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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Combined Technologies for In Situ Remediation of Tc-99 and U in Subsurface Sediments

In this study, combinations of chemical remedies were tested in bench-scale batch experiments to evaluate a two-step reduction-sequestration approach to effectively stabilize high concentrations of inorganic contaminant mixtures. Bench tests simulated contaminant and geochemical conditions of a perched aquifer located within the Central Plateau at the Hanford Site, located in southeastern Washington State (USA). Pairwise combinations of a reductant [e.g., zero valent iron, sulfur modified iron (SMI), or calcium polysulfide] and a sequestering agent [e.g., calcite, apatite, or dilute alkaline solution (e.g., NaOH)] were evaluated for immobilization and stabilization of technetium (Tc) (50,000 pCi/L), uranium (U) (150 mg/L), and nitrate (NO 3 ) (200 mg/L) in high ionic strength groundwater. The results of these batch studies demonstrated that reduction by SMI and sequestration in apatite or calcite are the most effective combination for these contaminant mixtures and conditions. Aqueous concentrations of Tc and U decreased by 95.6% ± 2.5% and 101.1% ± 5.2%, respectively, with SMI-apatite and 98.3% ± 0.0% and 101.2% ± 5.2%, respectively, with SMI-calcite. Sequential extractions showed that sequestered contaminants had limited capacity for re-oxidation; in fact, less than 10% of immobilized Tc and U was recovered by selective extraction of mineral phases most susceptible to oxidation. In addition, X-ray absorption near edge structure analysis of the sediment samples treated with SMI-calcite showed the presence of only U(IV), while both U(IV) and U(VI) were present in the SMI apatite combination [ratio of 0.43 U(IV):0.59 U(VI)].This study describes preliminary results that a two-step approach for stabilizing contaminant mixtures of long-lived radionuclides can be effective at reducing contaminant fluxes to groundwater from vadose and perched water zones.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2005

Cycom 977-2 Composite Material: Impact Test Results

The reaction frequency data from 13A testing by MSFC and WSTF appear well behaved for the sample number used by each and exhibit the same type of energy level dependency. The reaction frequency shift in energy level is unexplained at this time. All the 13A data suggest that only a small amount of material is consumed when reactions take place. At ambient pressure, most of not all reactions are quenched as indicated by the small mass loss. As test pressure is increased in LOX using 13B results. Cycom does not support initiation of reactions or propagations of reactions in GOX at 100 psis based on tests at MSFC and WSTF at 72 ft-lb impact energy. No batch effect was identified in LOX or GOX.

Engel, Carl D.↗
NASA NTRS2014

Optical Properties of Nanosatellite Hardware

Over the last decade, a number of very small satellites have been launched into space. These have been called nanosatellites (generally of a weight between 1 and 10 kg) or picosatellites (weight <1 kg). This also includes CubeSats, which are based on 10-cm cube units. With the addition of the Japanese Experiment Module (JEM) Small Satellite Orbital Deployer (J-SSOD) to the International Space Station (ISS), CubeSats are easily cycled through the JEM airlock and deployed into space (fig. 1). The number of CubeSats launched since 2003 was approaching 100 at the time of publication, and the authors expect this trend in research to continue, particularly for high school and college flight experiments. Because these spacecraft are so small, there is usually no allowance for shielding or active heating or cooling of the avionics and other hardware. Parts that are usually ignored in the thermal analysis of larger spacecraft may contribute significantly to the heat load of a tiny satellite. In addition, many small satellites have commercial-off-the-shelf (COTS) components. To reduce costs, many providers of COTS components do not include the optical and physical parameters necessary for accurate thermal analysis. Marshall Space Flight Center participated in the development and analysis of the Space Missile Defense Command-Operational Nanosatellite Effect (SMDC-ONE) and the Edison Demonstration of Smallsat Networks (EDSN) nanosatellites. These optical property measurements are documented here in hopes that they may benefit future nanosatellite and picosatellite programs and aid thermal analysis to ensure project goals are met, with the understanding that material properties may vary by vendor, batch, manufacturing process, and preflight handling. Where possible, complementary data are provided from ground simulations of the space environment and flight experiments, such as the Materials on International Space Station Experiment (MISSE) series. NASA gives no recommendation, endorsement, or preference, either expressed or implied, concerning materials and vendors used. Solar absorptance was calculated from spectral reflectance measurements made from 250 to 2,800 nm with an AZ Technology Laboratory Portable Spectroreflectometer (LPSR) model 300. ASTM E-903 was the test method used under normal laboratory conditions, and ASTM E-490 was the solar spectral irradiance data used to calculate solar absorptance. Most of the samples were flat, but stray light was minimized as much as possible with either a blackbody or black cloth as sample background. The LPSR has repeatability of approximately +/-1%, where solar absorptance is given as range, that is, from actual measurements taken across the sample. Infrared emittance measurements were made with an AZ Technology TEMP 2000A infrared reflectometer. This instrument measures the total hemispheric reflectance averaged over 3-35 micrometer wavelengths. ASTM E-408 was the test method used under normal laboratory conditions. 3 Stray light was minimized as much as possible. The TEMP 2000A has repeatability of approximately +/-0.5%, where infrared emittance is given as a range, that is, from actual measurements taken across the sample.

Finckenor, M. M.↗
DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗
DOE OSTI2022

Impact of Concurrent Solubilization and Fines Migration on Fracture Aperture Growth in Shales during Acidized Brine Injection

Acidic hydraulic fracturing fluid chemically and physically alters shale rock fabric during injection and shut-in, creating a “reaction-altered zone” along the fracture faces. To better characterize the variable thickness and composition of this reaction-altered zone under advective flow, we take a coupled experimental and modeling approach. A fluidic cell, with six fiducial markers, is first fabricated to keep the rock sample in place during the core floods and to allow image alignment of acquired images. Then, we conduct a series of reactive core floods in a clay-rich siliceous Wolfcamp shale sample with 10 wt % carbonate, using a synthetic fracturing fluid under no confining stress and at room temperature. High-resolution computed tomography (CT) scans are periodically conducted to observe the spatial alteration of the fracture network. We then perform scanning electron microscopy (SEM-EDS) on the two orthogonal surfaces (fracture surface and freshly cut profile face) to generate high-resolution elemental maps that show the change in mineralogy, both with distance along a given flow path along a fracture surface and with depth from the fracture surface into the shale matrix. These results are contrasted against a two-dimensional (2D) advection-diffusion reaction model developed previously for batch reactions between shale and synthetic fracturing fluids. The model simulates the geochemical interaction occurring at the fracture/matrix interface and penetrating into the shale matrix during the reactive core flood. Both model and experimental results show that the acidic brine is neutralized during the core flood, corresponding to an increase in fracture aperture as a function of fluid volume injected with the greatest change near the inlet. SEM-EDS scans reveal significant dissolution of carbonates on the fracture surface without pyrite oxidation. The reactive transport model indicates that carbonate depletion into the shale interior should be observable, yet SEM-EDS shows no discernible loss of carbonate in the orthogonal profile face. The combination of these observations suggests an additional fracture evolution mechanism in the reactive system, i.e., fines migration. We show that fines migration enhances the access of fracturing fluid to the matrix resulting in a more pronounced fracture widening. Finally, we conclude that coupled mineral dissolution and fines migration govern fracture aperture growth during acidized brine injection. In this work, we effectively show the underlying risk of relying solely on models that do not include an important (transport) process that can alter the system significantly and propose a combined chemomechanical mechanism for fracture evolution appropriate for this shale mineralogy.

58 GEOSCIENCES↗
DOE OSTI2024

Emulating ab initio computations of infinite nucleonic matter

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for > 10 6 different parametrizations of a chiral interaction model with explicit Δ -isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He 4 , we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Tetrafluoroboric Acid Digestion for Accurate Determination of Rare Earth Elements in Coal and Fly Ash by ICP-MS Analysis

Coal and coal-related fly ash often contain rare earth elements (REEs) that have the potential to be utilized as valuable mineral resources. Accurately determining the REE content in coal and fly ash is crucial for resource evaluation. The conventional approach involves using hydrofluoric acid (HF) to dissolve silicates and release REEs, which, however, prolongs the digestion process due to the additional step of complexing fluoride ions (F−) with boric acid (H3BO3). Determining the correct amount of H3BO3 for neutralization can be challenging, and in some instances, the binding of fluoride ions with certain lanthanides (Lns) hampers the accurate determination of all 14 naturally occurring rare earth elements in a single digestion batch by inductively coupled plasma mass spectrometry (ICP-MS). In this study, we present an alternative method that achieves the accurate determination of all 14 naturally occurring REEs using tetrafluoroboric acid (HBF4) followed by ICP-MS analysis. This approach eliminates the need for an F− complexing step. We tested this method on certified REE reference materials, including NIST 1632e (coal) and NIST 1633c (fly ash), as well as the REE geological reference material USGS AGV-1 (andesite). Our results demonstrated excellent recovery rates (relative standard deviation, RSD < ±10%), with a correlation coefficient (r2) exceeding 0.99. Using this method, we investigated the concentrations of all 14 REEs in coal and fly ash samples collected from various locations in the southwestern USA. This improved digestion technique streamlines the analysis process and enhances the accuracy of REE determination, facilitating a more comprehensive evaluation of REE-rich coal and fly ash deposits for resource exploration.

58 GEOSCIENCES↗
DOE OSTI2024

Thermochemical Transformation of Calcium during Biomass Burning and the Effects on Postfire Aqueous Dissolution of Macronutrients

Calcium is commonly the most abundant element in fire residues and its speciation largely determines the geochemical properties of fire residues and their effects on postfire soil chemistry. To explore the effects of biomass composition and fire conditions on ash Ca speciation, this study characterizes the speciation of Ca in charcoal and ash samples that were derived from different plant compartments and thermal conditions, using Ca K-edge X-ray absorption near edge spectroscopy. Results showed that biomass contains abundant organic Ca complexes, which were mineralized into fairchildite and calcite after heating at 450 to 600 °C and then CaO, as temperature increased to 750 °C. Apatite could be an abundant Ca species in fire residues if the Ca/P molar ratio of the biomass is small (<2). The mineralization of organic Ca to the identified Ca minerals during burning was negligibly affected by the oxygen level. Calcium speciation in prescribed fire residues resembled that of biomass ash burned at 550 °C with similar Ca/P molar ratios. Batch experiments showed that macronutrients (Ca, Mg, K, and P) were differentially released, as a result of different solubility of minerals in ashes and reprecipitation of minerals. The aqueous solubility of Ca, Mg, and P decreased as pH increased from 5 to 9, while K showed no pH dependency and was almost completely soluble. Results from this study improve our understanding of the chemistry of fire residues and their geochemical behaviors, which can help evaluate the impact of fire on postfire soil properties and macronutrient cycling.

36 MATERIALS SCIENCE↗
NASA NTRS2001

First Protein Crystallization Experiments on The International Space Station: Sweet Success in Space With Thaumatin

We determined the room temperature 1.2 A structure of thaumatin using a crystal grown in the first protein crystallization experiment conducted aboard the International Space Station (ISS). The crystals were grown in the Enhanced Gaseous Nitrogen Dewar (EGN) developed by Alexander McPherson and co-workers. EGN transports frozen solutions contained in tygon tubing in a liquid nitrogen Dewar to ISS where the tubes then thaw. Batch, free interface diffusion (FID), or vapor diffusion crystallization occurs after thawing. EGN was flown to the ISS on STS-106 on September 8, 2000. This was a "risk mitigation" flight that tested EGN performance and the process of conducting experiments on ISS. We focused on how to map a hanging drop crystallization recipe to the EGN FID method. Thaumatin was chosen as the test system. Three series of crystallization recipes were set-up. Each series tested different volume ratios of protein-rich solution to precipitant-rich solution. The series differed from each other by fixing either the protein concentration or the amount of protein in the solutions. Upon return of the samples to Earth on October 24 by STS-92, bubbles that spanned the diameter of the tubing were observed in all tubes. Such bubbles interrupt liquid-liquid diffusion and force vapor diffusion equilibration to occur instead. Nonetheless, crystals grew in 9 of 30 tubes. Many large crystals were grown, the largest being 2.0 x 1.1 x 1.0 cubic mm. The largest crystal was used to collect data at room temperature on beamline 7-1 of the Stanford Synchrotron Radiation Source to a maximum resolution of 1.2 A. The structure was refined anisotropically using SHELX with a data to parameter ratio of 4.5 to give an R(sub factor) of 15.8% (R(sub free) = 18.2%) for ail reflections without generated hydrogens. This refinement is proceeding. Comparisons of this 1.2 A microgravity structure to previous reports of the thaumatin structure at 1.75 A and to ground control crystals will be presented.

Kundrot, Craig E.↗
NASA NTRS1992

Running SINDA '85/FLUINT interactive on the VAX

Computer software as engineering tools are typically run in three modes: Batch, Demand, and Interactive. The first two are the most popular in the SINDA world. The third one is not so popular, due probably to the users inaccessibility to the command procedure files for running SINDA '85, or lack of familiarity with the SINDA '85 execution processes (pre-processor, processor, compilation, linking, execution and all of the file assignment, creation, deletions and de-assignments). Interactive is the mode that makes thermal analysis with SINDA '85 a real-time design tool. This paper explains a command procedure sufficient (the minimum modifications required in an existing demand command procedure) to run SINDA '85 on the VAX in an interactive mode. To exercise the procedure a sample problem is presented exemplifying the mode, plus additional programming capabilities available in SINDA '85. Following the same guidelines the process can be extended to other SINDA '85 residence computer platforms.

Simmonds, Boris↗
DOE OSTI2021

SB10 Frit Recommendation, and Evaluations of the Glass Variability Study and Cs-137 Concentrations in Strip Effluent Based on May 2021 Projections

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26F, Alternate Feed Stock-2 (AFS-2) and Sodium Reactor Experiment (SRE) material from H-Canyon. In support of SB10 qualification, frit development using 2020 Tank 40 blend projections and experimental work for the glass variability study were previously conducted. Frit 473 and Frit 209 were identified as candidate frits and both were included in the development of the variability study test matrix; however, a final frit recommendation was postponed until more information could be determined about the composition of SB10 after washing. In May 2021, Savannah River Remediation (SRR) reprojected SB10 based on the analytical results from the Tank 51 qualification sample that was washed in the Savannah River National Laboratory (SRNL) Shielded Cells Facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2001

Tracking and Data Relay Satellite (TDRS-3) Range Biases and Momentum Unload Modeling for Terra (EOS-AMI)

The Flight Dynamics Facility (FDF) reports its performance in meeting Tracking and Data Relay Satellite (TDRS) predicted ephemeris accuracy requirements with TDRS-3. The Terra (Earth Observing System AM-1) satellite has 3-sigma TDRS requirements of 75 m for total position accuracy predicted over one day onboard. The study sample includes selected cases over 21 months after Guam Remote Ground Terminal (GRGT) support started in June 1998. For daily solutions with a 1.5-day prediction span, predicted results of the study were below the Terra requirement by at least 12 m. Refined range bias estimation and modeled momentum unloads are needed to meet Terra's requirements for TDRS-3. Maintained at 275 W longitude over the zone of exclusion, TDRS-3 is analyzed separately from other TDRSs because of its unique tracking data. Only the Bilateration Ranging Transponder (BRT) at Alice Springs (ALS), Australia, and the Telemetry, Tracking and Command (TT&C) system at Guam are used for routine operational tracking data for TDRS-3. Simultaneous batch orbit solutions with three TDRSs and either the Compton Gamma Ray Observatory (GRO) or Terra were done with the Goddard Trajectory Determination System (GTDS) to periodically refine the TT&C and BRT System (BRTS) range biases. As new biases were determined, significant changes were made in estimating the absolute position. FDF achieved similar results using a sequential filter with all operational TDRSs and four user satellites. Definitive accuracy (3-sigma) is expected to be below 50 m. The White Sands Complex (WSC) performs momentum unloads to maintain three-axis stabilized attitude of TDRSs. The relationship between velocity changes (delta-V) and reaction wheel speed changes was empirically determined for roll/yaw unloads. A theoretical relationship was verified and used for pitch unloads. Modeling both pitch and roll/yaw momentum unloads is necessary to meet the 75-m requirement. Moving the orbit solution epoch an hour before a momentum unload can improve delta-V optimization and prediction accuracy over 1.5 days.

Ward, Douglas T.↗
DOE OSTI2023

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

High pressure, high flow rate batch mixing apparatus for high throughput experiments

An automated, high pressure, high flow rate batch mixing apparatus has been designed and constructed for rapid, stable, and repeatable mixing of multiple gases and vapors. The apparatus operates as an intermittent batch mixer with cycles of topping off fresh mixture to maintain pressure in an accumulator tank until consumed in an experimental apparatus. At high duty cycles, the apparatus can also function at steady state. This style of mixing is suitable for experiments such as high repetition rate shock tubes and other devices with intermittent flow demands. It is compact and portable, facilitating use in locations such as synchrotron light sources. The entire apparatus is heated to permit the mixing of vapors from species with low volatilities. The apparatus is fully automated and runs for extended periods with the only intervention being to refresh reagent supplies. Here, the accuracy and repeatability of the apparatus were verified by periodic gas sampling and analysis with gas chromatography. Multi-component mixtures spanning a wide range of complexity, dilution, and volatility of constituents have been prepared. The compositions of the majority of the mixture were found to be stable over several filling cycles, repeatable, and with the proper calibration of set-point conditions, accurate. Challenges were encountered preparing a mixture from multi-component liquids, and potential solutions are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation

Here, we present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks (GANs), normalizing flows, and variational auto-encoders (VAEs), are usually considered as unsupervised learning models, because labeled data are usually unavailable for training. Despite the success of the generative models, there are several issues with the unsupervised training, e.g., requirement of reversible architectures, vanishing gradients, and training instability. To enable supervised learning in generative models, we utilize the score-based diffusion model to generate labeled data. Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method. This approach uses mini-batch-based Monte Carlo estimators to directly approximate the score function at any spatial-temporal location in solving an ordinary differential equation (ODE), corresponding to the reverse-time stochastic differential equation (SDE). This approach can offer both high accuracy and substantial time savings in neural network training. Once the labeled data are generated, we can train a simple, fully connected neural network to learn the generative model in the supervised manner. Compared with existing normalizing flow models, our method does not require the use of reversible neural networks and avoids the computation of the Jacobian matrix. Compared with existing diffusion models, our method does not need to solve the reverse-time SDE to generate new samples. As a result, the sampling efficiency is significantly improved. We demonstrate the performance of our method by applying it to a set of 2D datasets as well as real data from the University of California Irvine (UCI) repository.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Low Temperature Regolith Bricks for In-Situ Structural Material

Current technology for producing in-situ structural materials on future missions to Mars or the moon relies heavily on energy-intensive sintering processes to produce solid bricks from regolith. This process requires heating the material up to temperatures in excess of 1000 C and results in solid regolith pieces with compressive strengths in the range of 14000 to 28000 psi, but are heavily dependent on the porosity of the final material and are brittle. This method is currently preferred over a low temperature cementation process to prevent consumption of precious water and other non-renewable materials. A high strength structural material with low energy requirements is still needed for future colonization of other planets. To fulfill these requirements, a nano-functionalization process has been developed to produce structural bricks from regolith simulant and shows promising mechanical strength results. Functionalization of granular silicate particles into alkoxides using a simple low temperature chemical process produces a high surface area zeolite particles that are held together via inter-particle oxygen bonding. Addition of water in the resulting zeolite particles produces a sol-gel reaction called "inorganic polymerization" which gives a strong solid material after a curing process at 60 C. The aqueous solution by-product of the reaction is currently being investigated for its reusability; an essential component of any ISRU technology. For this study, two batches of regolith bricks are synthesized from JSC-1A; the first batch from fresh solvents and chemicals, the second batch made from the water solution by-product of the first batch. This is done to determine the feasibility of recycling necessary components of the synthesis process, mainly water. Characterization including BET surface area, SEM, and EDS has been done on the regolith bricks as well as the constituent particles,. The specific surface area of 17.53 sq m/g (average) of the granular regolith material was obtained from nitrogen adsorption isotherm measurement. The size, shape and textures of regolith from SEM shows that the particles are 25-50 micrometers in size and mostly irregular in shape (Figure 1a). The elemental composition of regolith was identified from EDS analysis showed the presence of Si, Al, Fe, Na, Mg, Ca, Ti, O and C (see figure 1b). Each set of cylindrical brick samples were prepared by low energy process, and cured for 21 and 28 days, respectively to compare their compressive strength. Figure 1c, and d shows the JSC-1A brick and the compressive strength measurements. The results from the 21 day cured bricks (2 bricks) have been done and yielded an aver-age strength of 3050 psi, considerably higher than Portland cement mortars (Type IV and V). This promising technology provides the benefits of construction material similar to concrete, with a low complexity, low energy synthesis process and the likelihood of complete reusability of precious resources. Compressive strength using this method can be improved by increasing the surface area of the particles, using bi-modal particle size distribution, and adding certain additives to increase inter-particle forces.

ISRU↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗