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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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This data set shows the operation of the fuel cell inverter under grid-forming mode of operation, grid-following mode of operation and transition between the two modes.
The practical application of lithium (Li) metal battery is impeded by the Li dendrite growth and unstable solid electrolyte interphase (SEI) layer. Herein, an ultra-stretchable and ionic conducting chemically crosslinked pressure-sensitive adhesive (cPSA) synthesized via the copolymerization of 2-ethylhexyl acrylate and acrylic acid with poly(ethyleneglycol)dimethacrylate as crosslinker (short for 70cPSA), is developed as both artificial SEI layer and solid polymer electrolyte (SPE) for stable Li-metal electrode, enabling all-solid-state Li metal batteries with excellent cycling performance. As an artificial SEI layer, the 70cPSA-modified electrodes exhibit excellent electrochemical performance in Li|70cPSA@Cu half cells and 70cPSA@Li|70cPSA@Li symmetric cells. In full cells with LiFePO 4 (LFP) as cathode, the 70cPSA@Li|LFP cell exhibits stable cycling performance over 250 cycles. Utilized as SPE, the all-solid-state Li|SPE|LFP cell delivers excellent cycling stability with a capacity retention of 86% over 500 cycles. With high-voltage LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) as cathode, the Li|SPE|NMC811 cell exhibits a discharge capacity of 124.3 mAh g -1 with a capacity retention of 71% after 200 cycles. Furthermore, the rational design of PSAs and investigation of their dual role for stable and safe Li-metal batteries may shed a light on adhesive polymers for battery applications.
Direct recycling lithium-ion battery cathodes, a process that retains the engineered oxide structures from end-of-life materials, presents a cost-effective and energy-efficient alternative to other battery recycling methods. However, while direct-recycled cathodes have demonstrated performance comparable to that of pristine materials at low cycling rates, their high-rate performance remains uncertain. Morphology changes in cathode particles, a main mode of degradation, directly impact rate performance by limiting surface kinetics and solid-phase diffusion. If direct recycling processes do not sufficiently restore pristine-like morphologies, the recycled materials may retain structural defects that hinder high-rate performance. The present work uses a physics-based pseudo-2D model to simulate hybrid electrodes with pristine and artificially “aged/recycled” NMC materials to investigate potential impacts of incorporating performance-limited aged cathode materials into cells. The study highlights how differences in transport and kinetic properties can influence rate capabilities in mixed electrodes — particularly in high-loading cells in high-demand applications. However, model results also reveal a possible mitigation strategy via dual-layer electrode architectures with lower-performing materials positioned near the current collector. Simulations of 4.0 mAh cm −2 cells cycled at 4C using a dual-layer architecture provided approximately 5%–30% more capacity in constant-current protocols compared to homogeneously blended electrode architectures with the same loadings and mixed-material compositions. These findings highlight the importance of strategic electrode design in minimizing potential performance losses and facilitating the integration of recycled materials into high-performance batteries, advancing sustainable and cost-effective battery manufacturing.
Previous calculations of jet-in-crossflow problems have been sensitive to the turbulence and artificial viscosity models and to the grid. Consequently, the eddy viscosity model in the PARC3D code was modified to consider the turbulent jet by switching from the Baldwin-Lomax (1978) model to an axisymmetric jet model. A modified artificial viscosity model has been utilized and evaluated in this study as well. The new model includes cell size scaling and a directional dependence in the coefficients. Computational results from PARC3D demonstrate the effects of the viscosity models on the pressure distribution fore and aft of the jet and the ability of the adaptive grid scheme to adjust to the three-dimensional gradients around the jet.
This data set contains the three phase AC voltage, three phase AC current, DC voltage and DC current. These data sets were captured during fuel cell inverter operation in grid-connected dispatch, islanded load changes, transition from grid-connected mode to islanded mode and vice-versa.
We report this paper aims to develop numerical approximations of the Keller–Segel equations that mimic at the discrete level the lower bounds and the energy law of the continuous problem. We solve these equations for two unknowns: the organism (or cell) density, which is a positive variable, and the chemoattractant density, which is a non-negative variable. We propose two algorithms, which combine a stabilized finite element method and a semi-implicit time integration. The stabilization consists of a nonlinear artificial diffusion that employs a graph-Laplacian operator and a shock detector that localizes local extrema. As a result, both algorithms turn out to be nonlinear and can generate cell and chemoattractant numerical densities fulfilling lower bounds. However, the first algorithm requires a suitable constraint between the space and time discrete parameters, whereas the second one does not. We design the latter to attain a discrete energy law on acute meshes. We report some numerical experiments to validate the theoretical results on blowup and nonblowup phenomena. In the blowup setting, we identify a locking phenomenon that relates the L ∞ (Ω)-norm to the L 1 (Ω)-norm limiting the growth of the singularity when supported on a macroelement.
The Fibrin Slide Technique of Hau C. Kwaan and Tage Astrup is discussed. This relatively simple assay involves two steps: the formation of an artificial clot and then the addition of an enzyme (UKOKINASE) to dissolve the clot. The actual dissolving away of the clot is detected by the appearance of holes (lysis zones) in the stained clot. The procedure of Kwaan and Astrup is repeated, along with modifications and suggestions for improvements based on experience with the technique.
As the demand for low-cost, high-efficiency solar energy technologies grows, metal halide perovskite (MHP) solar cells have emerged as a promising candidate for next-generation photovoltaics due to their high power conversion efficiencies. However, their poor durability and issues with manufacturing consistency remain significant barriers to commercialization. In this work, we develop deep learning models to support materials characterization and provide insight into features and processes influencing performance. The models are trained using transfer learning of a pretrained model to predict relevant current-voltage (IV) metrics based on different combinations of input electroluminescence (EL) and photoluminescence (PL) images of MHP devices. We examine which image types are most informative in accurately predicting different IV metrics. Additionally, we use explainable artificial intelligence (XAI) techniques to provide insights into specific spatial features in the devices that drive differences in performance. We find that stabilized luminescence images (e.g. those collected after biasing the devices for at least 1 min) are better for predicting metrics of open-circuit voltage (by PL) and short-circuit current (by PL with EL), but that predicting fill factor and overall power output may use the time-evolution of EL images. Based on attribution masks generated by integrated gradients for each device performance metric, we further suggest different loss mechanisms associated with categories of large and small spatial defects. Overall, this case study highlights the potential applicability of XAI methodology for streamlining MHP device analysis and accelerating detailed understanding of the relationships between spatial defects and impacts on performance.
In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science. We demonstrate how targeted collaborations between different institutions from academic, national lab, and industry backgrounds and different scientific disciplines like theory, experiment, and characterization can yield unique insights into fuel cell catalysts. We comment on such insights into material designs for platinum-group-metal alloys, transition metal oxides, and non-traditional materials including metal–organic frameworks; systems that have served as the foundational building blocks for our consortium. We also motivate a renewed focus on catalyst durability in light of emerging technological requirements and paths forward in understanding in situ and operando electrochemical stability. Lastly, we describe new frontiers ORR research can take and how emerging artificial intelligence tools can assist researchers in capturing data, selecting new experiments, and guiding characterization to accelerate the design and discovery of fuel cell catalysts. A main goal of sharing this perspective is to discuss the rationale for our future research plans based on our consortium work. However, we also hope to illustrate both the potential impact of a collaborative strategy with the hopes of inspiring a higher degree of Industry-Academia-National Laboratory collaboration and encourage other centers and consortiums to distill and share their findings in a similar perspective-type article. Together we hope to enable the fuel cell research community to engage in a discussion of strategies for research and accelerated development of catalysts with improved activity and stability.
A three-dimensional (3D) culture system for growing long-lived B lymphocytes has been invented. The capabilities afforded by the system can be expected to expand the range of options for immunological research and related activities, including testing of immunogenicity of vaccine candidates in vitro, generation of human monoclonal antibodies, and immunotherapy. Mature lymphocytes, which are the effectors of adaptive immune responses in vertebrates, are extremely susceptible to apoptotic death, and depend on continuous reception of survival-inducing stimulation (in the forms of cytokines, cell-to-cell contacts, and antigen receptor signaling) from the microenvironment. For this reason, efforts to develop systems for long-term culture of functional, non-transformed and non-activated mature lymphocytes have been unsuccessful until now. The bone-marrow microenvironment supports the growth and differentiation of many hematopoietic lineages, in addition to B-lymphocytes. Primary bone-marrow cell cultures designed to promote the development of specific cell types in vitro are highly desirable experimental systems, amenable to manipulation under controlled conditions. However, the dynamic and complex network of stromal cells and insoluble matrix proteins is disrupted in prior plate- and flask-based culture systems, wherein the microenvironments have a predominantly two-dimensional (2D) character. In 2D bone-marrow cultures, normal B-lymphoid cells become progressively skewed toward precursor B-cell populations that do not retain a normal immunophenotype, and such mature B-lymphocytes as those harvested from the spleen or lymph nodes do not survive beyond several days ex vivo in the absence of mitogenic stimulation. The present 3D culture system is a bioreactor that contains highly porous artificial scaffolding that supports the long-term culture of bone marrow, spleen, and lymph-node samples. In this system, unlike in 2D culture systems, B-cell subpopulations developing within 3D cultures that have been modified to foster lymphopoiesis retain an immunophenotype that closely recapitulates cells in fresh bone marrow harvests. The 3D culture system has been found to be capable of supporting long-lived (8 weeks) populations of B and T lymphocytes from peripheral lymphoid organs, in the absence of activation signals, to an extent not achievable by conventional culture techniques. Interestingly, it has been found that 3D-culture B cells display a phenotype that has characteristics of both B1a and B2 cells. These promising preliminary observations suggest that the 3D culture system could be used with success in the study of peripheral-B-lymphocyte biology and in the development of biotechnological techniques and processes.
Here, in this work, we present a hydrocode Pagosa and explore the Richtmyer-Meshkov Instability (RMI) at an air/high explosive (HE) interface for the first time that is important but has not received much attention yet in the high explosive safety field. Thus, the presented Pagosa can be expected to predict the whole deflagration-to-detonation transition (DDT) process in future. In Pagosa, spatial discretization is implemented on cubic staggered grids by computing different variables at the vertex and the cell center, respectively, a special operator-splitting technique is employed to reduce the computational cost, and an artificial viscosity is added to handle the discontinuous shock waves in our simulations. To quantitatively evaluate the capability of Pagosa to solve these kinds of instabilities, the single mode Rayleigh-Taylor instability (RTI) and the multimode RMI at an air/SF 6 interface are first performed, respectively. The Pagosa results are compared with the related numerical solutions in the existing references and the experimental result. Moreover, a theoretical derivation of growth of RTI is also provided based on our numerical method. Subsequently, we explore the multi-mode RMI at an air/HE interface as well as the effects of several factors using Pagosa. Numerical results show that Pagosa is a powerful toolset to generate the right structures and the amplitude of RTI and RMI at an air/SF 6 interface. The solid HE can be penetrated by a strong shock wave and forms RMI deformations. The RMI at an air/HE interface behaves very different than at an air/SF 6 interface, periodic, decreased oscillation is observed due to material character, and is very sensitive to the initial simulation settings, that is, a tiny change in physical quantities will lead to a remarkable RMI structure, which is also observed in a shock bubble interaction. The findings in this work are significant, and will present a new insight for the high explosive field.
Abstract The intertwining of strands into 3D spirals is ubiquitous in biology, enabling functions from information storage to maintenance of cell structure and directed locomotion. In synthetic systems, entwined fibers can provide superior mechanical properties and act as artificial muscle or structural reinforcements. Unlike structures in nature, the entwinement of synthetic materials typically requires application of an external stimulus, such as mechanical actuation, light, or a magnetic field. Herein, we use computational modeling to design microscale sheets that mimic biology by transducing chemical energy into mechanical action, and thereby self-organize and interlink into 3D spirals, which spontaneously rotate. These flexible sheets are immersed in a fluid-filled microchamber that encompasses an immobilized patch of catalysts on the bottom wall. The sheets themselves can be passive or active (coated with catalyst). Catalytic reactions in the solution generate products that occupy different volumes than the reactants. The resulting density variations exert a force on the fluid (solutal buoyancy force) that causes motion, which in turn drives the interlinking and collective swirling of the sheets. The individual sheets do not rotate; rotation only occurs when the sheets are interlinked. This level of autonomous, coordinated 3D structural organization, intertwining, and rotation is unexpected in synthetic materials systems operating without external controls. Using physical arguments, we identify dimensionless ratios that are useful in scaling these ideas to other systems. These findings are valuable for creating materials that act as “machines”, and directing soft matter to undergo self-sustained, multistep assembly that is governed by intrinsic chemical reactions.
This project focused on the theory of the electronic properties of magnetic moire materials. Moire materials can be formed by overlaying two or more two-dimensional crystals that are either semiconductors or semimetals and establishing a moire pattern. Low-energy electronic properties are then described by a continuum model with crystalline periodicity. Moire materials are therefore artificial two-dimensional crys- tals whose periodicity is at the tens of nanometers scale, increasing the unit cell area by a factor of about 10,000 compared to real crystals. They are important because the main tuning knob of chemistry, the number of electrons per effective atom or molecule (the analog of the number of electrons per unit cell in real crystals), can be shifted by more than one simply by using electrical gates. The research covered two diffeerent classes of moire materials, graphene multilayers twisted to a rotation angle at which correlations are strong, and transition metal dichalcogenide semiconductors. The proposal identifed one project in each area both related very broadly to magnetism: i) Advancing understanding of broken spin-valley and sublattice symmetries in Magic Angle Twisted Bilayer Graphene and ii) Developing the theory of itinerant electron magnetism in Gamma-valley and K-valley transition metal dichalcogenide moire materials.
A method is described for constructing artificial data that realistically simulate photospheric velocity fields. The velocity fields include rotation, differential rotation, meridional circulation, giant cell convection, supergranulation, convective limb shift, p-mode oscillations, and observer motion. Data constructed by this method can be used for testing algorithms designed to extract and analyze these velocity fields in real Doppler velocity data.
We have implemented a three-dimensional compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the 'chimera' approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. A parallel machine like the CM-5 is well-suited for finite-difference methods on structured grids. The regular pattern of connections of a structured mesh maps well onto the architecture of the machine. So the first design choice, finite differences on a structured mesh, is natural. We use centered differences in space, with added artificial dissipation terms. When numerically solving the Navier-Stokes equations, there are liable to be some mesh cells near a solid body that are small in at least one direction. This mesh cell geometry can impose a very severe CFL (Courant-Friedrichs-Lewy) condition on the time step for explicit time-stepping methods. Thus, though explicit time-stepping is well-suited to the architecture of the machine, we have adopted implicit time-stepping. We have further taken the approximate factorization approach. This creates the need to solve large banded linear systems and creates the first possible barrier to an efficient algorithm. To overcome this first possible barrier we have considered two options. The first is just to solve the banded linear systems with data spread over the whole machine, using whatever fast method is available. This option is adequate for solving scalar tridiagonal systems, but for scalar pentadiagonal or block tridiagonal systems it is somewhat slower than desired. The second option is to 'transpose' the flow and geometry variables as part of the time-stepping process: Start with x-lines of data in-processor. Form explicit terms in x, then transpose so y-lines of data are in-processor. Form explicit terms in y, then transpose so z-lines are in processor. Form explicit terms in z, then solve linear systems in the z-direction. Transpose to the y-direction, then solve linear systems in the y-direction. Finally transpose to the x direction and solve linear systems in the x-direction. This strategy avoids inter-processor communication when differencing and solving linear systems, but requires a large amount of communication when doing the transposes. The transpose method is more efficient than the non-transpose strategy when dealing with scalar pentadiagonal or block tridiagonal systems. For handling geometrically complex problems the chimera strategy was adopted. For multiple zone cases we compute on each zone sequentially (using the whole parallel machine), then send the chimera interpolation data to a distributed data structure (array) laid out over the whole machine. This information transfer implies an irregular communication pattern, and is the second possible barrier to an efficient algorithm. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran. We make use of the Connection Machine Scientific Software Library (CMSSL) for the linear solver and array transpose operations.
In cells irradiation by heavy ions has been hypothesized to produce microlesions, regions of local damage. In cell membranes this damage is thought to manifest itself in the form of holes. The primary evidence for microlesions comes from morphological studies of cell membranes, but this evidence is still controversial, especially since holes also have been observed in membranes of normal, nonirradiated, cells. However, it is possible that damage not associated with histologically discernable disruptions may still occur. In order to resolve this issue, we developed a system for detecting microlesions based on liposomes filled with fluorescent dye. We hypothesized that if microlesions form in these liposomes as the result of irradiation, then the entrapped dye will leak out into the surrounding medium in a measurable way. Polypropylene vials containing suspensions of vesicles composed of either dipalmitoyl phosphatidylcholine, or a combination of egg phosphatidylcholine and cholesterol were irradiated at the Brookhaven National Laboratory using 56Fe ions at 1 GeV/amu. In several cases we obtained a significant loss of the entrapped dye above the background level. Our results suggest that holes may form in liposomes as the result of heavy ion irradiation, and that these holes are large enough to allow leakage of cell internal contents that are at least as large as a 1 nm diameter calcein molecule. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.
An artificial convolutional neural network was created to efficiently mimic a micromechanics model, the High Fidelity Generalized Method of Cells, for use in multi-scale structural finite element analysis. The network was found to quickly and accurately replicate the stiffness predicted by the micromechanics model using a 2D image of an idealized representative volume element of a fiber/matrix microstructure. The long-term goal of this work is to efficiently apply multi-scale methods for predicting the damage progression of a composite structure.
The purpose of the NASA In-Space Production Applications (InSPA) program is to provide funding and expertise to help brilliant United States innovators and businesses traverse the technology “Valley of Death” by proving out their concepts for in-space manufactured materials and products that will ultimately be sold to customers on the Earth. Scientific and technological advances on the International Space Station (ISS) and on Earth coupled with evolving societal needs are collectively enabling InSPA-funded teams to produce data streams and advanced biological, chemical, and physical materials solutions with economic value. We report on an extraordinary year of accomplishments on the ISS and highlight top InSPA and ISS National Lab results that span historic firsts in cancer research, stem cells, crystal production, optical fiber production, drug discovery, in-space treatments with RNA therapeutics, and production of artificial retinas from space. We assert that the results have enormous potential, are transforming the space exploration ecosystem and are the “seeds” of a microgravity industrial revolution that are shaping national microgravity strategy.