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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Active predation, phylogenetic diversity, and global prevalence of myxobacteria in wastewater treatment plants

The operation of modern wastewater treatment plants (WWTPs) is driven by activated sludge microbiota, a complex assemblage of trophically interacting microorganisms. Microbial predation is crucial to fundamental understanding of how biological interactions drive microbiome structuring and functioning of WWTPs. However, predatory bacteria have received little attention regarding their diversity, activity, and ecological function in activated sludge, limiting the exploitation of food web interactions for wastewater microbiome engineering. Here, by using rRNA-stable isotope probing of activated sludge microbiota with 13 C-labeled prey bacteria, we uncovered diverse as-yet-uncultivated putative predatory bacteria that actively incorporated 13 C-biomass. Myxobacteria, especially Haliangium and the mle1-27 clade, were found as the dominant active predators, refreshing conventional views based on a few predatory isolates of Bdellovibrionota from WWTPs. The identified predatory bacteria showed more selective predation on prey compared with the protists dominated by ciliates, providing in situ evidence for inter-domain predation behavior divergence in activated sludge. Putative predatory bacteria were tracked over a two-year microbiome monitoring effort at a local WWTP, revealing the predominance of Myxococcota (6.5 ± 1.3%) over Bdellovibrionota (1.0 ± 0.2%) lineages. Phylogenetic analysis unveiled highly diverse myxobacteria inhabiting activated sludge and suggested a habitat filtering effect in global WWTPs. Further mining of a global activated sludge microbiome dataset revealed the prevalence of Myxococcota (5.4 ± 0.1%) species and potential impacts of myxobacterial predation on process performance. Collectively, our findings provided unique insights into the predating activity, diversity, and prevalence of Myxococcota species in activated sludge, highlighting their links with wastewater treatment processes via trophic regulation of enteric and functional bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Tailorable multiferroic tunnel junctions from all-van der Waals multilayer stacking

Multiferroic tunnel junctions (MFTJs) represent a class of multistate, non-volatile spintronic devices, in which electron tunnelling can be manipulated by switching long-range lattice and spin orders. In contrast to conventional oxide-based MFTJs, MFTJs constructed from two-dimensional van der Waals (vdW) crystals promise minimal defect concentration in the constituents and at interfaces, which may allow for probing intrinsic tunnelling physics and the development of high-performance devices. Here, in this study, we construct Fe 3 GeTe 2 /CuInP 2 S 6 /Fe 3 GeTe 2 all-vdW MFTJs by assembling multilayer flakes of ferromagnetic Fe 3 GeTe 2 electrodes and a ferroelectric CuInP 2 S 6 spacer. These MFTJs exhibit four non-volatile resistance states featuring sizable tunnelling magnetoresistance of ∼10 2 % and tunnelling electroresistance of ∼10 4 %. To tune the properties of the vdW MFTJ, we make use of the flexibility in material choice offered by vdW heterostructure devices; we use Fe 3 GeTe 2 /Fe 5 GeTe 2 asymmetric electrodes to boost the tunnelling electroresistance by 10 3 %, we integrate In 2 Se 3 as a ferroelectric with a smaller bandgap to enhance the ON-state current density by 10 4 % to 10 4 A cm −2 and we use Fe 3 GaTe 2 electrodes to demonstrate room temperature operation. Furthermore, when we combine the asymmetric ferromagnetic electrodes with the small-bandgap ferroelectric spacer to construct Fe 3 GeTe 2 /In 2 Se 3 /Fe 5 GeTe 2 MFTJs, we simultaneously realized tunnelling electroresistance of 10 6 % and an ON-state current density of 10 4 A cm −2 , both two orders of magnitude higher than the highest values achieved with conventional oxide-based MFTJs. In the future, our all-vdW MFTJs with the tailorability of all functional layers may make it possible to investigate fundamental aspects of interlayer tunnelling and enable the design of functional magnetoelectric nanodevices.

Xie, Ti [University of Maryland, College Park, MD ↗
NASA NTRS2019

Utilization of Unsupervised Anomalies Detector as a Tool for Managing the TDRS Constellation at GSFC

NASA’s Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The mission of the TDRS constellation is to provide relay communications from low-earth orbiting spacecraft to the primary ground station at the White Sands Complex in Las Cruces, New Mexico. Major customers include the International Space Station and Hubble Space Telescope. The NASA Space Network project office at GSFC manages the constellation of spacecraft. The constellation is over 30 years old, and a wide range of technologies and manufacturing techniques are represented on-orbit. Since 1983, the TDRS constellation has recorded thousands of gigabytes of telemetry data. Spacecraft telemetry data has changed throughout the three generations of TDRS spacecraft, however each spacecraft has the same basic functions with some generational enhancements. The constellation includes several spacecraft that have significantly outlived the manufacturer's projected lifetime. This has provided NASA with a significant benefit in terms of return on investment, however it places a burden on efficient management of the assets for maximum life without permitting a TDRS spacecraft to become stranded in its geosynchronous orbital slot. Consequently, the highest level of attention is paid to systems whose failure could strand a TDRS spacecraft in orbit. In this paper, we proposed two stages of analyzing spacecraft anomalies using data mining (DM) to enhance on-going predictions of spacecraft life, subsystem performance, and analysis of subsystem anomalies. The first stage conducts the unsupervised anomaly detector to detect potential anomalies in real-time telemetry data. The second stage introduced telemetry weight (TW) to each telemetry parameter to determine which parameter caused the strongest anomaly. We will present case studies of some of these analyses and how the data can impact decisions on the management of the constellation.

Ma, Kenneth Y.↗
DOE OSTI2021

Identifying schools at high-risk for elevated lead in drinking water using only publicly available data

Estimating the risk of lead contamination of schools' drinking water at the State level is a complex, important, and unexplored challenge. Variable water quality among water systems and changes in water chemistry during distribution affect lead dissolution rates from pipes and fittings. In addition, the locations of lead-bearing plumbing materials are uncertain. We tested the capability of six machine learning models to predict the likelihood of lead contamination of drinking water at the schools' taps using only publicly available datasets. The predictive features used in the models correspond to those with a proven correlation to the dominant, but commonly unavailable, factors that govern lead leaching: the presence of lead-bearing plumbing materials and water quality conducive to lead corrosion. By combining water chemistry data from public reports, socioeconomic information from the US census, and spatial features using Geographic Information Systems, we trained and tested models to estimate the likelihood of lead contaminated tap water in over 8,000 schools across California and Massachusetts. Our best-performing model was a Random Forest, with a 10-fold cross validation score of 0.88 for Massachusetts and 0.78 for California using the average Area Under the Receiver Operating Characteristic Curve (ROC AUC) metric. The model was then used to assign a lead leaching risk category to half of the schools across California (the other half was used for training). There was good agreement between the modeled risk categories and the actual lead leaching outcomes for every school; however, the model overestimated the lead leaching risk in up to 17% of the schools. This model is the first of its kind to offer a tool to predict the risk of lead leaching in schools at the State level. Further use of this model can help deploy limited resources more effectively to prevent childhood lead exposure from school drinking water.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Materials Design Directions for Solar Thermochemical Water Splitting

The sustainable, economical production of molecular hydrogen is a crucial component of a net zero-greenhouse-gas-emissions future. Solar thermochemical water splitting (STWS) offers a renewable route to hydrogen with the potential to help decarbonize several industries, including transportation, manufacturing, mining, metals processing, and electricity generation, as well as provide sustainable hydrogen as a chemical feedstock. STWS uses high temperatures generated from concentrated sunlight or other sustainable means for high-temperature heat to produce hydrogen and oxygen from steam. For example, in its simplest form of a two-step thermochemical cycle, a redox-active metal oxide is heated to ≈1700-2000 K, driving off molecular oxygen while producing oxygen vacancies in the material. The reduced metal oxide then cools (ideally with the extracted heat recuperated for re-use) and, in a separate step, comes into contact with steam, which reacts with oxygen vacancies to produce molecular hydrogen while recovering the original state of the metal oxide. Despite its promising use of the entire solar spectrum to split water thermochemically, the current estimated cost of hydrogen produced via STWS is ≈4-6× the U.S. Department of Energy (DOE) Hydrogen Shot target value of $1/kg. One contributing approach to bridging this cost gap is the design of new materials with improved thermodynamic properties to enable higher efficiencies. The state-of-the-art (SOA) redox-active metal oxide for STWS is ceria (CeO 2 ), due to its close to optimal, although too high, oxygen vacancy formation enthalpy and large configurational and electronic entropy of reduction. However, ceria requires high operating temperatures and its efficiency is insufficient. Therefore, efforts to increase the efficiency of STWS cycles have focused on further optimizing oxygen vacancy formation enthalpies and augmenting the reduction entropy via substitution or doping and materials discovery schemes. Examples of the latter include the perovskites BaCe 0.25 Mn 0.75 O 3 and (Ca,Ce)(Ti,Mn)O 3 . These efforts and others have revealed intuitive chemical principles for the efficient and systematic design of more effective materials, such as the strong correlation between the enthalpies of crystal bond dissociation and solid-state cation reduction with the enthalpy of oxygen vacancy formation, as well as configurational entropy augmentation via the coexistence of two or more redox-active cation sublattices. The purpose of this chapter is to prepare the reader with an up-to-date account of STWS redox-active materials, both the SOA and promising newcomers, as well as to provide chemically intuitive strategies for improving their cycle efficiencies through materials design – in conjunction with ongoing efforts in reactor engineering and gas separations – to reach the cost points for commercial viability. First, we will introduce the thermodynamics of STWS using a two-step, metal-oxide, thermochemical cycle with economics in mind. We also will compare the pros and cons of processes that do or do not involve phase changes. Second, we will describe the qualities that make ceria the SOA STWS redox-active material, as well as its limitations. Third, we will survey some of the most promising candidates to date in the search for materials to supplant ceria, emphasizing the post-ternary, metal-oxide-perovskite alloys. Lastly, we will enumerate and discuss the following materials design directions for STWS redox-active materials: crystal reduction potentials as a proxy for oxygen vacancy formation enthalpies, engineering the electronic and configurational entropy of reduction via f-shells and simultaneous redox, and vetting materials stability via temperature-dependent phase diagrams and melting-point prediction.

08 HYDROGEN↗
DOE OSTI2025

Physics-informed Deep Reinforcement Learning-based Control in Power systems

Incorporating physics information into the deep reinforcement learning (DRL) process is a promising approach for addressing the challenges faced in learning-based control design problems for physical systems. Power grid dynamics, being a physical system, adheres to specific physical laws, constraints, as well as operational and control rules. Therefore, consideration of such physics-based law improves the learning process drastically. In general, traditional grid control schemes rely on rule-based mechanisms that cannot adapt to changing operating conditions. To improve the adaptability and computation time, recent research has seen a surge of DRL-based applications in power grid control. A generic DRL-based control design imposes the system performance requirements through the design of reward functions. In some cases, some of the important physics information is injected through this reward function. However, due to the complex dynamics and large state-action space, learning an optimal DRL policy often becomes challenging. Inspired by the latest developments in general machine learning (ML) research, power system researchers have been investigating more direct ways of incorporating physics knowledge into DRL training. This chapter specifically focuses on these aspects of physics-informed DRL designs in grid control. It discusses the significance, applications, research gaps, and open problems that need to be addressed in future research.

artificial intelligence, machine learning↗
DOE OSTI2026

Unravelling chemical pathways of H 2 on Ga 2 O 3 surfaces with spectro-electrochemistry

This work highlights the capability of coupled spectroscopic and electrochemical techniques to probe dynamic surface processes under realistic operating conditions. By simultaneously employing in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and electrochemical impedance spectroscopy (EIS), we elucidate the mechanistic interaction between Ga 2 O 3 and hydrogen under elevated temperatures in a low-oxygen environment. This novel spectro-electrochemical approach allows chemistry to be correlated with the surface charge density of Ga 2 O 3 . Our results reveal a concentration-dependent transition in reaction pathway. At low concentrations, hydrogen reacts with ambient oxygen to form surface hydroxyls. At intermediate concentrations, hydrogen interacts with surface adsorbed oxygen to generate hydroxyl groups along with reducing the surface. Finally, at high H 2 concentrations, hydrogen reduces both hydroxyls and surface oxygen, leading to a highly conductive grain surface. As a result, hydrides form on the reduced Ga 2 O 3 surface. The gained insights are relevant for heterogeneous catalysis and gas sensing.

08 HYDROGEN↗
NASA NTRS2016

Initial Incidence of White Matter Hyperintensities on MRI in Astronauts

Introduction: Previous literature has described the increase in white matter hyperintensity (WMH) burden associated with hypobaric exposure in the U-2 and altitude chamber operating personnel. Although astronauts have similar hypobaric exposure pressures to the U2 pilot population, astronauts have far fewer exposures and each exposure would be associated with a much lower level of decompression stress due to rigorous countermeasures to prevent decompression sickness. Therefore, we postulated that the WMH burden in the astronaut population would be less than in U2 pilots. Methods: Twenty-one post-flight de-identified astronaut MRIs (5 mm slice thickness FLAIR sequences) were evaluated for WMH count and volume. The only additional data provided was an age range of the astronauts (43-57) and if they had ever performed an EVA (13 yes, 8 no). Results: WMH count in these 21 astronaut MRI was 21.0 +/- 24.8 (mean+/- SD) and volume was 0.382 +/- 0.602 ml, which was significantly higher than previously published results for the U2 pilots. No significant differences between EVA and no EVA groups existed. Age range of astronaut population is not directly comparable to the U2 population. Discussion: With significantly less frequent (sometimes none) and less stressful hypobaric exposures, yet a much higher incidence of increased WMH, this indicates the possibility of additional mechanisms beyond hypobaric exposure. This increase unlikely to be attributable just to the differences in age between astronauts and U2 pilots. Forward work includes continuing review of post-flight MRI and evaluation of pre to post flight MRI changes if available. Data mining for potential WMH risk factors includes collection of age, sex, spaceflight experience, EVA hours, other hypobaric exposures, hyperoxic exposures, radiation, high performance aircraft experience and past medical history. Finally, neurocognitive and vision/eye results will be evaluated for any evidence of impairment linked to increased WMH.

Norcross, Jason↗
NASA NTRS1994

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

J-ERS-1↗
NASA NTRSDate not supplied

Assessing the use of UAS-related terms in ASRS using Seed Topic Modeling

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database. Augmenting the discovery of topics of user interest in this online database would therefore be beneficial to the community it serves. Aim: We propose and execute an experiment to assess the use of seed term topic modeling using the database narratives to identify UAS reports. The use of seed term topic modeling would enable users to identify groups of related narratives associated to a topic of their interest. Method: We use a newly curated field in ASRS reports which identify UAS from non-UAS reports in combination of different set of UAS related terms to assess if seed topic modeling can be used in ASRS.

LDA↗
DOE OSTI2023

Analysis of backwash settings to maximize net water production in an engineering-scale ultrafiltration system for water reuse

Ultrafiltration (UF) has been widely utilized as water pretreatment for different applications especially in water reuse. The UF system operation is characterized by a filtration phase, where particles accumulate on the membrane surface resulting in an increase in the transmembrane pressure (TMP) and a cleaning phase, where foulants are removed through cleaning cycles including physical backwash and chemical-enhanced backwash (CEB). In this study, data from an engineering-scale UF system treating reclaimed wastewater were used to assess the impact of backwashing on the filtration process. TMP backwash trigger, backwash duration, and CEB frequency were purposely varied for a cycle-by-cycle investigation on the net water production, water recovery, initial operating TMP, and filtration cycle duration. As the TMP backwash trigger was varied between 62 and 145kPa, the maximum net water production (63 m 3 /d) was achieved at 103kPa and water recovery remained relatively constant at approximately 92%. Backwash durations of 45, 65, and 85s were performed where both net water production and water recovery yielded similar results (~63 m 3 /d and ~ 91%) compared with 103kPa TMP backwash trigger. The CEB frequency was also lowered from one every three backwashes (1/3) to 1/6 and 1/12 and resulted in decreased net water production and water recovery while the initial TMP increased. Interestingly, the total number of CEBs remained approximately constant regardless of their frequency. In conclusion, results suggest that CEB is an important fouling control process to maximize water production.

42 ENGINEERING↗
NASA NTRS2008

Inductive System Monitors Tasks

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

Source record↗
DOE OSTI2024

A Survey of Open Source Software Repositories in the U.S. Department of Energy’s National Laboratories

There are 17 national laboratory systems in the United States operating under the auspices of the U.S. Department of Energy (DOE). These government labs employ tens of thousands of people engaging in research software engineering activities across a variety of missions. To support this work, many open source projects are maintained. Further, many of these projects have broad utility to the computing community at large and domain scientists in a variety of fields. However, the complexity and decentralized nature of the laboratory system has resulted in a situation where no one entity even knows about all the open source software projects in this ecosystem, let alone crude metrics of their health. In this article, we do the first external inventory of open source software repositories with a nexus to DOE labs. We posit that a project’s need for sustainability support can be determined by comparing measures of active use to measures of active maintenance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

NASA Kennedy Space Center: Contributions to Sea Turtle Science and Conservation

The National Aeronautics and Space Administration (NASA) is a United States (US) federal agency that oversees US space exploration and aeronautical research. NASA's primary launch site, Kennedy Space Center (KSC) is located along the east coast of Florida, on Cape Canaveral and the western Atlantic Ocean. The natural environment within KSC's large land boundaries, not only functions as an extensive safety buffer-area, it performs simultaneously as a wildlife refuge and a national seashore. In the early 1960s, NASA was developing KSC for rocket launches and the US was establishing an awareness of, and commitment to protecting the environment. The US began creating regulations that required the consideration of the environment when taking action on federal land or with federal funds. The timing of the US Endangered Species Act (1973), the US National Environmental Policy Act (1972), coincided with the planning and implementation of the US Space Shuttle Program. This resulted in the first efforts to evaluate the impacts of space launch operation operations on waterways, air quality, habitats, and wildlife. The first KSC fauna and flora baseline studies were predominantly performed by University of Central Florida (then Florida Technological University). Numerous species of relative importance were observed and sea turtles were receiving regulatory review and protection as surveys by Dr. L Ehrhart (UCF) from 1973-1978 described turtles nesting along the KSC beaches and foraging in the KSC lagoon systems. These data were used in the first NASA Environmental Impact Statement for the Space Transportation System (shuttle program) in 1980. In 1982, NASA began a long term ecological monitoring program with contracted scientists on site. This included efforts to track sea turtle status and trends at KSC and maintain protective measures for these species. Many studies and collaborations have occurred on KSC over these last 45 years with agencies (USFWS, NOAA, NAVY), students, and universities (UCF, University of Toronto, Texas A&M, UF). This presentation will review the various studies and collaborations on sea turtles at KSC that include: nest distributions and success, stranding network development, aerial survey testing for nest counts, predator control assessments, the earliest baseline blood chemistry health determinations on nesting females, stress hormones in nesting females, multi-year study of hatchling sex ratios, genetics, species composition, abundance and distribution of in-water juveniles, turtle cold stun response, exterior lighting impacts and control, and satellite tag tracking of post-nesting turtles in the vicinity of near shore shoals and sand mining sites. Through these studies, monitoring, and recommendations, KSC has provided excellent stewardship and protection of the local environment. While conducting its space program mission, KSC has also made significant contributions of information for agencies charged with the conservation and management of these species

Provancha, Jane A.↗
DOE OSTI2022

King City Asbestos Corporation (KCAC) Mine Carbon Mineralization Field Test (Final Combined Report)

The overall objective of the KCAC carbon mineralization project is to determine the most successful approaches to CO 2 mineralization of asbestos-bearing serpentinite rocks and mine waste at the closed KCAC asbestos mine. The objectives of Budget Period 1 (BP1) are to characterize the site including, mineralogical and geochemical variability in site materials, baseline conditions including CO 2 flux and local climate, and to establish the designs for the second, experimental phase of the project. As described in Section 3 of this report, all tasks outlined in the Statement of Project Objective (SOPO) have been completed or are on schedule to be completed by the end of BP1. As described in Section 4, all success criteria and milestones have been met or will be met by the end of BP1. We conclude that the findings of BP1 strongly support moving to the second phase of the project to investigate methods to increase the rate of CO 2 mineralization. CO 2 flux monitoring during BP1 established an estimated baseline uptake of CO 2 over the 142,193 m 2 KCAC mine site of 147 and 179 metric tons CO 2 /yr using dynamic closed chamber and eddy covariance monitoring methods, respectively. Mineralogical analysis shows that the loose surficial waste material contains pyroaurite and minor hydromagnesite, indicating past carbon mineralization. Sediment samples at depths below 60 cm contained ~3 wt% brucite and localized high brucite contents of ~24 wt% were measured at depth, indicating significant unreacted material at relatively shallow depths. Together, these results demonstrate that despite prolonged exposure to the atmosphere, reactive material is still present and accessible and is naturally taking up atmospheric CO 2 . However, these natural rates are still well below rates that can be achieved by applying practices that can accelerate the CO 2 mineralization reaction. Designs for the Field-Testing Phase (BP2) of the project have been established, incorporating the findings of BP1. Based on results to date we have selected two methods to accelerate the rate of CO 2 mineralization, which we refer to as the Tilling Method and the Greenhouse Method. We hypothesize that these methods can increase the CO 2 mineralization rate by up to 5 times greater than the natural background rate measured in BP1. An Initial Lifecyle Assessment (LCA) and techno-economic analysis (TEA) were conducted for these two methods. The LCA concluded that the baseline version of the Greenhouse and Tilling methods at commercial scale are expected to achieve a CDR efficiency of 97% and 71%, respectively (cumulative, over 30 years of operation). Incorporating the net CO 2 removal rates calculated in the LCA, the TEA found the levelized, 30-year costs of the baseline Greenhouse and Tilling methods to be $\$$95/t-CO 2 and $\$$119/t-CO 2 , respectively, and that costs could be brought to well below $\$$100/t-CO 2 for either method by scaling up the volume of rock utilized. An initial EH&S Risk Assessment, evaluating the potential EH&S risks of the proposed carbon mineralization methods at commercial scale, was completed by LLNL EH&S professionals for these two methods.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

VIPER – Volatiles Investigating Polar Exploration Rover: Mission Overview

VIPER is a low cost, lunar volatiles detection and measurement mission that will be delivered to the lunar south pole by one of NASA’s Commercial Lunar Payload Services partners and will characterize the nature of the volatiles in the area and extrapolate this data to create global lunar water resource maps. It will be the first mining expedition on another world while simultaneously addressing fundamental planetary science questions. Prospecting for lunar water at the poles is the next step in understanding the resource potential and addressing key theories about water emplacement and retention. It now appears that potentially economically significant amounts of water ice exists at the poles of the Moon, however, the distribution of this water is still not understood at a level sufficient to fully evaluate economic models. The water ice (and other potential volatiles), the “ore body”, needs to be understood at the scales of 10s to 100s of meters to evaluate localization, extraction and processing techniques. To accomplish this, VIPER will survey permanently-shadowed regions, semi-permanent shadowed regions, and even semi and full sunlit areas in order to have a comprehensive survey of polar region volatiles, to best inform future mission architectures. In order to characterize the volatiles, a payload suite consisting of a neutron spectrometer, mass spectrometer, near infrared spectrometer and a 1-meter drill will be hosted on the VIPER mobile lunar rover platform. Since VIPER is a relatively low cost, schedule-constrained, risk-tolerant mission, there are architectural limitations that require unique mission planning constraints to enable exploration of the lunar south pole region. These regions offer unique challenges such as uncertain terrain conditions, rock and crater hazards, lunar dust, multipath communications effects, extreme thermal environments and multiple overlapping planning constraints. Mission design/traverse planning, system design capabilities and mission operations are all highly linked through initial development phases. We will describe the current mission overview and the unique approaches taken by the VIPER project based on our programmatic framework and unique mission environment.

VIPER↗
NASA NTRSDate not supplied

NASA Kennedy Space Center Swamp Works 10th Anniversary: Innovative Research & Technology Development Summary

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes rapid, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up fast, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This paper will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Robotic Mining↗
DOE OSTI2026

Accelerating Surface Radiation Content to Investigate the Impact of Radon Progeny on Superconducting Qubits

Ionizing radiation in the form of $α$, $β$, $γ$, and additional high-energy particles can induce decoherence via phonon and quasiparticle poisoning in superconducting qubits. Recent studies have explored this effect using cosmic rays or controlled radioactive sources held in the proximity of a qubit package, and have concluded that reductions in such ``external'' environmental radiation may benefit stable operation of qubit devices. However, the effect of long-lived, unstable daughters of $^{222}$Rn that ``plate out'' directly on device and packaging surfaces has not been as extensively explored. This plate-out process, well-known to the dark matter direct detection field, occurs throughout the fabrication and testing lifecycle of a device and (separately) its packaging, and produces a local source of $α$-decays which can remain active for decades. As this scales with chip area, understanding and managing this source of ionizing radiation is relevant for successfully scaling quantum computing architectures to larger numbers of qubits in a radiation-robust way. We present a setup capable of accelerating and enhancing radon daughter plateout by a factor of $7\times10^4$ over ambient, in order to study, \textit{in situ}, the impact of these events on superconducting qubits. We also provide outlook on the potential impact of this source of ionizing radiation on current and future qubit arrays.

Poudel, Sagar S. [South Dakota Sch. Mines Tech.]↗