown spectroscopy (LIBS) system. Limited tests were performed to evaluate LIBS for direct measurements of the low-activity waste melter feed. The use of a material balance would eliminate over 1200 samples each year if only 10% of the CRV and MFPV batches are sampled and could likely allow the WTP laboratory to operate on days only versus 24/7 operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗
DOE OSTI2026

Thermo-hydro-mechanical analysis of subsurface ice-based thermal energy storage

Ice-based thermal energy storage systems are widely utilized for cooling and managing peak electrical demand globally, offering daily or weekly storage capabilities for both individual homes and larger office buildings. However, scaling these systems for district-level cooling or integrating them with renewable energy sources presents challenges, especially in accommodating larger volumes and addressing seasonal storage requirements in densely populated urban areas. This paper proposes a novel solution by evaluating subsurface ice-based thermal energy storage, in which the underground is subjected to seasonal freeze/thaw cycles. However, these cycles may influence ground behavior, affecting pore pressure and inducing ground movement. To systematically investigate these challenges, we enhance the TOUGH-FLAC simulator by integrating water/ice phase change capabilities and updating the effective stress–strain constitutive relation. Both modifications are validated against analytical solutions or experimental data. Through numerical simulations spanning a decade with ten seasonal freeze/thaw cycles, we evaluate the performance and long-term stability of a generic subsurface ice-based thermal energy storage system, considering factors such as ground permeability, freezing pipe spacing, freeze/thaw damage, and glycol solution temperature. The simulations indicate that ice formation induces pore pressure variations that drive seasonal surface heave and settlement, controlled by ground permeability, pipe spacing, and glycol solution temperature, along with tensile and localized shear deformation around freeze pipes. This highlights the need for accurate ground property characterization and geomechanical analysis for subsurface ice-based thermal energy storage.

Ground freezing↗
DOE OSTI2025

Unveiling the Hidden Evolution of Crystal Defects and Disorder in Energy Materials

Control of point defects and disorder in functional thin films and 2D materials is critical to realizing their full potential in applications ranging from energy storage to advanced electronics. However, these phenomena are often poorly understood, difficult to characterize, and challenging to direct with precision. This presentation explores emerging multi-modal computer vision to decipher and predict order in materials across multiple length scales in the electron microscope, from the atomic to the nanoscale. By fusing data from diverse sources, these powerful models provide unprecedented insights into materials' lifecycles, enabling the control of defects and their associated properties at a fundamental level. This capability promises to transform materials design and accelerate the development of next-generation technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Design, modeling and simulation of nuclear-powered integrated energy systems with cascaded heating applications

Nuclear-renewable integrated energy systems (IES) consist of a variety of energy generation and conversion technologies and can be used to meet heterogeneous end uses (e.g., electricity, heat, and cooling demands). In addition to supply-demand balance, end-use heat demands usually require heat supply of certain temperature ranges. The effective and efficient utilization of heat produced within an IES is, therefore, a critical challenge. Here, this paper examines design options of an IES that includes heating processes of multiple temperature grades. We investigate a cascaded design configuration, where the remaining residual heat after high-grade heating processes [e.g., hydrogen production through high-temperature steam electrolysis (HTSE)] is recovered to meet the low-grade heating needs [e.g., district heating (DH)]. Additionally, a thermal energy storage system is integrated into the DH system to address the imbalance between heat supply and demand. This paper primarily focuses on the design and modeling of the proposed system and evaluates its operation with a 24-h transient process simulation using a DH demand profile with hourly resolution. The results indicate that the residual heat from the HTSE exhaust is insufficient for the DH demand, and additional topping heat directly from the reactor process steam is needed. Furthermore, the inclusion of thermal energy storage within the DH system provides the necessary balance between thermal generation and demand, thereby ensuring a consistent rated temperature of the DH supply water. This approach helps minimize the control actions needed on the reactor side.

08 HYDROGEN↗
DOE OSTI2024

Multivariate prognosis of battery advanced state of health via transformers

De-risking energy storage investments necessary to meet CO 2 reduction targets requires a deep understanding of the connections between battery health, design, and use. The historical definition of the battery state of health (SOH) as the percentage of current versus initial capacity is inadequate for this purpose, motivating an expanded SOH consisting of an interrelated set of descriptors including capacity, energy, ionic and electronic impedances, open-circuit voltages, and microstructure metrics. In this work, we introduce deep transformer networks for the simultaneous prognosis of 28 battery SOH descriptors using two cycling datasets representing six lithium-ion cathode chemistries, multiple electrolyte/anode compositions, and different charge-discharge scenarios. The accuracy of these predictions for battery life (with an unprecedented mean absolute error of 19 cycles in predicting end of life for a lithium-iron-phosphate fast-charging dataset) illustrates the promise of deep learning toward providing enhanced understanding and control of battery health.

25 ENERGY STORAGE↗
DOE OSTI2023

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Coupled Heat Power Operation of Smart Buildings via Modular Pumped Hydro Storage

In the United States, building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings’ energy efficiency and reduce operational expenses under the constraints of satisfying occupants’ comfort requirements. However, the majority of these studies consider building electricity demand and thermal load being satisfied by unidirectional electricity flow from the power grid or on-site renewable energy generation to electrical and thermal home appliances. Opportunities for leveraging low-grade heat for electricity have largely been overlooked due to impracticality at small scale. In 2016, a modular pumped hydro storage technology was invented in Oak Ridge National Laboratory, named Ground Level Integrated Diverse Energy Storage (GLIDES). In GLIDES, employing high-efficiency hydraulic machinery instead of gas compressor/turbine, liquid is pumped to compress gas inside high-pressure vessel creating head on ground level. This unique design eliminates the geographical limitation associated with the existing state-of-the-art energy storage technologies. It is easy to be scaled for building level, community level, and grid level applications. By using this novel hydro-pneumatic storage technology, opportunities for leveraging low-grade heat in building can be economical. In this research, the potential of utilizing low-grade thermal energy to augment electricity generation of GLIDES is investigated. Since GLIDES relies on gas expansion in the discharge process and the gas temperature drops during this non-isothermal process, available thermal energy, e.g., from thermal storage, combined cooling, heat and power system (CCHP), can be utilized by GLIDES to counter the cooling effect of the expansion process and elevate the gas temperature and pressure and boost the roundtrip efficiency. Here, several groups of comparison experiments have been conducted, and the experimental results show that a maximum 12.9% cost saving could be achieved with unlimited heat source for GLIDES, and a moderate 3.8% cost improvement can be expected when operated coordinately with CCHP and thermal energy storage in a smart building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Operating Characteristics of Metal Hydride-Based Solar Energy Storage Systems

Thermochemical energy storage systems, based on a high-temperature metal hydride coupled with a low-temperature metal hydride, represent a valid option to store thermal energy for concentrating solar power plant applications. The operating characteristics are investigated for a tandem hydride bed energy storage system, using a transient lumped parameter model developed to identify the technical performance of the proposed system. The results show that, without operational control, the system undergoes a thermal ratcheting process, causing the metal hydride concentrations to accumulate hydrogen in the high-temperature bed over time, and deplete hydrogen in the low temperature. This unbalanced system is compared with a ’thermally balanced’ system, where the thermal ratcheting is mitigated by thermally balancing the overall system. The analysis indicates that thermally balanced systems stabilize after the first few cycles and remain so for long-term operation, demonstrating their potential for practical thermal energy storage system applications.

25 ENERGY STORAGE↗
DOE OSTI2024

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↗
DOE OSTI2022

Oxidative control over the morphology of Cu 3 (HHTP) 2 , a 2D conductive metal–organic framework

The morphology of electrically conductive metal–organic frameworks strongly impacts their performance in applications such as energy storage and electrochemical sensing. However, identifying the appropriate conditions needed to achieve a specific nanocrystal size and shape can be a time-consuming, empirical process. Here we show how partial ligand oxidation dictates the morphology of Cu 3 (HHTP) 2 (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene), a prototypical 2D conductive metal–organic framework. Using organic quinones as the chemical oxidant, we demonstrate that partial oxidation of the ligand prior to metal binding alters the nanocrystal aspect ratio by over 60-fold. Systematically varying the extent of initial ligand oxidation leads to distinct rod, block, and flake-like morphologies. These results represent an important advance in the rational control of Cu 3 (HHTP) 2 morphology and motivate future studies into how ligand oxidation impacts the nucleation and growth of 2D conductive metal–organic frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Porin-Inspired Ionomers with sub-nm Gated Ion Channels for High Ion Conductivity and Selectivity (Final Project Report (2026))

The physiological functions of living systems heavily rely on biological ion channels, whose malfunction can lead to disease. These channels enable selective and regulated transport of water, ions, or small molecules across membranes. Analogously, ionomers used in energy conversion and storage technologies govern ion transport within membrane separators and catalyst binder layers. This DOE Office of Science Early CAREER project aimed to achieve molecular-level control over ionic conductivity and ion permselectivity by translating the functionalities of biological, gated ion channels into a novel class of ion-conducting polymers (ionomers) incorporating macrocyclic calix[4]arene-based repeat units. The overarching goal was to establish fundamental design principles and elucidate proton conduction mechanisms through strategic design of macrocyclic calix[4]arene-containing ionomers, with close relevance to energy conversion and storage devices, including proton exchange membrane fuel cells (PEMFCs). The project leveraged sub-nm-sized macrocyclic pores to facilitate exceptionally fast ion transport (beneficial to addressing sluggish ORR kinetics of PEMFC electrodes) and achieve functionalities of ionic diodes under applied electrochemical fields, beneficial for selective transport/separation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Angularly quantized spin rotations in hexagonal LuMnO 3

Optical control of the spin degree of freedom is often desired in application of the spin technology. Here we report spin-rotational excitations observed through inelastic light scattering of the hexagonal LuMnO 3 in the antiferromagnetically (AFM) ordered state. We propose a model based on the spin–spin interaction Hamiltonian associated with the spin rotation of the Mn ions, and find that the spin rotations are angularly quantized by 60°, 120°, and 180°. Angular quantization is considered to be a consequence of the symmetry of the triangular lattice of the Mn-ion plane in the hexagonal LuMnO 3 . These angularly-quantized spin excitations may be pictured as isolated flat bubbles in the sea of the ground state, which may lead to high-density information storage if applied to spin devices. Optically pumped and detected spin-excitation bubbles would bring about the advanced technology of optical control of the spin degree of freedom in multiferroic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Exploring the Feasibility of a Carbon Dioxide Storage Hub in Western North Dakota

The University of North Dakota Energy & Environmental Research Center (EERC) and project partner ONEOK, Inc. (ONEOK) are investigating the feasibility of establishing a CO2 (carbon dioxide) storage hub in western North Dakota—in the heart of the Williston Basin. The conceived Roughrider Carbon Storage Hub would store CO2 captured from six gas-processing plants owned and operated by project partner ONEOK and a planned gas-to-liquids plant. This 2-year U.S. Department of Energy-sponsored Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Phase II feasibility study is evaluating the aggregation of the CO2 captured from these seven sources for injection into stacked geologic storage complexes. The proposed hub includes several aspects that make it a highly qualified candidate for a feasibility study with a notably reduced project risk profile. These include 1) a project partner (ONEOK) with a committed goal to reduce greenhouse gas emissions; 2) prior subsurface data analysis supporting a potential stacked storage configuration with adequate CO2 storage resource; 3) commitment from local, regional, and state-level stakeholders; and 4) a state with U.S. Environmental Protection Agency underground injection control Class VI primacy. ONEOK’s assets in the Williston Basin provide significant environmental benefits by capturing and processing natural gas that may otherwise be flared or vented. Storing CO2 from these gas-processing facilities will reduce overall CO2 emissions in the basin while providing essential services to producers there and contributing to continued energy independence in the domestic markets.

03 NATURAL GAS↗
DOE OSTI2023

Impact of sanitizer application on Salmonella mitigation and microbiome shift on diced tomato during washing and storage

Here, this study examined the shift in Salmonella and indigenous microbiota on diced tomato after washing with three different sanitizers and during post-wash cold storage. Roma tomatoes were inoculated with a Salmonella cocktail (initial level ~ 5.6 CFU g –1 ), diced and washed along with uninoculated diced tomato in simulated flume wash water with sanitizers, including 10 mg L –1 free chlorine (FC10), 90 mg L –1 peracetic acid (PA90), PA90 in combination with a proprietary acidified surfactant blend (PS90), and unsanitized control (CK). Salmonella, total mesophilic aerobic bacteria (MAB), and yeast and mold (YM) populations on both inoculated and uninoculated samples were measured before and after washing, and during storage at 4 °C. 16S rRNA amplicon sequencing was also performed to determine the shift in bacterial microbiome. Washing with all tested sanitizers, especially PS90 (> 4 log Salmonella reduction), reduced Salmonella and MAB populations on inoculated diced tomatoes. Additionally, application of sanitizers mitigated Salmonella cross-contamination onto uninoculated samples. PS90 treatment inhibited the proliferation of most dominant bacteria on diced tomatoes during storage, including Erwiniaceae, Curtobacterium, Pantoea, Erwinia and Enterobacterales, which may benefit product quality and safety.

16S rRNA amplicon sequencing↗
DOE OSTI2023

Machine learning assisted phase and size-controlled synthesis of iron oxide particles

Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗