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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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An experimental heat transfer investigation was conducted on an air-cooled turbine vane made from wire-wound cloth material and supported by a central strut. Vane temperature data obtained are compared with temperature data from two full-coverage film-cooled vanes made of different laminated construction. Measured porous-airfoil temperatures are compared with predicted temperatures.
The Interface Configuration Experiment (ICE) is actually a series of experiments that explore the striking behavior of liquid-vapor interfaces (i.e., fluid surfaces) in a low gravity environment under which major shifts in liquid position can arise from small changes in container shape or contact angle. Although these experiments are designed to test current mathematical theory, there are numerous practical applications that could result from these studies. When designing fluid management systems for space-based operations, it is important to be able to predict the locations and configurations that fluids will assume in containers under low-gravity conditions. The increased ability to predict, and hence control, fluid interfaces is vital to systems and/or processes where capillary forces play a significant role both in space and on the Earth. Some of these applications are in general coating processes (paints, pesticides, printing, etc.), fluid transport in porous media (ground water flows, oil recovery, etc.), liquid propellant systems in space (liquid fuel and oxygen), capillary-pumped loops and heat pipes, and space-based life-support systems. In space, almost every fluid system is affected, if not dominated, by capillarity. Knowledge of the liquid-vapor interface behavior, and in particular the interface shape from which any analysis must begin, is required as a foundation to predict how these fluids will react in microgravity and on Earth. With such knowledge, system designs can be optimized, thereby decreasing costs and complexity, while increasing performance and reliability. ICE has increased, and will continue to increase this knowledge, as it probes the specific peculiarities of current theory upon which our current understanding of these effects is based. Several versions of ICE were conducted in NASA Lewis Research Center's drop towers and on the space shuttle during the first and second United States Microgravity Laboratory missions (USML-1 and USML-2). Additional tests are planned for the space shuttle and for the Russian Mir space station. These studies will focus on interfacial problems concerning surface existence, uniqueness, configuration, stability, and flow characteristics.
Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 10 9 Pa s m −3 . When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials.
SARS-CoV-2 spread rapidly, causing millions of deaths across the globe. As a result, demand for medical supplies and personal protective equipment (PPE) surged and supplies dwindled. Separate entirely, hospital-acquired infections have become commonplace and challenging to treat. To explore the potential of novel sterilization techniques, this study evaluated the disinfection efficacy of Fathhome's ozone-based, dry-sanitizing device by dose and time response. Inactivation of human pathogens was tested on non-porous (plastic) surfaces. 95.42-100% inactivation was observed across all types of vegetative microorganisms and 27.36% inactivation of bacterial endospores tested, with no residual ozone detectable after completion. These results strongly support the hypothesis that Fathhome's commercial implementation of gas-based disinfection is suitable for rapid decontamination of a wide variety of pathogens on PPE and other industrially relevant materials.
The use of exogenous nucleic acid technologies to modulate aberrant protein expression resulting from genetic mutations is a promising therapeutic approach for the treatment of diseases such as advanced prostate cancer (PC). The promise of nucleic-based therapeutics is dependent on the development of platforms that effectively protect nucleic acids from nuclease degradation and deliver the nucleic acids to the cytosol of target cells. In this work, we present the development of a divalent metal-mediated nucleic acid entrapment strategy with a porous silica matrix. This simple strategy results in efficient loading percentages of both siRNA (>60%) and mRNA (>80%) as well as their release within relevant biological environments (80%). Additionally, our data supports that the current method reduces endosomal entrapment and supports the lipid coating of mesoporous silica nanoparticles (LC-MSNs). Finally, the metal-enhanced nanosystem is assessed for biocompatibility, stability, and circulation within in vitro, ex ovo, and in vivo models of PC.
Multifunctional metal–organic frameworks (MOFs) that possess permanent porosity are promising catalysts in organic transformation. Herein, we report the construction of a hierarchical MOF functionalized with basic aliphatic amine groups and polyvinylpyrrolidone-capped platinum nanoparticles (Pt NPs). The postsynthetic covalent modification of organic ligands increases basic site density in the MOF and simultaneously introduces mesopores to create a hierarchically porous structure. The multifunctional MOF is capable of catalyzing a sequential Knoevenagel condensation–hydrogenation–intramolecular cyclization reaction. The unique selective reduction of the nitro group to intermediate hydroxylamine by Pt NPs supported on MOF followed by intramolecular cyclization with a cyano group affords an excellent yield (up to 92%) to the uncommon quinoline N-oxides over quinolines. The hierarchical MOF and polyvinylpyrrolidone capping agent on Pt NPs synergistically facilitate the enrichment of substrates and thus lead to high activity in the reduction–intramolecular cyclization reaction. The bioactivity assay indicates that the synthesized quinoline N-oxides evidently inhibit the proliferation of lung cancer cells. Finally, our findings demonstrate the feasibility of MOF-catalyzed direct synthesis of bioactive molecules from readily available compounds under mild conditions.
The STS-42 Space Shuttle Program Mission Report contains a summary of the vehicle subsystem operations during the forty-fifth flight of the Space Shuttle Program and the fourteenth flight of the Orbiter vehicle Discovery (OV-103). In addition to the Discovery vehicle, the flight vehicle consisted of the following: an External Tank (ET) designated as ET-52 (LWT-45); three Space Shuttle main engines (SSME's), which were serial numbers 2026, 2022, and 2027 in positions 1, 2, and 3, respectively; and two Solid Rocket Boosters (SRB's) designated as BI-048. The lightweight redesigned Solid Rocket Motors (RSRM's) installed in each one of the SRB's were designated as 360L020A for the left SRM and 360Q020B for the right SRM. The primary objective of the STS-42 mission was to complete the objectives of the first International Microgravity Laboratory (IML-1). Secondary objectives were to perform all operations necessary to support the requirements of the following: Gelation of Sols: Applied Microgravity Research (GOSAMR); Student Experiment 81-09 (Convection in Zero Gravity); Student Experiment 83-02 (Capillary Rise of Liquid Through Granular Porous Media); the Investigation into Polymer Membrane Processing (IPMP); the Radiation Monitoring Equipment-3 (RME-3); and Get-Away Special (GAS) payloads carried on the GAS Beam Assembly.
The phase distribution of lithiated LVO in thick (~500 μm) porous electrodes (TPEs) designed to facilitate both ion and electron transport was determined using synchrotron-based operando energy dispersive X-ray diffraction (EDXRD). Probing 3 positions in the TPE while cycling at a 1C rate revealed a homogeneous phase transition across the thickness of the electrode at the 1st and 95th cycles. Additionally, continuum modelling indicated uniform lithiation across the TPE in agreement with the EDXRD results and ascribed decreasing accessible active material to be the cause of loss in delivered capacity between the 1st and 95th cycles. The model was supported by the observation of significant particle fracture by SEM consistent with loss of electrical contact. Overall, the combination of operando EDXRD, continuum modeling, and ex situ measurements enabled a deeper understanding of lithium vanadium oxide transport properties under high rate extended cycling within a thick highly porous electrode architecture.
Titanium-based porous transport layers (PTLs) and iridium-based catalyst layers (CLs) are two main components of proton exchange membrane water electrolyzers (PEMWEs). PTLs are typically coated with platinum to minimize interfacial losses and to support long-term operation. Optimizing coatings and the PTL-CL interface requires comprehensive characterization. This study establishes time-of-flight secondary ion mass spectrometry (ToF-SIMS) as a valuable technique for PTL characterization, addressing capabilities and limitations related to PTL morphology. A methodology was developed that uses a Cs + sputter beam for dynamic depth profiling, with data collected in both positive-ion (MCs + ) and negative-ion modes to generate depth profiles, 2D ion maps, and 3D ion reconstructions. ToF-SIMS detected relative differences in platinum-layer thickness between samples; these trends were validated by cross-sectional scanning transmission electron microscope (STEM) measurements and flat-titanium substrate controls. Interfacial oxide layers are identified in both ion modes, with enhanced oxide sensitivity in negative mode. The technique’s high sensitivity enables detection of nanometer-scale coatings and trace impurities within the bulk PTL structure. These results provide a methodological framework for analyzing Pt-coated PTLs, with the potential to extend to other components in PEMWEs and other electrolyzer systems.
Copper catalyst gas diffusion electrodes (GDEs) have demonstrated unique electrochemical selectivity converting CO 2 to C 2 -hydrocarbons such as ethylene and ethanol but have been challenged by their hydrophobic chemical stability and internal electrical resistance leading to low energy efficiency. Carbon-supported GDEs have low electrical resistance but lack sufficient stability at industrially relevant current densities. While polymer-supported GDEs have improved hydrophobicity, they also display high in-plane electrical resistance, particularly at industrial scales. Here, in this work, we demonstrate a composite gas diffusion layer that combines hydrophobic porous polymers with an electrically conductive backbone addressing these core gas diffusion electrode (GDE) scaling challenges. We investigate the material properties of standalone porous perfluoropolyether (PFPE) polymers, including porosity and surface morphology, under varying processing conditions and then incorporate these polymers into a porous copper foam. This composite enhances the mechanical rigidity necessary for cell assembly and provides a through-plane electrical conduction path to reduce electrical resistive losses. This enhanced PFPE composite GDE displays efficient CO 2 reduction, achieving 15% ethylene energy efficiency at 100 cm 2 . These findings contribute to the development of advanced catalyst materials and electrode architectures and promote scalable strategies for electrochemical conversion of CO 2 into high-value carbon products.
Low-temperature direct ammonia fuel cells (DAFCs) use carbon-neutral ammonia as a fuel, which has attracted increasing attention recently due to ammonia's low source-to-tank energy cost, easy transport and storage, and wide availability. However, current DAFC technologies are greatly limited by the kinetically sluggish ammonia oxidation reaction (AOR) at the anode. Herein, we report an AOR catalyst, in which ternary PtIrZn nanoparticles with an average size of 2.3 ± 0.2 nm were highly dispersed on a binary composite support comprising cerium oxide (CeO 2 ) and zeolitic imidazolate framework-8 (ZIF-8)-derived carbon (PtIrZn/CeO 2 -ZIF-8) through a sonochemical-assisted synthesis method. Additionally, the PtIrZn alloy, with the aid of abundant OH ad provided by CeO 2 and uniform particle dispersibility contributed by porous ZIF-8 carbon (surface area: ~600 m 2 g -1 ), has shown highly efficient catalytic activity for the AOR in alkaline media, superior to that of commercial PtIr/C. The rotating disk electrode (RDE) results indicate a lower onset potential (0.35 vs. 0.43 V), relative to the reversible hydrogen electrode at room temperature, and a decreased activation energy (~36.7 vs. 50.8 kJ mol -1 ) relative to the PtIr/C catalyst. Notably, the PtIrZn/CeO 2 -ZIF-8 catalyst was assembled with a high-performance hydroxide anion-exchange membrane to fabricate an alkaline DAFC, reaching a peak power density of 91 mW cm -2 . Unlike in aqueous electrolytes, supports play a critical role in improving uniform ionomer distribution and mass transport in the anode. PtIrZn nanoparticles on silicon dioxide (SiO 2 ) integrated with carboxyl-functionalized carbon nanotubes (CNT–COOH) were further studied as the anode in a DAFC. A significantly enhanced peak power density of 314 mW cm -2 was achieved. Density functional theory calculations elucidated that Zn atoms in the PtIr alloy can reduce the theoretical limiting potential of *NH 2 dehydrogenation to *NH by ~0.1 V, which can be attributed to a Zn-modulated upshift of the Pt–Ir d-band that facilitates the N–H bond breakage.
In this work, we evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.
In traditional applications in soil physics it is convention to scale porous media properties, such as hydraulic conductivity, soil water diffusivity, and capillary head, with the gravitational acceleration. In addition, the Richards equation for water flux in partially saturated porous media also contains a gravity term. With the plans to develop plant habitats in space, such as in the International Space Station, it becomes necessary to evaluate these properties and this equation under conditions of microgravitational acceleration. This article develops models for microgravity steady state two-phase flow, as found in irrigation systems, that addresses critical design issues. Conventional dimensionless groups in two-phase mathematical models are scaled with gravity, which must be assigned a value of zero for microgravity modeling. The use of these conventional solutions in microgravity, therefore, is not possible. This article therefore introduces new dimensionless groups for two-phase models. The microgravity models introduced here determined that in addition to porous media properties, important design factors for microgravity systems include applied water potential and the ratio of inner to outer radii for cylindrical and spherical porous media systems.
A flexible substrate having a caustic resistant support and at least one membrane comprising a solid polymeric matrix containing a network of interconnected pores and interdispersed inorganic filler particles with a ratio of filler: polymer in the polymeric matrix of between about 1:1 to 5:1, is made by coating at least one side of the support with a filler:coating formulation mixture of inorganic filler particles and a caustic resistant, water insoluble polymer dissolved in an organic solvent, and removing the solvent from the mixture to provide a porous network within the polymeric matrix.
Magnetite sometimes takes the form of a plaquette - barrel-shaped stack of magnetite disks - in carbonaceous chondrites (CC) that show evidence of aqueous alteration. The asymmetric nature of the plaquettes caused Pizzarello and Groy to propose magnetite plaquettes as a naturally asymmetric mineral that can indroduce symmetry-breaking in organic molecules. Our previous synchrotron X-ray computed microtomography (SXRCT) and electron backscatter diffraction (EBSD) analyses of the magnetite plaquettes in fifteen CCs indicate that magnetite plaquettes are composed of nearly parallel discs, and the crystallographic orientations of the discs change around a rotational axis normal to the discs surfaces. In order to further investigate the nanostructures of magnetite plaquettes, we made two focused ion beam (FIB) sections of nine magnetite plaquettes from a thin section of CI Orgueil for transmission electron microscope (TEM) analysis. The X-ray spectrum imaging shows that the magnetite discs are purely iron oxide Fe3O4 (42.9 at% Fe and 57.1 at% O), which suggest that the plaquettes are of aqueous origin as it is difficult to form pure magnetite as a nebular condensate. The selected area electron diffraction (SAED) patterns acquired across the plaquettes show that the magnetite discs are single crystals. SEM and EBSD analyses suggest that the planar surfaces of the magnetite discs belong to the {100} planes of the cubic inverse spinel structure, which are supported by our TEM observations. Kerridge et al. suggested that the epitaxial relationship between magnetite plaquette and carbonate determines the magnetite face. However, according to our TEM observation, the association of magnetite with porous networks of phyllosilicate indicates that the epitaxial relationship with carbonate is not essential to the formation of magnetite plaquettes. It was difficult to determine the preferred rotational orientation of the plaquettes due to the symmetry of the cubic structure, however, we are able to observe small but consistent rotational orientation across several discs within a plaquette.
Ti6Al4V superalloy is recognized as a good candidate for bone implants owing to its biocompatibility, corrosion resistance, and high strength-to-weight ratio. While dense metal implants are associated with stress shielding issues due to the difference in densities, stiffness, and modulus of elasticity compared to bone tissues, the surface of the implant/scaffold should mimic the properties of the bone of interest to assure a good integration with a strong interface. In this study, we investigated the additive manufacturing of porous Ti6Al4V scaffolds and coating modification for enhanced osteoconduction using osteoblast cells. The results showed the successful fabrication of porous Ti6Al4V scaffolds with adequate strength. Additionally, the surface treatment with NaOH and Dopamine Hydrochloride (DOPA) promoted the formation of Dopamine Hydrochloride (DOPA) coating with an optimized coating process, providing an environment that supports higher cell viability and growth compared to the uncoated Ti6Al4V scaffolds, as demonstrated by the higher proliferation ratios observed from day 1 to day 29. These findings bring valuable insights into the surface modification of 3D-printed scaffolds for improved osteoconduction through the coating process in solutions.
Resorcinol formaldehyde-derived carbon xerogel (RFC) is a versatile material with tuneable properties, synthesized through a simple sol-gel method. This study presents nitrogen-doped RF carbon xerogel (N-RFC) with 11.8 at% nitrogen doping, offering a microporous architecture ideal for alkali metal-ion (Li, Na, K) batteries. The porous N-doped framework enhances electrochemical performance by improving ion transport, increasing active storage sites, and significantly boosting metal-ion adsorption, particularly through pyrrolic nitrogen, as revealed by first-principles calculations supported by XPS analysis. N-RFC anodes showed excellent cycling stability, high-capacity retention, and fast charge/discharge capabilities, rendering them suitable for commercial applications. Notably, the N-RFC anode demonstrates high-rate long-term cycling stability, retaining its capacity of 83.5 % (188 mAh/g at 2 C-rate) and 50 % (133 mAh/g at 1250 mA/g) over 1000 cycles for Li and Na-ion batteries, respectively, favorable for commercial battery applications. Additionally, N-RFC demonstrates a reversible capacity of 120 mAh/g after 394 cycles with a retention of 82 % for K-ion batteries. The ability of the material to accommodate larger ions like Na + and K + further emphasizes its versatility and potential application in diverse alkali metal-ion battery systems.
Industrial demand for rare earth elements (REEs) has surged over the past three decades due to their unique properties that support sustainable energy and new technologies. Separating individual REEs is challenging and hazardous, typically done through liquid-liquid extraction. There is an urgent need for environmentally friendly and efficient separation technologies for REEs. Porous materials offer promising advances for sustainable REE separation via ion-selective capture. We hypothesize that REE separation can be efficiently achieved in reactive nanopores, such as Zr(IV) and Cr(III) metal-organic frameworks (MOFs), through surface functionalization. By integrating material synthesis, interfacial chemistry experiments, theory, computation, and machine learning, we gained insights into the chemical factors controlling REE speciation and their competitive adsorption on MOFs. Our findings show that these materials’ selectivity can be tuned by surface functionalization. The machine learning component addressed ion-specific diffusion based on MOF topology and chemistry.