Results for “Sustained presence” — Page 23

NASA NTRS2004

Using Iron to Treat Chlorohydrocarbon-Contaminated Soil

A method of in situ remediation of soil contaminated with chlorinated hydrocarbon solvents involves injection of nanometer-size iron particles. The present method exploits a combination of prompt chemical remediation followed by longer-term enhanced bioremediation and, optionally, is practiced in conjunction with the method of bioremediation described earlier. Newly injected iron particles chemically reduce chlorinated hydrocarbons upon contact. Thereafter, in the presence of groundwater, the particles slowly corrode via chemical reactions that effect sustained release of dissolved hydrogen. The hydrogen serves as an electron donor, increasing the metabolic activity of the anaerobic bacteria and thereby sustaining bioremediation at a rate higher than the natural rate.

Hitchens, G. Duncan↗

NASA NTRSDate not supplied

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

NASA NTRSDate not supplied

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

NASA NTRS1974

Stability study of the Large Space Telescope /LST/ system with nonlinear CMG gimbal friction

The purpose of the investigation reported upon is to study the existence and characteristics of self-sustained oscillations in the dynamic behavior of the Large Space Telescope (LST) system due to the presence of nonlinear gimbal friction in the control moment gyroscopes (CMGs). A continuous-data single-axis model of the LST is considered. A solid friction model is used to represent CMG gimbal friction. A rigorous mathematical model is derived for use in a continuous describing function analysis. Conditions for self-sustained oscillations are then determined.

Kuo, B. C.↗

DOE OSTI2021

Sustained Ability of a Natural Microbial Community to Remove Nitrate from Groundwater

Abstract Microbial‐mediated nitrate removal from groundwater is widely recognized as the predominant mechanism for nitrate attenuation in contaminated aquifers and is largely dependent on the presence of a carbon‐bearing electron donor. The repeated exposure of a natural microbial community to an electron donor can result in the sustained ability of the community to remove nitrate; this phenomenon has been clearly demonstrated at the laboratory scale. However, in situ demonstrations of this ability are lacking. For this study, ethanol (electron donor) was repeatedly injected into a groundwater well (treatment) for six consecutive weeks to establish the sustained ability of a microbial community to remove nitrate. A second well (control) located upgradient was not injected with ethanol during this time. The treatment well demonstrated strong evidence of sustained ability as evident by ethanol, nitrate, and subsequent sulfate removal up to 21, 64, and 68%, respectively, as compared to the conservative tracer (bromide) upon consecutive exposures. Both wells were then monitored for six additional weeks under natural (no injection) conditions. During the final week, ethanol was injected into both treatment and control wells. The treatment well demonstrated sustained ability as evident by ethanol and nitrate removal up to 20 and 21%, respectively, as compared to bromide, whereas the control did not show strong evidence of nitrate removal (5% removal). Surprisingly, the treatment well did not indicate a sustained and selective enrichment of a microbial community. These results suggested that the predominant mechanism(s) of sustained ability likely exist at the enzymatic‐ and/or genetic‐levels. The results of this study demonstrated the in situ ability of a microbial community to remove nitrate can be sustained in the prolonged absence of an electron donor.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRSDate not supplied

NASA SIBatt-3D: In-Space and On-Surface 3D Printing Sodium-Ion Batteries from ISRU Materials

Sustainable on-demand power solutions are an absolute necessity as humanity works to establish a permanent presence on the moon and make the journey to Mars. NASA’s SIBatt-3D project is developing shape-conformable Sodium-Ion batteries that can be 3D printed in-space as needed during extended space missions. SIBatt-3D seeks to utilize materials found in Lunar/Martian regolith as feedstocks to provide sustainable power for surface operations. SIBatt-3D’s batteries also have terrestrial implications such as improved battery safety and sustainability.

Cameroun Sherrard↗

DOE OSTI2023

Enzymatic Nitrogen Incorporation Using Hydroxylamine

Hydroxylamine-derived reagents have enabled versatile nitrene transfer reactions for introducing nitrogen-containing functionalities in small-molecule catalysis as well as biocatalysis. These reagents, however, result in poor atom economy and stoichiometric organic waste. Activating hydroxylamine (NH 2 OH) for nitrene transfer offers a low-cost and sustainable route to amine synthesis, since water is the sole byproduct. Despite its presence in nature, however, hydroxylamine is not known to be used for enzymatic nitrogen incorporation in biosynthesis. Here, we report an engineered heme enzyme that can utilize hydroxylammonium chloride, an inexpensive commodity chemical, for nitrene transfer. Directed evolution of Pyrobaculum arsenaticum protoglobin generated efficient enzymes for benzylic C–H primary amination and styrene aminohydroxylation. Mechanistic studies supported a stepwise radical pathway involving rate-limiting hydrogen atom transfer. Furthermore, this unprecedented activity is a useful addition to the ‘nitrene transferase’ repertoire and hints at possible future discovery of natural enzymes that use hydroxylamine for amination chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

Field-Aligned Poynting Flux Observations in the High-Latitude Ionosphere

We have used data from Dynamics Explorer 2 to investigate the rate of conversion of electromagnetic energy into both thermal and bulk flow particle kinetic energy in the high-latitude ionosphere. The flux tube integrated conversion rate E(dot)J can be determined from spacecraft measurements of the electric and magnetic field vectors by deriving the field-aligned Poynting flux, S(parallel) = S(dot)B(sub 0), where B(sub 0) is in the direction of the geomagnetic field. Determination of the Poynting flux from satellite observations is critically dependent upon the establishment of accurate values of the fields and is especially sensitive to errors in the baseline (unperturbed) geomagnetic field. We discuss our treatment of the data in some detail, particularly in regard to systematically correcting the measured magnetic field to account for attitude changes and model deficiencies. S(parallel) can be used to identify the relative strengths of the magnetosphere and thermospheric winds as energy drivers and we present observations demonstrating the dominance of each of these. Dominance of the magnetospheric driver is indicated by S(parallel) directed into the ionosphere. Electromagnetic energy is delivered to and dissipated within the region. Dominance of the neutral wind requires that the conductivity weighted neutral wind speed in the direction of the ion drift be larger than the ion drift, resulting in observations of an upward directed Poynting flux. Electromagnetic energy is generated within the ionospheric region in this case. We also present observations of a case where the neutral atmosphere motion may be reaching a state of sustained bulk flow velocity as evidenced by very small Poynting flux in the presence of large electric fields.

Slavin, J. A.↗

NASA NTRS2011

Deep Space Habitat ECLS Design Concept

Life support is vital to human spaceflight, and most current life support systems employ single-use hardware or regenerable technologies that throw away the waste products, relying on resupply to make up the consumables lost in the process. Because the long-term goal of the National Aeronautics and Space Administration is to expand human presence beyond low-earth orbit, life support systems must become self-sustaining for missions where resupply is not practical. From May through October 2011, the life support team at the Johnson Space Center was challenged to define requirements, develop a system concept, and create a preliminary life support system design for a non-planetary Deep Space Habitat that could sustain a crew of four in near earth orbit for a duration of 388 days. Some of the preferred technology choices to support this architecture were passed over as the mission definition also has an unmanned portion lasting 825 days. The main portion of the architecture was derived from technologies currently integrated on the International Space Station as well as upcoming technologies with moderate Technology Readiness Levels. The final architecture concept contains only partially-closed air and water systems, as the breakeven point for some of the closure technologies was not achieved with the mission duration.

Curley, Su↗

NASA NTRS2011

Allocation of Functions in a Far-Term Air Traffic Control Environment

A human-in-the-loop exploration of a ground-based automated separation assurance concept was conducted that involved the allocation of certain functions between humans and automation. This exploration included operations that were sustained for prolonged periods of time with high levels of traffic in the presence of convective weather and scheduling constraints. An investigation into the acceptability of the defined roles and performance of tasks was conducted where it was found that the participants rated the concept and allocation of functions with a high level of acceptability. However, issues were encountered with the automation related to the detection of and response to tactical conflicts. Lower ratings were given on account of these concerns, and it was found that a key contributor to the underlying problems was transitioning aircraft and the uncertainty of their trajectories. Stemming from those results, participants responded that they would rather have direct control over aircraft transitions as well as more control over the tactical conflict resolution automation. In contrast, participants responded that they would rather have the automation place aircraft back on trajectory, and perform weather avoidance and scheduling tasks.

Homola, Jeffrey↗

NASA NTRS2012

Deep Space Habitat ECLSS Design Concept

Life support is vital to human spaceflight, and most current life support systems employ single-use hardware or regenerable technologies that throw away the waste products, relying on resupply to make up the consumables lost in the process. Because the long-term goal of the National Aeronautics and Space Administration is to expand human presence beyond low-earth orbit, life support systems must become self-sustaining for missions where resupply is not practical. From May through October 2011, the life support team at the Johnson Space Center was challenged to define requirements, develop a system concept, and create a preliminary life support system design for a non-planetary Deep Space Habitat that could sustain a crew of four in near earth orbit for a duration of 388 days. Some of the preferred technology choices to support this architecture were passed over because the mission definition has an unmanned portion lasting 825 days. The main portion of the architecture was derived from technologies currently integrated on the International Space Station as well as upcoming technologies with moderate Technology Readiness Levels. The final architecture concept contains only partially-closed air and water systems, as the breakeven point for some of the closure technologies was not achieved with the mission duration.

Curley, Su↗

DOE OSTI2025

Biotransformation of Pesticides across Biological Systems: Molecular Mechanisms, Omics Insights, and Biotechnological Advances for Environmental Sustainability

The widespread application of pesticides such as organophosphates, organochlorides, and triazines in modern agriculture has led to their notable presence in soils, water bodies, and food chains, raising concerns about persistence, bioaccumulation, and adverse effects on nontarget organisms. Biotransformation, the enzymatic transformation of xenobiotic compounds by microorganisms, plants, and animals, plays a pivotal role in the degradation and detoxification of these chemicals. This review provides a comprehensive examination of the mechanisms, key enzyme classes (e.g., hydrolases, oxidoreductases, transferases), and environmental factors influencing pesticide biotransformation across different biological systems. Recent advances in omics technologies have revolutionized the understanding of microbial and plant metabolism, while synthetic biology offers opportunities for engineering enhanced degradation capabilities. The environmental fate of transformation products is also discussed, together with a critical analysis of challenges, unresolved questions, and future research directions, offering a holistic perspective on pesticide biotransformation as a key process for mitigating chemical pollution.

Biotransformation↗

NASA NTRS1979

Experimental investigation of flow and heating in a resonance tube

Experiments have been performed to determine the basic mechanism of heating in resonance tubes of square section with constant area excited by underexpanded jet flows. The jet flow between the nozzle exit and the tube inlet plays a key role in the performance of a resonance tube. A detailed and systematic investigation of the unsteady complex shock structure in this part of the flow region has led to a better understanding of the fundamental mechanisms associated with the gas heating in such tubes. A study of the effects of tube location in relation to free-jet shock location (without the presence of the resonance tube) has shed further light on the underlying mechanism of sustained oscillations of the flow in a resonance tube.

Sarohia, V.↗

NASA NTRS2009

Hypersonic Viscous Flow Over Large Roughness Elements

Viscous flow over discrete or distributed surface roughness has great implications for hypersonic flight due to aerothermodynamic considerations related to laminar-turbulent transition. Current prediction capability is greatly hampered by the limited knowledge base for such flows. To help fill that gap, numerical computations are used to investigate the intricate flow physics involved. An unstructured mesh, compressible Navier-Stokes code based on the space-time conservation element, solution element (CESE) method is used to perform time-accurate Navier-Stokes calculations for two roughness shapes investigated in wind tunnel experiments at NASA Langley Research Center. It was found through 2D parametric study that at subcritical Reynolds numbers, spontaneous absolute instability accompanying by sustained vortex shedding downstream of the roughness is likely to take place at subsonic free-stream conditions. On the other hand, convective instability may be the dominant mechanism for supersonic boundary layers. Three-dimensional calculations for both a rectangular and a cylindrical roughness element at post-shock Mach numbers of 4.1 and 6.5 also confirm that no self-sustained vortex generation from the top face of the roughness is observed, despite the presence of flow unsteadiness for the smaller post-shock Mach number case.

Chang, Chau-Lyan↗

NASA NTRS2016

Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric Disorders: Evidence Report

In April 2010, President Obama declared a space pioneering goal for the United States in general and NASA in particular. "Fifty years after the creation of NASA, our goal is no longer just a destination to reach. Our goal is the capacity for people to work and learn and operate and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite." Thus NASA's Strategic Objective 1.1 emerged as "expand human presence into the solar system and to the surface of Mars to advance exploration, science, innovation, benefits to humanity, and international collaboration" (NASA 2015b). Any space flight, be it of long or short duration, occurs in an extreme environment that has unique stressors. Even with excellent selection methods, the potential for behavioral problems among space flight crews remain a threat to mission success. Assessment of factors that are related to behavioral health can help minimize the chances of distress and, thus, reduce the likelihood of adverse cognitive or behavioral conditions and psychiatric disorders arising within a crew. Similarly, countermeasures that focus on prevention and treatment can mitigate the cognitive or behavioral conditions that, should they arise, would impact mission success. Given the general consensus that longer duration, isolation, and confined missions have a greater risk for behavioral health ensuring crew behavioral health over the long term is essential. Risk, which within the context of this report is assessed with respect to behavioral health and performance, is addressed to deter development of cognitive and behavioral degradations or psychiatric conditions in space flight and analog populations, and to monitor, detect, and treat early risk factors, predictors and other contributing factors. Based on space flight and analog evidence, the average incidence rate of an adverse behavioral health event occurring during a space mission is relatively low for the current conditions. While mood and anxiety disturbances have occurred, no behavioral emergencies have been reported to date in space flight. Anecdotal and empirical evidence indicate that the likelihood of an adverse cognitive or behavioral condition or psychiatric disorder occurring greatly increases with the length of a mission. Further, while cognitive, behavioral, or psychiatric conditions might not immediately and directly threaten mission success, such conditions can, and do, adversely impact individual and crew health, welfare, and performance.

Slack, Kelley J.↗

NASA NTRSDate not supplied

Comparison Study of Machine Learning Techniques to Predict Flight Energy Consumption for Advanced Air Mobility

This paper addresses the need to predict the flight energy consumption of aerial vehicles in the presence of wind using machine learning techniques. The presented work is critical to achieving sustainable and efficient operations for Advanced Air Mobility (AAM) and to evaluating the readiness of the ground-supporting energy infrastructure, e.g., electric grid and AAM portals. The flight energy consumption is described using the "energy per meter" (EPM) metric. We present a comparison study of influential machine learning techniques in predicting EPM using real-world flight test data. We presented new results of using the Decision Tree, Random Forest, and linear regression techniques, along with our previous results using the Recurrent Neural Network and Feed Forward Neural Network techniques. The comparison results show that the Linear Regression method outperforms other methods on the basis of the Mean Squared Error and error variance.

Machine Learning↗

NASA NTRSDate not supplied

SIBatt-3D In-Space/On-Surface 3D Printing of Sodium Ion Batteries using ISRU Materials

Sustainable on-demand power solutions are an absolute necessity as humanity works to establish a permanent presence on the moon and make the journey to Mars. NASA’s SIBatt-3D Early Career Initiative project at MSFC is developing shape-conformable Sodium-Ion batteries that can be 3D printed in-space as needed during extended space missions. SIBatt-3D makes use of the unique advantages of 3D printing to create shape-conformable batteries with improved performance that reduce dead volume in devices and seeks to utilize materials found in Lunar/Martian regolith as feedstocks to provide sustainable power for surface operations on the Moon and Mars. SIBatt-3D’s batteries also have terrestrial implications such as improved battery safety and sustainability.

3D Printing↗