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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine‐Learning‐Driven Exploration of Surface Reconstructions of Reduced Rutile TiO 2

Abstract Titanium dioxide (TiO 2 ) is widely used as a catalyst support due to its stability, tunable electronic properties, and surface oxygen vacancies, which are crucial for catalytic processes such as the reverse water‐gas shift (RWGS) reaction. Reduced TiO 2 surfaces undergo complex surface reconstructions that endow unique properties but are computationally challenging to describe. In this study, we utilize machine‐learning interatomic potentials (MLIPs) integrated with an active‐learning workflow to efficiently explore reduced rutile TiO 2 surfaces. This approach enabled the prediction of a phase diagram as a function of oxygen chemical potential, revealing a variety of reconstructed phases, including a previously unreported subsurface shear plane structure. We further investigate the electronic properties of these surfaces and validate our results by comparing experimental and theoretical high‐resolution transmission electron microscopy (HRTEM). Our findings provide new insights into how extreme surface reductions influence the structural and electronic properties of TiO 2 , with potential implications for catalyst design.

Lee, Yonghyuk [Chemistry and Biochemistry Universi↗
DOE OSTI2023

Diamonds in the Rough: Direct Surface Enhanced Infrared Spectroscopic Evidence of Nitrogen Reduction on Boron-Doped Diamond Supported Metal Catalysts

In situ investigations of electrocatalytic processes of increasing societal interest such as the nitrogen reduction reaction (NRR) re-quire aggressive experimental conditions that are not readily compatible with surface sensitive techniques such as attenuated total reflection surface enhanced infrared absorption spectroscopy (ATR-SEIRAS). A method for performing ATR-SEIRAS studies at very negative potentials where conventional IR-active films delaminate, and fail is reported. The method relies on a thin film of very robust boron-doped diamond deposited on a micromachined Si wafer, which provides extended mid-IR transparency at long wavelengths. SEIRAS activity is achieved by electrodepositing gold nanoparticles onto the conductive BDD layer. The Au@BDD layers are shown to sustain prolonged periods of electrolysis at negative potentials with no degradation of the modifying layer. The efficacy of these substrates for electrocatalysis is demonstrated by studying the reduction of N 2 at -1.5 V vs Ag/AgCl in an aqueous-based electrolyte. So under these conditions, direct spectroscopic evidence of both NH 3 and hydrazine formed from the nitrogen reduction reaction (NRR) is provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Study of active cooling for supersonic transports

The potential benefits of using the fuel heat sink of hydrogen fueled supersonic transports for cooling large portions of the aircraft wing and fuselage are examined. The heat transfer would be accomplished by using an intermediate fluid such as an ethylene glycol-water solution. Some of the advantages of the system are: (1) reduced costs by using aluminum in place of titanium, (2) reduced cabin heat loads, and (3) more favorable environmental conditions for the aircraft systems. A liquid hydrogen fueled, Mach 2.7 supersonic transport aircraft design was used for the reference uncooled vehicle. The cooled aircraft designs were analyzed to determine their heat sink capability, the extent and location of feasible cooled surfaces, and the coolant passage size and spacing.

Brewer, G. D.↗
NASA NTRS2017

The Potential for Health Monitoring in Expandable Space Modules: The Bigelow Expandable Activity Module on the ISS

Expandable modules for use in space and on the Moon or Mars offer a great opportunity for volume and mass savings in future space exploration missions. This type of module can be compressed into a relatively small shape on the ground, allowing them to fit into space vehicles with a smaller cargo/fairing size than a traditional solid, metallic structure based module would allow. In April 2016, the Bigelow Expandable Activity Module (BEAM) was berthed to the International Space Station (ISS). BEAM is the first human-rated expandable habitat/module to be deployed and crewed in space. BEAM is a NASA managed ISS payload project in partnership with Bigelow Aerospace. BEAM is intended to stay attached to ISS for an operational period of 2 years to help advance the technology readiness for future expandable modules. BEAM has been instrumented with a suite of space flight certified sensors systems which will help characterize the module's performance for thermal, radiation shielding and impact monitoring against potential Micro Meteoroid/Orbital Debris (MM/OD) providing fundamental information on the BEAM environment for potential health monitoring requirements and capabilities. This paper will provide an overview of how the sensors/instrumentation systems were developed, tested, installed and an overview of the current sensor system operations. It will also discuss how the MM/OD impact detection system referred to as the Distributed Impact Detection System (DIDS) data is being processed and reviewed on the ground by the principle investigators.

Wells, Nathan D.↗
DOE OSTI2026

Vapor-phase pillarization of MXenes for engineering hierarchical interlayer porosity

MXenes, a family of two-dimensional (2D) multilamellar materials, possess excellent thermal and electronic properties for a range of applications. Their use in heterogeneous catalysis, however, is limited by the low surface area resulting from stacked layers. Pillarization with inorganic oxides can create more open, mesoporous MXene structures, improving accessibility for guest species to diffuse, reside or react in the space between 2D layers. A previous liquid-phase pillarization method, however, involves excessive use of solvent-based precursors and multiple processing steps. Here, we report a vapor-phase pillarization (VPP) strategy to introduce pillars, exemplified by silica pillars, with high pillar precursor usage efficiency and a simplified processing workflow. The resulting silica-pillared mesoporous MXene exhibits significantly increased surface area and porosity. These textural properties can be easily tuned by the VPP synthesis conditions. When applied as a ruthenium (Ru) catalyst support for the hydrogenolysis of low-density polyethylene (LDPE), the silica-pillared MXene enabled high Ru dispersion and catalytic activity. This study highlights the potential of the VPP method for engineering mesoporous, 2D MXene materials and demonstrates the effectiveness of mesoporous MXene as a catalyst support in overcoming mass transport and active-site accessibility challenges in heterogeneous catalysis involving bulky substances, such as plastics upcycling.

Luo, Song [University of Delaware, Newark, DE (Uni↗
NASA NTRS1987

Hollow cathode plasma source for active spacecraft charge control

A prototype plasma source spacecraft discharge device has been developed to control overall and differential spacecraft surface charging. The plasma source is based on a unique hollow cathode discharge, where the plasma generation process is contained completely within the cathode. This device can be operated on argon, krypton, or xenon and has a rapid cold start time of less than 4 s. The discharge system design includes a spacecraft-discharge/net-charge sensing circuit which provides the ability to measure the polarity, magnitude, pulse shape, and time duration of a discharging event. Ion currents of up to 325 microA and electron currents ranging from 0.02 to 6.0 A have been extracted from the device. In addition, the spacecraft discharge device successfully discharged capacitively biased plates, from as high as + or - 2500 V, to ground potential, and discharged and clamped actively biased plates at +5 V with respect to ground potential during ground simulation testing.

Deininger, William D.↗
DOE OSTI2022

Survey of Relevant Data from the MSRP to Guide Development of MSR Chemistry Modeling Benchmarks

The Multiphysics Applications technical area of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is tasked with assessing, demonstrating, and applying NEAMS tools in solving multiphysics problems of nuclear reactors, such as liquid-fueled molten salt reactors (MSRs), which are the focus of this report. MSRs are actively being pursued as a potential candidate for power and heat generation by the nuclear industry. However, the inherent multiphysics nature of liquid-fueled MSRs, stemming from the strong interrelationship of neutronics, thermal fluids, and chemistry phenomena, provides unique challenges in modeling and simulation (mod/sim). Therefore, it will be important to develop mod/sim tools with varying types of multiphysics coupling that depend on the problem. The current work is focused on the initiation and development of MSR chemistry modeling benchmarks useful for validating current and potential future NEAMS tools. Development of such benchmarks include the following actions: 1) Summarize available chemistry data from the Oak Ridge National Laboratory (ORNL) MSR Program (MSRP) including operation of the Molten Salt Reactor Experiment (MSRE) and design studies for the Molten Salt Breeder Reactor (MSBR) concept; 2) Recommend simulation problems in MSR chemistry mod/sim based on (1); 3) Assess the current state of NEAMS tools that may support (2); 4) Demonstrate and validate the capabilities of the NEAMS tools in (3) while providing iterative feedback on future code development activities. The objective of this report is to initiate this effort by completing actions (1) and (2), which are discussed in Section 2. An overview of the relevant available MSRE experimental data is provided with examples of how this data may be useful in chemistry mod/sim problems, with the caveat that most of this data is over 50 years old, therefore some problem details as well as uncertainty estimates are often not provided. In Section 3, the current state of NEAMS tools is assessed for potential use in these mod/sim problems, with considerations for future code development activities, supporting action (3). Future work supporting this project under NEAMS may include a deeper dive into the specific phenomena discussed here including tasks such as the compilation of additional available data, updates in code development activities, and ultimately the demonstration and validation of these tools, supporting action (4).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2022

Nickel Hydroxide Nanofluid Cathodes with High Solid Loadings and Low Viscosity for Energy Storage Applications

Nanofluid electrodes with high loading of active solid materials have significant potential as high energy density flow battery electrolytes; however, two key criteria need to be met: they must have a manageable viscosity for pumping and simultaneously exhibit good electrochemical activity. A typical dispersion of nickel hydroxide nanoparticles (~100 nm) is limited to 5–10 wt.% of solids, above which it has a paste-like consistency, incompatible with flow applications. We report on the successful formulation of stable dispersions of a nano-scale nickel hydroxide cathode (β-Ni(OH) 2 ) with up to 60 wt.% of solids and low viscosity (32 cP at 25 °C), utilizing a surface graft of small organic molecules. The fraction of grafting moiety is less than 3 wt.% of the nanoparticle weight, and its presence is crucial for the colloidal stability and low viscosity of suspensions. Electrochemical testing of the pristine and modified β-Ni(OH) 2 nanoparticles in the form of solid casted electrodes were found to be comparable with the latter exhibiting a maximum discharge capacity of ~237 mAh/g over 50 consecutive charge–discharge cycles, close to the theoretical capacity of 289 mAh/g.

25 ENERGY STORAGE↗
DOE OSTI2023

An Immunomodulatory Polysaccharide–Protein Complex Isolated from the Polypore Fungus Royoporus badius

Many wild edible polypore mushrooms have medicinal value. In this study, we investigate the potential medicinal properties of the wild polypore mushroom Royoporus badius collected from north-central British Columbia, Canada. Water extract from R. badius was found to exhibit potent immunomodulatory activity. The extract was purified using DEAE-Sephadex anion-exchange chromatography as well as Sephacryl S-500 and HPLC BioSEC5 size-exclusion chromatography, to yield a novel polysaccharide-protein complex (IMPP-Rb).IMPP-Rb has a peak maxima molecular weight (M p ) of 950 kDa. GC-MS analyses showed that IMPP-Rb is composed predominantly of glucose (49.2%), galactose (11.3%), mannose (10.8%), rhamnose (9.6%), and galacturonic acid (8.2%), with smaller amounts of xylose (5.2%), fucose (2.8%), N-acetyl glucosamine (1.8%), and arabinose (1.2%). IMPP-Rb has multiple linkages, with 4-Glcp, 4-Manp, 6-Manp, 3,4-Manp, 4-Xylp, and 2-Rhap being the most prominent. IMPP-Rb is capable of inducing many cytokines in vitro and the protein component is indispensable for its immunomodulatory activity. IMPP-Rb has potential application as an immuno-stimulatory agent with pharmaceutical value.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Highly Active Hydrogen Evolution Reaction (HER) Catalysts Formed by Energetic Pt n Cluster Deposition: Deposition Dynamics and the HER Mechanism

Mass-selected Pt n + (n ≤ 7) were deposited at variable energies on highly oriented pyrolytic graphite (HOPG), creating highly active hydrogen evolution reaction (HER) electrocatalysts. HER mass activities were ~2 to >10 times higher than those for the surface atoms in bulk Pt and for Pt n deposited on several other supports. Thus, high activity reflects the Pt-C structures formed by energetic Pt n -HOPG impacts, in addition to high Pt surface availability. The Pt n /HOPG electrodes were probed by X-ray photoelectron spectroscopy, low energy ion scattering, and electron microscopy. Born-Oppenheimer molecular dynamics (BOMD) was used to simulate Pt n - HOPG impacts, revealing the types of structures formed at different energies, then DFT was used to probe their most important HER pathways. For low deposition energies, the Pt n deposit onto the HOPG surface with sub-unit sticking probability, aggregating at defects. With increasing deposition energy, the sticking probability initially decreases, then rises to unity as subplantation and defect creation allow formation of strongly bonded platinum-carbon structures. Barriers for HER on these structures were found to be low and weakly dependent on Pt n size, consistent with experiment. The activities were highest for small covalently-bonded Pt-C structures created at high deposition energies. The larger aggregated structures formed at low energies were less active, but still substantially better than the bulk Pt surface monolayer. The catalysts were stable in repeated potential cycling at reducing potentials, but electrodes containing subplanted Pt became more active when scanned to oxidizing potentials, due to emergence of subplanted Pt onto the surface.

08 HYDROGEN↗
DOE OSTI2021

Active anomaly detection for time-domain discoveries

Aims. We present the first evidence that adaptive learning techniques can boost the discovery of unusual objects within astronomical light curve data sets. Methods. Our method follows an active learning strategy where the learning algorithm chooses objects which can potentially improve the learner if additional information about them is provided. This new information is subsequently used to update the machine learning model, allowing its accuracy to evolve with each new information. For the case of anomaly detection, the algorithm aims to maximize the number of scientifically interesting anomalies presented to the expert by slightly modifying the weights of a traditional Isolation Forest (IF) at each iteration. In order to demonstrate the potential of such techniques, we apply the Active Anomaly Discovery (AAD) algorithm to 2 data sets: simulated light curves from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC) and real light curves from the Open Supernova Catalog. We compare the AAD results to those of a static IF. For both methods, we performed a detailed analysis for all objects with the ~2% highest anomaly scores. Results. We show that, in the real data scenario , AAD was able to identify ~80% more true anomalies than the IF. This result is the first evidence that AAD algorithms can play a central role in the search for new physics in the era of large scale sky surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Establishing a Theoretical Landscape for Identifying Basal Plane Active 2D Metal Borides (MBenes) toward Nitrogen Electroreduction

Abstract To achieve efficient ammonia synthesis via electrochemical nitrogen reduction reaction (NRR), a qualified catalyst should have both high specific activity and large active surface area. However, integrating these two merits into one single material remains a big challenge due to the difficulty in balancing multiple reaction intermediates. Here, it is demonstrated that the boron‐analogues of MXenes, namely “MBenes”, could cope with the challenge and achieve the high activity and large reaction region simultaneously toward NRR. Using extensive density functional theory computations and taking 16 MBenes as representatives, it is identified that seven MBenes (CrB, MoB, WB, Mo 2 B, V 3 B 4 , CrMnB 2 , and CrFeB 2 ) not only have intrinsic basal plane activity for NRR with limiting potentials ranging from −0.22 to −0.82 V, but also possess superior capability of suppressing the competitive hydrogen evolution reaction. Particularly, different from the MXenes whose surface oxidation may block the active sites, once oxidized, these MBenes can catalyze NRR via the self‐activating process, reducing O*/OH* into H 2 O* under reaction conditions, and favoring the N 2 electroreduction. As a result, the exceptional activity and selectivity, high active area (≈10 19 m −2 ), and antioxidation nature render these MBenes as pH‐universal catalysts for NH 3 production without introducing any dopants and defects.

Guo, Xiangyu↗
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2024

Antimicrobial mechanisms of g‐C 3 N 4 @ ZnO against oomycetes Phytophthora capsici: from its metabolism, membrane structures and growth

Abstract BACKGROUND Phytophthora capsici , a refractory and model oomycete plant pathogen, especially threatens multiple vegetable crops. A limited number of chemical pesticides play a vital role in controlling oomycete plant diseases. However, this approach often leads to excessive use of chemical agent, exacerbates environmental issues and more and more drug‐resistant strains of oomycete. Therefore, it is imperative to devise innovative solutions that can effectively address the infection of oomycete while maintaining high levels of environmental sustainability and low toxicity. RESULTS In this study, g‐C 3 N 4 @ZnO heterostructure was synthesized and characterized. The g‐C 3 N 4 @ZnO showed higher toxicity on Phytophthora capsici than graphitic carbon nitride (g‐C 3 N 4 ) nanosheets and zinc oxide (ZnO) nanoparticles in vitro and in vivo . Except the hyphal growth of Phytophthora capsici , their germination rate of spores, sporangium formation and number of spores were all suppressed by g‐C 3 N 4 @ZnO heterostructure. Furthermore, we found that this g‐C 3 N 4 @ZnO heterostructure has higher photocatalytic activity under visible light, which potentially enhanced the reactive oxygen species (ROS) mediated stress on Phytophthora capsici . Ultrastructural morphology, global changes of gene expression and weighted gene co‐expression network analysis all supported that the anti‐oomycete activity of g‐C 3 N 4 @ZnO was manifested in the destruction of membrane system and inhibition of multiple metabolisms of Phytophthora capsici under visible irradiation, which also could be attributed to the ROS and zinc ion (Zn 2+ ) mediated stress. CONCLUSION This works offers a novel oomycete disease management strategy by using g‐C 3 N 4 @ZnO, which were attributed to the ROS stress, destruction of membrane system and inhibition of multiple metabolisms. © 2023 Society of Chemical Industry.

Cai, Lin↗
DOE OSTI2020

Surface Charge and Electrostatic Spin Crossover Effects in CoN 4 Electrocatalysts

Carbon materials doped with nitrogen and 3d transition metals have attracted a great deal of interest for catalyzing electrochemical reactions such as water splitting, oxygen reduction, and carbon dioxide reduction. Here, we employed density functional theory to study Co–N-doped carbon as electrocatalysts for the oxygen reduction and oxygen evolution reactions. Specifically, we investigated the interplay among adsorption energies, the spin state of the CoN 4 active center, and the applied potential. We found that adsorption energies strongly depend on both the applied potential and the spin state of the Co center. Furthermore, spin state transitions induced by the applied potential also play an important role in determining the adsorption energies. Here, this effect originates from a different potential of zero charge and capacitance of each spin state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Forecasting the Solar Drivers of Severe Space Weather from Active-Region Magnetograms

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram. By empirically determining the conversion of the value of free-energy proxy measured from a GONG or HMI magnetogram to that which would be measured from an MDI magnetogram, we have made GONG and HMI magnetograms useable with our MDI-based forecasting curves to forecast event rates.

Falconer, David A.↗