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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Technology Strategy Assessment: Findings from Storage Innovations 2030 Thermal Energy Storage

The concept of thermal energy storage (TES) can be traced back to early 19th century, with the invention of the ice box to prevent butter from melting. Modern TES development began with building heating and cooling and concentrated solar thermal technologies for power generation in the early 1900s and late 1970s, respectively. TES systems provide many advantages compared with other long-duration energy storage (LDES) technologies, which include low costs, long operational lives, high energy density, synchronous power generation capability with inertia that inherently stabilizes the grid, and the ability to output both heat and electricity. TES Use Cases TES technologies can couple with most renewable energy systems, including wind, photovoltaic, and concentrated solar thermal energy, and can be used for heat-to-heat, heat-to-electricity, electricity-to-heat, and electricity-to-electricity (bidirectional electricity) applications. The three types of TES that have heat as an input or output are grouped together for the purposes of this report. Retrofitting retired thermal power plants can be a potential cost-effective option for TES with electricity output because they both use a similar thermal-to-electricity type of conversion. Additionally, TES can directly serve heat demand for buildings and industrial processes, displacing fossil fuels to achieve broad decarbonization. Bidirectional Electricity Figure 1 shows a bidirectional electricity TES (ETES) architecture that is emerging as a prime technology for LDES at a grid scale. The ETES technology can utilize existing TES technology infrastructures, has no geological limitations (such as mountains and water for pumped storage hydro, underground natural caverns for compressed-air energy storage, etc.), and is capable of deployment anywhere in the United States and the world for broad uses. Particularly, ETES technology can be placed at retired fossil-fueled thermal power plants to reuse decommissioned assets, protect job security in associated communities, and provide resilient and high-inertia (i.e., spinning) power to the grid. Heat Input and Output There also are many ways to integrate TES within heat-to-electricity, heat-to-heat, and electricity-to-heat applications, such as those used in concentrating solar power (CSP), buildings, district heating, and industry process heat applications. These categories can be further classified for low- and high-temperature applications. High-temperature thermal energy storage (HTTES) heat-to-electricity TES applications are currently associated with CSP deployments for power generation. TES with CSP has been deployed in the Southwestern United States with rich solar resources and has proved its value to the electric grid. Electricity-to-heat and heat-to-heat HTTES applications present great potential for decarbonizing energy-intensive industrial process heat applications [8, 9], such as iron ore processing, iron smelting, cement production, glass manufacturing, mineral processing, and chemical production. Some industrial processes require process heat at temperatures > 1,400°C, so HTTES can be utilized to reduce fuel consumption in those processes through fuel, oxidizer, and process material pre-heating. Thermal energy storage for augmenting existing industrial process heat applications makes a much more attractive economic case because the energy penalty due to thermal-to-electric conversion is eliminated. Co-located applications of power production and heat also can add to the value stacking of integrating utility-scale TES; however, these scenarios are very case specific and not practically possible in many cases. These constraints are primarily attributed to the existing infrastructure being designed, developed, and constructed for many decades around the most economically feasible technologies, such as electricity and a selection of fossil fuels for heat input. Low-temperature TES can be utilized for building and district heating and cooling, as well as some process heat applications in electricity-to-heat and heat-to-heat configurations. Lower temperature TES (LTTES) can be added to heat pump equipment (electric input), either directly interacting with the refrigerant in the condenser or evaporator, or through a secondary heat transfer fluid. It also can be integrated in the building envelope or within the ducts of the heating, ventilation, and air conditioning (HVAC) system. Cost-effective integration of TES into buildings adds significant cost, and it is one of the key barriers preventing the commercialization and deployment of TES. The optimal strategy for integrating TES with buildings has yet to be determined for various applications of TES. Nevertheless, thermal storage materials are far less costly per unit of energy stored than electricity storage materials. This means that thermal storage has the potential to reduce the cost to society of energy storage.

25 ENERGY STORAGE↗
DOE OSTI2023

Characterizing Quantum Classifier Utility in Natural Language Processing Workflows

Quantum Natural Language Processing (QNLP) develops natural language processing (NLP) models for deployment on quantum computers. We explore feature and data prototype selection techniques to address challenges posed by encoding high dimensional features. Our study builds quantum circuit classifiers that includes classical feature pre-processing, quantum embedding and quantum model training. The quantum models are built on 4 or 6 qubits and the quantum neural network (QNN) uses the established bricklayer design. We compare the dependence of model performance (in terms of accuracy and F1 scores) on feature length, embedding gates and parameterized unitary design. We compare the performance of quantum machine learning models to classical convolution neural network model (CNN) on binary and multi-class classification tasks using two datasets of synthetic features and labels. The first is the ECP-CANDLE P3B3 dataset a corpus of synthetically generated cancer pathology reports. The second dataset is extracted from well-known benchmark dataset (MADELON) - features are generated with a combination of informative, repeated and uninformative features. Both datasets are used for binary classification and multi-class classification with 3 classes. We observe robust, accurate performance from all models on the binary classification tasks, but multiclass classification is a challenge for the quantum models-there is a notable decrease in accuracy when using 3 classes. Overall the performance is comparable in terms of recall and accuracy between QNNs and CNNs, even with large datasets. These results provide a point of comparison between quantum and classical models on real-world datasets.

Hamilton, Kathleen↗
DOE OSTI2024

Microwave-assisted pyrolysis of hydrocarbons using iron-based alumina catalysts obtained via solution combustion synthesis

The demand for hydrogen is growing which makes the development of clean and efficient H2 synthesis technologies imperative. Microwave-assisted, thermocatalytic, dehydrogenation of hydrocarbons has demonstrated the ability to generate H2 with high yield and selectivity, leaving behind valuable solid carbon byproducts. However, this microwave-assisted process is unoptimized which prevents it from being utilized in industry. A critical component of optimization is the development of a catalyst that is catalytically active, a good microwave absorber, and can be regenerated for repeated dehydrogenation cycles. Previous studies that focused on plastic waste decomposition have used iron-based alumina (FeAlxOy) made via solution combustion synthesis (SCS). Unexplored is the effect of tuning SCS parameters on dehydrogenation performance, the use of these materials in hydrocarbon decomposition to H2, and the regeneration of these catalysts. This dissertation has three objectives: (1) characterize the relationship between SCS parameters and the material properties of FeAlxOy, (2) determine how differences in the material properties of FeAlxOy influence their performance as catalysts during microwave-assisted pyrolysis of fossil fuels, and (3) investigate the Boudouard reaction to regenerate the FeAlxOy post-dehydrogenation.

Chanoi, Zachary Aidan↗
DOE OSTI2022

Development of a chemical-free process utilizing ozone oxidative precipitation for the recovery of cobalt and manganese from acid mine drainage

Acid mine drainage (AMD) has been identified as a viable secondary resource of Co, and Mn. However, recovery of these elements while treating AMD is challenging due to the unfavorable pH and Eh conditions for Co-Mn precipitation. This study investigated the effects of various ligands (hydroxide, carbonate, ammonium, sulfate, and phosphate) and oxidizers (sodium persulfate, potassium permanganate, and ozone) on the precipitation of Co-Mn from AMD through experimental and solution chemistry studies. Ozone was found to be the most effective agent for the recovery of these elements. Based on the results, an AMD treatment process was formulated for selective recovery of multiple critical elements, including Al, REEs, Co, and Mn. More than 95 % of Co and Mn were recovered through the proposed process utilizing chemical-less ozone oxidative precipitation. In conclusion, a precipitate containing 0.9 % Co and 54.6 % Mn was obtained from an AMD source containing 0.9 ppm Co and 41.8 ppm Mn.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Area-selective deposition of germanium on patterned graphene/monolayer molybdenum disulfide stacks via dipole engineering

Heterogeneous integration of two-dimensional materials and the conventional semiconductor has opened opportunities for next-generation semiconductor devices and their processing. Heterogeneous integration has been studied for economical manufacturing by substrate recycling and novel functionalities by a combination of incommensurate materials. However, utilizing the integration requires controlling locations of the integrated architectures. Here, we show area-selective deposition (ASD) of germanium on the graphene/MoS 2 stack. Ge nucleation precisely occurred on the surfaces of the patterned graphene/MoS 2 stack via dipole engineering. In this study, the growth temperature of ASD of Ge was significantly lower than that based on precursor desorption on SiO 2 . The first-principles calculations revealed that Ge deposited by ASD on the graphene/MoS 2 stack was not affected by charge transfer. This work provides a viable way to utilize atomically thin materials for next-generation semiconductor devices, which can be applicable for “Beyond Moore” and “More Moore” approaches.

2D materials↗
DOE OSTI2024

First-Principles Insights into the Thermodynamics of Variable-Temperature Ammonia Synthesis on Transition-Metal-Doped Cu (100) and (111)

Ammonia (NH 3 ) is one of the most produced chemicals worldwide. NH 3 synthesis predominantly utilizes the Haber–Bosch (HB) process, requiring high temperatures and pressures. Despite significant process advances, ample opportunity remains for improving the rate, selectivity, catalyst stability, and energy efficiency. Inspired by a recently developed programmable heating and quenching (PHQ) technique, we present in this paper a first-principles screening of candidate single-atom alloy catalysts generated from doping (111) and (100) surfaces of copper (Cu), an ineffective HB catalyst in its pure form. We predict the thermodynamics of two rate-limiting reactions, N 2 dissociative adsorption and the final hydrogenation step leading up to NH 3 release, at 400 and 900 K. Thermodynamically, the former reaction is favored at low temperatures, while the latter is favored at high temperatures. Vanadium-, chromium-, and molybdenum-doped Cu surfaces, due to intermediate M–N covalent bonding character, emerge as appealing candidate catalysts for PHQ NH 3 synthesis, as they balance the thermodynamics of the above-mentioned reaction steps at their respective optimal temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Atomistic Simulations for Thermophysical Properties of Uranium-Containing Halide Molten Salts

Characterizing the thermophysical properties in both fuel and coolant salts are critical in modeling, developing, process optimizing and utilizing molten salt reactors (MSRs), as these properties directly relate to operation metrics and can inform on the selection of candidate salts. The demand for consistent, accurate and publicly available thermophysical property data has become more apparent in recent years as interests have increased from molten salt reactor developers. There are a number of challenges in experimentally measuring properties such as thermal conductivity, viscosity, density and heat capacity , which have led to sparse and often times conflicting data points or molten salts in general. Additionally, there are a number of hazards to consider when synthesizing, storing, using, treating and disposing of molten salts. With the advances in computational capabilities over the last 10 years, the use of atomistic simulations can be implemented to support these efforts. The primary objective of this work is characterize the thermophysical transport properties in a number of molten chloride salts, and in particular NaCl-UCl 3 using ab-initio molecular dynamic (AIMD) simulations. In this binary salt the UCl 3 acts as the primary fissile material and NaCl acts as a carrier salt due with its’ high solubility for actinides A number of studies on the thermophysical properties of NaCl-UCl 3 have been published but there is not a vast amount of viscosity data for this system. In 1975, Desyatnik, et al published a study reporting dynamic viscosities that were calculated from kinematic viscosity measurements, and using the coefficients provided the viscosity in a 70:30 NaCl:UCl 3 mixture is 2.29 cP and 2.88 for a 60:40 mixture. Termini et al. recently reported viscosities in the range of 2.75 – 3 cP for the 63:37 NaCl-UCl 3 mixture in the same temperature range using rolling ball viscosity measurements. Computational viscosity of a similar mixture (64:36) can be obtained from the work Andersson et al. using the reported diffusion coefficients, and the hydrodynamic radius from the pair-radial distribution functions (RDFs). Using Eq (1) (vida infra), the viscosity would be 2.50 cP at 1100K. This is not to say that these values are incorrect due to the varying reported values, but aims to highlight the necessity of this work. The data reported in this ongoing work are computations on a 64:36 mixture of NaCl-UCl 3 at 987K. This work is likely to be expanded into varying concentrations of this mixture along with the inclusion of other salt candidate mixtures.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Device and method for data compression using a metadata cache

A processing device is provided which includes memory comprising data cache memory configured to store compressed data and metadata cache memory configured to store metadata, each portion of metadata comprising an encoding used to compress a portion of data. The processing device also includes at least one processor configured to compress portions of data and select, based on one or more utility level metrics, portions of metadata to be stored in the metadata cache memory. The at least one processor is also configured to store, in the metadata cache memory, the portions of metadata selected to be stored in the metadata cache memory, store, in the data cache memory, each portion of compressed data having a selected portion of corresponding metadata stored in the metadata cache memory. Each portion of compressed data, having the selected portion of corresponding metadata stored in the metadata cache memory, is decompressed.

Das, Shomit N.↗
DOE OSTI2024

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Hedgehog–FGF signaling axis patterns anterior mesoderm during gastrulation

Significance Anterior–posterior axis patterning is a fascinating but poorly understood developmental process. Single-cell sequencing was utilized to interrogate patterning abnormalities in a mesoderm-specific Hedgehog (Hh) pathway mutant, which revealed selective anterior mesoderm defects. We found that Hh signaling was required for fibroblast growth factor (FGF) pathway activity in nascent mesoderm during gastrulation. Mouse genetics, cell biology, and genomic experiments indicate that FGF signaling acts downstream of Hh signaling in nascent mesoderm for anterior mesoderm morphogenesis. This work demonstrates the utility of applying single-cell technologies to resolve complex developmental phenotypes. Here, it revealed a role for Hh signaling from the node in organizing anterior mesoderm morphogenesis, independent of its role in left–right determination, by promoting FGF signaling in gastrulating mesoderm.

Guzzetta, Alexander↗
DOE OSTI2022

Code of Record: DOE Standard Canister (DOESC)

The United States Department of Energy (DOE) Spent Nuclear Fuel (SNF) Packaging Demonstration seeks to develop and demonstrate the designs, technology, processes, and regulatory framework for packaging DOE SNF for road-ready dry storage (RRDS); and establish the processes that will be used in a future production facility. The Packaging Demonstration will utilize the DOE Standard Canister (DOESC) for packaging select DOE-managed SNF types for interim storage, transportation and disposal as part of RRDS. Placing DOE-managed SNF into RRDS is part of the strategic framework for SNF on the Idaho National Laboratory (INL) site. To comply with DOE, INL and Nuclear Regulatory Commission (NRC) requirements, this Code of Record establishes the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section III, Division 3 as the Code that will govern DOESC and internal support structure constructioni, with certain clarifications. This Code of Record establishes a rationale for proceeding without construction certification of the DOESC (i.e., “N-stamping) and the extent to which a Registered Professional Engineer is required for the DOE Spent Fuel Packaging Demonstration. Given the (i) standard industry practice to pursue independent licensure of commercial storage casks and transportation packages by the NRC in lieu of ASME certification and (ii) guidance provided by 10 CFR 830, DOESC construction activities need not be certified (i.e., “stamped”) to the ASME BPVC. However, additional quality assurance requirements will apply as outlined in this Code of Record.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Final Report for ARPA-E LOCOMOTIVES Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) Project

The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool used to evaluate strategies for cost-effectively deploying advanced locomotive technologies and associated infrastructure. ALTRIOS simulates freight-demand-driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward trade-offs and operation integration of different technology rollout strategies. An open, integrated simulation tool is valuable for identifying future research needs and making decisions on technology development, routes, and train selection. This final report details the ALTRIOS software architecture, major modules and components, and data validation process. It demonstrates the software's utility through a 30-year rollout case study targeting high penetration of advanced powertrain technologies by 2050 for two BNSF Railway routes: loaded taconite ore trains from Hibbing, Minnesota, to Superior, Wisconsin, and mixed-freight trains from Superior to Minneapolis, Minnesota.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Resilience Assessment Framework For Electric Distribution Systems Performance Under Extreme Conditions

The devastating impact of extreme weather-related events is increasingly evident on power grids, especially on distribution grids. The severity of their potential impact calls for 1) developing a suitable resilience assessment framework to capture the system performance and 2) assessing relevant mitigative strategies to lessen the impact of such events. This paper proposes a framework to identify grid vulnerabilities using the energy-at-risk concept to select, disconnect and isolate grid portions due to a resilience event. The proposed framework mainly consists of two steps; i) processing the utility's available infrastructure, i.e., a network model, possible switching combinations, and outage information for those combinations, as a graph-based database, and ii) implementing a novel optimal switching algorithm leveraging database and grid simulated metrics. These switching actions are generated to implement load curtailment in a rolling manner during anticipated grid scarcity conditions. In this study, a test case is created using two taxonomy feeders and is simulated against an extreme temperature event, e.g., a long, relatively cold, and prolonged freeze peak, thereby creating stress on the grid. It is demonstrated that the proposed framework allows utilities to predict the energy-at-risk during such resilience events and design suitable outage management strategies.

Poudel, Shiva↗
DOE OSTI2024

Multicolor Inks of Black Phosphorus for Midwave‐Infrared Optoelectronics

Abstract Black phosphorus (bP) based ink with a bulk bandgap of 0.33 eV ( λ = 3.7 µm) has recently been shown to be promising for large‐area, high performance mid‐wave infrared (MWIR) optoelectronics. However, the development of multicolor bP inks expanding across the MWIR wavelength range has been challenging. Here a multicolor ink process based on bP with spectral emission tuned from 0.28 eV ( λ = 4.4 µm) to 0.8 eV ( λ = 1.5 µm) is demonstrated. Specifically, through the reduction of bP particle size distribution (i.e., lateral dimension and thickness), the optical bandgap systematically blueshifts, reaching up to 0.8 eV. Conversely, alloying bP with arsenic (bP 1− x As x ) induces a redshift in the bandgap to 0.28 eV. The ink processed films are passivated with an infrared‐transparent epoxy for stable infrared emission in ambient air. Utilizing these multicolor bP‐based inks as an infrared light source, a gas sensing system is demonstrated that selectively detects gases, such as CO 2 and CH 4 whose absorption band varies around 4.3 and 3.3 µm, respectively. The presented ink formulation sets the stage for the advancement of multiplex MWIR optoelectronics, including spectrometers and spectral imaging using a low‐cost material processing platform.

Kim, Jae Ik↗
DOE OSTI2023

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Best Practices for Smart Grid-Interactive Efficient Building Ready Performance Contracts

Grid-interactive efficient building (GEB) measures reduce costs and optimize energy use for additional grid services by coordinating building energy loads and providing continuous demand management. Incorporating GEB energy conservation measures (ECMs) in performance contracts is reliant upon multiple factors. These factors include site selection with utility tariffs and incentives favorable to GEB, the identification of GEB as a priority in the initial stages of the contracting process, integration of GEB within comprehensive performance contracts with multiple other ECMs, and careful consideration of GEB measurement and verification (M&V) for energy savings performance contracts (ESPCs) and performance assurance for utility energy service contracts (UESCs).

building energy loads↗