Results for “Sample curation” — Page 20

NASA NTRS2014

Ames Life Science Data Archive: Translational Rodent Research at Ames

The Life Science Data Archive (LSDA) office at Ames is responsible for collecting, curating, distributing and maintaining information pertaining to animal and plant experiments conducted in low earth orbit aboard various space vehicles from 1965 to present. The LSDA will soon be archiving data and tissues samples collected on the next generation of commercial vehicles; e.g., SpaceX & Cygnus Commercial Cargo Craft. To date over 375 rodent flight experiments with translational application have been archived by the Ames LSDA office. This knowledge base of fundamental research can be used to understand mechanisms that affect higher organisms in microgravity and help define additional research whose results could lead the way to closing gaps identified by the Human Research Program (HRP). This poster will highlight Ames contribution to the existing knowledge base and how the LSDA can be a resource to help answer the questions surrounding human health in long duration space exploration. In addition, it will illustrate how this body of knowledge was utilized to further our understanding of how space flight affects the human system and the ability to develop countermeasures that negate the deleterious effects of space flight. The Ames Life Sciences Data Archive (ALSDA) includes current descriptions of over 700 experiments conducted aboard the Shuttle, International Space Station (ISS), NASA/MIR, Bion/Cosmos, Gemini, Biosatellites, Apollo, Skylab, Russian Foton, and ground bed rest studies. Research areas cover Behavior and Performance, Bone and Calcium Physiology, Cardiovascular Physiology, Cell and Molecular Biology, Chronobiology, Developmental Biology, Endocrinology, Environmental Monitoring, Gastrointestinal Physiology, Hematology, Immunology, Life Support System, Metabolism and Nutrition, Microbiology, Muscle Physiology, Neurophysiology, Pharmacology, Plant Biology, Pulmonary Physiology, Radiation Biology, Renal, Fluid and Electrolyte Physiology, and Toxicology. These experiment descriptions and data can be accessed online via the public LSDA website (http://lsda.jsc.nasa.gov) and information can be requested via the Data Request form at http://lsda.jsc.nasa.gov/common/dataRequest/dataRequest.aspx or by contacting the ALSDA Office at: Alison.J.French@nasa.gov

Life Sciences↗

DOE OSTI2024

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2018

Three Proposed Compendia for Genesis Solar Wind Samples: Science Results, Collector Materials Characterization and Cleaning Techniques

Final Paper and not the abstract is attached. Introduction: Planetary material and cosmochemistry research using Genesis solar wind samples (including the development and implementation of cleaning and analytical techniques) has matured sufficiently that compilations on several topics, if made publically accessible, would be beneficial for researchers and reviewers. We propose here three compendia based on content, organization and source of documents (e.g. published peer-reviewed, published, internal memos, archives). For planning purposes, suggestions are solicited from potential users of Genesis solar wind samples for the type of science content and/or organizational style that would be most useful to them. These compendia are proposed as living documents, periodically updated. Similar to the existing compendia described below, the curation compendia are like library or archival finding aids, they are guides to published or archival documents and should not be cited as primary sources.

Allton, J. H.↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 2

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 3

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 4

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

NASA NTRS1992

Material selection and evaluation of new encapsulation compounds for electric cables for launch support system

Eight urethane compounds were evaluated as possible replacement for the existing encapsulating compoounds for electrical cables for the Launch Support System at Kennedy Space Center (KSC). The existing encapsulating compound, PR-1535, contains the curative MOCA 4-4'-Methylene-BIS (2-chloroaniline), which is a suspect carcinogen and hence may be the subject of further restrictions of its use by the Occupational Safety and Health Administration (OSHA). The samples made in the configuration of cable joints and in the form of disks were evaluated for flammability and hypergolic compatibility. These also underwent accelerated weatherability tests that measured the residual hardness of the exposed samples. Three candidates and the existing compound passed the hardness test. Of these, only one candidate and the existing compound passed the flammability test. The thermal and hydrolytic stability (weatherability) of these samples was studied using thermogravimetric analysis (DSC) techniques. The TMA and DSC data correlated with the residual hardness data; whereas, the TGA data showed no correlation. A hypergolic compatibility test will be conducted on the compound V-356-HE80, which passed both the flammability and accelerated weatherability tests.

Ray, Asit K.↗

NASA NTRS2022

Characterization of Lunar Polar Volatiles for Curation and ISRU - Executive Summary

The goal of this project is to support lunar exploration by simulating and characterizing ice and volatile-rich materials expected to be found at the lunar poles. These materials are highly sensitive to heating, which could significantly alter their composition and prevent scientific studies on lunar samples. During FY19, we obtained materials for and designed a simulated lunar environment, within which volatile-rich simulant could be made. We also refined the procedure for moderate-fidelity lunar simulants at cryogenic temperatures. In FY20, we completed our test setup, and we can now reach cryogenic temperatures and near-lunar pressures with active compositional monitoring of volatiles in the vapor phase. For FY21, we: 1) progressed towards developing sample storage temperature requirements for volatile-rich samples by completing storage testing, along with materials testing for Artemis geologic sampling, 2) obtained instrumentation for solid sample monitoring to characterize solid species, and 3) progressed towards water extraction testing for ISRU. Our test results will directly feed into Artemis science requirements, hardware designs for sample return, vehicle requirements (HLS, Gateway, Orion), and operations planning for lunar exploration activities.

Julie L Mitchell↗

DOE OSTI2026

Database of virus genomes from ultra-deep sequencing of wastewater

Researchers at University of Missouri have conducted ultra-deep RNA sequencing of viral concentrates from wastewater (1 billion Illumina reads per sample). The resulting dataset spans 321 samples collected weekly from 11 cities between 2023-2025. As part of a tri-lab collaboration, scientists at LLNL and LANL cleaned, assembled, and annotated this metagenomic data, identifying nearly 200,000 viral genomes. Careful data curation resulted in a database containing 21,015 high-quality, near-complete viral genomes from wastewater. This database contains viruses predicted to infect a range of hosts including bacteria (most common viruses), plants (most abundant viruses), and vertebrates (rarest viruses). There are also numerous novel viruses that could not be well identified and whose host(s) are unknown. Just 7% of all genomes in the wastewater virus database had genus-level matches in the public NCBI database, and 17% matched to a recently created metagenomic virus database at that level (metaVR). The database will provide baseline information about viruses in wastewater that may be used to additional identify novel viruses during ongoing monitoring

Allen, Jonathan [Lawrence Livermore National Labor↗

NASA NTRS2014

Rapid Classification of Ordinary Chondrites Using Raman Spectroscopy

Classification of ordinary chondrites is typically done through measurements of the composition of olivine and pyroxenes. Historically, this measurement has usually been performed via electron microprobe, oil immersion or other methods which can be costly through lost sample material during thin section preparation. Raman microscopy can perform the same measurements but considerably faster and with much less sample preparation allowing for faster classification. Raman spectroscopy can facilitate more rapid classification of large amounts of chondrites such as those retrieved from North Africa and potentially Antarctica, are present in large collections, or are submitted to a curation facility by the public. With development, this approach may provide a completely automated classification method of all chondrite types.

Fries, M.↗

NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Image Apollo Drive Tube 73002

The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the Moon. Although most Apollo samples are well characterized, several types of samples remain wholly or largely unstudied since their return: unopened and/or sealed drive tube samples, samples frozen upon return, and samples stored in a He-purged environment. NASA selected nine teams to participate in the Apollo Next Generation Sample Analysis (ANGSA) Program to study representative samples from each of these categories. The first sample studied as part of the ANGSA program is drive tube 73002, a 4 cm diameter unopened (but unsealed) drive tube collected on a landslide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube, and the bottom half of the tube (73001)was sealed under vacuum on the Moon (and will be studied next). As part of the preliminary examination of sample 73002, the entire drive tube was imaged with a high resolution X-ray Computed Tomography (XCT) scan prior to opening and dissecting the sample. Additionally, >50 XCT scans have been made of “large” clasts (>4 mm) removed from the core as part of the ongoing dissection process. Here we will present both the whole drive tube XCT data showing the overall structure of sample 73002 prior to dissection, as well as XCT scans of individual clasts that reveal the types and abundance of different lithologies present within the drive tube. We will also discuss the utility of the scans as part of the curation and preliminary examination process, as well as the potential for future science returns from the XCT scans.

Ryan A Zeigler↗

NASA NTRS2013

Coordinated in Situ Analyses of Organic Nanoglobules in the Sutter's Mill Meteorite

The Sutter's Mill meteorite is a newly fallen carbonaceous chondrite that was collected and curated quickly after its fall. Preliminary petrographic and isotopic investigations suggest affinities to the CM2 carbonaceous chondrites. The primitive nature of this meteorite and its rapid recovery provide an opportunity to investigate primordial solar system organic matter in a unique new sample. Here we report in-situ analyses of organic nanoglobules in the Sutter's Mill meteorite using UV fluorescence imaging, Fourier-transform infrared spectroscopy (FTIR), scanning transmission electron microscopy (STEM), NanoSIMS, and ultrafast two-step laser mass spectrometry (ultra-L2MS).

Nakamura-Messenger, K.↗

NASA NTRS2013

Coordinated In Situ Analyses of Organic Nanoglobules in the Sutter's Mill Meteorite

The Sutter s Mill meteorite is a newly fallen carbonaceous chondrite that was collected and curated quickly after its fall [1]. Preliminary petrographic and isotopic investigations suggest affinities to the CM2 carbonaceous chondrites. The primitive nature of this meteorite and its rapid recovery provide an opportunity to investigate primordial solar system organic matter in a unique new sample. Organic matter in primitive meteorites and chondritic porous interplanetary dust particles (CP IDPs) is commonly enriched in D/H and N-15/N-14 relative to terrestrial values [2-4]. These anomalies are ascribed to the partial preservation of presolar cold molecular cloud material [2]. Some meteorites and IDPs contain gm-size inclusions with extreme H and N isotopic anomalies [3-5], possibly due to preserved primordial organic grains. The abundance and isotopic composition of C in Sutter's Mill were found to be similar to the Tagish Lake meteorite [6]. In the Tagish Lake meteorite, the principle carriers of large H and N isotopic anomalies are sub-micron hollow organic spherules known as organic nanoglobules [7]. Organic nanoglobules are commonly distributed among primitive meteorites [8, 9] and cometary samples [10]. Here we report in-situ analyses of organic nano-globules in the Sutter's Mill meteorite using UV fluorescence imaging, Fourier-transform infrared spectroscopy (FTIR), scanning transmission electron microscopy (STEM), NanoSIMS, and ultrafast two-step laser mass spectrometry (ultra-L2MS).

Nakamura--Messenger, K.↗

NASA NTRS2015

Lunar Processing Cabinet 2.0: Retrofitting Gloveboxes into the 21st Century

In 2014, the Apollo 16 Lunar Processing Glovebox (cabinet 38) in the Lunar Curation Laboratory at NASA JSC received an upgrade including new technology interfaces. A Jacobs - Technology Innovation Project provided the primary resources to retrofit this glovebox into the 21st century. NASA Astromaterials Acquisition & Curation Office continues the over 40 year heritage of preserving lunar materials for future scientific studies in state-of-the-art facilities. This enhancement has not only modernized the contamination controls, but provides new innovative tools for processing and characterizing lunar samples as well as supports real-time exchange of sample images and information with the scientific community throughout the world.

Calaway, M. J.↗

NASA NTRS2007

Decontamination of Genesis Array Materials by UV Ozone Cleaning

Shortly after the NASA Genesis Mission sample return capsule returned to earth on September 8, 2004, the science team discovered that all nine ultra-pure semiconductor materials were contaminated with a thin molecular organic film approximately 0 to 100 angstroms thick. The organic contaminate layer, possibly a silicone, situated on the surface of the materials is speculated to have formed by condensation of organic matter from spacecraft off-gassing at the Lagrange 1 halo orbit during times of solar exposure. While the valuable solar wind atoms are safely secured directly below this organic contamination and/or native oxide layer in approximately the first 1000 angstroms of the ultra-pure material substrate, some analytical techniques that precisely measure solar wind elemental abundances require the removal of this organic contaminate. In 2005, Genesis science team laboratories began to develop various methods for removing the organic thin film without removing the precious material substrate that contained the solar wind atoms. Stephen Sestak and colleagues at Open University first experimented with ultraviolet radiation ozone (UV/O3) cleaning of several non-flight and flown Genesis silicon wafer fragments under a pure flowing oxygen environment. The UV/O3 technique was able to successfully remove organic contamination without etching into the bulk material substrate. At NASA Johnson Space Center Genesis Curation Laboratory, we have installed an UV/O3 cleaning devise in an ambient air environment to further experimentally test the removal of the organic contamination on Genesis wafer materials. Preliminary results from XPS analysis show that the UV/O3 cleaning instrument is a good non-destructive method for removing carbon contamination from flown Genesis array samples. However, spectroscopic ellipsometry results show little change in the thickness of the surface film. All experiments to date have shown UV/O3 cleaning method to be the best non-destructive method for removing organic contamination from the surface of the Genesis materials. The UV/O3 cleaning process can also clean carbon contamination to levels below non-flight standards. This can be seen by comparing sample 60260's carbon 10667 cps with non-flight Si carbon 21675 cps. Therefore, surface carbon contamination should not hinder the analysis of solar wind.

Calaway, Michael J.↗

DOE OSTI2025

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗

NASA NTRS2007

STARDUST Curation and Science at JSC

Dust particles released from comet 81P/Wild-2 were captured in silica aerogel on-board the STARDUST spacecraft and returned to Earth on January 15, 2006. STARDUST recovered thousands of particles ranging in size from 1 to 100 micrometers. During the six month Preliminary Examination period an international consortium of 180 scientists investigated their mineralogy/petrology, organic/inorganic chemistry, optical properties and isotopic compositions. Stardust samples are now available for research by the entire research community.

Nakamura-Messenger, K.↗