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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

New directions for nanoscale thermoelectric materials research

Many of the recent advances in enhancing the thermoelectric figure of merit are linked to nanoscale phenomena with both bulk samples containing nanoscale constituents and nanoscale materials exhibiting enhanced thermoelectric performance in their own right. Prior theoretical and experimental proof of principle studies on isolated quantum well and quantum wire samples have now evolved into studies on bulk samples containing nanostructured constituents. In this review, nanostructural composites are shown to exhibit nanostructures and properties that show promise for thermoelectric applications. A review of some of the results obtained to date are presented.

thermoelectric materials↗
DOE OSTI2025

Maximizing Calendering Effects Through the Mechanical Pulverization of Co-Free Nickel-Rich Cathodes in Lithium-Ion Cells

Calendering is a technique used to maximize the volumetric energy density of battery electrodes. However, higher amounts of calendering result in increased tortuosity and particle cracking. We propose a novel packing structure of electrode particles to maximize calendering benefits while minimizing particle fracture. Cobalt-free layered oxide cathode LiNi0.92Mn0.04Al0.04O2 (NMA) particles are pulverized through ball-milling and coated with lithium phosphate. Pulverized and pristine NMA are fabricated into “bimodal” electrodes, whereas “unimodal” electrodes consist of only pristine NMA. Each electrode type was made into 30% porosity, 40% porosity, and uncalendered coin cell samples. X-ray diffraction suggests that the unimodal samples suffer from more particle fracture than the bimodal samples when calendered to the same porosity of 30%. Electrochemical impedance spectroscopy suggests that the bimodal electrodes exhibit lower surface film resistance. This is supported by enhanced capacity retention for the bimodal samples after 100 cycles.

25 ENERGY STORAGE↗
NASA NTRS2013

Atomic Force Microscope Mediated Chromatography

The atomic force microscope (AFM) is used to inject a sample, provide shear-driven liquid flow over a functionalized substrate, and detect separated components. This is demonstrated using lipophilic dyes and normal phase chromatography. A significant reduction in both size and separation time scales is achieved with a 25-micron-length column scale, and one-second separation times. The approach has general applications to trace chemical and microfluidic analysis. The AFM is now a common tool for ultra-microscopy and nanotechnology. It has also been demonstrated to provide a number of microfluidic functions necessary for miniaturized chromatography. These include injection of sub-femtoliter samples, fluidic switching, and sheardriven pumping. The AFM probe tip can be used to selectively remove surface layers for subsequent microchemical analysis using infrared and tip-enhanced Raman spectroscopy. With its ability to image individual atoms, the AFM is a remarkably sensitive detector that can be used to detect separated components. These diverse functional components of microfluidic manipulation have been combined in this work to demonstrate AFM mediated chromatography. AFM mediated chromatography uses channel-less, shear-driven pumping. This is demonstrated with a thin, aluminum oxide substrate and a non-polar solvent system to separate a mixture of lipophilic dyes. In conventional chromatographic terms, this is analogous to thin-layer chromatography using normal phase alumina substrate with sheardriven pumping provided by the AFM tip-cantilever mechanism. The AFM detection of separated components is accomplished by exploiting the variation in the localized friction of the separated components. The AFM tip-cantilever provides the mechanism for producing shear-induced flows and rapid pumping. Shear-driven chromatography (SDC) is a relatively new concept that overcomes the speed and miniaturization limitations of conventional liquid chromatography. SDC is based on a sliding plate system, consisting of two flat surfaces, one of which has a recessed channel. A fluid flow is produced by axially sliding one plate past another, where the fluid has mechanical shear forces imposed at each point along the channel length. The shear-induced flow rates are very reproducible, and do not have pressure or voltage gradient limitations. SDC opens up a new range of enhanced separation kinetics by permitting the sample confinement with submicron dimensions. Small, highly confined liquid is advantageous for chromatographic separation because the separation rate is known to scale according to the square of the confined sample diameter. In addition, because shear-driven flows are not limited by fluid velocity, shear-driven liquid chromatography may provide up to 100,000 plate efficiency.

Anderson, Mark S.↗
NASA NTRS1988

IRAS observations of an optically selected sample of interacting galaxies

IRAS observations of a large, morphologically selected sample of strongly interacting disk-type galaxies have demonstrated that galaxy-galaxy collisions can lead to enhanced infrared emission, but not in all cases. Infrared luminosities of the interacting galaxies span a large range, but are about a factor of 2 higher, on average, than those of isolated disk galaxies. The data suggest the existence of a cutoff in blue luminosity, below which no galaxies show markedly enhanced infrared emission. Only the most strongly interacting systems in the sample show extreme values of infrared excess, suggesting that deep, interpenetrating collisions are necessary to drive infrared emission to extreme levels. Comparisons with optical indicators of star formation show that infrared excess and color temperatures correlate with the level of star-formation activity in the interacting galaxies. All interacting galaxies in our sample that exhibit an infrared excess and have higher than normal color temperatures also have optical indicators of high levels of star formation. It is not necessary to invoke processes other than star formation to account for the enhanced infrared luminosity in this sample of interacting galaxies.

Bushouse, Howard A.↗
NASA NTRS2000

Ammonia 15N/14N Isotope Ratio in the Jovian Atmosphere

Data from the Galileo Probe Mass Spectrometer has been used to derive the N-15/N-14 isotope ratio in ammonia at Jupiter. Although the mass spectral interference from the water contribution to 18 amu makes an accurate derivation of the (N-15)H3/(N-14)H3 ratio difficult from measurements of the singly ionized signals at 18 and 17 amu, this interference is not present in the doubly charged 8.5 and 9.0 amu signals from (N-14)H3++ and (N-15)H3++ respectively. Although the count rate from the 9 amu signal is low during the direct sampling of the atmosphere, the ammonia signal was considerably enhanced during the first enrichment cell (EC1) experiment that measured gas sampled between 0.8 and 2.8 bar. Count rates at 9 amu in the EC1 experiment reach 60/second and measure ammonia sampled from 0.88 to 2.8 bar. In the EC1 measurements the 8.5 amu signal is not measured directly, but can be calculated from the ammonia contribution to 17 amu and the ratio of NH3 ions of a double to single charged observed during a high resolution mass scan taken near the end of the descent. The high resolution scan gives this ratio from ammonia sampled much deeper in the atmosphere. These results are described and compared with Infrared Space Observatory-Short Wavelength Spectrometer (ISO-SWS) observations that give this ratio at 400 mbar.

Mahaffy, P.R.↗
NASA NTRS2013

Method for Processing Lunar Regolith Using Microwaves

A paper describes a method of using microwave heating experiments on lunar simulants to determine the mechanism that causes lunar regolith to be such an excellent microwave absorber. The experiments initially compared the effects of sharp particle edges to round particle edges on the heating curves. For most compositions, sharp particle edged samples were more effective in being heated by microwaves than round particle edged materials. However, the experiments also showed an unexpected effect for both types of particles. Upon heating the sample surface above 400 C, the sample experienced some sort of internal structure change that caused it to heat much more efficiently. This enhancement may be associated with the unique microwave volumetric heating that can produce a large temperature gradient within the sample leading to melting of some components at the center of the sample. This new effect that may also be happening in lunar regolith samples is probably the cause of the previously observed enhanced heating of a sample of lunar regolith. Properly designed microwave applicators could heat and solidify the lunar regolith to form roads and building blocks for structures needed on the Moon

Barmatz, Martin B.↗
DOE OSTI2025

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Support modification by phosphonic acid ligands controls ethylene hydroformylation on single-atom rhodium sites

To investigate the ability of surface-bound ligands to control activity toward ethylene hydroformylation, we modified site-isolated Rh 1 /TiO 2 with a series of substituted benzyl phosphonic acids. We found that modification of the support by phosphonic acids reduced break-in times for hydroformylation by 4× and increased absolute hydroformylation activity by up to 18× compared to unmodified catalyst at 150 °C. All functionalized catalysts improved hydroformylation activity by at least 9× and improved selectivity by between 7× and 60× relative to the unmodified catalyst. Carbon monoxide probe–molecule spectroscopy indicated that the enhancements in activity among modified samples were due to changes in the local environment of the active Rh site. Specifically, the bite angle of adsorbed carbon monoxide, as determined from infrared spectra, correlated with hydroformylation activity. These findings demonstrate that Rh 1 active sites are highly sensitive to modification of the support with organic ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

D–MOPH–25: diverse MOF–molecule pairs for Henry’s constants prediction

Computational methods like grand-canonical Monte Carlo simulations and machine learning (ML) have accelerated metal–organic frameworks (MOF) exploration but are typically limited to a narrow range of adsorbates due to data availability and force field constraints. In this study, we introduce a dataset of diverse MOF–molecule pairs for Henry’s constant prediction, D–MOPH–25, which systematically explores a diverse chemical space by combining 113 molecular adsorbates with over 5000 MOF structures through an active learning process. D–MOPH–25 constitutes the most diverse adsorbate dataset used in any ML study of molecular adsorption in MOFs to date. Our workflow builds a benchmark for predicting Henry’s constants at 300 K, leveraging conformal prediction for uncertainty quantification. Assessment through Shannon entropy and uniform manifold approximation and projection confirms the comprehensiveness of D–MOPH–25 while highlighting the importance of robust classification to filter out unphysical data points in regression tasks. Although future enhancements in model architecture and sampling criteria could improve predictive performance, our dataset already spans the target space using only 2.31% of total possibilities. This comprehensive dataset facilitates assessment of model generalizability across adsorbate species and can establish a foundation for high-throughput MOF screening and ML-driven separation processes.

active learning↗
DOE OSTI2024

Selective laser sintering and spark plasma sintering of (Zr,Nb,Ta,Ti,W)C compositionally complex carbide ceramics

Abstract Two advanced manufacturing processes, spark plasma sintering (SPS) and selective laser sintering (SLS), have been developed for synthesis of (Zr,Nb,Ta,Ti,W)C compositionally complex carbide (CCC) via reactive sintering of a powder mixture of constitute monocarbides. X‐ray diffraction analysis confirmed that the single‐phase CCC can be formed by both SPS and SLS. While a homogenous microstructure with uniform metal element distributions was developed during SPS, three‐layer microstructures with a thin TiC‐rich layer and two TaC‐rich layers along with a TiO 2 ‐rich surface layer containing W nanoparticles were formed during SLS. In addition, cellular structures with W, Zr, and Ti element segregation and dislocations on cell boundaries were observed in the SLS‐CCC sample, indicating the effect of nonequilibrium conditions on microstructure formation during laser melting followed by rapid cooling and solidification process. Compared to the SPS‐CCC sample, the SLS‐CCC showed enhanced hardness and reduced thermal conductivity, which may be related to their unique cellular structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Contribution of coherent electron production to measurements of heavy-flavor decayed electrons in heavy-ion collisions

Abstract Heavy quarks, produced at early stages of heavy-ion collisions, are an excellent probe of the Quark-Gluon Plasma (QGP) also created in these collisions. Electrons from open heavy-flavor hadron decays (HFE) are good proxies for heavy quarks, and have been measured extensively in the last two decades to study QGP properties. These measurements are traditionally carried out by subtracting all known background sources from the inclusive electron sample. More recently, a significant enhancement of $$e^+e^-$$ e + e - pair production at very low transverse momenta was observed in peripheral heavy-ion collisions. The production characteristics is consistent with coherent photon–photon interactions, which should also constitute a background source to the HFE measurements. In this article, we provide theoretical predictions for the contribution of coherent electron production to HFEs as a function of transverse momentum, centrality and collision energy in Au+Au and Pb+Pb collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Superconducting nanowire single-photon detector enhanced near-infrared II portable confocal microscopy for tissue imaging with indocyanine green

In this Letter a novel, to our knowledge, approach for near-infrared (NIR) fluorescence portable confocal microscopy is introduced, aiming to enhance fluorescence imaging of biological samples in the NIR-II window. By integrating a superconducting nanowire single-photon detector (SNSPD) into a confocal microscopy, we have significantly leveraged the detection efficiency of the NIR-II fluorescence signal from indocyanine green (ICG), an FDA-approved dye known for its NIR-II fluorescence capabilities. The SNSPD, characterized by its extremely low dark count rate and optimized NIR system detection efficiency, enables the excitation of ICG with 1 mW and the capture of low-light fluorescence signals from deep regions (up to 512 µm). Consequently, our technique was able to produce high-resolution images of bio samples with a superior signal-to-noise ratio, making a substantial advancement in the field of fluorescence microscopy and offering a promising opportunity for future clinical study.

Liu, Yifan (ORCID:0000000328877704)↗
DOE OSTI2025

Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems

Resource allocation in High Performance Computing (HPC) environments presents a complex and multifaceted challenge for job scheduling algorithms. Beyond the efficient allocation of system resources, schedulers must account for and optimize multiple performance metrics, including job wait time and system throughput. Traditional heuristic-based scheduling algorithms increasingly struggle and lack the efficiency needed to meet the demands and address the complexity and scale of modern HPC systems. Consequently, recent research efforts have focused on leveraging advancements in Artificial Intelligence (AI) and Deep Learning (DL), particularly Reinforcement Learning (RL), to develop more adaptable and intelligent scheduling strategies. Previous RL-based scheduling approaches have explored a range of algorithms, from Deep Q-Networks (DQN) to Proximal Policy Optimization (PPO), and more recently, hybrid methods that integrate Graph Neural Networks (GNNs) with RL techniques. However, a common limitation across these methods is their reliance on relatively small datasets, with few methods being evaluated using large-scale, multi-million-job trace datasets representative of real-world HPC workloads. Moreover, existing RL schedulers face scalability issues due to centralized policy updates, which hinder training efficiency and performance when applied to large datasets. This study introduces a novel RL-based scheduler utilizing Decentralized Distributed Proximal Policy Optimization (DD-PPO) algorithm, which supports large-scale distributed training across multiple workers without requiring parameter synchronization at every step. By eliminating reliance on centralized updates to a shared policy, the DD-PPO scheduler enhances scalability, training efficiency, and sample utilization. Experimental validation using a large real-world dataset containing over 11.5 million job traces collected from petascale HPC systems over six years assesses the influence of dataset scale on training effectiveness and compares DD-PPO performance to traditional and advanced scheduling approaches. The experimental results demonstrate improved scheduling performance in comparison to both heuristic-based schedulers and existing RL-based scheduling algorithms.

AI↗
NASA NTRS1977

Volatile products from the interaction of KCl(g) with Cr2O3 and LaCrO3 in oxidizing environments

Cooled target collection techniques and high pressure mass spectrometric sampling were used to measure the relative rates of oxidative vaporization and to identify the volatile products emanating from samples of chromia and Mg-doped lanthanum chromite. The materials were exposed to partial pressures of KCl with and without H2O in one atmosphere of slowly flowing oxygen at elevated temperatures. Chromia and fresh samples of lanthanum chromite exhibited enhanced rates of oxidative vaporization upon exposure to these reactants. Mass spectrometric identification showed that the enhancements resulted from the heterogeneous formation of complex molecules of the type KCl sub 1,2,3 CrO3 and KOH sub l,2 CrO3. Lanthanum chromite that had undergone prolonged oxidative vaporization exhibited no enhanced oxidation upon exposure to the reactants.

Kohl, F. J.↗
NASA NTRS1983

Environmental data display

Methods for using a combination of computer-generated color graphics and image processing techniques to display a large data base of environment information are described. The data source can be either field data or mathematical models, reduced to summary statistics that characterize the data field as a whole. Sharp gradients are plotted into contour plots, which can also feature shades, degree of brightness, and saturation levels for fine-tuning the image. The basic concepts of digital image processing are reviewed, including location of the pixels, intensity mapping operations, pseudocolor enhancements, neighborhood averaging, and smoothing. Sample applications are presented in terms of emissions and air quality distributions over the south coast air basin of southern California.

Hussey, K. J.↗
NASA NTRS1990

Macromolecular assemblies in reduced gravity environments

The assembly of protein macro molecules into structures commonly produced within biological systems was achieved using in vitro techniques carried out in nominal as well as reduced gravity environments. Appropriate hardware was designed and fabricated to support such studies. Experimental protocols were matched to the available reduced gravity test opportunities. In evaluations of tubulin, fibrin and collagen assembly products the influence of differing gravity test conditions are apparent. Product homogeneity and organization were characteristic enhancements documented in reduced gravity samples. These differences can be related to the fluid flow conditions that exist during in vitro product formation. Reduced gravity environments may provide a robust opportunity for directing the products formed in a variety of bioprocessing applications.

Moos, Philip J.↗
NASA NTRS1991

Solar particle abundances at energies of greater than 1 MeV per nucleon and the role of interplanetary shocks

The abundances of elements in large solar energetic-particle events in the energy range of 2-12 MeV per nucleon are examined. It is confirmed that the abundances relative to mean values vary approximately monotonically as a function of mass, except for He-4; some events show a gradual depletion of heavy ions, whereas a small number displays a gradual increase. A further organization of abundance data is shown, which depends on the longitude of the source region. Enhancements in Fe/C and other heavy elements relative to C occur when source regions are near west 60 deg; the enhancements are attributed to the sampling of a flare-heated material. Depletions of these elements are found to be greatest for source regions near central meridian; they are matched by a steepening of the spectrum and can be understood in terms of diffusive shock acceleration.

Cane, H. V.↗
NASA NTRS1991

Distances to diffuse interstellar clouds from IRAS measurements and observations of optical absorption lines

Distances to diffuse interstellar clouds were determined from the amount of ultraviolet radiation that penetrates into the cloud and that arises from a nearby B star. The environment around 67 Ophiuchi, 20 Aquilae, kappa Aquilae, and 9 Cephei were studied. The intensities at 60 and 100 micron, as measured by IRAS, were used to derive dust temperatures for the clouds. Enhanced dust temperatures would indicate an influence of the star's radiation field on a cloud. Observation of molecular absorption were compared to the results of simplified chemical models in order to search for enhanced photodissociation that is caused by the star. Enhanced dust temperatures were observed for clouds in the vicinities of 20 Aql, kappa Agl, and 9 Cep. The range of the star's influence was found to be typically 1-5 pc. On the other hand, chemical analyses of the molecular data, which pertain to foreground gas, did not reveal the presence of enhanced dissociative flux from the sample of stars. Thus, upper limits were derived for the distances from the sun to the foreground material.

Federman, S. R.↗