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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Microbial detection with low molecular weight RNA

The need to monitor microorganisms in the environment has increased interest in assays based on hybridization probes that target nucleic acids (e.g., rRNA). We report the development of liquid-phase assays for specific bacterial 5S rRNA sequences or similarly sized artificial RNAs (aRNAs) using molecular beacon technology. These beacons fluoresce only in the presence of specific target sequences, rendering as much as a 27-fold fluorescence enhancement. The assays can be used with both crude cell lysates and purified total RNA preparations. Minimal sample preparation (e.g., heating to promote leakage from cells) is sufficient to detect many Gram-negative bacteria. Using this approach it was possible to detect an aRNA-labeled Escherichia coli strain in the presence of a large background of an otherwise identical E. coli strain. Finally, by using a longer wavelength carboxytetramethylrhodamine beacon it was possible to reduce the fraction of the signal due to cellular autofluorescence to below 0.5%.

NASA Discipline Life Sciences Technologies↗
DOE OSTI2021

Exploring wave propagation in heterogeneous metastructures using the relaxed micromorphic model

Metamaterials are artificial structures that can manipulate and control sound waves in ways not possible with conventional materials. While much effort has been undertaken to widen the bandgaps produced by these materials through design of heterogeneities within unit cells, comparatively little work has considered the effect of engineering heterogeneities at the structural scale by combining different types of unit cells. In this paper, we use the relaxed micromorphic model to study wave propagation in heterogeneous metastructures composed of different unit cells. We first establish the efficacy of the relaxed micromorphic model for capturing the salient characteristics of dispersive wave propagation through comparisons with direct numerical simulations for two classes of metamaterial unit cells: namely phononic crystals and locally resonant metamaterials. We then use this model to demonstrate how spatially arranging multiple unit cells into metastructures can lead to tailored and unique properties such as spatially-dependent broadband wave attenuation, rainbow trapping, and pulse shaping. In the case of the broadband wave attenuation application, we show that by building layered metastructures from different metamaterial unit cells, we can slow down or stop wave packets in an enlarged frequency range, while letting other frequencies through. In the case of the rainbow-trapping application, we show that spatial arrangements of different unit cells can be designed to progressively slow down and eventually stop waves with different frequencies at different spatial locations. Finally, in the case of the pulse-shaping application, our results show that heterogeneous metastructures can be designed to tailor the spatial profile of a propagating wave packet. Collectively, these results show the versatility of the relaxed micromorphic model for effectively and accurately simulating wave propagation in heterogeneous metastructures, and how this model can be used to design heterogeneous metastructures with tailored wave propagation functionalities.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Single-shot femtosecond laser-induced breakdown spectroscopy in low-density gases

Single-shot fs laser-induced breakdown spectroscopy (LIBS) has been used to interrogate low-density gases of H 2 ⁠, CH 4 ⁠, CO 2 ⁠, and H 2 O ranging from 0.5 × 10 15 to 9.1 × 10 15 cm −3 (15–275 mTorr). Strong spectral signatures were observed above the noise baseline for each test gas at all densities considered. Unique molecular signatures were observed for both CH 4 and CO 2 along with atomic features for each gas. The LIBS intensity response with respect to density was determined for each species using Voigt lineshape fitting or numerical integration. Finally, the collection and analysis of LIBS spectra of composite mixtures of CH 4 –CO 2 and CH 4 –H 2 demonstrates that the extraction of individual densities from gas mixtures is feasible at low densities.

Artificial neural networks↗
DOE OSTI2020

Nanoengineering of Complex Materials

We are primarily interested in two important biomimetic principles, namely, self-assembly based on supramolecular chemistry and the use of these structures to template in organic phases as observed in biomineralization. The projects proposed are inspired by some of our achievements in the previous funding period described above, and also by preliminary data gathered recently which we describe below. In addition to our broad objective of acquiring knowledge in supramolecular self-assembly and templating of organic–inorganic hybrid materials, we also propose here work on biomolecular structures based on DNA, peptide nucleic acids, and peptides which can serve as models for artificial materials based on biomimetic principles. The proposed work is divided into three sections, supramolecular systems, hybrid systems, and biomolecular and biological systems. In terms of functions, we are using systems that have relevance to solar cells, catalysis, dynamic/active materials, and ferroelectrics.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Time-marching solution of incompressible Navier-Stokes equations for internal flow

Primitive variables with central differencing on a staggered grid are used in the present, factored ADI finite-difference scheme for artificial compressibility method solution of the incompressible Navier-Stokes equations, leading to a close coupling between velocity and pressure that both enhances stability and eliminates the need for artificial damping. Computational efficiency is enhanced through the use of a spatially variable, fixed Courant number-based time-step. The numerical results obtained for a driven cavity at Re of 10,000, with local cell Re as high as 100, exhibits no flow variable spatial oscillations on a 40 x 40 stretched grid solution.

Soh, W. Y.↗
DOE OSTI2023

Cell Free and Immobilization Technologies (CFIT)

Today, several key factors negatively impact the production of fuels and chemicals from renewable sources. Common hindrances in the biological production of biochemicals are: (1) end-product or intermediate toxicity to the microbial biocatalyst, (2) the diversion of carbon to biomass formation, and (3) co-production of undesired byproducts. A particularly attractive alternative is to eliminate the biocatalyst entirely and instead operate the desired metabolic pathways in isolation, thus circumventing the roadblocks of biological toxicity, lower yields, and lack of specificity. However, cell-free enzyme systems still suffer from low productivities owing in part to the effects of free diffusion of intermediates, lack of long term enzyme stability, cofactor cost or inefficient recycling rates, and finally, the cost of enzyme production/purification. This project represents a new effort to propose innovative and cost competitive routes to producing biochemicals from a variety of feedstocks using cell free approaches. These routes will help reduce the current risk and cost associated with classical cell free production. Cell free technologies show promise for application to the production of toxic/inhibitory products or products difficult to separate from microbial growth media and can help reduce the production barriers in multiple areas of biological conversion of feedstocks to biochemicals. More specifically, we are developing new technologies and routes that could be used to produce high value biochemicals such as 2,3 BDO and terpenes (among many others) from biomass derived C5/C6 sugars or lignin but also from waste byproducts such as glycerol. This project will lead to significant innovation and also lead to new concepts and rational design of pathways and enzymes. Within this project, we will develop new metabolic enzyme cascades that will represent natural or artificial combinations of enzymes to produce the desired biochemicals from a variety of feedstocks. We are also developing basic design principals for constructing synthetic metabolons, using fusion proteins and synthetic protein scaffolds, to promote substrate channeling and stability while conserving peak activity. Additionally, our efforts include a techno economic analysis (TEA) of cell free approaches to provide the sensitivities of the process to enzyme loading, activity, pH, reactor volumes, cofactor recycling rates. Finally, we are focusing on further increasing stability, operating lifetime and efficiency of the pathway enzymes by immobilization on support surfaces. We are also focus on immobilizing pathway enzymes or combinations of enzymes on several different conducting polymers and evaluate the effect on stability and operating lifetime. As more combinations become available we will conduct a more systematic study of the means of immobilizing these enzymes. This preliminary work will enable the in-depth study of cofactor recycling at these interfaces using mediators for electron transfer. Taken together, these approaches will enable process intensification, continuous operation, lower capital and separations costs and end-product flexibility, and thus has the potential to contribute significantly to BETO's goals of cost competitive biofuels and bioproducts. To date we have demonstrated 1) the conversion of pyruvate to 2,3 BDO (4 enzymes with cofactor recycling, no additional cofactors needed) at >100g/L (>3g/L/h) using our enzyme tethering approach, 2) Generated mutants of a key redox enzyme with >180- fold improvement in NADH utilization over WT to >85% of NADPH utilization. 3) Produced mevalonate at >10g/L from glucose, limonene at >10g/L from mevalonate and more than >5g/L from glucose with crude enzyme preparations and complete cofactor recycling. 4) successfully generated fully active cross-linked aggregates (CLEAs) of NOX, a cofactor-regenerating water-forming oxidase that is key to our process with increased stability 5) Engineered and identified enzymes able to use the biomimetic cofactor NMN and synthesized new synthetic cofactors.

biocatalysis↗
NASA NTRS1989

A cell-vertex multigrid method for the Navier-Stokes equations

A cell-vertex scheme for the Navier-Stokes equations, which is based on central difference approximations and Runge-Kutta time stepping, is described. Using local time stepping, implicit residual smoothing, a multigrid method, and carefully controlled artificial dissipative terms, very good convergence rates are obtained for a wide range of two- and three-dimensional flows over airfoils and wings. The accuracy of the code is examined by grid refinement studies and comparison with experimental data. For an accurate prediction of turbulent flows with strong separations, a modified version of the nonequilibrium turbulence model of Johnson and King is introduced, which is well suited for an implementation into three-dimensional Navier-Stokes codes. It is shown that the solutions for three-dimensional flows with strong separations can be dramatically improved, when a nonequilibrium model of turbulence is used.

Radespiel, R.↗
DOE OSTI2021

Enabling 4C Fast Charging of Lithium–Ion Batteries by Coating Graphite with a Solid–State Electrolyte

Enabling fast-charging (≥4C) of lithium-ion batteries is an important challenge to accelerate the adoption of electric vehicles. However, the desire to maximize energy density has driven the use of increasingly thick electrodes, which hinders rate capability. Herein, atomic layer deposition is used to coat a single-ion conducting solid electrolyte (Li 3 BO 3 -Li 2 CO 3 ) onto postcalendered graphite electrodes, forming an artificial solid-electrolyte interphase (SEI). When compared to uncoated control electrodes, the solid electrolyte coating: 1) eliminates natural SEI formation during preconditioning; 2) decreases interphase impedance by >75% compared to the natural SEI; and 3) extends cycle life under 4C charging conditions, enabling retention of 80% capacity after 500 cycles (compared to 12 cycles in the uncoated control) in pouch cells with >3 mAh cm –2 loading. Furthermore, this work demonstrates that 4C charging without Li plating can be achieved through purely interfacial modification without sacrificing energy density and sheds new light on the role of the SEI in Li plating and fast-charge performance.

25 ENERGY STORAGE↗
DOE OSTI2021

Regulating lithium deposition via electropolymerization of acrylonitrile in rechargeable lithium metal batteries

Here, we report acrylonitrile (AN) as an effective additive in carbonate-based electrolytes to enable uniform and dense lithium (Li) deposition and to improve the coulombic efficiency of Li metal anode. Our electrochemical, spectroscopic, and theoretical study reveal that AN is cathodically electropolymerized on the Li surface prior to the electrochemical decomposition of the electrolyte during Li deposition. The resultant polyacrylonitrile artificial solid electrolyte interphase enables uniform nucleation and growth of Li deposition with significantly reduced side reactions. The effectiveness of the AN additive is demonstrated in 0.4 Ah Li||LiNi 0.6 Mn 0.2 Co 0.2 O 2 pouch cells (using 50-μm Li anode, 3 mAh cm -2 cathode areal capacity, and 4g Ah -1 electrolyte) with excellent cycle stability under realistic charge-discharge condition

25 ENERGY STORAGE↗
NASA NTRS1993

An adaptive mesh-moving and refinement procedure for one-dimensional conservation laws

We examine the performance of an adaptive mesh-moving and /or local mesh refinement procedure for the finite difference solution of one-dimensional hyperbolic systems of conservation laws. Adaptive motion of a base mesh is designed to isolate spatially distinct phenomena, and recursive local refinement of the time step and cells of the stationary or moving base mesh is performed in regions where a refinement indicator exceeds a prescribed tolerance. These adaptive procedures are incorporated into a computer code that includes a MacCormack finite difference scheme wih Davis' artificial viscosity model and a discretization error estimate based on Richardson's extrapolation. Experiments are conducted on three problems in order to qualify the advantages of adaptive techniques relative to uniform mesh computations and the relative benefits of mesh moving and refinement. Key results indicate that local mesh refinement, with and without mesh moving, can provide reliable solutions at much lower computational cost than possible on uniform meshes; that mesh motion can be used to improve the results of uniform mesh solutions for a modest computational effort; that the cost of managing the tree data structure associated with refinement is small; and that a combination of mesh motion and refinement reliably produces solutions for the least cost per unit accuracy.

Biswas, Rupak↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗
NASA NTRS1992

A 3D finite element multigrid solver for the Euler equations

A low storage, computationally efficient algorithm for the solution of the compressible Euler equations on unstructured tetrahedral meshes is developed. The algorithm takes the form of a centered scheme with the explicit addition of a high accuracy artificial viscosity and the solution is advanced to steady state by means of a multistage timestepping method. The side-based data structure which is employed enables a clear connection to be established between the proposed algorithm and upwind cell vertex schemes for unstructured meshes. The computational efficiency of the procedure is improved by incorporating an unstructured multigrid acceleration procedure. A number of flows of practical interest are analyzed to demonstrate the numerical performance of the proposed approach.

Peraire, J.↗
NASA NTRS1991

Aerodyne Research mobile infrared methane monitor

An improved real-time methane monitor based on infrared absorption of the 3.39 micron line of a HeNe laser is described. Real time in situ measurement of methane has important applications in stratospheric and tropospheric chemistry, especially when high accuracy measurements can be made rapidly, providing fine spatial-scale information. The methane instrument provides 5 ppb resolution in a 1 sec averaging time. A key feature in this instrument is the use of magnetic (Zeeman) broadening to achieve continuous tunability with constant output power over a range of 0.017/cm. The instruments optical absorption path length is 47 m through sampled air held at 50 torr in a multipass cell of the Herriott (off-axis resonator) type. A microprocessor controls laser frequency and amplitude and collects data with minimal operator attention. The instrument recently has been used to measure methane emissions from a variety of natural and artificial terrestrial sources.

Mcmanus, J. B.↗
NASA NTRS1995

Space Station Biological Research Project

NASA Ames Research Center is responsible for the development of the Space Station Biological Research Project (SSBRP) which will support non-human life sciences research on the International Space Station Alpha (ISSA). The SSBRP is designed to support both basic research to understand the effect of altered gravity fields on biological systems and applied research to investigate the effects of space flight on biological systems. The SSBRP will provide the necessary habitats to support avian and reptile eggs, cells and tissues, plants and rodents. In addition a habitat to support aquatic specimens will be provided by our international partners. Habitats will be mounted in ISSA compatible racks at u-g and will also be mounted on a 2.5 m diameter centrifuge except for the egg incubator which has an internal centrifuge. The 2.5 m centrifuge will provide artificial gravity levels over the range of 0.01 G to 2 G. The current schedule is to launch the first rack in 1999, the Life Sciences glovebox and a second rack early in 2001, a 4 habitat 2.5 in centrifuge later the same year in its own module, and to upgrade the centrifuge to 8 habitats in 2004. The rodent habitats will be derived from the Advanced Animal Habitat currently under development for the Shuttle program and will be capable of housing either rats or mice individually or in groups (6 rats/group and at least 12 mice/group). The egg incubator will be an upgraded Avian Development Facility also developed for the Shuttle program through a Small Business and Innovative Research grant. The Space Tissue Loss cell culture apparatus, developed by Walter Reed Army Institute of Research, is being considered for the cell and tissue culture habitat. The Life Sciences Glovebox is crucial to all life sciences experiments for specimen manipulation and performance of science procedures. It will provide two levels of containment between the work volume and the crew through the use of seals and negative pressure. The glovebox will accommodate use by two crew persons simultaneously and the capability for real time video down-link and data acquisition. In house testbeds and Phase B studies of the centrifuge validated the concepts of vibration isolation and autobalancing systems to meet the ISSA microgravity requirements. The vibration isolation system is effective above the centrifuge rotation frequency while the autobalancing system on the rotor removes vibration at and below the rotation rate. Torque of the Station, induced by spin-up/spindown of the centrifuge, can be minimized by controlling spin-up/spin-down rates. The SSBRP and ISSA will provide the opportunity to perform long-term, repeatable and high quality science. The long duration increments available on the Station will permit multigeneration studies of both plants and animals which have not previously been possible. The u-g habitat racks and the eight habitat centrifuge will accommodate sufficient number of specimens to permit statistically significant sampling of specimens to investigate the time course of adaptation to altered gravity environments. The centrifuge will, for the first time, permit investigators to use gravity itself as a tool to investigate fundamental processes, to investigate the intensity and duration of gravity to maintain normal structure and function, to separate the effects of u-g from other environmental factors and to examine artificial gravity as a potential countermeasure for the physical deconditioning observed during space flight.

Johnson, Catherine C.↗
NASA NTRSDate not supplied

Lunar Payloads to Constrain Exospheric Water through the NASA M-STAR program

Our understanding of water cycles on the Moon has significantly enhanced recent observations by Chang E-5, Lunar Prospector, and Chandrayaan-1 missions indicating the existence of an active water cycle on the Moon. In a new partnership between Delaware State University (DSU) and NASA Goddard Space Flight Center, enabled through the NASA’s M-STAR (MUREP Space Technology Artemis Research) program, we are developing low mass and power lunar rover payloads to enable long-duration human exploration missions. Payload technologies include wavelength modulation absorption spectroscopy to simultaneously detect water (H16OH) and isotopes (H16OD) in the (6700 nm) mid-infrared region using a closed path in compact Herriot cell optical design and wavelength modulation spectroscopy, and (2) Laser-induced breakdown spectroscopy (LIBS) to simultaneously detect and correlate water isotopes with characteristics elemental composition of lunar regolith. Due to the airless atmosphere of the Moon, we will utilize Artificial intelligence (AI) and Machine learning (ML) approaches to discriminate spectral interference with instrument drifts and correlate mid-IR trace gas profile with LIBS spectral information. This partnership will initiate a STEM engagement space program, e.g., Lander and CubeSat payload technology development for students and the next-generation NASA workforce for future lunar and Mars missions. DSU, a Historically Black University, prides itself in its proven excellence in teaching and research. It enrolls a diverse population of students (~5000) traditionally underrepresented in STEM disciplines. DSU has established itself at the forefront of optics and photonics research that transcends multidisciplinary fields of earth sciences, environmental, defense, and biomedical sensing applications.

water cycles↗
DOE OSTI2026

Toward durable stacks: glass-ceramic sealants for intermediate-temperature protonic ceramic electrochemical systems

Protonic ceramic electrochemical cells (PCECs) are emerging as promising technologies for efficient energy conversion and hydrogen production because they operate at intermediate temperatures with improved efficiency and durability compared with conventional solid oxide electrochemical cells. However, the long-term reliability and commercialization of PCEC stacks remain strongly limited by the performance of sealants, which are required to maintain gas tightness, electrical insulation, and mechanical integrity under harsh thermal and chemical environments. Among various sealing approaches, glass-ceramic sealants are considered the most practical and scalable due to their excellent wettability, chemical tunability, and strong interfacial adhesion. This review provides a comprehensive overview of recent advances in glass-ceramic sealants for intermediate-temperature protonic ceramic electrochemical systems. The fundamental design principles of sealant compositions are first discussed, followed by recent developments in deposition methods, sintering strategies, surface treatments, and degradation monitoring techniques. Particular attention is given to the unique challenges associated with PCEC operating conditions, including hydrothermal degradation, interfacial reactions with barium-containing electrolytes, and thermal mismatch. Finally, future opportunities involving sustainable materials, multiscale modeling, additive manufacturing, and artificial intelligence-assisted sealant optimization are highlighted.

glass–ceramic sealants↗
DOE OSTI2020

Machine Learning-Enabled Correlation and Modeling of Multimodal Response of Thin Film to Environment on Macro and Nanoscale Using “Lab-on-a-Crystal”

To close the feedback loop between artificial intellegence-controlled materials synthesis and characterization, material functionality must be rapidly tested. A platform for high-throughput multifunctional materials characterization is developed using a quartz crystal microbalance with auxiliary in-plane electrodes and a custom gas/vapor flow cell, enabling simultaneous scanning probe microscopy and electrical, optical, gravimetric, and viscoelastic characterization on the same film under controlled environment. The lab-on-a-crystal in situ multifunctional output allows direct correlations between the gravimetric/viscoelastic, electrical, and optical responses of polymer film in response to environment. Finally, when multiple film properties are used to augment the training set for machine learning regression, prediction of material response to the environment improves by a factor of 13 when <5% of the total dataset is used for model training.

36 MATERIALS SCIENCE↗