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NEEMO - NASA's Extreme Environment Mission Operations: On to a NEO

During NEEMO missions, a crew of six Aquanauts lives aboard the National Oceanic and Atmospheric Administration (NOAA) Aquarius Underwater Laboratory the world's only undersea laboratory located 5.6 km off shore from Key Largo, Florida. The Aquarius habitat is anchored 62 feet deep on Conch Reef which is a research only zone for coral reef monitoring in the Florida Keys National Marine Sanctuary. The crew lives in saturation for a week to ten days and conducts a variety of undersea EVAs (Extra Vehicular Activities) to test a suite of long-duration spaceflight Engineering, Biomedical, and Geoscience objectives. The crew also tests concepts for future lunar exploration using advanced navigation and communication equipment in support of the Constellation Program planetary exploration analog studies. The Astromaterials Research and Exploration Science (ARES) Directorate and Behavioral Health and Performance (BHP) at NASA/Johnson Space Center (JSC), Houston, Texas support this effort to produce a high-fidelity test-bed for studies of human planetary exploration in extreme environments as well as to develop and test the synergy between human and robotic curation protocols including sample collection, documentation, and sample handling. The geoscience objectives for NEEMO missions reflect the requirements for Lunar Surface Science outlined by the LEAG (Lunar Exploration Analysis Group) and CAPTEM (Curation and Analysis Planning Team for Extraterrestrial Materials) white paper [1]. The BHP objectives are to investigate best meas-ures and tools for assessing decrements in cogni-tive function due to fatigue, test the feasibility study examined how teams perform and interact across two levels, use NEEMO as a testbed for the development, deployment, and evaluation of a scheduling and planning tool. A suite of Space Life Sciences studies are accomplished as well, ranging from behavioral health and performance to immunology, nutrition, and EVA suit design results of which will directly support the investigation of open questions and operational concepts that will enable NASA to continue its plan for planetary exploration.

Bell, M. S.↗

GeoLab: A Geological Workstation for Future Missions

The GeoLab glovebox was, until November 2012, fully integrated into NASA's Deep Space Habitat (DSH) Analog Testbed. The conceptual design for GeoLab came from several sources, including current research instruments (Microgravity Science Glovebox) used on the International Space Station, existing Astromaterials Curation Laboratory hardware and clean room procedures, and mission scenarios developed for earlier programs. GeoLab allowed NASA scientists to test science operations related to contained sample examination during simulated exploration missions. The team demonstrated science operations that enhance theThe GeoLab glovebox was, until November 2012, fully integrated into NASA's Deep Space Habitat (DSH) Analog Testbed. The conceptual design for GeoLab came from several sources, including current research instruments (Microgravity Science Glovebox) used on the International Space Station, existing Astromaterials Curation Laboratory hardware and clean room procedures, and mission scenarios developed for earlier programs. GeoLab allowed NASA scientists to test science operations related to contained sample examination during simulated exploration missions. The team demonstrated science operations that enhance the early scientific returns from future missions and ensure that the best samples are selected for Earth return. The facility was also designed to foster the development of instrument technology. Since 2009, when GeoLab design and construction began, the GeoLab team [a group of scientists from the Astromaterials Acquisition and Curation Office within the Astromaterials Research and Exploration Science (ARES) Directorate at JSC] has progressively developed and reconfigured the GeoLab hardware and software interfaces and developed test objectives, which were to 1) determine requirements and strategies for sample handling and prioritization for geological operations on other planetary surfaces, 2) assess the scientific contribution of selective in-situ sample characterization for mission planning, operations, and sample prioritization, 3) evaluate analytical instruments and tools for providing efficient and meaningful data in advance of sample return and 4) identify science operations that leverage human presence with robotic tools. In the first year of tests (2010), GeoLab examined basic glovebox operations performed by one and two crewmembers and science operations performed by a remote science team. The 2010 tests also examined the efficacy of basic sample characterization [descriptions, microscopic imagery, X-ray fluorescence (XRF) analyses] and feedback to the science team. In year 2 (2011), the GeoLab team tested enhanced software and interfaces for the crew and science team (including Web-based and mobile device displays) and demonstrated laboratory configurability with a new diagnostic instrument (the Multispectral Microscopic Imager from the JPL and Arizona State University). In year 3 (2012), the GeoLab team installed and tested a robotic sample manipulator and evaluated robotic-human interfaces for science operations.

Evans, Cynthia↗

Mars Sample Return Science Planning Group Phase 2 (MSPG2): Overview & Interim Report

Mars Sample Return (MSR) has been a high priority of the international planetary science community for decades. In recent years, significant programmatic advances have brought MSR closer to becoming a reality. In 2018, NASA and the European Space Agency (ESA) signed a joint Statement of Intent to continue defining respective roles and responsibilities in the flight missions required to realize MSR. In October 2020, NASA and ESA formalized this partnership with the signature of a Memorandum of Understanding for the MSR flight elements. The MSR campaign consists of M2020, two MSR flight elements and the ground-based infrastructure to receive, handle and curate the samples from Mars. In an engineering sense, MSR consists of a linked set of missions, and a concluding set of ground-based activities, that we refer to as the MSR Campaign.

G. Kminek↗

LSKnowledge: Nexus for Transformative Scientific Discoveries and Enhanced Information Retrieval in NASA Life Sciences Portal

We stand at the brink of an extraordinary transformation in the field of AI, driven by the convergence of generative AI and semantic technologies (e.g., knowledge graphs). This fusion holds immense potential and could redefine the future of scientific exploration, particularly in the realm of life sciences research. In this context, we shed light on the pivotal roles that Large Language Models (LLMs) and semantic technologies will play in advancing research, unearthing and comprehending life sciences information through innovative approaches, and empowering researchers to extract insights from NASA's extensive Life Sciences Data Archive. Within the NASA Life Sciences Portal (NLSP), the integration of LLMs and semantic technologies unlocks several advanced capabilities. First and foremost, it equips scientists with sophisticated tools to manage the ever-expanding wealth of scientific literature and data. Furthermore, it facilitates the creation of knowledge graphs that visually represent intricate relationships among biological entities, enabling comprehensive systems-level analysis. Additionally, the fusion of generative AI (including LLMs) and semantic technology can significantly benefit NASA's life sciences research by enhancing information retrieval and hypothesis generation. These tools enhance natural language understanding, facilitating knowledge discovery within NLSP. The overarching vision is to establish a cohesive knowledge ecosystem within NLSP, harnessing the power of LLMs and semantic technologies to synthesize and cross-reference data from diverse missions, disciplines, and research domains. This holistic approach ultimately deepens our understanding of how space environments impact life sciences data. To advance this initiative, we have launched LSKnowledge, aimed at enhancing the information retrieval capabilities of NLSP. In the short term, our primary goal is to develop a robust semantic search system. This system will empower HRP (Human Research Program) researchers to navigate NLSP data repositories more efficiently and precisely, catalyzing the process of hypothesis formation and scientific breakthroughs. To achieve this, we have employed pre-trained LLMs as part of a semantic search tool that can rank and highlight the most relevant records for user queries. To assess the tool's performance, we have curated a set of approximately 200 queries from subject matter experts (SMEs) and manually ranked the top records retrieved by both the current search system and the new semantic search, using SME judgments as the gold standard for relevancy. Herein, we present the results of our comparative analysis and illustrate how these findings have informed the fine-tuning of the system for enhanced performance. In the long term, our objectives include 1) retrieving publicly available information and integrating it with NLSP data to provide more precise answers to user queries, and 2) incorporating non-textual information from the NLSP database into our approach. In conclusion, the fusion of LLMs and semantic technologies within NLSP represents a pioneering stride towards reshaping the landscape of scientific discovery. This synergy not only equips researchers with powerful tools to navigate the burgeoning sea of information but also facilitates a deeper understanding of complex biological relationships, all while accelerating hypothesis generation and knowledge discovery. Through our initiative, LSKnowledge, we are committed to continually refining and expanding these capabilities, with the aim of not only enhancing information retrieval but also integrating diverse data sources to provide more precise insights. In the grand vision, NLSP strives to become the cornerstone of a comprehensive knowledge ecosystem, unraveling the enigmatic intricacies of life sciences phenomena in the context of space environments.

Life Sciences↗

Stardust Curation at Johnson Space Center: Photo Documentation and Sample Processing of Submicron Dust Samples from Comet Wild 2 for Meteoritics Science Community

Dust particles released from comet 81P/Wild-2 were captured in silica aerogel on-board the STARDUST spacecraft and successfully returned to the Earth on January 15, 2006. STARDUST recovered thousands of particles ranging in size from 1 to 100 micrometers. The analysis of these samples is complicated by the small total mass collected ( < 1mg), its entrainment in the aerogel collection medium, and the fact that the cometary dust is comprised of submicrometer minerals and carbonaceous material. During the six month Preliminary Examination period, 75 tracks were extracted from the aerogel cells , but only 25 cometary residues were comprehensively studied by an international consortium of 180 scientists who investigated their mineralogy/petrology, organic/inorganic chemistry, optical properties and isotopic compositions. These detailed studies were made possible by sophisticated sample preparation methods developed for the STARDUST mission and by recent major advances in the sensitivity and spatial resolution of analytical instruments.

Nakamura-Messenger, K.↗

GLORIA - A Globally Representative Hyperspectral In Situ Dataset for Optical Sensing of Water Quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a , total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.

remote sensing of water quality↗

Extending the Reach of IGSN Beyond Earth: Implementing IGSN Registration to Link Nasa's Apollo Lunar Samples and Their Data

The rock and soil samples returned from the Apollo missions from 1969-72 have supported 46 years of research leading to advances in our understanding of the formation and evolution of the inner Solar System. NASA has been engaged in several initiatives that aim to restore, digitize, and make available to the public existing published and unpublished research data for the Apollo samples. One of these initiatives is a collaboration with IEDA (Interdisciplinary Earth Data Alliance) to develop MoonDB, a lunar geochemical database modeled after PetDB (Petrological Database of the Ocean Floor). In support of this initiative, NASA has adopted the use of IGSN (International Geo Sample Number) to generate persistent, unique identifiers for lunar samples that scientists can use when publishing research data. To facilitate the IGSN registration of the original 2,200 samples and over 120,000 subdivided samples, NASA has developed an application that retrieves sample metadata from the Lunar Curation Database and uses the SESAR API to automate the generation of IGSNs and registration of samples into SESAR (System for Earth Sample Registration). This presentation will describe the work done by NASA to map existing sample metadata to the IGSN metadata and integrate the IGSN registration process into the sample curation workflow, the lessons learned from this effort, and how this work can be extended in the future to help deal with the registration of large numbers of samples.

Todd, Nancy S.↗

In-Lab Rapid Analytical Detection of Lunar Volatiles By Universal Gas Analyzer With Comparison to GC-MS System

Introduction: The curation of permanently shadowed regions (PSRs) [1] on the lunar surface is centered around studies based upon the observed volatiles from the LCROSS mission [2]. The rapid detection of important volatile gases and vapors present in planetary bodies and Astromaterials by a standalone analytical device is an area of intense research interest in our group and Planetary Exploration & Astromaterials Research Laboratory (PEARL) facility and this work is relevant to the future preparation of viable lunar simulants for testing curation efforts down the road. The groundbreaking results obtained from the LCROSS Mission [2] open the requirements for the direct detection of volatiles present in regolith materials collected from the lunar surface. The mass spectrometry of volatile chemicals is a general technique that utilizes a set of instruments that creates charged ions from a gaseous chemical species and measures the intensities vs. mass-to-charge ratio (m/z) [3]. In this context, we discuss in-lab experimental results and procedures for rapid qualitative analysis of main LCROSS volatiles (water, H2S, NH3, CO2, and CH3OH) by a Universal Gas Analyzer (UGA) instrument. Additionally, the instrument performance was evaluated by measuring the isotopic abundance ratio of atmospheric Ar-40 to Ar-36 present in room air since, argon is a relevant gas in planetary studies as it can provide an insight and reference point to isotope studies [4]. Additional, cross comparisons were attempted and made between the two instruments to develop a robust analytical technique by comparing mass spectral data for H2S headspace samples with a Trace-1310/ ISQ 7000 (ThermoFisher Scientific.) GC-MS system. Background: The benchtop UGA System is equipped with an SRS UGA 300 quadrupole mass spectrometer designed and built by Stanford Research Systems [5]. This system can be configured for several types of gaseous chemical analysis. The inlet line continuously samples gases at low flow rates (several milliliters per minute) through a capillary limiting the intake pressure making the instrument ideal for online analysis of select gases and/or room atmosphere. Moreover, in our current UGA system, a change in composition at the inlet can be detected in about 200 milliseconds and a complete spectrum is acquired (for a range of 1-100 amu) in under 45 sec with masses measured at rates up to 25 msec per point [5]. This system provides a quick upstream analytical data that we can then compare to results obtained by our GC-MS system. Sample Preparation: Small volume (2-4 mL) of analyte sample was taken in a 10 mL glass vial and sealed with a crimped cap and purged with pure Ar or N2 gas to displace air from the top. The headspace sample was scanned by the UGA instrument at analog, histogram, and pressure vs. time modes. The isotopic abundance ratio for 40Ar-to-36Ar was estimated by measuring partial pressure vs. time scans and setting the mass at 40 and 36 respectively. Results and Discussions: In this work, we have investigated the applicability of the UGA system by qualitative analysis of a series of LCROSS volatiles measured individually. Fig. 1 demonstrates a set of vertically offset spectra for the partial pressures measured as a function of mass-to-charge (m/z) ratios. The average acquisition time for each spectrum was less than a minute suggesting that the UGA system is ideal for quick analysis of geochemical volatiles. For the cross-comparison, we analyzed an H2S headspace sample by a Trace-1310/ISQ-7000 system and compared mass spectral data with previously measured UGA histogram scan data (Fig. 2). In both cases, major peak positions are the same, however, the intensities of fragment ions ([1H132S]+ and [32S]+) are higher for UGA suggesting that the fragment ionization process is stronger in UGA compared to that of GC-MS. To investigate how the integrated area under each chromatogram varies with the headspace sample volume, a set of five H2S headspace samples with increasing volumes was analyzed by the GC-MS system (Fig. 3, inset). A small volume (e.g., 200 to 1000 µL) of H2S/H2O vapor was withdrawn from a 20 mL stock sample vial containing ~5 mL of 0.4% H2S in water by a gas-tight syringe and added to another 20 mL vial filled with argon and analyzed by the GC-MS system. Finally, the UGA detector sensitivity was evaluated by calculating the atmospheric 40Ar-to-36Ar isotopic abundance ratio in room air by running a partial pressure vs. time scan with setting the atomic mass at 40, and 36. Fig. 4(a) shows a ~25 min duration “P vs. time” scan for 40Ar (plot for 36Ar is not shown). The partial pressure values (~100 points) were corrected by subtracting the corresponding background pressure value for 37Ar and utilized to calculate 40Ar-to-36Ar isotopic abundance ratios as shown by Fig. 4b. The average isotopic abundance ratio is ~306 with a 2*STDEV ~13. This abundance ratio is significantly close to the previously reported value of 298.56 [6] and the ratio obtained by our GC-MS system (303 for a UHP grade Ar sample). Conclusions: Our study strongly evidenced that the benchtop UGA system is a valuable analytical tool for the detection of major LCROSS volatiles. The rapid scanning capability, the inexpensiveness of the whole system, and impressive detection sensitivity prove its worthiness as an essential device for advanced geochemical applications. Moreover, cross comparisons with the GC-MS provide important bridges into advanced curatorial efforts into the future. References: [1] Bickel, V.T., et al. (2021) Nat Commun 12, 5607. [2] Colaprete, A., et al. (2010) Science, 330, 463-468. [3] Glavin, D. P. et al. (2012) 2012 IEEE Aerospace Conference, 1-11. [4] Willett, C. D., et al. (2022) Geochimica et Cosmochimica Acta 329, 119-134. [5] Operation Manual and Programming Reference. (2018) Universal gas Analyzers, Stanford Research Systems. [6] Lee, J. Y., et al. (2006) Geochimica et Cosmochimica Acta 70, 4507–4512. Notes: (4 figures are attached with text as shown by the attached file)

Curation↗

AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and Autonomous Operations

The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. This poster presents AssistTaxi, which is a comprehensive novel dataset which is a collection of images for runway and taxiway analysis. The dataset comprises of more than 300,000 frames of diverse and carefully collected data, gathered from Melbourne (MLB) and Grant-Valkaria (X59) general aviation airports. The importance of AssistTaxi lies in its potential to advance autonomous operations, enabling researchers and developers to train and evaluate algorithms for efficient and safe taxiing. Researchers can utilize AssistTaxi to benchmark their algorithms, assess performance, and explore novel approaches for runway and taxiway analysis. Additionally, the dataset serves as a valuable resource for validating and enhancing existing algorithms as well as facilitating innovation in autonomous operations for aviation. We also propose an initial approach to label the dataset using a contour based detection and line extraction technique.

Data Collection↗

Tours of High-containment and Pristine Facilities in Support of Mars Sample Return (MSR) Sample Receiving Facility (SRF) Definition Studies

During 2019 and 2020, the NASA Tiger Team RAMA (acronym of the authors) toured several high-containment biosafety laboratories and pristine space-mission facilities worldwide to better understand their practices, capabilities, and lessons-learned to aid in planning a Sample Receiving Facility (SRF) in support of Mars Sample Return (MSR). The team also included tours of a manufacturer of mobile and modular high-containment facilities as well as manufacturers of isolators and gloveboxes. In addition, the team visited the European Space Agency (ESA)ultraclean and sterile ISO 3 / airborne molecular contamination -9 (AMC-9) isolator line to clean and assemble the most critical hardware for ESA’s ExoMars Mars Lander System, and researchers developing a novel double-walled isolator (DWI) and robotic handling techniques in support of an MSR SRF. The RAMA team visits covered several construction modalities for an MSR SRF: (1) a new traditional fixed facility; (2) use of an existing fixed Biosafety Level 4(BSL-4) facility; (3) a novel modular BSL-4 approach; and (4) a hybrid combination of fixed, modular, and existing facilities. A new fixed facility approach can be tailored to MSR’s needs and is the approach used by all U.S. BSL-4 laboratories constructed to date. However, this approach could be the most expensive modality, take the longest to implement (8-12 years), and have significant programmatic risk of delay. The utilization of an existing BSL-4 facility may be possible depending on the final contamination control and science requirements for the MSR SRF. Due to the internal dimensions of the labs visited and facility structural requirements, it is unlikely that any modification can be made to the facility to meet cleanliness requirements. Furthermore, due to possible construction delays, possible capacity issues, and potential cross contamination vectors from in-house select agents, there may also be significant programmatic risks for sharing an existing facility. Another approach is building a contemporary modular facility. This is a novel approach that has recently been used for a BSL-3/3Ag facilities. The modular elements would be installed in a traditional building or shell structure. A modular facility has many advantages over a traditional fixed facility with lower costs, shorter design/construction/ commissioning schedule, and flexibility for easier retrofits and future expansion. Lastly, a hybrid approach of combining the use of either: (1) a modular facility inside a new fixed facility or (2) a modular and/or fixed BSL-4 annex in conjunction with an existing BSL-4 space should be considered. The advantage of a hybrid approach is that the facility could leverage the strengths of other approaches. Beyond facility construction approaches, the RAMA team investigated technologies and techniques for isolating and handling Martian samples in pristine environments. For example, ESA has been studying and developing a DWI breadboard along with other sample-handling technologies. The research and development investment for clean, remote manipulation and robotics at the start of the facility design phase would be beneficial to the SRF. Additionally, under-standing the lessons learned from Thales Alenia Space during the construction and operation of the most advanced state-of-the-art precision cleaning, sterilization, and assembly glovebox isolators ever developed for spacecraft hardware are also critical for the SRF. The RAMA team lays out a summary of the 18 facilities toured, and includes 43 observations,18 findings, and 22 areas of possible follow-up that the RAMA team and others could pursue to enable further findings. The observations and findings illustrate that constructing an MSR SRF would combine the complexity of both high-containment and pristine facilities, and merging these technologies would be challenging, but achievable.

Mars Sample Return↗

NASA Ames Institutional Scientific Collection (ISC)

NASA's current human space flight research is directed towards enabling human space exploration beyond Low Earth Orbit (LEO). The Space Flight Payload Projects; Rodent Research, Cell Science, and Microbial Labs, flown on the International Space Station (ISS), benefit both the global life sciences and commercial space communities. Verified data sets, science results, peer-reviewed publications, and returned biospecimens, collected and analyzed for flight and ground investigations, are all part of the knowledge base within NASA’s Human Exploration and Operations Mission Directorate’s Space Life and Physical Sciences Research and Applications (SLPSRA) Division, specifically the Human Research and Space Biology Programs. These data and biospecimens are made available through the public LSDA website. The Ames Institutional Scientific Collection (ISC), or ARC Biobank, stores flight and ground biospecimens from Space Shuttle and ISS programs. These specimens are curated and managed by the Ames Life Sciences Data Archive (ALSDA), an internal node of NASA's Life Sciences Data Archive (LSDA). The ARC Biolbank stores over 15,000 specimens from experiments dating from 1984 to present. Currently available specimens include tissues from the circulatory, digestive, endocrine, excretory, integumentary, muscular, neurosensory, reproductive, respiratory and skeletal systems. The most recent contributions include RNA, DNA and protein extracts from Rodent Research 1 and tissues from Rodent Research 4. NASA's biospecimen collection represents a unique and limited resource. The use of these biospecimens maximizes utilization and scientific return from these unique spaceflight payload and ground control research subjects. These biospecimens are harvested following complex, costly NASA research activities to meet primary scientific objectives. Once the primary scientific objectives have been met, the remaining specimens are made available to provide secondary opportunities for complementary studies or new investigations to broaden research without large expenditures of time or resources. Innovative ways of sharing this information ultimately advances the frontiers of human space exploration as well as scientific understanding of the effects of gravity on life on earth.

French, Alison J.↗

Cislunar Trajectory Design and Maneuver Autonomy for NASA's Moon to Mars Architecture

NASA’s Moon to Mars architecture is an ambitious roadmap of manned cislunar and deep space exploration. The extensive amount of orbital assets required will place a significant burden on ground-based resources, such as communication networks and operations facilities. Spacecraft autonomy is essential for maintaining a vast number of complex missions beyond Earth orbit. To achieve full autonomy, spacecraft must be able to employ methods of robust maneuver design without an explicit dependence on commands sent from the ground. This level of autonomy is needed not only for stationkeeping, but also for outbound transfers. To address the need of spacecraft maneuver design autonomy, this work investigates the use of neural networks (NNs) in a supervised learning environment. A supervised learning approach for NNs allows for a curated training data set, consisting exclusively of perturbations applied to a desired mission concept of operations (ConOps). The proposed approach allows humans on the ground to design a specific mission ConOps before flight, then employ NNs to fly the mission robustly and autonomously. This investigation numerically tests maneuver autonomy in four highly sensitive regions of flight: orbit raising, translunar injection burns, powered lunar flybys, and invariant manifold insertion burns. These straining cases are contextualized by testing them in a demonstration mission, targeting an Earth-Moon L3 orbit. The study first establishes feasibility by automating impulsive burn maneuvers. However, some guidance algorithms will need more intensive commands, such as inertial pointing and angular rates. To validate this method, NN maneuver autonomy is applied to a finite burn model of the demonstration mission. The use of sequential, mission specific maneuvers provide an appropriate testbed to demonstrate the robustness of a NN trained on feasible perturbed states. Moreover, these scenarios provide preliminary proof-of-concept for fully autonomous missions that execute maneuvers without dependence upon explicit command uplinks. As a result, the technological advancement proposed in this work may significantly ease the strain on ground-based mission operations. This would enable complex and autonomous mission execution in cislunar and deep space regimes, filling a technology gap required to support future manned missions.

NASA↗

Finding Atmospheric Composition (AC) Metadata

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

metadata search↗

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗

Preserving the Science Legacy from the Apollo Missions to the Moon

Six Apollo missions landed on the Moon from 1969-72, returning to Earth 382 kg of lunar rock, soil, and core samples-among the best documented and preserved samples on Earth that have supported a robust research program for 45 years. From mission planning through sample collection, preliminary examination, and subsequent research, strict protocols and procedures are followed for handling and allocating Apollo subsamples. Even today, 100s of samples are allocated for research each year, building on the science foundation laid down by the early Apollo sample studies and combining new data from today's instrumentation, lunar remote sensing missions and lunar meteorites. Today's research includes advances in our understanding of lunar volatiles, lunar formation and evolution, and the origin of evolved lunar lithologies. Much sample information is available to researchers at curator.jsc.nasa.gov. Decades of analyses on lunar samples are published in LPSC proceedings volumes and other peer-reviewed journals, and tabulated in lunar sample compendia entries. However, for much of the 1969-1995 period, the processing documentation, individual and consortia analyses, and unpublished results exist only in analog forms or primitive digital formats that are either inaccessible or at risk of being lost forever because critical data from early investigators remain unpublished. We have initiated several new efforts to rescue some of the early Apollo data, including unpublished analytical data. We are scanning NASA documentation that is related to the Apollo missions and sample processing, and we are collaborating with IEDA to establish a geochemical database called Moon DB. To populate this database, we are working with prominent lunar PIs to organize and transcribe years of both published and unpublished data. Other initiatives include micro-CT scanning of complex lunar samples to document their interior structure (e.g. clasts, vesicles); linking high-resolution scans of Apollo film products to samples; and new procedures for systematic high resolution photography of samples before additional processing, enabling detailed 3D reconstructions of the samples. All of these efforts will provide comprehensive access to Apollo samples and support better curation of the samples for decades to come.

Evans, Cindy↗

Mars Sample Receiving Facility Research and Development to Enable Preservation, Safe Containment, and Scientific Research of Martian Samples on Earth

NASA and ESA are working together to plan a joint campaign to potentially bring back the first Martian samples to Earth in the early 2030s. On the surface of Mars, the Mars 2020Perseverance Rover is selecting and packaging samples that could be returned to Earth for careful examination by an international team of scientists. In preparation for this historic sample return, advance planning is underway to design and build a Mars Sample Receiving Facility (SRF) in the mid-2020s. In 2022, a Mars Sample Receiving Facility Assessment Study(MSAS) will be conducted to further define construction modality and capability options for a facility in the conterminous United States. Since Mars Sample Return (MSR) is currently categorized as a planetary protection restricted Earth return, this new facility would feature biosafety level 4 (BSL-4)-like high containment to protect Earth’s biosphere from any potential hazard. In addition, the facility also requires integration of cleanroom technologies to mitigate against terrestrial contamination and preserve sample integrity for science investigations. The integration of both clean handling and high containment requires significant technology research and development (R&D) by the mid-2020s to support the definition and planning of a SRF before commencing the site specific design phase. The SRF project will need to solidify the inorganic, organic, and biological contamination control (CC) requirements for the facility. This could entail a translation of Mars 2020 mission CC requirements for geologic material to engineering requirements for surfaces and airborne molecular contamination inside isolators and cleanrooms. In tandem, the project will need to determine precision cleaning and sterilization approaches for cleanrooms, isolators, equipment, and tools. Initial material selections for the facility construction materials, cleanrooms, isolators, and BSL-4 suits/garments are an important activity. The recent construction of the OSIRIS-REx and Hayabusa2 curation cleanroom laboratories greatly benefited from early materials testing, before the design phase, to reduced organic outgassing and particulate shedding inside the laboratory. While the early biohazard investigations in the SRF may deem the samples safe to release to laboratories throughout the world, sterilization methods need to be defined to safely release Martian samples. One key aspect of enabling simultaneous sample containment and cleanliness is the concept of a Double-Walled Isolator (DWI) that ESA has been pursuing. Further R&D is needed about DWIs, sample handling, and instrumentation interfaces before beginning the SRF site specific design phase. A working isolator/DWI engineering model should be developed and fabricated. Isolator sizes, connections, pass-through antechambers, and configurations and basic interfaces with instruments and tools as well as the use of robotic, mechanical, and/or human manipulation need to be considered. Inert high purity gas supply (one-pass or recirculation) and other isolator utilities must be determined. Special accommodations for large instruments (e.g., XCT,SEM, etc.) need to be developed. Techniques for opening the sample tubes packaged by M2020and extracting the headspace gas while keeping samples pristine will be challenging, requiring additional R&D, and engagement of the M2020 project. In addition, careful micromanipulation for subdivision and packaging of samples will also need to be included. These combined R&D activities are important before commencing the SRF design phase to ensure safe biohazard containment, sample preservation, and science integrity for the samples that would be studied in the SRF and in laboratories around the world.

mars sample return↗

NASA’s In-Space Manufacturing Project: Update on Manufacturing Technologies and Materials to Enable More Sustainable and Safer Exploration

NASA’s In-Space Manufacturing (ISM) project seeks to develop the materials, processes, and manufacturing technologies needed to provide an on-demand manufacturing capability for deep space exploration missions. The ability to manufacture and recycle some parts on demand rather than launch them from earth has the potential to reduce logistics requirements on long duration missions and enhance crew safety. With the launch of the first 3D printer (built and operated by Made in Space through a Small Business Innovative Research – SBIR -- contract) to the International Space Station (ISS) in 2014, the ISM project demonstrated the feasibility of operating an on-demand manufacturing system in a microgravity environment. This paper will provide an update on recent advancements in ISM under three key technology areas: manufacturing, recycling, and development of a design database. ISM continues to pursue development of manufacturing technologies for space applications and use the ISS as a critical test bed to prove out these technologies before deploying them on next generation exploration systems. Activities under this focus area include: characterization of materials manufactured using the Additive Manufacturing Facility (AMF), the second generation commercial 3D-printer on ISS, also owned and operated by Made in Space; development of prototype payloads for metal manufacturing through phase II SBIR contracts with Tethers Unlimited, Made in Space, and Ultra Tech Machinery; development of a multi-material fabrication laboratory capable of processing metals and providing inspection of manufactured parts through a Broad Agency Announcement (Techshot, Interlog, and Tethers Unlimited); an in-line sensing system for ISM platforms; and development of higher strength feedstocks for 3D polymer printers. In the area of recycling, the Tethers Unlimited Refabricator payload (an integrated 3D printer and recycler for ULTEM 9085) launched to ISS in November 2018 and began operating in early 2019. This payload represents the first demonstration of on-orbit recycling; down massed specimens will assess material degradation in the polymer over multiple recycling cycles to define limits on material re-use. Other work in the recycling area includes development of common use materials intended to be reused and recycled on space missions (Tethers Unlimited and Cornerstone Research Group) and a sterilization capability for multiple-use materials (ERASMUS from Tethers Unlimited). Concurrent with manufacturing technology and materials development work is creation of a design database, a curated list of parts that can be manufactured using the suite of In-Space Manufacturing capabilities.

Tracie Prater↗

Dividing the Concentrator Target From the Genesis Mission

The Genesis spacecraft, launched in 2001, traveled to a Lagrangian point between the Earth and Sun to collect particles from the solar wind and return them to Earth. However, during the return of the spacecraft in 2004, the parachute failed to open during descent, and the Genesis spacecraft crashed into the Utah desert. Many of the solar wind collectors were broken into smaller pieces, and the field team rapidly collected the capsule and collector pieces for later assessment. On each of the next few days, the team discovered that various collectors had survived intact, including three of four concentrator targets. Within a month, the team had imaged more than 10,000 fragments and packed them for transport to the Astromaterials Acquisition and Curation Office within the ARES Directorate at JSC. Currently, the Genesis samples are curated along with the other extraterrestrial sample collections within ARES. Although they were broken and dirty, the Genesis solar wind collectors still offered the science community the opportunity to better understand our Sun and the solar system as a whole. One of the more highly prized concentrator collectors survived the crash almost completely intact. The Genesis Concentrator was designed to concentrate the solar wind by a factor of at least 20 so that solar oxygen and nitrogen isotopes could be measured. One of these materials was the Diamond-on-Silicon (DoS) concentrator target. Unfortunately, the DoS concentrator broke on impact. Nevertheless, the scientific value of the DoS concentrator target was high. The Genesis Allocation Committee received a request for approximately 1 cm(sup 2) of the DoS specimen taken near the focal point of the concentrator for the analysis of solar wind nitrogen isotopes. The largest fragment, Genesis sample 60000, was designated for this allocation and needed to be precisely cut. The requirement was to subdivide the designated sample in a manner that prevented contamination of the sample and minimized the risk of losing or breaking the precious requested sample fragment. The Genesis curator determined that the use of laser scribing techniques to "cut" a precise line and subsequently cleave the sample (in a controlled break of the sample along that line) was the best method for accomplishing the sample subdivision. However, there were risks, including excess heating of the sample, that could cause some of the implanted solar wind to be lost via thermal diffusion. Accidentally breaking the sample during the handling and cleaving process was an additional risk. Early in fiscal year 2013, to address this delicate, complicated task, the ARES Directorate assembled its top scientists to develop a cutting plan that would ensure success when applied to the actual concentrator target wafer; i.e., to produce an approximately 1 cm(sup 2) piece from the requested area of the wafer. The team, subsequently referred to as the JSC Genesis Tiger Team, spent months researching and testing parameters and techniques related to scribing, cleaving, transporting, handling, and holding (i.e., mounting) the specimen. The investigation required considerable "thinking outside the box," and many, many trials using nonflight wafer analogs. After all preliminary testing, the following method was adopted as the final cutting plan. It was used in two final end-to-end practice runs before being used on the actual flight target wafer. The wafer was oriented on the laser cutting stage with the 100 and 010 directions of the wafer parallel to the corresponding X and Y directions of the cutting stage. The laser was programed to scribe 31 lines of the appropriate length along the Y stage direction. The programed scribe lines were separated by 5 micron in the X direction. The laser parameters were set as follows: (1) The laser power was 0.5 watts; (2) each line consisted of 50 passes, with the Z position being advanced 5 micron per pass; and (3) 30 s would elapse before the next line was scribed to allow for wafer cool down from any possible heating via the laser. The ablated material that "stuck" in the "scribe-cut" was removed from the "cut" using an ultrasonic micro-tool. After all the ablated silicon was removed from the wafer, the wafer was repositioned in exactly the same orientation on the laser stage. The laser was focused using the bottom of the wafer channel, and the 31-line scribing pattern described above was reprogrammed using the Z position of the groove bottom as the starting Z value instead of the top wafer surface, which was used previously. Upon completion of the second set of scribes, the ultrasonic micro-tool was again used to clean out the cut. The wafer was remounted on the stage in exactly the same orientation as before. The laser was again focused on the bottom of the groove. This time, however, the laser was.programed to scribe only one line down the exact center of the channel. The final scribe line consisted of 100 passes with a Z advance of 5 micron per pass and with the laser power set at 0.5 watts. As mentioned above, the final cutting plan was practiced in two end-to-end trials using non-flight, triangular-shaped silicon wafers similar in size and orientation to the actual DOS 60000 target sample. The actual scribing of the triangular-shaped wafers required scribing two lines and cleaving (i.e. scribe-cleave, then scribe-cleave) to obtain the piece requested for allocation. Early in December 2012, after many months of experiments and practicing and perfecting the techniques and procedures, the team successfully subdivided the Genesis DoS 60000 target sample, one of the most scientifically important samples from the Genesis mission (figure 2). On December 17, 2012, the allocated piece of concentrator target sample was delivered to the requesting principal investigator.The cutting plan developed for the subdivision of this sample will be used as the model for subdividing future requested Genesis flight wafers (appropriately modified for different wafer types).

Lauer, H. V., Jr.↗