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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Nanophase and Composite Optical Materials

This talk will focus on accomplishments, current developments, and future directions of our work on composite optical materials for microgravity science and space exploration. This research spans the order parameter from quasi-fractal structures such as sol-gels and other aggregated or porous media, to statistically random cluster media such as metal colloids, to highly ordered materials such as layered media and photonic bandgap materials. The common focus is on flexible materials that can be used to produce composite or artificial materials with superior optical properties that could not be achieved with homogeneous materials. Applications of this work to NASA exploration goals such as terraforming, biosensors, solar sails, solar cells, and vehicle health monitoring, will be discussed.

Source record↗
NASA NTRS2013

Chromatin Folding, Fragile Sites, and Chromosome Aberrations Induced by Low- and High- LET Radiation

We previously demonstrated non-random distributions of breaks involved in chromosome aberrations induced by low- and high-LET radiation. To investigate the factors contributing to the break point distribution in radiation-induced chromosome aberrations, human epithelial cells were fixed in G1 phase. Interphase chromosomes were hybridized with a multicolor banding in situ hybridization (mBAND) probe for chromosome 3 which distinguishes six regions of the chromosome in separate colors. After the images were captured with a laser scanning confocal microscope, the 3-dimensional structure of interphase chromosome 3 was reconstructed at multimega base pair scale. Specific locations of the chromosome, in interphase, were also analyzed with bacterial artificial chromosome (BAC) probes. Both mBAND and BAC studies revealed non-random folding of chromatin in interphase, and suggested association of interphase chromatin folding to the radiation-induced chromosome aberration hotspots. We further investigated the distribution of genes, as well as the distribution of breaks found in tumor cells. Comparisons of these distributions to the radiation hotspots showed that some of the radiation hotspots coincide with the frequent breaks found in solid tumors and with the fragile sites for other environmental toxins. Our results suggest that multiple factors, including the chromatin structure and the gene distribution, can contribute to radiation-induced chromosome aberrations.

Zhang, Ye↗
DOE OSTI2026

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗
NASA NTRS2000

A Technique for Rapidly Deploying a Concentration Gradient with Applications to Microgravity

The latter half of the last century has seen rapid advancements in semiconductor crystal growth powered by the demand for high performance electronics in myriad applications. The reduced gravity environment of space has also been used for crystal growth tests, especially in instances where terrestrial growth has largely been unsuccessful. While reduced gravity crystal growth affords some control of the gravity parameter, many crystals grown in space, to date, have structural flaws believed to result from convective motions during the growth phase. The character of these instabilities is not well understood but is associated with thermal and solutal density variations near the solidification interface in the presence of residual gravity and g-jitter. In order to study these instabilities in a separate, controlled space experiment, a concentration gradient would first have to be artificially established in a timely manner as an initial condition. This is generally difficult to accomplish in a microgravity environment because the momentum of the fluid injected into a test cell tends to swirl around and mix in the absence of a restoring force. The use of magnetic fields to control the motion and position of liquids has received growing interest in recent times. The possibility of using the force exerted by a non-uniform magnetic field on a ferrofluid to not only achieve fluid manipulation but also to actively control fluid motion makes it an attractive candidate for space applications. This paper describes a technique for quickly establishing a linear or exponential fluid concentration gradient using a magnetic field in place of gravity to stabilize the deployment. Also discussed is a photometric technique for measuring the concentration profile using light attenuation. Results of the ground-based experiments indicate that the concentration distribution is within 3% of the predicted value. Although any range of concentations can be realized, photometric constraints are discussed which impose some limitations on measurements.

Leslie, Fred↗
NASA NTRS2000

The Use of Ferrofluids to Model Materials Processing (MSFC Center Director's Discretionary Fund)

Many crystals grown in space have structural flaws believed to result from convective motions during the growth phase. The character of these instabilities is not well understood but is associated with thermal and solutal density variations near the solidification interface in the presence of residual gravity and g-jitter. To study these instabilities in a separate, controlled space experiment, a concentration gradient would first have to be artificially established in a timely manner as an initial condition. This is generally difficult to accomplish in a microgravity environment because the momentum of the fluid injected into a test cell tends to swirl around and mix in the absence of a restoring force. The use of magnetic fields to control the motion and position of liquids has received recent, growing interest. The possibility of using the force exerted by a non-uniform magnetic field on a ferrofluid to not only achieve fluid manipulation but also to actively control fluid motion makes it an attractive candidate for space applications. This paper describes a technique for quickly establishing a linear or exponential fluid concentration gradient using a magnetic field in place of gravity to stabilize the deployment. Also discussed is a photometric technique for measuring the concentration profile using light attenuation. Although any range of concentrations can be realized, photometric constraints impose some limitations on measurements. Results of the ground-based experiments indicate that the species distribution is within 3 percent of the predicted value.

Leslie, F.↗
DOE OSTI2021

Molecular dynamics simulation of metallic Al–Ce liquids using a neural network machine learning interatomic potential

Al-rich Al-Ce alloys have the possibility of replacing heavier steel and cast-irons for use in high-temperature applications. Knowledge about the structures and properties of Al-Ce alloys at liquid state is vital for optimizing the manufacture process to produce desired allows. However, reliable molecular dynamics simulation of Al-Ce alloy systems remains a great challenge due to the lack of accurate Al-Ce interatomic potential. In this work, an artificial neural network (ANN) deep machine learning (ML) method is used to develop a reliable interatomic potential for Al-Ce alloy. Ab initio molecular dynamics (AIMD) simulation data on Al-Ce liquid with small unit cell (~200 atoms) and on the known Al-Ce crystalline compounds are collected to train the interatomic potential using ANN-ML. The obtained ANN-ML model reproduces well the energies, forces, and atomic structure of Al 90 Ce 10 liquid and crystalline phases of Al-Ce compounds in comparison with ab initio results. The developed ANN-ML potential is applied in molecular dynamics simulations to study the structures and properties of metallic Al 90 Ce 10 liquid, which would provide useful insight for guiding experimental process to produce desired Al-Ce allows.

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

Engineering 2‐Pyrone‐4,6‐Dicarboxylic Acid Production Reveals Metabolic Plasticity of Poplar

Woody biomass is a promising source of fermentable sugars for biofuels and bio-based chemicals, but its industrial use is limited by the costly biorefinery process. A viable strategy to reduce costs involves enhancing both biomass processability and the generation of high-value co-products. Here, we report the implementation of a synthetic metabolic pathway in Populus tremula × P. alba to produce 2-pyrone-4,6-dicarboxylic acid (PDC), a key building block for biodegradable plastics and high-performance materials. This artificial pathway—comprising microbial genes AroG, QsuB, PmdA, PmdB, and PmdC—enabled de novo PDC production in the stems of transgenic poplar. Pathway expression also induced substantial metabolic reprogramming and altered cell wall composition. These include the hyperaccumulation of simple phenolics like protocatechuic acid (PCA) and vanillic acid (VA), alongside reduced levels of p-hydroxybenzoic acid. A large portion of VA was ester-linked to cell wall lignin, while PCA was incorporated into the lignin backbone, forming novel benzodioxane units; concurrently, lignin in transgenic plants exhibited a drastic reduction in guaiacyl- and syringyl-units, with a notable increase in p-hydroxyphenyl-units. Hemicellulose content, particularly xylan, was also significantly increased. Moreover, expression of the PDC-pathway led to the formation of novel VA-derived suberin aromatics, enhancing suberization in bark and roots and improving salt stress tolerance. These changes led to improved saccharification efficiency, with up to 25% more glucose and 2.5 times xylose released from woody biomass. These results demonstrate the metabolic flexibility of poplar and highlight its potential for engineering cost-effective, stress-resilient bioenergy crops with enhanced biorefinery traits.

2-pyrone-4↗
DOE OSTI2023

Effects of macroparticle weighting in axisymmetric particle-in-cell Monte Carlo collision simulations

In this paper, the effects of macroparticle (MP) weighting on the plasma discharge, particularly near the centerline, are investigated using a two-dimensional axisymmetric particle-in-cell Monte Carlo collision (PIC/MCC) model. A variable MP weight according to the radial position of the MPs is employed to maintain sufficient number of MPs near the centerline of the plasma source. Finally, the plasma density obtained from the PIC/MCC simulations for low-pressure (25–100 mTorr) capacitively coupled plasmas is found to be artificially large when the MP weight near the centerline is not well resolved, demonstrating the need for particle convergence studies for axisymmetric PIC/MCC simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Hydrophobic Molecule Monolayer Brush-Tethered Zinc Anodes for Aqueous Zinc Batteries

Aqueous zinc batteries are of great interest as a rechargeable energy storage system, particularly owing to the low cost and high safety of aqueous electrolytes, as well as the high capacity of zinc anodes. Unfortunately, the wide commercialization of aqueous zinc batteries is impeded by the irreversible water reduction and irregular zinc evolution issues on the anode side. Hereby, a hydrophobic and ultrathin polystyrene molecule brush layer is tethered onto the surface of zinc metal anodes to tackle the above limitations. Here, experimental investigations reveal that the waterproof artificial layer can sustain fast interfacial ionic transportation, minimize hydrogen evolution, and smoothen Zn deposition, thus conferring enhanced electrochemical performance to the as-protected Zn anode in both symmetric Zn//Zn cells and Zn//LiV 3 O 8 full cells.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1999

Ciliated protozoa of two antarctic lakes: analysis by quantitative protargol staining and examination of artificial substrates

Planktonic and artificial substrate-associated ciliates have been identified in two perennially ice-covered antarctic lakes of the McMurdo Dry Valleys. Abundances estimated by quantitative protargol staining ranged from < 5 to 31690 cells l-1, levels that are comparable to those previously obtained using other methods. Nineteen ciliate taxa were identified from these lakes, with the most frequently encountered genera being Plagiocampa, Askenasia, Monodinium, Sphaerophrya and Vorticella. The taxonomic findings compare favorably with those of previous investigators; however four previously unreported genera were observed in both Lakes Fryxell and Hoare. The variability in the depth distributions of ciliates in Lake Fryxell is explained in terms of lake physicochemical properties and ciliate prey distributions, while factors related to temporal succession in the Lake Hoare assemblage remain unexplained. Local marine or temperate zone freshwater habitats are a more likely source than the surrounding dry valleys soils for present ciliate colonists in these lakes. Although the taxonomic uncertainties require further examination, our results suggest that ciliate populations in these antarctic lakes undergo significant fluctuations and are more diverse than was previously recognized.

NASA Discipline Exobiology↗
DOE OSTI2023

Spatial Interactions in Hydrogenated Perovskite Nickelate Synaptic Networks

A key aspect of how the brain learns and enables decision-making processes is through synaptic interactions. Electrical transmission and communication in a network of synapses are modulated by extracellular fields generated by ionic chemical gradients. Emulating such spatial interactions in synthetic networks can be of potential use for neuromorphic learning and the hardware implementation of artificial intelligence. Here, in this work, we demonstrate that in a network of hydrogen-doped perovskite nickelate devices, electric bias across a single junction can tune the coupling strength between the neighboring cells. Electrical transport measurements and spatially resolved diffraction and nanoprobe X-ray and scanning microwave impedance spectroscopic studies suggest that graded proton distribution in the inhomogeneous medium of hydrogen-doped nickelate film enables this behavior. We further demonstrate signal integration through the coupling of various junctions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A far‐red‐emitting (Gd,Y) 3 (Ga,Al) 5 O 12 :Mn 2+ ceramic phosphor with enhanced thermal stability for plant cultivation

Abstract As for plants, far‐red (FR) light with wavelength from 700 nm to 740 nm is critical for processes of photosynthesis and photomorphogenesis. Light‐controlled development depends on light to control cell differentiation, structural and functional changes, and finally converge into the formation of tissues and organs. Phosphor converted FR emission under LED excitation is a cost‐effective and high‐efficient way to provide artificial FR light source. With the aim to develop an efficient FR phosphor that can promote the plant growth, a series of gadolinium yttrium gallium garnet (GYGAG) transparent ceramic phosphors co‐doped with Mn 2+ and Si 4+ have been fabricated via chemical co‐precipitation method, followed sintered in O 2 and hot isostatic pressing in this work. Under UV excitation, the phosphor exhibited two bright and broadband red emission spectra due to Mn 2+ : 4 T 1 → 6 A 1 spin‐forbidden transition, and one of which located in the right FR region. And then, Ce 3+ ions were co‐doped as the activator to enhance the absorption at blue light region and the emission of Mn 2+ . It turns out that the emission band of GYGAG transparent ceramic phosphors matches well with the absorption band of phytochrome P FR , which means they are promising to be applied in plant cultivation light‐emitting diodes (LEDs) for modulating plant growth. Besides, the thermal stability of this material was investigated systematically, and an energy transferring model involves defects was also proposed to explain the phenomenon of abnormal temperature quenching.

Qiu, Xuting↗
DOE OSTI2025

Two-dimensional burn velocity and analysis of burn products of nitromethane at high pressure

We have studied the laser-initiated deflagration of nitromethane (CH 3 NO 2 ) under high static pressure in the diamond anvil cell. Time-resolved images of the deflagrations have been obtained using intensified CCDs (ICCD). In contrast with previous work, we rely on spontaneous emission from the reaction, rather than changes in the speckle pattern produced by artificial illumination of the sample. Furthermore, as opposed to the 1D records obtained previously with streak cameras, ICCDs permit imaging of the burn in two dimensions providing the ability to directly observe anisotropic deflagration behavior. Here, we report several examples of this behavior and discuss its possible origins. We have also investigated the products of the reaction using Raman spectroscopy. At pressures below 25 GPa, the burn product is observed to be opaque and has a Raman spectrum consistent with a carbonaceous soot. At pressures above 25 GPa, the burn product is observed to be transparent (consistent with earlier reports) and its Raman spectrum reveals the presence of molecular N 2 and a nitrogen-carbonate species. The latter species can be recovered to ambient pressure and has a Raman spectrum consistent with ammonium carbonate or ammonium bicarbonate. To aid interpretation of the Raman spectra, measurements have also been made on the isotopologues CH 3 15 NO 2 and 13 CH 3 NO 2 . This work establishes the importance of advanced time-resolved imaging to reveal the details of deflagration under high pressure and further advances our understanding of the corresponding chemistry.

Deflagration↗
DOE OSTI2025

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2020

Photoinduced electron transfer from zinc meso -tetraphenylporphyrin to a one-dimensional perylenediimide aggregate: Probing anion delocalization effects

Organic photovoltaics incorporating non-fullerene acceptors based on perylenediimide (PDI) now rival fullerene acceptor-based devices in performance, although the mechanisms of charge generation in PDI-based devices are not yet fully understood. Fullerene-based systems are proposed to undergo electron transfer directly from the photoexcited donor into a band of delocalized acceptor states, thus increasing charge generation efficiency. Similarly, anion delocalization has been shown to enhance the rate of electron transfer from a photoexcited donor to two electronically coupled PDI acceptors. Here we investigate how additional electron acceptors may further increase the rate of electron transfer from the donor zinc meso-tetraphenylporphyrin (ZnTPP) to an aggregate of PDI acceptors (PDI[Formula: see text]. Femtosecond transient visible and mid-infrared absorption spectroscopies show that the rate of electron transfer from 1 *ZnTPP to the PDI assembly ZnTPP 2 -PDI 3 is statistically identical to that of the previously examined ZnTPP-PDI 2 . A Marcus theory analysis indicates that the parameters governing electron transfer are nearly identical for the two molecules, suggesting that the maximum electron transfer rate enhancement has been achieved in a cofacial PDI dimer because the ZnTPP directly couples to the first two PDI acceptors whereas the coupling to the third PDI is too weak.

bio-inspired↗
DOE OSTI2022

All-Carbon Nanotube Solar Cell Devices Mimic Photosynthesis

We report that both solar cells and photosynthetic systems employ a two-step process of light absorption and energy conversion. In photosynthesis, they are performed by distinct proteins. However, conventional solar cells use the same semiconductor for optical absorption and electron-hole separation, leading to inefficiencies. Here, we show that an all-semiconducting single-walled carbon nanotube (s-SWCNTs) device provides an artificial system that models photosynthesis in a tandem geometry. We use distinct chirality s-SWCNTs to separate the site and direction of light absorption from those of power generation. Using different bandgap s-SWCNTs, we implement an energy funnel in dual-gated p-n diodes. The device captures photons from multiple regions of the solar spectrum and funnels photogenerated excitons to the smallest bandgap s-SWCNT layer, where they become free carriers. We demonstrate an increase in the photoresponse by adding more s-SWCNT layers of different bandgaps without a corresponding deleterious increase in the dark leakage current.

14 SOLAR ENERGY↗
NASA NTRS1988

General-Aviation Control Loader

Artificial-feel system designed for general-aviation flight simulators. New system developed to replace directly lateral and longitudinal controls in general-aviation cockpit for use in flight-simulation research. Using peaucellier's cell to convert linear motion to rotary motion, control-loading system provides realistic control-force feedback to cockpit wheel and column controls.

Baltrus, Daniel W.↗