Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Storage Complex”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Solid Electrolyte Bimodal Grain Structures for Improved Cycling Performance

Here, the application of solid-state electrolytes in Li batteries is hampered by the occurrence of Li-dendrite-caused short circuits. To avoid cell failure, the electrolytes can only be stressed with rather low current densities, severely restricting their performance. As grain size and pore distributions significantly affect dendrite growth in ceramic electrolytes such as Li 7 La 3 Zr 2 O 12 and its variants; here, a “detour and buffer” strategy to bring the superiority of both coarse and fine grains into play, is proposed. To validate the mechanism, a coarse/fine bimodal grain microstructure is obtained by seeding unpulverized large particles in the green body. The rearrangement of coarse grains and fine pores is fine-tuned by changing the ratio of pulverized and unpulverized powders. The optimized bimodal microstructure, obtained when the two powders are equally mixed, allows, without extra interface decoration, cycling for over 2000 h as the current density is increased from 1.0 mA·cm -2 , and gradually, up to 2.0 mA·cm -2 . The “detour and buffer” effects are confirmed from postmortem analysis. The complex grain boundaries formed by fine grains discourage the direct infiltration of Li. Simultaneously, the coarse grains further increase the tortuosity of the Li path. This study sheds light on the microstructure optimization for the polycrystalline solid-state electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2024

Switching-cycle-based Startup for Grid-connected Inverters

Conventional inverter startups, or grid synchronization, are hindered by slow dynamics and inrush current issues, which impede the integration of more renewable energy resources into the power grid. This paper overcomes the barriers by introducing a novel switching cycle-based startup approach for grid-connected inverters, eliminating the need for voltage sensors and phase-locked loops (PLLs). The proposed method surpasses the bandwidth constraints of traditional PLL-based techniques and achieves grid synchronization in just two switching cycles. Relying solely on sensed three-phase currents, synchronization is accomplished without inrush currents or the need for additional hardware or increased software complexity, resulting in a faster inverter startup. The paper also presents a sensitivity analysis to discuss the impact of critical parameters on the method's accuracy. As a result, the effectiveness of the proposed technique is demonstrated through simulation and experimental results.

14 SOLAR ENERGY↗
DOE OSTI2022

Review—“Knees” in Lithium-Ion Battery Aging Trajectories

Lithium-ion batteries can last many years but sometimes exhibit rapid, nonlinear degradation that severely limits battery lifetime. In this work, we review prior work on “knees” in lithium-ion battery aging trajectories. We first review definitions for knees and three classes of “internal state trajectories” (termed snowball, hidden, and threshold trajectories) that can cause a knee. We then discuss six knee “pathways”, including lithium plating, electrode saturation, resistance growth, electrolyte and additive depletion, percolation-limited connectivity, and mechanical deformation—some of which have internal state trajectories with signals that are electrochemically undetectable. Additionally, we also identify key design and usage sensitivities for knees. Finally, we discuss challenges and opportunities for knee modeling and prediction. Our findings illustrate the complexity and subtlety of lithium-ion battery degradation and can aid both academic and industrial efforts to improve battery lifetime.

25 ENERGY STORAGE↗
DOE OSTI2024

Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Enhancing ion transport in charged block copolymers by stabilizing low symmetry morphology: Electrostatic control of interfaces

Recently, the interest in charged polymers has been rapidly growing due to their uses in energy storage and transfer devices. Yet, polymer electrolyte-based devices are not on the immediate horizon because of the low ionic conductivity. In the present study, we developed a methodology to enhance the ionic conductivity of charged block copolymers comprising ionic liquids through the electrostatic control of the interfacial layers. Unprecedented reentrant phase transitions between lamellar and A15 structures were seen, which cannot be explained by well-established thermodynamic factors. X-ray scattering experiments and molecular dynamics simulations revealed the formation of fascinating, thin ionic shell layers composed of ionic complexes. The ionic liquid cations of these complexes predominantly presented near the micellar interfaces if they had strong binding affinity with the charged polymer chains. Therefore, the interfacial properties and concentration fluctuations of the A15 structures were crucially dependent on the type of tethered acid groups in the polymers. Overall, the stabilization energies of the A15 structures were greater when enriched, attractive electrostatic interactions were present at the micellar interfaces. Contrary to the conventional wisdom that block copolymer interfaces act as “dead zone” to significantly deteriorate ion transport, this study establishes a prospective avenue for advanced polymer electrolyte having tailor-made interfaces.

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

TomoPyUI : a user-friendly tool for rapid tomography alignment and reconstruction

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data ( i.e. organizing data/metadata, applying image filters etc. ) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI , a user interface for the well known tomography data processing package TomoPy . This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI , along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI , and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Performance of Hybrid Renewable Energy Power System for a Residential Building

Using fossil fuels as the primary way to generate electricity causes a significant effect on the environment. In 2019, more than 64% of the electricity in the United States of America was generated using fossil-fuel resources, while renewable energy (RE) resources contributed to only 17% of the U.S. electricity generation for the same year. Additionally, due to the complex terrain distribution of many states in the U.S., a massive opportunity of utilizing RE resources in rural and remote areas can reduce the cost of electrical grid installation for such areas. In this study, a typical residential building with an average energy utilization of 30.25 kWh/day with a demand peak of 5.34 kW was considered a case study in each state to optimize a hybrid RE system and find the best alternative electrical grid system. This study presents the best configuration between solar and wind energy with different types of energy storage. It was discovered the photovoltaic (PV) solar panels—diesel generators with battery best services in all states. The daily radiation and diesel prices substantially affect the levelized cost of energy (COE) values in each state.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Experimental Protocols for Studying Organic Non-aqueous Redox Flow Batteries

We report that Redox flow batteries (RFBs) are promising devices for grid-scale energy storage due to the decoupling of power and energy, which can be independently scaled by the electrode area and storage tank size, respectively. To date, only aqueous RFBs, such as the vanadium RFB, have been implemented commercially. Nevertheless, the limited energy densities and high-cost materials may preclude their wider market penetration. Organic non-aqueous redox-flow batteries (O-NRFBs), which utilize redox-active organic molecules (ROMs), have been offered as an attractive alternative. Many possible advantages include the use of earth-abundant elements (C, H, N, O, S, F), wherein the ROMs can be prepared from low-cost and sustainable materials. Additionally, a large variety of electroactive moieties are accessible as building blocks, providing a synthetic platform to tune the properties of ROMs through rational design. As a consequence, the development of novel ROMs has attracted researchers with diverse backgrounds, prompting remarkable innovations in the past decade. However, consistency in experimental protocols (e.g., electrochemical methods, cycling stability, experimental conditions) has not coincided with this uptick in research, leading to sometimes ambiguous and incomparable results. This is further convoluted by the complexity innate to battery development, such as cell design, detection, and characterization of reactions and active components. The O-NRFB application imposes stringent requirements on the physical or/and chemical processes involved in electrochemical cycling. Yet such considerations are often overlooked. Further, while quantum mechanical calculations provide a convenient tool for evaluating and selecting ROM candidates, this simulation is not always performed. Thus, in this Energy Focus, we detail a means to standardize experimental protocols for studies of O-NRFBs and suggest practices to facilitate fundamental understanding and development of ROMs.

25 ENERGY STORAGE↗
DOE OSTI2023

MODELING A SPENT NUCLEAR FUEL CASK SEISMIC TEST

The US Department of Energy Spent Fuel and Waste Science and Technology (SFWST) program is planning to conduct a series of full-scale shake table tests to simulate hypothetical earthquake conditions and record the response of surrogate spent nuclear fuel (SNF) assemblies in a canister dry storage system mockup. The shake table motions will represent a range of hypothetical earthquake conditions at hypothetical locations in the continental US to generally define the range of mechanical loads that SNF can be expected to experience during extended dry storage periods. The earthquake conditions will represent seismic hazards in the 2,000-to-20,000-year return period range. The test will use instrumented pressurized water reactor fuel assemblies with surrogate mass inside the fuel rods instead of radioactive fuel pellets. Dummy assemblies with similar mass and dimensions to actual fuel assemblies will occupy the rest of the fuel assembly locations in a SNF canister that holds 32 fuel assemblies. The canister will be located inside a mockup vertical concrete cask. Instrumentation will record the motion of the major components of the complex dynamic system, and strain gauges will be used to record the cladding strain at select locations. Preparations for the test require modeling predictions to identify the range of response of the system and to help select specific earthquake cases to be simulated on the shake table from a large set of potential cases. This paper describes the pretest nonlinear finite element modeling efforts that have been completed to date, including cask system level modeling and fuel assembly modeling in LS-DYNA. The cask system level models are critical for anticipating sliding or tipping of an unanchored cask during the test. The fuel assembly model is needed to estimate the range of cladding strain response and fuel assembly structural response to be expected during the test and cladding strain measurements will be key metrics for model validation and the development of modeling best practices after the test is concluded.

Klymyshyn, Nicholas A.↗
DOE OSTI2025

Modeling Electrodeposition in 3D Porous Architectures for Solid-State Li-Metal Batteries

Li-metal storage in three-dimensional (3D) electrodes is considered a potential dendrite-mitigation strategy. The large surface area and high porosity of these electrodes result in reduced local Li-plating current densities. The porous topology provides a scaffold for Li-deposition and stripping, maintaining both mechanical integrity and Li accessibility. The goal of this study is to understand how characteristics, such as geometry and material properties, affect the current distribution and deposition pattern. To this end, we developed a computational method to track material growth driven by electrodeposition within a complex geometry. This method ensures that the finite-element discretization remains conforming to the moving boundary while preserving an adequate mesh quality, and thus maintains solution accuracy. Using this new computational tool, we analyze the conditions under which porous anode architectures effectively expand the surface area of the charge-transfer interface, and self-regulate current density and dendrite growth.

3D electrode architectures↗
DOE OSTI2025

Electrocatalytic Oxidation of Ammonia for Energy Conversion and Storage (Final Report)

Ammonia is one of the most promising candidates to be a major renewable fuel. Ammonia is synthesized from H 2 and N 2 , which is the most abundant gas in the Earth’s atmosphere, using the Haber-Bosch (HB) process in the largest scale production of a chemical commodity. Using H 2 generated from renewable resources would result in a scalable, carbon-free, high energy density liquid fuel. The HB reaction is almost thermoneutral, which means hydrogen’s intrinsic energy is largely retained in the ammonia product, making NH 3 possibly the best candidate for storing and transporting H 2 . The conversion of NH 3 to energy has received very little attention, however. As part of this project we demonstrated the first example of a well-defined complex capable of driving electrocatalytic ammonia oxidation to N 2 , protons and electrons. We further thoroughly investigated the mechanistic underpinnings of the electrocatalytic reactions. We have also developed new chemistry to synthesize transition metal complexes aimed at increasing the efficiency and activity of electrocatalysts for the conversion of NH 3 to H 2 and N 2 at ambient temperatures.

08 HYDROGEN↗
DOE OSTI2020

A highly stable Cu(OH) 2 -Poly(vinyl alcohol) nanocomposite membrane for dramatically enhanced direct borohydride fuel cell performance

Nano-additive aggregation, limited performance, and unclear modification mechanisms are the main obstacles in developing nanocomposite anion exchange membranes (AEMs). In this work, for the first time, an effective and highly stable Poly(vinyl alcohol) (PVA)-based AEMs with dispersive Cu(OH)$_2$ nanoclusters (Cu-AEMs) are prepared by a simple and eco-friendly three-step method: ‘CuCl$_2$ doping-casting-KOH immersing’. The doped Cu$^{2+}$ ions chemically combine with OH- ions to form anionic conductive Cu(OH)2 nanoclusters intermediated by attaching resins. The PVA skeletons wrap around Cu(OH)$_2$ while the hydroxyl groups expose to bulk water, forming Cu(OH)$_2$-PVA complex, which avoids nano-additive aggregation, increases anionic channels, and strengthens additive-matrix connection. A direct borohydride fuel cell using Cu-AEM with 0.56 wt % CuCl$_2$ possess the highest power density of 403.3 mW cm$^{-2}$ at 60 °C and a life span of over 200 h. The high-performance and durability come from the unique structure of Cu(OH)$_2$ nanoclusters-PVA complex. ‘Vehicle’ theory is considered to be the dominant mechanism for enhancing such nanocomposite Cu-AEMs. This work demonstrates a new concept for preparing the stable AEMs toward high-performance fuel cells. The synthetic chemistry involved can be broadly extended for fabricating versatile AEMs.

25 ENERGY STORAGE↗
DOE OSTI2020

Kinetic versus Thermodynamic Stability of LLZO in Contact with Lithium Metal

Li 7 La 3 Zr 2 O 12 (LLZO) garnet-based oxides are a promising class of solid electrolytes used as the separator in all-solid-state batteries (ASSBs). While LLZO is considered to have a wide electrochemical stability window, its intrinsic stability in contact with lithium metal is not sufficiently well understood, and there is still a debate on the key question of whether LLZO does or does not form passivation layers before and during cycling. Utilizing both in situ and operando X-ray photoelectron spectroscopy techniques, in this work we reveal the presence of a kinetic barrier to the reduction of LLZO by Li metal, with the extent of oxygen-deficient interphase (ODI) formation depending sensitively on the energetics of Li metal arriving at the Li vertical bar LLZO interface. Despite the clear presence of a kinetic barrier to reduction, the electrochemical response of the Li vertical bar LLZO interface is unchanged by the presence of the ODI, indicating that ODI formation during electrochemical cycling does not hinder charge transfer across the Li vertical bar LLZO interface. Overall, these results reveal that the reactivity of LLZO with Li metal depends not only on the material properties of the adjoining phases (i.e., surface purity and active contact) and their resulting thermodynamic stability but also on the energy input at the interface and the resulting reaction kinetics. Furthermore, the presence of a kinetic barrier to reduction highlights the additional complexities governing the reactivity of solid-state interfaces in ASSBs and underscores the importance of operando characterization of interfacial stability to design more robust, high-performance protection strategies for solid electrolytes in contact with reactive electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Revisiting the pseudo-supercritical path method: An improved formulation for the alchemical calculation of solid–liquid coexistence

Alchemical free energy calculations via molecular dynamics have been applied to obtain thermodynamic properties related to solid–liquid equilibrium conditions, such as melting points. In recent years, the pseudo-supercritical path (PSCP) method has proved to be an important approach to melting point prediction due to its flexibility and applicability. In the present work, we propose improvements to the PSCP alchemical cycle to make it more compact and efficient through a concerted evaluation of different potential energies. The multistate Bennett acceptance ratio (MBAR) estimator was applied at all stages of the new cycle to provide greater accuracy and uniformity, which is essential concerning uncertainty calculations. In particular, for the multistate expansion stage from solid to liquid, we employed the MBAR estimator with a reduced energy function that allows affine transformations of coordinates. Free energy and mean derivative profiles were calculated at different cycle stages for argon, triazole, propenal, and the ionic liquid 1-ethyl-3-methyl-imidazolium hexafluorophosphate. Comparisons showed a better performance of the proposed method than the original PSCP cycle for systems with higher complexity, especially the ionic liquid. Furthermore, a detailed study of the expansion stage revealed that remapping the centers of mass of the molecules or ions is preferable to remapping the coordinates of each atom, yielding better overlap between adjacent states and improving the accuracy of the methodology.

25 ENERGY STORAGE↗
DOE OSTI2024

Electric Utility Industry Standards Landscape

The electric utility industry relies on robust communication protocols to manage complex electrical grid data. The inherent networked nature of electrical grids, coupled with the radial structure of the “last mile” portion delivering power to end-use customers, presents difficulties in describing electrical models using simple data constructs. The paper provides an overview of communication protocols that address electric utility data, including grid data, and classifies these protocols through identification key characteristics that make them suitable for different electric grid data domains. Because of their variety, grid edge devices and their associated dedicated protocols are assessed by groups: those primarily designed for energy production and storage, those related to flexible loads, and those related to electric vehicles. The intent of this report is to provide guidance for stakeholders to navigate the challenges posed by the numerous overlapping protocols available to address electric grid data. Although further industry review, refinement, and validation of the categorization of these protocols is recommended, the authors propose this categorization as a start to improve electric grid awareness and understanding. In addition, this report includes three recommended industry actions regarding protocols to improve communications on the electric grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Atomic Scale Crystal Field Mapping of Polar Vortices in Oxide Superlattices

Polar vortices in oxide superlattices can be utilized as potential candidates for data storage applications due to their unique polarization topologies. The structure and dipole arrangement in polar vortices has been studied via X-ray scattering techniques, (scanning) transmission electron microscopy ((S)/TEM) and computational calculations. However, the fundamental correlation between the atomic structure and the electronic structure (which is manifested in the chemical bonding) has heretofore not been explored. Further, The hybridization between nominally empty $\textit{d}$ orbitals on the B-site with the occupied O 2$\textit{p}$ orbitals favors the condensation of a polar (ferroelectric) state in $\textit{AB}$O 3 perovskite oxides. The complex, continuously rotating local polarization texture of the vortices, in turn, can result in especially intricate $\textit{d}$- orbital interactions. Soft X-ray spectroscopy can probe these interactions at the transition metal $\textit{L}$-edge, but these techniques do not have the spatial resolution to resolve variations within one vortex (~5 nm region). Electron energy loss spectroscopy (EELS) in the STEM mode uses inelastically scattered electrons to probe the core-shell excitations (empty density of states) of transition metals at atomic resolution.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation

The ever-increasing volume of data produced by HPC simulations necessitates scalable methods for data exploration and knowledge extraction. Scientific data analysis often involves complex queries across distributed datasets, requiring manipulation of multiple primary variables and generating derived data that needs to be handled efficiently, creating challenges for applications that need to parse many large datasets. Relying on individual applications to handle all intermediate data generally leads to redundant computations across studies and unnecessary data transfers. In this paper, we investigate the performance of different approaches where applications define derived variables as quantities of interest (QoIs) and offload the computation and transfer of these QoIs to the I/O library. This significantly reduces redundancy and optimizes data movement across the distributed storage and processing infrastructure by allowing control over when and where derived variables are computed. We present a detailed analysis of the performance-storage trade-offs associated with different solutions and showcase results for our study on two large-scale datasets created from climate and combustion simulations.

Gainaru, Ana↗