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At least 721 records · Page 40
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NASA NTRS2022

Abundant phosphorus expected for possible life in Enceladus’s ocean

Saturn’s moon Enceladus has a potentially habitable subsurface water ocean that contains canonical building blocks of life (organic and inorganic carbon, ammonia, possibly hydro-gen sulfide) and chemical energy (disequilibria for methanogenesis). However, its habit-ability could be strongly affected by the unknown availability of phosphorus (P). Here, we perform thermodynamic and kinetic modeling that simulates P geochemistry based on recent insights into the geochemistry of the ocean–seafloor system on Enceladus. We find that aqueous P should predominantly exist as orthophosphate (e.g., HPO422), and total dissolved inorganic P could reach 1027to 1022mol/kg H2O, generally increasing with lower pH and higher dissolved CO2, but also depending upon dissolved ammonia and silica. Levels are much higher than<10210mol/kg H2Ofrompreviousestimatesand close to or higher than∼1026mol/kg H2O in modern Earth seawater. The high P concentration is primarily ascribed to a high (bi)carbonate concentration, which decreases the concentrations of multivalent cations via carbonate mineral formation, allowing phosphate to accumulate. Kinetic modeling of phosphate mineral dissolution suggests that geologically rapid release of P from seafloor weathering of a chondritic rocky core could supply millimoles of total dissolved P per kilogram of H2Owithin105y, much less than the likely age of Enceladus’s ocean (108to 109y). These results provide further evidence of habitable ocean conditions and show that any oceanic life would not be inhibited by low P availability.

Enceladus ocean↗
NASA NTRSDate not supplied

Modeling Ring-Opening Polymerization with Machine-Learned Committors

Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.

machine learning, polymer simulations, molecular d↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
NASA NTRSDate not supplied

Near-Term Policy Considerations for Lunar Missions

Near-Term Policy Considerations for Lunar Missions. Therese Jones1, Gabriel Swiney,1 and Katie McBrayer,2 1NASA HQ, 300 Hidden Figures Way SW, Washington, D.C. 20546, 2NASA Langley Re-search Center, 1 NASA Drive, Hampton, VA, 23666. (Contact: therese.m.jones@nasa.gov) Introduction: More than two dozen lunar missions are planned prior to the Artemis III crewed lunar landing, from Russian, Chinese, Indian, Japanese and U.S. government orbiters and landers to Commercial Lunar Payload Ser-vices missions to commercial crewed flybys. While the Artemis Accords have established an international consortium of countries seeking to mitigate interference between operations on the Moon, a number of unaddressed policy issues remain that may be critical to lunar operations. In this lightning talk, we build upon NASA’s Of-fice of Technology, Policy, and Strategy’s Sep-tember 2022 Report “Lunar Landing and Oper-ations Policy Analysis” [1], to give an overview of policy questions that remain open, including: whether to prioritize certain landing locations or avoid certain scientifically valuable locations, design and coordination of safety zones, notifi-cation of other actors of potential dangers posed by landing, whether to avoid placing equipment in operationally valuable locations, and end-of-life disposal. We will also discuss how these policy implications could apply to planned missions.. References: [1] Swiney, G., and Hernandez, A. Lunar Landing and Operations Policy Analy-sis, NASA Office of Technology, Policy, and Strategy, September 30, 2022 https://www.nasa.gov/sites/default/files/atoms/files/nasa-otps-lunar-landing-and-operations-policy-analysis-final-report_2.pdf

Therese Jones↗
NASA NTRS2022

Electroactive ZnO: Mechanisms, Conductivity, and Advances in Zn Alkaline Battery Cycling

Zinc oxide is of great interest for advanced energy devices because of its low cost, wide direct bandgap, non-toxicity, and facile electrochemistry. In zinc alkaline batteries, ZnO plays a critical role in electrode passivation, a process that hinders commercialization and remains poorly understood. Here, novel observations of an electroactive type of ZnO formed in Zn-metal alkaline electrodes are disclosed. The electrical conductivity of battery-formed ZnO is measured and found to vary by factors of up to 104, which provides a first-principles-based understanding of Zn passivation in industrial alkaline batteries. Simultaneous with this conductivity change, protons are inserted into the crystal structure and electrons are inserted into the conduction band in quantities up to ≈1020 cm−3 and ≈1 mAh gZnO−1. Electron insertion causes blue electrochromic coloration with efficiencies and rates competitive with leading electrochromic materials. The electroactivity of ZnO is evidently enabled by rapid crystal growth, which forms defects that complex with inserted cations, charge-balanced by the increase of conduction band electrons. This property distinguishes electroactive ZnO from inactive classical ZnO. Knowledge of this phenomenon is applied to improve cycling performance of industrial-design electrodes at 50% zinc utilization and the authors propose other uses for ZnO such as electrochromic devices.

Brendan E. Hawkins↗
NASA NTRS2024

Substrate Matters: Ionic Silver Alters Lettuce Growth, Nutrient Uptake, and Root Microbiome in a Hydroponics System

Ionic silver (Ag+) is being investigated as a residual biocide for use in NASA spacecraft potable water systems on future crewed missions. This water will be used to irrigate future spaceflight crop production systems. We have evaluated the impact of three concentrations (31 ppb, 125 ppb, and 500 ppb) of ionic silver biocide solutions on lettuce in an arcillite (calcinated clay particle substrate) and hydroponic (substrate-less) growth setup after 28 days. Lettuce plant growth was reduced in the hydroponic samples treated with 31 ppb silver and severely stunted for samples treated at 125 ppb and 500 ppb silver. No growth defects were observed in arcillite-grown lettuce. Silver was detectable in the hydroponic-grown lettuce leaves at each concentration but was not detected in the arcillite-grown lettuce leaves. Specifically, when 125 ppb silver water was applied to a hydroponics tray, Ag+ was detected at an average amount of 7 μg/g (dry weight) in lettuce leaves. The increase in Ag+ corresponded with a decrease in several essential elements in the lettuce tissue (Ca, K, P, S). In the arcillite growth setup, silver did not impact the plant root zone microbiome in terms of alpha diversity and relative abundance between treatments and control. However, with increasing silver concentration, the alpha diversity increased in lettuce root samples and in the water from the hydroponics tray samples. The genera in the hydroponic root and water samples were similar across the silver concentrations but displayed different relative abundances. This suggests that ionic silver was acting as a selective pressure for the microbes that colonize the hydroponic water. The surviving microbes likely utilized exudates from the stunted plant roots as a carbon source. Analysis of the root-associated microbiomes in response to silver showed enrichment of metagenomic pathways associated with alternate carbon source utilization, fatty-acid synthesis, and the ppGpp (guanosine 3′-diphosphate 5′-diphosphate) stringent response global regulatory system that operates under conditions of environmental stress. Nutrient solutions containing Ag+ in concentrations greater than 31 ppb in hydroponic systems lacking cation-exchange capacity can severely impact crop production due to stunting of plant growth.

lettuce↗
NASA NTRSDate not supplied

Degradation of Yttria-Stabilized Zirconia in Molten Regolith Electrolysis Applications

The generation of oxygen from lunar resources is an enabling technology to support a sustained human presence on the lunar surface. Molten regolith electrolysis is a promising process for directly electrolyzing lunar regolith, which is primarily a mixture of oxide minerals. During electrolysis, metallic products (Fe, Si) are formed at the cathode and oxygen is produced at the anode. In order to perform electrolysis, the regolith must be molten to enable ionic transport of metallic cations and oxygen anions, requiring an operating temperature of 1600C. Common refractory oxide materials, such as Al2O3 and MgO, undergo rapid degradation due to the high operating temperature and contact with the corrosive molten regolith. This work investigates yttria-stabilized zirconia (YSZ) for molten regolith electrolysis applications. Corrosion studies are presented to elucidate the degradation mechanism of YSZ powders and crucibles exposed to lunar regolith simulants at 1600C. Two regolith simulants are used to represent regolith from the lunar maria (JSC-1A) and the lunar highlands (LHS-1). Degradation of YSZ in contact with regolith simulants is evaluated using SEM/EDS, XRD, and EBSD. Furthermore, a modified molten regolith electrolysis reactor is presented utilizing YSZ at the anode to enable facile collection of oxygen produced during electrolysis.

Kevin Yu↗
NASA NTRS2024

Basalt Alteration in a CO 2 -SO 2 Atmosphere: Implications for Surface Processes on Venus

Venus’ surface and interior dynamics remain largely unconstrained, due in great part to the major obstacles to exploration imposed by its 470°C, 90 bar surface conditions and its thick, opaque atmosphere. Orbiter-based thermal emission data provide opportunities to characterize the surface composition of Venus. However, interpretations of such spectra depend on understanding interactions between the planet’s surface basaltic rocks and its caustic, sulfur dioxide (SO 2 )-bearing carbon dioxide (CO 2 ) atmosphere. Several studies, using remote sensing, thermodynamic modeling, and laboratory experiments, have placed constraints on basaltic alteration mineralogies and rates. Yet constraint with respect to SO 2 -mediated reactions with basalts of contrasting compositions remains incomplete. Here, we present new data from a series of gas-solid reaction experiments, in which samples of two basalt compositions were reacted in an SO 2 -bearing CO 2 atmosphere, at relevant Venus temperatures, pressure, and oxygen fugacity. We subjected reacted specimens to scanning electron microscopy (SEM) and scanning transmission electron microscopy (STEM) analyses using sample cross-sections produced with focused ion beam (FIB) milling. Surface alteration products were characterized, and their abundances estimated; subsurface cation concentrations were mapped to show depth of alteration. We demonstrate that the initial rate of reaction in our experiments is very rapid. Alkaline basalt samples are coated by (meta)thenardite (Na 2 SO 4 ) and amorphous calcium carbonate (CaCO 3 ) alteration products, and tholeiitic basalt samples are primarily covered by anhydrite (CaSO 4 ), Fe-oxide (Fe x O y : likely magnetite, Fe 3 O 4 ), and other minor phases.

Venus↗
NASA NTRS1995

Effect of modulator sorption on gradient shape in ion-exchange chromatography

Mobile phase additives, or modulators, are used in gradient elution chromatography to facilitate separation and reduce separation time. The modulators are usually assumed to be linearly adsorbed or unadsorbed. Here, the consequences of nonlinear modulator adsorption are examined for ion-exchange gradient elution through a series of simulations. Even when the buffer salt is identical to the modulator salt, gradient deformation is observed; the extent of deformation increases as the volume of the feed is increased. When the modulator salt is different from the buffer salt, unusual effects are observed, and the chromatograms are quite different from those predicted by classical gradient elution theory. In particular, local increases in the buffer concentration are found between feed bands, and serve to improve the separation. These effects become more pronounced as the feed volume increases, and could therefore prove valuable in preparative applications.

NASA Discipline Life Support Systems↗
NASA NTRS1986

Enhancement of nitrate uptake and growth of barley seedlings by calcium under saline conditions

The effect of Ca2+ on NO3- assimilation in young barley (Hordeum vulgare L. var CM 72) seedlings in the presence and absence of NaCl was studied. Calcium increased the activity of the NO3- transporter under saline conditions, but had little effect under nonsaline conditions. Calcium decreased the induction period for the NO3- transporter under both saline and nonsaline conditions but had little effect on its apparent Km for NO3- both in the presence and absence of NaCl. The enhancement of NO3- transport by Ca2+ under saline conditions was dependent on the presence of Ca2+ in the uptake solution along with the salt, since Ca2+ had no effect when supplied before or after salinity stress. Although Mn2+ and Mg2+ enhanced NO3- uptake under saline conditions, neither was as effective as Ca2+. In longer studies, increasing the Ca2+ concentration in saline nutrient solutions resulted in increases in NO3- assimilation and seedling growth.

NASA Discipline Number 61-10↗
NASA NTRS1993

Evolution in vitro: analysis of a lineage of ribozymes

Background: Catalytic RNAs, or ribozymes, possessing both a genotype and a phenotype, are ideal molecules for evolution experiments in vitro. A large, heterogeneous pool of RNAs can be subjected to multiple rounds of selection, amplification and mutation, leading to the development of variants that have some desired phenotype. Such experiments allow the investigator to correlate specific genetic changes with quantifiable alterations of the catalytic properties of the RNA. In addition, patterns of evolutionary change can be discerned through a detailed examination of the genotypic composition of the evolving RNA population. Results: Beginning with a pool of 10(13) variants of the Tetrahymena ribozyme, we carried out in vitro evolution experiments that led to the generation of ribozymes with the ability to cleave an RNA substrate in the presence of Ca2+ ions, an activity that does not exist for the wild-type molecule. Over the course of 12 generations, a seven-error variant emerged that has substantial Ca(2+)-dependent RNA-cleavage activity. Advantageous mutations increased in frequency in the population according to three distinct dynamics--logarithmic, linear and transient. Through a comparative analysis of 31 individual variants, we infer how certain mutations influence the catalytic properties of the ribozyme. Conclusions: In vitro evolution experiments make it possible to elucidate important aspects of both evolutionary biology and structural biochemistry on a reasonable short time scale.

Non-NASA Center↗
NASA NTRS1989

Calcium ion involvement in growth inhibition of mechanically stressed soybean (Glycine max) seedlings

A 40-50% reduction in soybean [Glycine max (L.) Merr. cv. Century 84] hypocotyl elongation occurred 24 h after application of mechanical stress. Exogenous Ca2+ at 10 mM inhibited growth by 28% if applied with the Ca2+ ionophore A23187 to the zone of maximum hypocotyl elongation. La3+ was even more inhibitory than Ca2+, especially above 5 mM. Treatment with ethyleneglycol-bis-(beta-aminoethylether)-N, N, N', N'-tetraacetic acid (EGTA) alone had no effect on growth of non-stressed seedlings at the concentrations used but negated stress-induced growth reduction by 36% at 4 mM when compared to non-treated, stressed controls. Treatment with EDTA was ineffective in negating stress-induced growth inhibition. Calmodulin antagonists calmidazolium, chlorpromazine, and 48/80 also negated stress-induced growth reduction by 23, 50, and 35%, respectively.

NASA Discipline Plant Biology↗
NASA NTRS1990

Characterization and effect of light on the plasma membrane H(+) -ATPase of bean leaves

Proton excretion from bean (Phaseolus vulgaris L.) leaf cells is increased by bright white light. To test whether this could be due, at least in part, to an increase in plasma membrane (PM) ATPase activity, PM vesicles were isolated from primary leaves by phase partitioning and used to characterize PM ATPase activity and changes in response to light. ATPase activity was characterized as magnesium ion dependent, vanadate sensitive, and slightly stimulated by potassium chloride. The pH optimum was 6.5, the Km was approximately 0.30 millimolar ATP, and the activity was about 60% latent. PM vesicles were prepared from leaves of plants grown for 11 days in dim red light (growing slowly) or grown for 10 days in dim red light and then transferred to bright white-light for 1 day (growing rapidly). For both light treatments, ATPase specific activity was approximately 600 to 700 nanomoles per milligram protein per minute, and the latency, Km, and sensitivity to potassium chloride were also similar. PM vesicles from plants grown in complete darkness, however, exhibited a twofold greater specific activity. We conclude that the promotion of leaf growth and proton excretion by bright white light is not due to an increase in ATPase specific activity. Light does influence ATPase activity, however; both dim red light and bright white light decreased the ATPase specific activity by nearly 50% as compared with dark-grown leaves.

NASA Program Space Biology↗
NASA NTRS1999

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

NASA Center LaRC↗
NASA NTRS1999

Effect of osteoblastic culture conditions on the structure of poly(DL-lactic-co-glycolic acid) foam scaffolds

Poly(DL-lactic-co-glycolic acid) (PLGA) foams are an osteoconductive support that holds promise for the development of bone tissue in vitro and implantation into orthopedic defects. Because it is desirable that foams maintain their shape and size, we examined a variety of foams cultured in vitro with osteoblastic cells. Foams were prepared with different porosities and pore sizes by the method of solvent casting/porogen leaching using 80, 85, and 90 wt% NaCl sieved with particle sizes of 150-300 and 300-500 microm and characterized by mercury intrusion porosimetry. Foams seeded with cells were found to have volumes after 7 days in static culture that decreased with increasing porosity: the least porous exhibited no change in volume while the most porous foams decreased by 39 +/- 10%. In addition, a correlation was observed between decreasing foam volume after 7 days in culture and decreasing internal surface area of the foams prior to seeding. Furthermore, foams prepared with the 300-500 microm porogen had lower porosities, greater mean wall thicknesses between adjacent pores, and larger volumes after 7 days in culture than those prepared with the smaller porogen. Two culture conditions for maintaining cells, static and agitated (in a rotary vessel), were found to have similar influences on foam size, cell density, and osteoblastic function for 7 and 14 days in culture. Finally, we examined unseeded foams in aqueous solutions of pH 3.0, 5.0, and 7.4 and found no significant decrease in foam size with degradation. This study demonstrates that adherent osteoblastic cells may collapse very porous PLGA foams prepared by solvent casting/particulate leaching: a potentially undesirable property for repair of orthopedic defects.

NASA Program Fundamental Space Biology↗
NASA NTRS1999

Mineral induced formation of pentose-2,4-bisphosphates

Formation of rac.-pentose-2,4-bisphosphates is demonstrated, starting from glycolaldehyde phosphate and glyceraldehyde-2-phosphate, and induced by mixed valence double layer metal hydroxide minerals. The reactions proceed from dilute aqueous reactant solutions (1.5 mM) at near neutral pH. Conditions have been established, where ribose-2,4-bisphosphate is the major product (approximately 48%) among the pentose-2,4-bisphosphates, which are formed with up to 25% yield.

Non-NASA Center↗