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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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The key capability established through the research funded by this award are erasure coded computations for linear systems, in serial and in parallel. This capability enables powerful efficient and scalable alternatives to existing linear system solvers in fault-prone computational systems.
Current production of LiOH, which is needed to make Li-ion battery cathode active materials, utilizes a multistep process including solar evaporation, precipitation with Na 2 CO 3 and then conversion to LiOH using Ca(OH) 2 . This process requires a large amount of land area for solar evaporation, the right weather conditions, and chemicals for the conversion process that result in NaCl and CaCO 3 waste products. The production of Ca(OH) 2 is very energy intensive and evolves significant quantities of CO 2 . An alternative process flow utilizing direct lithium extraction techniques, followed by a chemical free conversion process can have benefits in reducing the needed land requirements and chemicals for traditional brine processing. There are many potential direct lithium extraction technologies that are currently being developed. The direct lithium extraction process from typical brine sources will produce a LiCl solution with some impurities including typically high concentrations of Na. This brine then needs to be converted to LiOH for use in battery cathode production. Ideally this conversion could occur without the use of additional chemicals. Electrochemistry can do this conversion either via electrolysis or bipolar membrane electrodialysis (BPED) to produce LiOH and HCl in solution. BPED utilized bipolar membranes to split water, which has a reduced potential as compared to splitting water at electrodes into hydrogen and oxygen gas. This reduced potential required results in a significant energy savings for BPED over electrolysis methods. This CRADA project aimed to develop such an integrated process using direct lithium extraction followed by BPED to produce a LiOH solution. That solution can then be crystallized into battery grade LiOH. In particular, Albemarle utilized a direct lithium extraction process to produce a concentrated LiCl solution that could be used for the BPED process. The BPED process was first tested using various LiCl solutions with impurity ions added at bench scale to understand the effects of impurities and determine processing parameters. Then testing was performed using the direct lithium extracted brine at the bench scale before scaling the process up. After the process was scaled up a long duration test was carried out to estimate the lifetime of the membranes, which is key to the economics of the BPED process.
Here, we report electrocatalytic decarboxylation (ECDX) of valeric acid into paraffins, olefins, and alcohols via (non-)Kolbe electrolysis on electrodes with RuO 2 and Pt nanoparticles (NPs) as a greener alternative to thermocatalytic decarboxylation. The turnover frequency of ECDX increases, while the specific activity peaks as RuO 2 NP size increases. These opposing trends make the particle size of ∼ 12 nm the optimum size for ECDX on RuO 2 . Bulk Pt was active for ECDX, while Pt NPs were only active for the oxygen evolution reaction under our conditions. ECDX current efficiency remained constant in the studied potential range on RuO 2 NPs. Esterification was the favored reaction at 2.5 V vs. RHE; however, Kolbe electrolysis was the favored reaction at the expense of the esterification at 4.5 V vs. RHE. This work highlights the performance of nanostructured materials as an alternative to bulk materials as anodes for oxidative upgrading of carboxylic acids.
The substantial integration of renewable energy brings significant challenges to balance the system in real time because of the variability and intermittency of renewable power. For the reliable system operation, the frequency regulation service is used to stabilize the system frequency through automatically balancing the system generation and load. On one hand, with the substantially increasing deployment of renewable energy in electricity system, the requirement of frequency regulation (FR) services increases significantly. On the other hand, the current main resource of FR services, the controllable conventional generation, is continuously decreasing in the system generation mix. This means that in the future high renewable penetration power system, additional and alternative reliable FR services providers such as distributed energy storage (DES) resources should be explored. Although the capability of utility-scale energy storage to provide FR services has been demonstrated, the integrated control and dynamic modeling of distributed energy resource (DER) providing frequency regulation grid services has been rarely explored. There are several challenges to adopt DERs to provide reliable grid services as illustrated in FERC 755. First, the distributed installation of DES requires a comprehensive cyber-physical dynamic system (CPDS) modeling to fully consider the impacts of the communication latency variability on its real time FR provision capability. Unlike the conventional generators, there are two-layer communication between DERs and system operators which increase the communication delay. Second, unlike the conventional generators whose dynamic models have been comprehensively studied, the difference among individual DER components' power-dynamic characteristic brings challenges in the accurate dynamic AGC modeling of its power-frequency relationship. Third, the temporal dependent state of charge uncertainty of DERs challenges DERs' power and frequency regulation capacities scheduling in the look-ahead generation scheduling. Therefore, the aggregator should optimize the frequency regulation provision from individual DER in real time. To overcome these challenges, this project proposes a cyber-physical dynamic system (CPDS) model to handle the uncertainty of DERs two-layer communication latency and power dynamics. The variability of DERs' communication delay and dynamic constraints will be comprehensively modeled. The DERs' AGC model with communication delay is designed to validate DESs' frequency regulation services. Like current performance-based frequency regulation evaluation, the delivery of DERs' frequency regulation will be assessed through post-analysis of the actual AGC response with respect to the AGC control signal from system operators. Consequently, the reliability improvement with DERs providing reliable frequency regulation services can be evaluated from a comprehensive perspective considering all the dynamics of communication and power.
Abstract The separation of alkane isomers is an important yet challenging process in the petrochemical industry. Being a crucial step to produce premium gasoline components as well as optimum ethylene feed, the current industrial separation by distillation is extremely energy intensive. Adsorptive separation based on zeolite is limited by insufficient adsorption capacity. Metal‐organic frameworks (MOFs) hold enormous promise as alternative adsorbents due to their diverse structural tunability and exceptional porosity. Precise control of their pore geometry/dimensions has led to superior performance. In this minireview, we highlight the recent progresses in developing MOFs for the separation of C6 alkane isomers. Representative MOFs are reviewed based on their separation mechanisms. Emphasis is put on the material design rationale for achieving optimal separation capability. Finally, we briefly discuss the existing challenges, possible solutions, and future directions of this important field.
Membrane-based systems, such as electrodialysis, play an important role in desalination and industrial separation processes. Electrodialysis uses alternating anion- and cation-exchange membranes with a perpendicular electric field to generate concentrated and diluate streams from a feed solution. It is known that under overlimiting current conditions, reduced charge and mass transfer at the membrane interface leads to regions of high ion depletion generating instability and vortices termed electroconvection. While electroconvective mixing is known to directly impact the separation efficiency of electrodialysis, the influence of ion concentration gradients across the membrane experienced in a functional electrodialysis system is not known. Here, we report the influence of ion concentration gradients across a cation exchange membrane (Nafion) that is both aligned with and opposed to the applied electric field. Experiments were conducted by coflowing NaCl solutions of different concentrations (0.1–100 mM) on each side of the membrane, and electroconvection was visualized with a fluorescence dye (Rhodamine 6G). Here, we obtained concentration profiles from fluorescence image data and systematically measured the thickness of the depletion boundary layer d BL under different conditions. We found smaller d BL values at a higher flow rate both with and without concentration gradients. Our results show that electroconvection is enhanced when the electric field is opposite to the direction of the concentration gradient.
Conventional thermochemical syntheses by continuous heating under near-equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways. As an alternative, we present a non-equilibrium, continuous synthesis technique that uses pulsed heating and quenching (for example, 0.02 s on, 1.08 s off) using a programmable electric current to rapidly switch the reaction between high (for example, up to 2,400 K) and low temperatures. The rapid quenching ensures high selectivity and good catalyst stability, as well as lowers the average temperature to reduce the energy cost. Using CH4 pyrolysis as a model reaction, our programmable heating and quenching technique leads to high selectivity to value-added C2 products (>75% versus <35% by the conventional non-catalytic method and versus <60% by most conventional methods using optimized catalysts). Our technique can be extended to a range of thermochemical reactions, such as NH 3 synthesis, for which we achieve a stable and high synthesis rate of about 6,000 μmol g Fe –1 h –1 at ambient pressure for >100 h using a non-optimized catalyst. Furthermore, this study establishes a new model towards highly efficient non-equilibrium thermochemical synthesis.
Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations. However, the generation time often requires an expensive denoising process with hundreds of function evaluations, restricting the current applicability of these models in a realistic setting. In this work, we report updates on the CaloScorearchitecture, detailing the changes in the diffusion process, which produces higher quality samples, and the use of progressive distillation, resulting in a diffusion model capable of generating new samples with a single function evaluation. Here we demonstrate these improvements using the Calorimeter Simulation Challenge 2022 dataset.
The purpose of this study is to provide broader understanding of the significant role that the pension system has in the Spanish economy by estimating the sectoral production, employment and income sustained by pensioners' consumption. Based on input-output tables by the World Input-Output Database and consumption data from the Household Budget Survey by the Spanish Statistical Office, a demoeconomic model is applied to quantify the direct impacts, indirect impacts from interindustry links and induced impacts from income-consumption connections over a nine-year period (2006–2014). Then, the factors driving the evolution of total output, employment and value added during such period have been examined by using structural decomposition analysis. The growing participation of consumption by pensioner households in final demand had proven crucial during the 2008 crisis to alleviate the negative trend in production and employment derived from the collapse in consumption suffered by the rest of households. Determining the underlying factors driving changes in both employment and income during the 2008 crisis can be of interest in political decision-making on the sustainability of the Spanish pension system. The results of estimating both the employment and income supported by pensioners' consumption reveal the significant stabilizing effect of the public spending on pensions, particularly during the 2008 crisis. The current Spanish approach of attaining the pension system sustainability by merely reducing social protection costs ignores the adverse consequences of a lower pensioners' demand. This paper addresses an alternative view in which pension spending is not considered a burden on economic growth but rather a means of improving the level of production and employment.
Given the increasing concern around greenhouse gas emissions and the decline in the availability of fossil fuels, there is increasing global demand to develop alternate fuels for maritime transportation that are sustainable and which have lower greenhouse gas emissions. Methanol is one such alternative fuel that has garnered considerable attention given its potential to be produced by more sustainable processes and its more favorable greenhouse gas emission profile in comparison with current fossil fuels. Understanding the physical and chemical properties of methanol under a range of conditions is essential for its development as a marine fuel. In this study, we seek to define physical and chemical properties of different methanol samples to simulate real-world storage conditions as these data are lacking in the literature. Several methanol samples were evaluated: nearly pure methanol; International Organization for Standardization (ISO) marine methanol (MM) grades A, B, and C; and methanol plus higher alcohols. We first evaluated all methanol samples for impurities, acetic acid content, density, and distillation range. We then characterized the effects of water absorption and found that methanol can easily absorb unacceptable water content from humid air within hours, necessitating storage conditions that prevent this process. In eight-week aging experiments at 20 °C and 40 °C in ambient air, we did not observe significant oxidation for any of the methanol samples; however, we did observe increases in acid number. We assessed the impact of contamination of methanol with water, marine gas oil (MGO), and an MGO–biodiesel mixture on density, viscosity, distillation range, and lubricity. Finally, we show that MGO contamination of methanol results in a slight increase in sooting tendency. In aggregate, our results provide an in-depth analysis of physical and chemical properties of methanol as well as the impacts of storage conditions and impurities on the properties of fuel methanol.
Various technologies pertaining to integrating a positioning or timing solution from an alternative position, navigation, or timing (PNT) system into a satellite-based-navigation system are described herein. The PNT system generates a position/timing (P/T) solution that indicates a current position or current time of the PNT system. The P/T solution is provided as input to a simulation of a satellite constellation of the satellite-based-navigation system, and a constellation signal is generated based on the simulation and the P/T solution. The constellation signal is formatted according to a navigation signal format of the satellite-based-navigation system such that when the constellation signal is provided to a receiver of the satellite-based-navigation system, the receiver computes a P/T solution that indicates the current position or the current time identified by the PNT system.
The push for sustainability in all facets of manufacturing has led to an increased interest in biomass as an alternative to non-renewable materials. Hemp bast fiber mats were produced from a bacterial retting process, named BFM, as the fiber reinforcement. The objective of this study was to evaluate the feasibility of laminating BFM with polylactic acid (PLA) for a composite panel product. Since both BFM and PLA are biodegradable, the resulting BFM-PLA composites will be 100% biodegradable. PLA pallets were processed into thin polymer sheets which served as the matrix. The BFM and PLA plates were laminated in five layers and compression-molded into composite panels. Experiments were conducted on the three BFM-to-PLA ratios (35/65, 45/55, and 50/50). Mechanical properties (tensile and bending properties) and physical properties (thickness swell and water absorption) were tested and compared to the currently commercial sheet molding compound (SMC) from fiber glass. The thermal behavior of the BFM/PLA composites was characterized using dynamic mechanical analysis (DMA) and differential scanning calorimetry (DSC). The developed BFM/PLA composite product is a sustainable alternative to existing synthetical fiber-reinforced polymer (FRP) that is biodegradable in landfill at the end of life.
We report the rate of data generated by cutting-edge experimental science facilities and large-scale simulations enabled by current high-performance computing (HPC) systems has continued to grow at a far greater pace than the development of the network and storage capabilities on which these systems rely. To cope with this challenge, scientist are moving toward the creation of autonomous experiments and HPC simulations using machine learning. However, efficiently moving, storing, and processing large amounts of data away from the point of origin presents an incredible challenge. In-memory computing, in situ analysis, data staging, and data streaming are recognized viable alternatives to traditional file-based methods for transferring data between coupled workflows. However, the performance trade-offs and limitations for these methods are not fully understood when used in HPC applications. This article presents a comprehensive performance assessment of the current solutions for data staging when applied to applications that are not necessary I/O intensive which makes them not ideal candidates for these methods. Our study is based on experiments running at scale on Oak Ridge National Laboratory's Summit supercomputer using applications and simulations that cover typical computational motifs and patterns. We investigated the usability and cost/benefit trade-offs of staging algorithms for HPC applications under different scenarios and highlight opportunities for optimizing the dataflow between coupled simulation workflows.
In a trend toward clean energy alternatives, recent years have seen great strides in the marine energy space. Consequently, there is a pressing need for the design, development, and validation of novel energy harvesting technologies such as hydrokinetic devices, which capture kinetic energy from waves, tides, and currents. However, these devices span numerous concepts and designs that often lack solid benchmark research that can be freely referenced throughout their development. This work focuses on the design process of an open-source composite hydrokinetic turbine blade for a three-bladed marine turbine rotor assembly with a diameter of 2.5 m. The proposed blade consists of two structural composite skins that are bonded with an adhesive and filled with a foam core. This study also explores and contrasts the efficiency and resolution of low-fidelity rapid design methodologies and comprehensive high-fidelity approaches in the context of blade design, modeling, and analysis efforts, a key objective in this research. Blade hydrodynamic loads were modeled and applied to finite-element blade models to study deformations and potential failure. Ongoing and upcoming efforts will result in blade manufacture and structural testing at the National Renewable Energy Laboratory. In future work, multiple blades will be deployed at the Living Bridge site at the University of New Hampshire and will be compared to rigid aluminum blades of the same geometry, developed by Sandia National Laboratories. Ultimately, this research will lay foundational groundwork for researchers and manufacturers, establishing a baseline composite blade design that will serve as a benchmark in the development of future hydrokinetic turbine blades.
The separation of alkane isomers is an important yet challenging process in the petrochemical industry. Being a crucial step to produce premium gasoline components as well as optimum ethylene feed, the current industrial separation by distillation is extremely energy intensive. Adsorptive separation based on zeolite is limited by insufficient adsorption capacity. Metal-organic frameworks (MOFs) hold enormous promise as alternative adsorbents due to their diverse structural tunability and exceptional porosity. Precise control of their pore geometry/dimensions has led to superior performance. In this minireview, we highlight the recent progresses in developing MOFs for the separation of C6 alkane isomers. Representative MOFs are reviewed based on their separation mechanisms. Emphasis is put on the material design rationale for achieving optimal separation capability. Lastly, we briefly discuss the existing challenges, possible solutions, and future directions of this important field.
Abstract Many operational analyses of wind power plants require a statistical relationship, which can be called the wind plant power curve, to be developed between wind plant energy production and concurrent atmospheric variables. Currently, a univariate linear regression at monthly resolution is the industry standard for post‐construction yield assessments. Here, we evaluate the benefits in augmenting this conventional approach by testing alternative regressions performed with multiple inputs, at a finer time resolution, and using nonlinear machine‐learning algorithms. We utilize the National Renewable Energy Laboratory's open‐source software package OpenOA to assess wind plant power curves for 10 wind plants. When a univariate generalized additive model at daily or hourly resolution is used, regression uncertainty is reduced, in absolute terms, by up to 1.0 % and 1.2 % (corresponding to a −59 % and −80 % relative change), respectively, compared to a univariate linear regression at monthly resolution; also, a more accurate assessment of the mean long‐term wind plant production is achieved. Additional input variables also reduce the regression uncertainty: when temperature is added as an input to the conventional monthly linear regression, the operational analysis uncertainty connected to regression is reduced, in absolute terms, by up to 0.5 % (−43 % relative change) for wind power plants with strong seasonal variability. Adding input variables to the machine‐learning model at daily resolution can further reduce regression uncertainty, with up to a −10 % relative change. Based on these results, we conclude that a multivariate nonlinear regression at daily or hourly resolution should be recommended for assessing wind plant power curves.
Current heating, venting, and air conditioning (HVAC) systems have drawbacks of high energy consumption, large CO 2 emissions, and low efficiency. Electrocaloric (EC) cycles present an eco-friendly alternative by converting thermal energy to electrical energy. Defect-free thin films with uniform thickness are required to achieve optimal EC performance. A scalable thin film fabrication process is essential for integrating EC cycles into HVAC systems. This study introduces EC thin films prepared by electrospray (ES) processing, a manufacturing method that deposits EC polymer layer by layer using high voltage. The resulting films show superior thickness control, smoother surfaces, and improved thermal and electrical properties compared with solution casting. In addition, post-annealing at 120°C enhances the thermal and EC performance, with films achieving a temperature change (ΔT) of 3.6°C at 100 MV/m when tested near room temperature. With the potential for future scalability, the ES method offers a promising approach for fabricating EC thin films.
Abstract The finite nature of fossil fuels and the environmental impact of its use have raised interest in alternate renewable energy sources. Specifically, nonfood carbohydrates, such as lignocellulosic biomass, can be used to produce next generation biofuels, including cellulosic ethanol and other nonethanol fuels like butanol. However, currently there is no native microorganism that can ferment all lignocellulosic sugars to fuel molecules. Thus, research is focused on engineering improved microbial biocatalysts for production of liquid fuels at high productivity, titer, and yield. A clear understanding and application of the basic principles of microbial physiology and biochemistry are crucial to achieve this goal. In this review, we present and discuss the construction of microbial biocatalysts that integrate these principles with ethanol-producing Escherichia coli as an example of metabolic engineering. These principles also apply to fermentation of lignocellulosic sugars to other chemicals that are currently produced from petroleum.