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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Discovery of LaAlO 3 as an efficient catalyst for two-electron water electrolysis towards hydrogen peroxide

Electrochemical two-electron water oxidation reaction (2e-WOR) has drawn significant attention as a promising process to achieve the continuous on-site production of hydrogen peroxide (H 2 O 2 ). However, compared to the cathodic H 2 O 2 generation, the anodic 2e-WOR is more challenging to establish catalysts due to the severe oxidizing environment. In this study, we combine density functional theory (DFT) calculations with experiments to discover a stable and efficient perovskite catalyst for the anodic 2e-WOR. Our theoretical screening efforts identify LaAlO 3 perovskite as a stable, active, and selective candidate for catalyzing 2e-WOR. Our experimental results verify that LaAlO 3 achieves an overpotential of 510 mV at 10 mA cm -2 in 4 M K 2 CO 3 /KHCO 3 , lower than those of many reported metal oxide catalysts. In addition, LaAlO 3 maintains a stable H 2 O 2 Faradaic efficiency with only a 3% decrease after 3 h at 2.7 V vs. RHE. This computation-experiment synergistic approach introduces another effective direction to discover promising catalysts for the harsh anodic 2e-WOR towards H 2 O 2 .

08 HYDROGEN↗
DOE OSTI2024

Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease.

Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Molecular Transformation and Metabolic Insights of Microbial Electrolysis Treatment and Valorization of Post-hydrothermal Liquefaction Wastewater

Hydrothermal liquefaction (HTL) presents a promising approach for the conversion of wet waste into biocrude and biofuels. However, the post-hydrothermal liquefaction wastewater (PHW) poses significant challenges for treatment and valorization due to its high concentration and complex nature. In this study, we investigated the conversion pathways of major organic contaminants within the microbial electrolytic treatment of PHW from food waste HTL. To achieve this, we employed high-performance liquid chromatography (HPLC) and 2D nuclear magnetic resonance (NMR). Our findings demonstrate volatile fatty acids (VFAs) and monohydric and polyhydric alcohols were effectively transformed through the synergistic metabolism of fermentative and electroactive bacteria, which led to over 70% COD removal of the recalcitrant compounds and a record high H2 production rate (1.62 L L -1 d -1 ). We also employed the liquid-state 15N NMR on wastewater samples for the first time and revealed that the nitrogen-containing heteroaromatics were persistent to microbial electrochemical treatment. By integrating the chemical profiles with bioanode community profiles, we constructed a metabolic network that provides insights for enhancing treatment efficiency and facilitating resource recovery.

08 HYDROGEN↗
DOE OSTI2022

Reduced defect recovery in self-ion damaged W due to simultaneous deuterium exposure during annealing

Deuterium (D) plasma exposure during annealing of self-ion damaged tungsten (W) is shown to exhibit reduced defect recovery when compared to annealing without D plasma exposure. In these experiments, samples were first damaged with 20 MeV W ions. Next, samples were annealed either with or without simultaneous D 2 plasma exposure. The simultaneous annealed samples were first decorated by D 2 plasma at 383 K prior to ramping up to an annealing temperature of 473, 573, 673, or 773 K and held for 1 h with concurrent plasma exposure. The vacuum annealed samples each had a corresponding temperature history but without D 2 plasma treatment. Finally, all samples were exposed to D 2 plasma at 383 K to decorate any remaining defects. Nuclear reaction analysis and thermal desorption spectroscopy (TDS) shows that the simultaneous plasma-exposed and annealed samples exhibited virtually no defect recovery at annealing temperatures of up to 673 K, and had higher D retention than found in the vacuum annealed samples. TDS results indicate that only the lowest detrapping energy defects recover at an 773 K anneal for the simultaneous plasma annealed samples, while the vacuum annealed samples showed defect recovery at all anneal temperatures. Furthermore, this experiment clearly demonstrates that D occupied defects can significantly reduce or eliminate defect annealing in W, and is consistent with the existence of synergistic plasma exposure/displacement damage effects in fusion-energy relevant plasma facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Conformal Pressure and Fast-Charging Li-Ion Batteries

Batteries capable of extreme fast-charging (XFC) are a necessity for the deployment of electric vehicles. Material properties of electrodes and electrolytes along with cell parameters such as stack pressure and temperature have coupled, synergistic, and sometimes deleterious effects on fast-charging performance. We develop a new experimental testbed that allows precise and conformal application of electrode stack pressure. We focus on cell capacity degradation using single-layer pouch cells with graphite anodes, LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) cathodes, and carbonate-based electrolyte. In the tested range (10–125 psi), cells cycled at higher pressure show higher capacity and less capacity fading. Additionally, Li plating decreases with increasing pressure as observed with scanning electron microscopy (SEM) and optical imaging. While the loss of Li inventory from Li plating is the largest contributor to capacity fade, electrochemical and SEM examination of the NMC cathodes after XFC experiments show increased secondary particle damage at lower pressure. We infer that the better performance at higher pressure is due to more homogeneous reactions of active materials across the electrode and less polarization through the electrode thickness. Our study emphasizes the importance of electrode stack pressure in XFC batteries and highlights its subtle role in cell conditions.

25 ENERGY STORAGE↗
NASA NTRS1987

Strong metal-support interactions

It has been demonstrated that synergistic metal-support effects can occur which markedly enhance specific activity and alter selectivity in certain reactions. Because of the presence of such effects in certain reactions conducted under reducing conditions (that is, under H2 pressure), but not others, the creation of unique sites at the metal-support interface seems to be the best model at the present time to explain this behavior. The postulation of these sites, which are specific for a certain reactant such as CO, provides an effective explanation for the higher methanation rates that have been reported over some catalysts. The creation of these sites in the adlineation zone is facilitated by hydrogen spillover from the metal surface, and this same process can also enhance the reduction of many oxide supports. Although oxygen spillover is much less probable due to its higher heat of adsorption, it is much less well understood and the possibility of rate enhancements in CO oxidation caused by special interface sites cannot be discounted at the present time. Consequently, this seems to be an important area of future research.

Vannice, M. Albert↗
NASA NTRS2019

Proceedings of the NASA Technical Interchange Meeting on Active Optical Systems for Supporting Science, Exploration, and Aeronautics Measurements Needs

Active optical (Laser/Lidar) measurement techniques are critical for the future National Aeronautics and Space Administration (NASA) Earth, Planetary Science, Exploration, and Aeronautics measurements. The latest science decadal surveys recommend a number of missions requiring active optical systems to meet the science measurement objectives and the aeronautics community continues to use Laser/Lidar technologies to meet the aeronautics measurement objectives. With these drivers, the NASA Agency Program Management Council (APMC), chaired by the NASA Associate Administrator, has tasked the NASA Sensors and Instrumentation (S&I) Capability Leadership Team (CLT) Leader to determine if the Agency has the necessary expertise and capabilities to execute successfully the active optical-based systems necessary to make the required measurements for Science, Exploration, and Aeronautics. This NASA Technical Interchange Meeting (TIM) was a forum to exchange perspectives on the current state of the discipline’s technologies and the direction NASA needs to take in the future to raise the Technical Readiness Level (TRL) of the measurement technologies to meet these measurement needs in the applications domains. The information developed at this TIM was used in formulating the Agency-level strategy and solutions for advancing high-risk Laser/Lidar technologies that are not currently being sufficiently planned, developed, or risk-reduced to meet NASA’s mission requirements. Given the crosscutting synergies in critical Active Optical measurements for NASA Science, Exploration, and Aeronautics, a strategic approach is needed to identify areas where NASA should “lead, leverage or collaborate” with existing national and international industries to meet its future needs. The TIM aimed at focusing NASA’s directions to attain the necessary TRLs to meet the Agency-level priority Active Optical measurements in Space and Aeronautics. The TIM presentations and strategic inputs were synthesized by the NASA Active Optical Tiger Team for presentation to the NASA APMC with a suggested strategy to address the Agency’s needs in a crosscutting, synergistic and cost-effective manner.

Singh, Upendra N↗
DOE OSTI2026

Photooxidation of Organic Sulfide Enhanced by Heavy Atom Effect in Porphyrin Metal–Organic Frameworks with a Sea Topology

The photoactivity of three porphyrin-based metal-organic frameworks (PMOFs) incorporating Al, Ga, and In nodes was systematically evaluated using the photooxidation of an organic sulfide (2-chloroethyl ethyl sulfide, or CEES; a mustard gas simulant). Faster photodegradation of CEES was observed for PMOFs with heavier metal nodes, placing In-PMOF as the most efficient photocatalyst in the series. Guided by this insight, we developed CSLA-10, a MOF integrating In nodes and Sn-doped porphyrin linker to synergistically amplify heavy-atom effects at both the nodes and ligand levels. CSLA-10 exhibited the fastest reported CEES photooxidation to date, achieving a half-life of 38 s in methanol under blue LED irradiation. When grafted onto textiles, CSLA-10 enabled solvent-free CEES degradation in air/O 2 with a half-life of 2.7 min and complete conversion within 7 min, representing the most rapid full degradation reported under solvent-free conditions. Furthermore, this work establishes a dual heavy-atom strategy for enhancing intersystem crossing and singlet oxygen generation in porphyrin MOFs, providing a rational design principle for next-generation photocatalysts for the degradation of toxic organic sulfides.

Metal-organic frameworks↗
DOE OSTI2022

Enhancing glycerol electrooxidation from synergistic interactions of platinum and transition metal carbides

To effectively utilize glycerol as a fuel for electrochemical fuel cells, it is necessary to optimize catalysts for effective C-C bond cleavage and complete oxidation of reaction intermediates to achieve maximum efficiency. Here, the current work showed that the synergistic interactions of platinum (Pt) with transition metal carbide (TMC) substrates, such as tungsten carbide (WC) and tantalum carbide (TaC), fulfilled these criteria. The TMC-supported Pt catalysts showed higher activity and selectivity for complete glycerol oxidation than commercial 10 wt% Pt/C. In-situ FTIR analysis revealed that 5 wt% Pt/WC was the most effective catalyst among those tested for complete glycerol oxidation at 0.9 V vs RHE. In-situ X-ray absorption fine structure characterization and density functional theory calculations provided additional insight into the synergistic interactions for glycerol oxidation over Pt/TMC catalysts.

25 ENERGY STORAGE↗
DOE OSTI2025

Computational alchemy clarifies origins of alloy strengthening

Solid solution strengthening (SSS) is widely used to enhance mechanical properties of metals. Originally developed for dilute alloys, classical SSS theories are presently challenged by the rise of complex concentrated alloys (CCA) with nearly equiatomic compositions. Here, we propose and develop a method of “computational alchemy” in which interatomic interactions are modified to systematically vary two key physical parameters defining SSS - atomic size misfit and elastic stiffness misfit - over a maximally wide range of two misfits. The resulting alchemical alloys are subjected to massive (~10 8 atoms) molecular dynamics (MD) simulations reproducing full complexity of plastic strength response. At variance with prevailing views, stiffness misfit is observed to contribute to SSS on par if not more than size misfit. Furthermore, depending on exactly how two misfits are combined, they result in synergistic (amplification) or antagonistic (compensation) effect on alloy strengthening. Unlike real CCAs in which each component element comes with its own specific size and stiffness, our alchemical model alloys span the space of two misfits continuously revealing trends in alloy strengthening unrecognized so far. Our study demonstrates unique value of intentionally unrealistic models for gaining deep physical insights into material behaviors that are difficult to reveal otherwise.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Perspectives on Machine Learning-assisted Plasma Medicine: Towards Automated Plasma Treatment

Cold atmospheric plasmas (CAPs) have shown great promise for medical applications through their synergistic chemical, electrical, and thermal effects, which can induce therapeutic outcomes. However, safe and reproducible plasma treatment of complex biological surfaces poses a major hurdle to the widespread adoption of CAPs for medical applications. Predictive modeling of the mutual interactions between the plasma and biological surfaces and, thus, systematic approaches to quantify and predict plasma treatment outcomes remain largely elusive due to the lack of mechanistic understanding of plasma-surface interactions that can span across vastly different length-and time-scales. In addition, real-time sensing capabilities in biomedical CAP devices are often limited, which can be detrimental to plasma treatment due to the intrinsic plasma and surface variability during the treatment, as well as sensitivity to external perturbations. All of these challenges can make reproducible and effective plasma treatment of biological surfaces difficult to realize, which is further compounded by errors due to human operation of hand-held CAP devices. Machine learning and data-driven approaches can be particularly useful in addressing these challenges in three major ways: (i) data-driven modeling of hard-to-model plasma-surface interactions and plasma treatment outcomes; (ii) learning data analytics for plasma and surface diagnostics in real-time; and (iii) developing predictive controllers that enable reliable and effective CAP treatments. Furthermore, this paper discusses the promise of machine learning to accelerate plasma medicine research in these areas, toward machine learning-assisted and automated CAP treatment of complex biological surfaces.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

The role of the Long Duration Exposure Facility in the development of space systems

The Long Duration Exposure Facility (LDEF) presents the international, aerospace community with an unprecedented opportunity to examine the synergistic, long term, space environmental effects on systems and materials. The analysis of the data within appropriate environmental contexts is essential to the overall process of advancing the understanding of space environmental effects needed for the continuing development of strategies to improve the reliability and durability of space systems and to effectively deal with the future challenges that new space initiatives will likely present.

Sally A. Little↗
NASA NTRS1999

Mesoscale Simulations of a Florida Sea Breeze Using the PLACE Land Surface Model Coupled to a 1.5-Order Turbulence Parameterization

A sophisticated land-surface model, PLACE, the Parameterization for Land Atmospheric Convective Exchange, has been coupled to a 1.5-order turbulent kinetic energy (TKE) turbulence sub-model. Both have been incorporated into the Penn State/National Center for Atmospheric Research (PSU/NCAR) mesoscale model MM5. Such model improvements should have their greatest effect in conditions where surface contrasts dominate over dynamic processes, such as the simulation of warm-season, convective events. A validation study used the newly coupled model, MM5 TKE-PLACE, to simulate the evolution of Florida sea-breeze moist convection during the Convection and Precipitation Electrification Experiment (CaPE). Overall, eight simulations tested the sensitivity of the MM5 model to combinations of the new and default model physics, and initialization of soil moisture and temperature. The TKE-PLACE model produced more realistic surface sensible heat flux, lower biases for surface variables, more realistic rainfall, and cloud cover than the default model. Of the 8 simulations with different factors (i.e., model physics or initialization), TKE-PLACE compared very well when each simulation was ranked in terms of biases of the surface variables and rainfall, and percent and root mean square of cloud cover. A factor separation analysis showed that a successful simulation required the inclusion of a multi-layered, land surface soil vegetation model, realistic initial soil moisture, and higher order closure of the planetary boundary layer (PBL). These were needed to realistically model the effect of individual, joint, and synergistic contributions from the land surface and PBL on the CAPE sea-breeze, Lake Okeechobee lake breeze, and moist convection.

Lynn, Barry H.↗
NASA NTRS2004

Effects of Various Wavelength Ranges of Vacuum Ultraviolet Radiation on Teflon FEP Film Investigated

Teflon Fluorinated Ethylene Propylene (FTP) films (DuPont) have been widely used for spacecraft thermal control and have been observed to become embrittled and cracked upon exposure to the space environment. This degradation has been attributed to a synergistic combination of radiation and thermal effects. A research study was undertaken at the NASA Glenn Research Center to examine the effects of different wavelength ranges of vacuum ultraviolet (VUV) radiation on the degradation of the mechanical properties of FEP. This will contribute to an overall understanding of space radiation effects on Teflon FEP, and will provide information necessary to determine appropriate techniques for using laboratory tests to estimate space VUV degradation. Research was conducted using inhouse facilities at Glenn and was carried out, in part, through a grant with the Cleveland State University. Samples of Teflon FEP film of 50.8 microns thickness were exposed to radiation from a VUV lamp from beneath different cover windows to provide different exposure wavelength ranges: MgF2 (115 to 400 nm), crystalline quartz (140 to 400 nm), and fused silica (FS, 155 to 400 nm). Following exposure, FEP film specimens were tensile tested to determine the ultimate tensile strength and elongation at failure as a function of the exposure duration for each wavelength range. The graphs show the effect of ultraviolet exposure on the mechanical properties of the FEP samples.

Dever, Joyce A.↗
DOE OSTI2025

From Pollutant Removal to Renewable Energy: MoS2-Enhanced P25-Graphene Photocatalysts for Malathion Degradation and H2 Evolution

The widespread presence of pesticides—especially malathion—in aquatic environments presents a major obstacle to conventional remediation strategies, while the ongoing global energy crisis underscores the urgency of developing renewable energy sources such as hydrogen. In this context, photocatalytic water splitting emerges as a promising approach, though its practical application remains limited by poor charge carrier dynamics and insufficient visible-light utilization. Herein, we report the design and evaluation of a series of TiO2-based ternary nanocomposites comprising commercial P25 TiO2, reduced graphene oxide (rGO), and molybdenum disulfide (MoS2), with MoS2 loadings ranging from 1% to 10% by weight. The photocatalysts were fabricated via a two-step method: hydrothermal integration of rGO into P25 followed by solution-phase self-assembly of exfoliated MoS2 nanosheets. The composites were systematically characterized using X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), UV-Vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) spectroscopy. Photocatalytic activity was assessed through two key applications: the degradation of malathion (20 mg/L) under simulated solar irradiation and hydrogen evolution from water in the presence of sacrificial agents. Quantification was performed using UV-Vis spectroscopy, gas chromatography–mass spectrometry (GC-MS), and thermal conductivity detection (GC-TCD). Results showed that the integration of rGO significantly enhanced surface area and charge mobility, while MoS2 served as an effective co-catalyst, promoting interfacial charge separation and acting as an active site for hydrogen evolution. Nearly complete malathion degradation (~100%) was achieved within two hours, and hydrogen production reached up to 6000 µmol g−1 h−1 under optimal MoS2 loading. Notably, photocatalytic performance declined with higher MoS2 content due to recombination effects. Overall, this work demonstrates the synergistic enhancement provided by rGO and MoS2 in a stable P25-based system and underscores the viability of such ternary nanocomposites for addressing both environmental remediation and sustainable energy conversion challenges.

Chemistry↗
NASA NTRS1990

The role of the Long Duration Exposure Facility in the design of the Space Station Freedom

The Long Duration Exposure Facility (LDEF) satellite retrieved this year by the U.S. Space Shuttle offers spacecraft designers an unprecedented opportunity to examine synergistic, long-term space environmental effects on systems and materials. This paper discusses the strategy for data development and the role its implementation will play in the design of the Space Station Freedom. Examples are provided from three key areas (environments definition, protection of external surfaces, and verification of system components) to illustrate LDEF's potential contribution.

Little, S. A.↗
NASA NTRS2002

Commercial Research and Development: Power to Explore, Opportunities from Discovery

The technical and economic goals of commercial use of space are laudable, and are addressed as a high priority by almost every national space program and most major aerospace companies the world over. Yet, the focus of most organizational agendas and discussions tends to focus on one or two very narrow enabling aspects of this potentially large technological and economic opportunity. While government sponsored commercial launch activities and private space platforms are an integral part of efforts to leverage the commercial use of space, these activities are possibly one of the smallest parts of creating, a viable and sustainable market for the commercial use of space. Most of the current programs usually do not appropriately address some of the critical issues of the current, already interested, potential space user communities. Current programs place the focus of the majority of the user requirements on the vehicle payload weight and mass performance considerations as the primary payload economical factor in providing a commercial market with a stimulating price for gaining access to the space environment. The larger user challenges of transformation from Earth-based research and development approaches to space environment approaches are not addressed early enough in programs to impact the new business considerations of potential users. Currently, space-based research and development user activities require a large user investment in time, in development of new areas of support expertise, in development of new systems, in risk of schedule to completion, and in long term capital positioning. The larger opportunities for stimulating a strong market driven interest in commercial use of space that could result from the development of vehicle payload "leap ahead technologies" for users are being missed, and there is a real risk of limiting the potentially broader market base to support a more technologically advanced and economically lucrative outcome. A major driving force for strengthening the commercial space activities is not only the technological advances in launch vehicle, or newer satellites, but the myriad of enabling payloads technologies that could, as a goal, result in an almost transparent facilitation to regular CD a, -n access to space and microgravity environments by the future users from the existing Earth-based research and development organizations market segments. Rather than focusing only on developing high lift performance launch vehicles and then developing payloads to fit them, the real focus from a business model perspective should to be on the customer payloads requirements, and on designing launch vehicles and platforms systems for a space transportation and facility infrastructure to support all aspects of the business model for the user market. To harness the full potential of space commercialization, new efforts need to be made to comprehensively examine all the critical business model areas for commercial research, development, and manufacturing in space so as to identify specific products and efforts; to determine how such operations must be both similar to and different from current Earth-based activities; to evaluate the enabling technological devices, processes and efforts so that like efforts can be addressed in a synergistic fashion for maximum user cost effectiveness; to delineate the services that are both needed and can be provided by such activities; and to use this information to drive design and development of space commercialization efforts and policy.

Casas, Joseph C.↗
DOE OSTI2020

Prediction of histone post-translational modifications using deep learning

Abstract Motivation Histone post-translational modifications (PTMs) are involved in a variety of essential regulatory processes in the cell, including transcription control. Recent studies have shown that histone PTMs can be accurately predicted from the knowledge of transcription factor binding or DNase hypersensitivity data. Similarly, it has been shown that one can predict PTMs from the underlying DNA primary sequence. Results In this study, we introduce a deep learning architecture called DeepPTM for predicting histone PTMs from transcription factor binding data and the primary DNA sequence. Extensive experimental results show that our deep learning model outperforms the prediction accuracy of the model proposed in Benveniste et al. (PNAS 2014) and DeepHistone (BMC Genomics 2019). The competitive advantage of our framework lies in the synergistic use of deep learning combined with an effective pre-processing step. Our classification framework has also enabled the discovery that the knowledge of a small subset of transcription factors (which are histone-PTM and cell-type-specific) can provide almost the same prediction accuracy that can be obtained using all the transcription factors data. Availabilityand implementation https://github.com/dDipankar/DeepPTM. Supplementary information Supplementary data are available at Bioinformatics online.

Baisya, Dipankar Ranjan (ORCID:0000000267847359)↗