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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Classification of Ion Mobility Data Using the Neural Network Approach

Determination of atmospheric and surface elemental and molecular composition of various solar system bodies is essential to the development of a firm understanding of the origin and evolution of the solar system. Furthermore, such data is needed to address the intriguing question of whether or not life exists or once existed elsewhere in the Solar System. As such, these measurements are among the primary scientific goals of NASA s current and future planetary missions. In recent years, significant progress toward both miniaturization and field portability of in situ analytical separation and detection devices have been made with future planetary explorations in mind. However, despite all these advances, accurate in situ identification of atmospheric and surface compounds remains a big challenge. In response to that we are developing various hardware and software tools which would enable us to uniquely identify species of interest in a complex chemical environment.

Duong, T. A.↗
NASA NTRS2021

Predicting the Functional State of Protein Kinases Using Interpretable Graph Neural Networks

Kinases are a family of proteins that function as molecular switches, regulating several essential cellular activities such as cell proliferation. Dysfunctional kinases are implicated in several types of cancers and hence they are actively pursued as drug targets. Given the vast number of complex kinase structures that are available in the protein data bank (PDB), there is a necessity to develop methodologies that can identify structurally important moieties of the kinases in an automated fashion, for such techniques can be instrumental in identifying novel drug targets. In this work, we develop a graph neural network (GNN) based deep learning framework for classifying the functionally active and inactive states of a large set of eukaryotic protein kinases, making use of their 3D structure from the PDB. We show that GNN based machine learning models can classify protein states with an accuracy greater than 97%. We further use the GNN models to automatically identify regions of the kinases that are important for its function. For this purpose, Gradient-weighted Class Activation Mapping (Grad-CAM) was implemented on the protein graphs. Remarkably, Grad-CAM consistently identifies the highly conserved DFG motif as the most important part of the protein across the entire kinome, without any prior input. Other regions of the hydrophobic core such as the HRD motif were also identified by the interpretable GNN framework, consistent with the literature. We discuss the significance of each of these regions in detail.

Ashwin Ravichandran↗
NASA NTRS2003

Modeling beta-adrenergic control of cardiac myocyte contractility in silico

The beta-adrenergic signaling pathway regulates cardiac myocyte contractility through a combination of feedforward and feedback mechanisms. We used systems analysis to investigate how the components and topology of this signaling network permit neurohormonal control of excitation-contraction coupling in the rat ventricular myocyte. A kinetic model integrating beta-adrenergic signaling with excitation-contraction coupling was formulated, and each subsystem was validated with independent biochemical and physiological measurements. Model analysis was used to investigate quantitatively the effects of specific molecular perturbations. 3-Fold overexpression of adenylyl cyclase in the model allowed an 85% higher rate of cyclic AMP synthesis than an equivalent overexpression of beta 1-adrenergic receptor, and manipulating the affinity of Gs alpha for adenylyl cyclase was a more potent regulator of cyclic AMP production. The model predicted that less than 40% of adenylyl cyclase molecules may be stimulated under maximal receptor activation, and an experimental protocol is suggested for validating this prediction. The model also predicted that the endogenous heat-stable protein kinase inhibitor may enhance basal cyclic AMP buffering by 68% and increasing the apparent Hill coefficient of protein kinase A activation from 1.0 to 2.0. Finally, phosphorylation of the L-type calcium channel and phospholamban were found sufficient to predict the dominant changes in myocyte contractility, including a 2.6x increase in systolic calcium (inotropy) and a 28% decrease in calcium half-relaxation time (lusitropy). By performing systems analysis, the consequences of molecular perturbations in the beta-adrenergic signaling network may be understood within the context of integrative cellular physiology.

Non-NASA Center↗
NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗
NASA NTRS2001

Cancer Detection Using Neural Computing Methodology

This paper describes a novel learning methodology used to analyze bio-materials. The premise of this research is to help pathologists quickly identify anomalous cells in a cost efficient method. Skilled pathologists must methodically, efficiently and carefully analyze manually histopathologic materials for the presence, amount and degree of malignancy and/or other disease states. The prolonged attention required to accomplish this task induces fatigue that may result in a higher rate of diagnostic errors. In addition, automated image analysis systems to date lack a sufficiently intelligent means of identifying even the most general regions of interest in tissue based studies and this shortfall greatly limits their utility. An intelligent data understanding system that could quickly and accurately identify diseased tissues and/or could choose regions of interest would be expected to increase the accuracy of diagnosis and usher in truly automated tissue based image analysis.

liquid crystal tunable filters↗
NASA NTRS2007

NASA Tech Briefs, September 2007

Topics covered include; Rapid Fabrication of Carbide Matrix/Carbon Fiber Composites; Coating Thermoelectric Devices To Suppress Sublimation; Ultrahigh-Temperature Ceramics; Improved C/SiC Ceramic Composites Made Using PIP; Coating Carbon Fibers With Platinum; Two-Band, Low-Loss Microwave Window; MCM Polarimetric Radiometers for Planar Arrays; Aperture-Coupled Thin-Membrane L-Band Antenna; WGM-Based Photonic Local Oscillators and Modulators; Focal-Plane Arrays of Quantum-Dot Infrared Photodetectors; Laser Range and Bearing Finder With No Moving Parts; Microrectenna: A Terahertz Antenna and Rectifier on a Chip; Miniature L-Band Radar Transceiver; Robotic Vision-Based Localization in an Urban Environment; Programs for Testing an SSME-Monitoring System; Cathodoluminescent Source of Intense White Light; Displaying and Analyzing Antenna Radiation Patterns; Payload Operations Support Team Tools; Space-Shuttle Emulator Software; Soft Real-Time PID Control on a VME Computer; Analyzing Radio-Frequency Coverage for the ISS; Nanorod-Based Fast-Response Pressure-Sensitive Paints; Capacitors Would Help Protect Against Hypervelocity Impacts; Diaphragm Pump With Resonant Piezoelectric Drive; Improved Quick-Release Pin Mechanism; Designing Rolling-Element Bearings; Reverse-Tangent Injection in a Centrifugal Compressor; Inertial Measurements for Aero-assisted Navigation (IMAN); Analysis of Complex Valve and Feed Systems; Improved Path Planning Onboard the Mars Exploration Rovers; Robust, Flexible Motion Control for the Mars Explorer Rovers; Solar Sail Spaceflight Simulation; Fluorine-Based DRIE of Fused Silica; Mechanical Alloying for Making Thermoelectric Compounds; Process for High-Rate Fabrication of Alumina Nanotemplates; Electroform/Plasma-Spray Laminates for X-Ray Optics; An Automated Flying-Insect Detection System; Calligraphic Poling of Ferroelectric Material; Blackbody Cavity for Calibrations at 200 to 273 K; KML Super Overlay to WMS Translator; High-Performance Tiled WMS and KML Web Server; Modeling of Radiative Transfer in Protostellar Disks; Composite Pulse Tube; Photometric Calibration of Consumer Video Cameras; Criterion for Identifying Vortices in High- Pressure Flows; Amplified Thermionic Cooling Using Arrays of Nanowires; Delamination-Indicating Thermal Barrier Coatings; Preventing Raman Lasing in High-Q WGM Resonators; Procedures for Tuning a Multiresonator Photonic Filter; Robust Mapping of Incoherent Fiber-Optic Bundles; Extended-Range Ultrarefractive 1D Photonic Crystal Prisms; Rapid Analysis of Mass Distribution of Radiation Shielding; Modeling Magnetic Properties in EZTB; Deep Space Network Antenna Logic Controller; Modeling Carbon and Hydrocarbon Molecular Structures in EZTB; BigView Image Viewing on Tiled Displays; and Imaging Sensor Flight and Test Equipment Software.

Source record↗
NASA NTRS2003

An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member of the (multi)gene families present and the metabolic networks that are operative. Additionally, one key to identifying physiological functions for many of these (and other) unknown genes, and their corresponding metabolic networks, awaits the development of technologies to comprehensively study molecular processes at the single cell level in particular tissues and organs, in order to establish the actual metabolic context.

NASA Program Fundamental Space Biology↗
NASA NTRS2017

Osteogenic Transcription Regulated by Exaggerated Stretch Loading via Convergent Wnt Signaling

Cell and animal studies conducted onboard the International Space Station and formerly the Shuttle flights have provided data illuminating the deleterious biological response of bone to mechanical unloading. Down regulation of proliferative mechanisms within stem cell populations of the osteogenic niche is a suggested mechanism for loss of bone mass. However the intercellular communicative cues from osteoblasts and osteocytes in managing stem cell proliferation and osteogenic differentiation are largely unknown. In this investigation, MLO-Y4 osteocyte-like and MC3T3-E1 osteoblast-like cells, are co-culture under dynamic tensile conditions and evaluated for phenotypic expression of biochemical signaling proteins influential in driving stem cell differentiation. MLO-Y4 and MC3T3-E1 were co-cultured on polyethersulfone membrane with a 0.45m porosity to permit soluble factor transfer and direct cell-cell gap junction signaling. Cyclic tensile stimulation was applied for 48 h at a frequency of 0.1Hz and strain of 0.1. Total Live cell counts indicate mechanical activation of MC3T3-E1s inhibits proliferation while MLO-Y4s increase in number. However, the percent of live MLO-Y4s within the population is low (46.3 total count, *p0.05, n4) suggesting a potential apoptotic signaling cascade. Immunofluorescence demonstrated that stimulation of co-cultures elicits increased gap junction communication. Previously reported PCR evaluation of osteogenic markers further corroborate that the co-cultured populations communicative networks play a role in translating mechanical signals to molecular messaging. These findings suggest that an osteocyte-osteoblast signaling feedback mechanism may regulate mechanotransduction of an apoptotic cascade within osteocytes and transcription of cytokine signaling proteins responsible for stem cell niche recruitment much more directly than previously believed.

mechanical stimulation↗
NASA NTRS2016

Mechanotransductive Regulation of Gap-Junction Activity Between MLO-Y4 Osteocyte-Like and MC3T3-E1 Osteoblast-Like Cells in Three-Dimensional Co-Culture.

Cell and animal studies conducted onboard the International Space Station and formerly on Shuttle flights have provided groundbreaking data illuminating the deleterious biological response of bone to mechanical unloading. However the intercellular communicative mechanisms associated with the regulation of bone synthesis and bone resorption cells are still largely unknown. Connexin-43 (CX43), a gap junction protein, is hypothesized to play a significant role in osteoblast and osteocyte signaling. The purpose of this investigation was to evaluate within a novel three-dimensional microenvironment how the osteocyte-osteoblast gap-junction expression changes when cultures are exposed to exaggerated mechanical load. MLO-Y4 osteocyte-like cells were cultured on a 3D-Biotek polystyrene insert and placed in direct contact with an MC3T3-E1 pre-osteoblast co-cultured monolayer and exposed to 48 h of mechanical stimulation (pulsatile fluid flow (PFF) or monolayer cyclic stretch (MCS)) then evaluated for viability, proliferation, metabolism, and CX43 expression. Mono-cultured MLO-Y4 and MC3T3-E1 control experiments were conducted under PFF and MCS stimulation to observe how strain application stimuli (PFF cell membrane shear or MCS cell focal adhesion/attachment loading) initiates different signaling pathways or downstream regulatory controls. TotalLive cell count, viability and metabolic reduction (Trypan Blue, LIVEDead and Alamar Blue analysis respectively) indicate that mechanical activation of MC3T3-E1 cells inhibits proliferation while maintaining an average 1.04E4 reductioncell metabolic rate, *p0.05 n4. MLO-Y4s in monolayer culture increase in number when exposed to MCS loading but the percent of live cells within the population is low (46.3 total count, *p0.05 n4), these results may indicate an apoptotic signaling cascade. PFF stimulation of the three-dimensional co-cultures elicits a universal increase in CX43 in MLO-Y4 and MC3T3-E1 cells, illustrated by immunohistological observation. Increased CX43 expression is also observed with the three-dimensional co-cultures with MC3T3-E1 MCS stimulation but the increased gap-junction protein presence was limited to the osteoblast-osteocyte interface region. Previously reported PCR evaluation of osteogenic markers further corroborate that the co-cultured populations communicative networks play a role in translating mechanical signals to molecular messaging. These findings suggests an osteocyte-osteoblast gap-junction signaling feedback mechanism may regulate mechanotransduction of apoptosis initiation and transcription of cytokine signaling proteins responsible for stem cell niche recruitment much more directly than previously believed.

mechanical loading↗
NASA NTRS2016

Mechanotransductive Regulation of Gap-Junction Activity Between MLO-Y4 Osteocyte-Like and MC3T3-E1 Osteoblast-Like Cells in Three-Dimensional Co-Culture

Cell and animal studies conducted onboard the International Space Station and formerly on Shuttle flights have provided groundbreaking data illuminating the deleterious biological response of bone to mechanical unloading. However the intercellular communicative mechanisms associated with the regulation of bone synthesis and bone resorption cells are still largely unknown. Connexin-43 (CX43), a gap junction protein, is hypothesized to play a significant role in osteoblast and osteocyte signaling. The purpose of this investigation was to evaluate within a novel three-dimensional microenvironment how the osteocyte-osteoblast gap-junction expression changes when cultures are exposed to exaggerated mechanical load. MLO-Y4 osteocyte-like cells were cultured on a 3D-Biotek polystyrene insert and placed in direct contact with an MC3T3-E1 pre-osteoblast co-cultured monolayer and exposed to 48 h of mechanical stimulation (pulsatile fluid flow (PFF) or monolayer cyclic stretch (MCS)) then evaluated for viability, proliferation, metabolism, and CX43 expression. Mono-cultured MLO-Y4 and MC3T3-E1 control experiments were conducted under PFF and MCS stimulation to observe how strain application stimuli (PFF cell membrane shear or MCS cell focal adhesionattachment loading) initiates different signaling pathways or downstream regulatory controls. TotalLive cell count, viability and metabolic reduction (Trypan Blue, LIVEDead and Alamar Blue analysis respectively) indicate that mechanical activation of MC3T3-E1 cells inhibits proliferation while maintaining an average 1.04E4 reductioncell metabolic rate, *p0.05 n4. MLO-Y4s in monolayer culture increase in number when exposed to MCS loading but the percent of live cells within the population is low (46.3 total count, *p0.05 n4), these results may indicate an apoptotic signaling cascade. PFF stimulation of the three-dimensional co-cultures elicits a universal increase in CX43 in MLO-Y4 and MC3T3-E1 cells, illustrated by immunohistological observation. Increased CX43 expression is also observed with the three-dimensional co-cultures with MC3T3-E1 MCS stimulation but the increased gap-junction protein presence was limited to the osteoblast-osteocyte interface region. Previously reported PCR evaluation of osteogenic markers further corroborate that the co-cultured populations communicative networks play a role in translating mechanical signals to molecular messaging. These findings suggests an osteocyte-osteoblast gap-junction signaling feedback mechanism may regulate mechanotransduction of apoptosis initiation and transcription of cytokine signaling proteins responsible for stem cell niche recruitment much more directly than previously believed.

Juran, C. M.↗
NASA NTRS2020

Molecular Dynamics Investigation of the Structural and Mechanical Properties of Off-Stoichiometric Epoxy Resins

We carried out molecular dynamics (MD) simulations to measure the mechanical properties of various off-stoichiometric polymers regarding amine to epoxy ratios (r) and to understand the stiffness of the polymers in terms of their structures. The aerospace-grade API-60 epoxy resin is used as an adhesive bond for assembling large-scale composite structures via the co-curing-ply bonding method. This method will produce a reliable and certifiable composite joint without additional fasteners. Calculated Young's modulus was measured from the uniaxial tension simulation with several high strain rates, and the experimental modulus was estimated by extrapolating the simulation results. We found that the stiffness was associated with molecular packing caused by chemical cross-linking. We also found that the number of network clusters gradually decreased as the ratio approached r = 1.0, which made the tighter cluster and the system much stiffer with an increase in the molecular weight and the degree of cross-linking. Structural properties such as Rg, MSD were measured to figure out the degree of stiffness with respect to the r.

Jang, Chang Woon↗
NASA NTRS1979

Viscoelastic properties of entangled polymers - Ternary blends of monodisperse homopolymers

In a previous publication from this laboratory, the Rouse-Bueche-Zimm molecular theory of viscoelasticity has been extended by using a transient network model to apply to binary blends of monodisperse polymers with chain entanglements. The dynamics of the entanglements were modeled both by the enhanced frictional coefficients and by the additional elastic couplings. It was recognized that entanglements not only may form between chains of the same lengths (intracomponent entanglements) but also between those of different lengths (intercomponent entanglements). At a given intercomponent entanglement, the longer chain was assumed to have the frictional coefficient of the shorter chain. Similarly, for blends consisting of several monodisperse components with different molecular weights, such modifications are also required to predict their linear viscoelastic behavior. The frequency of these interactions is assumed to be proportional to the weight ratio of the respective component chains in the blend. Equations of motion are formulated for each component and solved numerically for the relaxation time spectra. Linear viscoelastic properties such as the dynamic mechanical moduli, stress relaxation moduli, and zero-shear viscosity can then be computed for these systems by linear summation of those of the components.

Soong, D.↗
NASA NTRS2000

Diversity and regulation of plant Ca2+ pumps: insights from expression in yeast

The spatial and temporal regulation of calcium concentration in plant cells depends on the coordinate activities of channels and active transporters located on different organelles and membranes. Several Ca2+ pumps have been identified and characterized by functional expression of plant genes in a yeast mutant (K616). This expression system has opened the way to a genetic and biochemical characterization of the regulatory and catalytic features of diverse Ca2+ pumps. Plant Ca(2+)-ATPases fall into two major types: AtECA1 represents one of four or more members of the type IIA (ER-type) Ca(2+)-ATPases in Arabidopsis, and AtACA2 is one of seven or more members of the type IIB (PM-type) Ca(2+)-ATPases that are regulated by a novel amino terminal domain. Type IIB pumps are widely distributed on membranes, including the PM (plasma membrane), vacuole, and ER (endoplasmic reticulum). The regulatory domain serves multiple functions, including autoinhibition, calmodulin binding, and sites for modification by phosphorylation. This domain, however, is considerably diverse among several type IIB ATPases, suggesting that the pumps are differentially regulated. Understanding of Ca2+ transporters at the molecular level is providing insights into their roles in signaling networks and in regulating fundamental processes of cell biology.

Review, Academic↗
NASA NTRS1991

Thermal characterization and toughness of ethynyl containing blends

As part of an effort to develop high performance structural resins with an attractive combination of properties for aerospace applications, a series of ethynyl-terminated polysulfones of different molecular weights were prepared and blended with a low molecular weight ethynyl-terminated coreactant. Upon heating above 200 C, these ethynyl containing materials react to form a chain extended and crosslinked network structure. This reaction renders the materials insoluble in common solvents, but also reduces the toughness as compared to high molecular weight linear polysulfones. The thermal characterization of these blends and the toughness of the resulting cured materials are discussed.

Jensen, Brian J.↗
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 9

The following topics were discussed: Monitoring floods with NASA's ST6 autonomous spacecraft experiment; Dynamical cloud models constrained by high resolution spectroscopy of zodiacal light; The oxygen isotopic composition of the sun and implications for oxygen processing in molecular clouds; A nochian/hisperian hiatus and erosive reactivation of martian valley networks; Hard x-ray spectro-microscopy techniques; Thermoluminescence studies of carbonaceous chondrites, etc.

Source record↗
NASA NTRSDate not supplied

Exploring Quantum State Preparation Using Tensor Networks and Sparse Wavefunction Simulations

The variational quantum eigenvalue solver is a powerful hybrid quantum-classical approach that has been suggested as a candidate method to run on near-term quantum hardware for computing ground state electronic energies of molecular systems. However, even for small molecules, the number of variational parameters and qubits required to minimize the electronic energy is beyond the reach of current quantum computers except for small basis sets. We explore a new paradigm for state preparation where we test how much of the optimization can be approximately prepared with classical computers to reduce the number of optimization steps performed using a quantum device. By adapting a recent algorithm for the factorized form of the UCC ansatz, we can study molecular electronic structure problems with up to 64 qubits. In addition, we also test a related approach of using tensor networks to optimize quantum circuits in order to benchmark various lattice models. We present results using these approaches and discuss strategies for incorporating these ideas into variational algorithms involving near-term quantum computers. Our results help demonstrate the strength of the UCC ansatz and address pressing questions about optimal initial parameterizations and circuit construction.

quantum computing↗
NASA NTRS2002

Molnets: An Artificial Chemistry Based on Neural Networks

The fundamental problem in the evolution of matter is to understand how structure-function relationships are formed and increase in complexity from the molecular level all the way to a genetic system. We have created a system where structure-function relationships arise naturally and without the need of ad hoc function assignments to given structures. The idea was inspired by neural networks, where the structure of the net embodies specific computational properties. In this system networks interact with other networks to create connections between the inputs of one net and the outputs of another. The newly created net then recomputes its own synaptic weights, based on anti-hebbian rules. As a result some connections may be cut, and multiple nets can emerge as products of a 'reaction'. The idea is to study emergent reaction behaviors, based on simple rules that constitute a pseudophysics of the system. These simple rules are parameterized to produce behaviors that emulate chemical reactions. We find that these simple rules show a gradual increase in the size and complexity of molecules. We have been building a virtual artificial chemistry laboratory for discovering interesting reactions and for testing further ideas on the evolution of primitive molecules. Some of these ideas include the potential effect of membranes and selective diffusion according to molecular size.

Colombano, Silvano↗