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654 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

Compiling a Comprehensive EVA Training Dataset for NASA Astronauts

Training for a spacewalk or extravehicular activity (EVA) is considered a hazardous duty for NASA astronauts. This places astronauts at risk for decompression sickness as well as various musculoskeletal disorders from working in the spacesuit. As a result, the operational and research communities over the years have requested access to EVA training data to supplement their studies. The purpose of this paper is to document the comprehensive EVA training data set that was compiled from multiple sources by the Lifetime Surveillance of Astronaut Health (LSAH) epidemiologists to investigate musculoskeletal injuries. The EVA training dataset does not contain any medical data, rather it only documents when EVA training was performed, by whom and other details about the session. The first activities practicing EVA maneuvers in water were performed at the Neutral Buoyancy Simulator (NBS) at the Marshall Spaceflight Center in Huntsville, Alabama. This facility opened in 1967 and was used for EVA training until the early Space Shuttle program days. Although several photographs show astronauts performing EVA training in the NBS, records detailing who performed the training and the frequency of training are unavailable. Paper training records were stored within the NBS after it was designated as a National Historic Landmark in 1985 and closed in 1997, but significant resources would be needed to identify and secure these records, and at this time LSAH has not pursued acquisition of these early training records. Training in the NBS decreased when the Johnson Space Center in Houston, Texas, opened the Weightless Environment Training Facility (WETF) in 1980. Early training records from the WETF consist of 11 hand-written dive logbooks compiled by individual workers that were digitized at the request of LSAH. The WETF was integral in the training for Space Shuttle EVAs until its closure in 1998. The Neutral Buoyancy Laboratory (NBL) at the Sonny Carter Training Facility near JSC opened in March 1997 and is the current site for US EVA training. Other space agencies also have used water to simulate weightlessness and train for EVAs. Russia has a training facility similar to the NBL named the Hydro Lab. The Hydro Lab began operations at the Gagarin Cosmonaut Training Center (GCTC) in 1980 and has been used extensively to the present. Although a majority of training in the Hydro Lab uses the Russian Orlan suit, a small number of sessions have been conducted using a NASA suit. The Japanese Weightlessness Environment Test System (WETS) went into service at the Tsukuba Space Center in 1997 but was closed in 2011 due to extensive earthquake damage. Several sessions were performed using a NASA suit, but these sessions were short and considered "development" runs. LSAH has assembled records from the WETF, NBL and Hydro Lab. Recording of the EVA training data has changed considerably from 1967 to present. The goal of early record keeping was to track use of hardware components, and the person involved was treated as a suited operator, not as a focus of interest. Records from the past two decades are fairly precise with the person, date, suit type and size noted. On occasion the length of the session was listed, but this data is not included on all records. Records were merged from data sources and extensive cleaning of the records was required since the multiple sources frequently overlapped and duplicated records. To date the LSAH EVA training dataset includes over 12,500 EVA training sessions performed by NASA astronauts since 1981. The following variables are included for most records: Name, Sex, Event date, Event name, HUT type, HUT size, Facility, and Estimated run time. For a smaller subset of records, the following variables are available: Actual run time, Time inverted, and the suit components Waist bearing type, Shoulder harness, Shoulder pads, and Teflon inserts. The LSAH dataset is currently the most complete resource for data regarding EVA training sessions performed by NASA astronauts. However, it is not 100 percent complete since the WETS (Japan) and NBS (Marshall) training facility data were not included. This dataset has been compiled by LSAH to study the relationship of EVA training to musculoskeletal injuries but has many other non-medical applications. This dataset can be provided to other groups in order to respond to program and research questions with appropriate board approvals.

Laughlin, M. S.↗
NASA NTRS2021

Characterization of Spacesuit Associated Microbial Communities and their Implications for NASA Missions

Crewed National Aeronautics and Space Administration (NASA) missions to other solar system bodies are currently being planned. One high-profile scientific focus during such expeditions would be life detection, specifically the discovery of past or present microbial life, if they exist. However, both humans and associated objects typically carry a high microbial burden. Thus, it is essential to distinguish between microbes brought with the expedition and those present on the exploring planets. Modern spacesuits are unique, customized spacecraft which provide protection, mobility and life support to crew during spacewalks, yet they vent continuously, and the mobility of microbes through spacesuits has not been studied. To evaluate the microbial colonization of spacesuits, NASA used an Extravehicular Activity swab kit to examine viable microbial populations of 48 samples from spacesuits using both traditional microbiological methods and molecular sequencing methods. The cultivable microbial population ranged from below the detection limit to 9 x 102 colony forming units per 25 cm2 of sample and also significantly varied by the location. The cultivable microbial diversity was dominated by members of Bacillus, Arthrobacter, and Ascomycota. However, 16S rRNA-based viable bacterial burden ranged from 105 to 106 copies per 25 cm2 of sample. Shotgun metagenome sequencing revealed the presence of a diverse microbial population on the spacesuit surfaces, including Curtobacterium and Methylobacterium from across all sets of spacesuits in high abundance. Among bacterial species identified, higher abundance of Cutibacterium acnes, Methylobacterium oryzae, and M. phyllosphaerae reads were documented. The results of this study provide evidence that identical microbial strains may live on the wrist joint, inner gauntlet, and outer gauntlet of spacesuits. This raises the possibility, but does not confirm, that viable microbes are able to migrate between the interior and exterior of spacesuits. Overall, these data provide the first estimate of microbial dispersion from internal to external spacesuit surfaces, which will help future mission planners develop effective planetary protection strategies.

spacesuit↗
DOE OSTI2022

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cost Efficient and Highly Weather-Resistant Solar Panel Backsheet Produced through Continuous Co-Extrusion Processing

The efficient generation and delivery of ‘clean energy” through photovoltaic (PV) technology relies heavily on the cost, performance and reliability of solar panels, along with the individual components used in assembly of those panels. In order to continue towards the Department of Energy’s (DOE) goals of driving costs down, the lifetime of high-output power generation equipment (i.e. solar modules) must be extended to reduce costs associated with power output degradation and replacement of failed or degraded panels. One of the major sources of module failures in the past 30 years has been the failure of the solar panel backsheet. Failure of this component causes severe output losses due to oxidation and yellowing of the module while creating safety concerns as the major electrical insulation of the module is compromised. Tomark-Worthen LLC was formed in 2012 with the goal of designing and manufacturing novel PV backsheets and encapsulants that would be produced in the United States of America and exceed expectations of domestic and international module producers. These backsheets would improve upon known backsheet design failures (i.e. Isovoltaic’s AAA backsheet) and create domestic manufacturing jobs in the PV sector. This goal became a reality with a first-generation product in 2018 and now, with the support of the DOE, Tomark-Worthen has launched a second-generation product known as PhotoMark® Reflections™ 205-3 and 360-3. This 2+ year effort began in late 2017 with a screening of potential polymeric materials and backsheet structural designs. Performance evaluations of each material provided the necessary data needed to select the proper material combinations and move forward into the design of the manufacturing process. These decisions were made by teaming with a local university, well-respected government laboratories, and private research organizations who provided the tools necessary to predict long-term performance of these materials in much shorter periods of time. Once the go/no-go criteria were met at the mid-point of the project, the effort transitioned to predicting 30+ year performance, achieving certifications, and improving manufacturing efficiencies designed to lower costs in order to be competitive in a cost-driven market. Major project accomplishments include recognition of the new backsheet by Underwriters Laboratories (UL) and international certification for 1000V and 1500V modules by TUV Sud. Both 1000V and 1500V products have been proven on several module manufacturing lines and initial customer orders have been received by both domestic and international module producers. Accelerated exposure testing has shown that the performance of this backsheet exceeds the prior polyamide-based backsheet known to fail in the field. Cost-models and initial customer orders have shown the ability to produce this backsheet at a cost acceptable to many domestic manufacturers, while International costs for standard backsheet remains extremely low. Tomark-Worthen remains one of the only U.S. companies manufacturing backsheet domestically and this has drawn interest from many domestic module manufacturers looking to improve their material supply logistics by avoiding long lead times and custom’s headaches while avoiding current tariffs on Chinese-made components. Along with the launch of a new PV backsheet, this project has provided a critical deliverable to the PV R&D community. This deliverable is the knowledge that not all polyamide-containing backsheets are doomed to failure as the earlier versions did. There has been a fear amongst the PV community to consider these materials due to the failure of one design. This effort has brought a new level of interest to the scientific community as it has been shown that polyamides can be used successfully in a well-designed backsheet. As we move forward from this project, we are excited to see how backsheet technology and manufacturing in the U.S. will continue to progress and grow.

14 SOLAR ENERGY↗
DOE OSTI2025

Genomic and transcriptomic characterization of carbohydrate-active enzymes in the anaerobic fungus Neocallimastix cameroonii var. constans

Anaerobic gut fungi effectively degrade lignocellulose in the guts of large herbivores, but there remain a limited number of isolated, publicly available, and sequenced strains that impede our understanding of the role of anaerobic fungi within microbial communities. We isolated and characterized a new fungal isolate, Neocallimastix cameroonii var. constans, providing a transcriptomic and genomic understanding of its ability to degrade diverse carbohydrates. This anaerobic fungal strain was stably cultivated for multiple years in vitro among members of an initial enrichment microbial community derived from goat feces, and it demonstrated the ability to pair with other microbial members, namely, archaeal methanogens to produce methane from lignocellulose. Genomic analysis revealed a higher number of predicted carbohydrate-active enzymes encoded in the N. cameroonii var. constans genome compared to most other sequenced anaerobic fungi. The carbohydrate-active enzyme profile for this isolate contained 660 glycoside hydrolases, 160 carbohydrate esterases, 194 glycosyltransferases, and 85 polysaccharide lyases. Differential gene expression analysis showed the upregulation of thousands of genes (including predicted carbohydrate-active enzymes) when N. cameroonii var. constans was grown on lignocellulose (reed canary grass) compared to less complex substrates, such as cellulose (filter paper), cellobiose, and glucose. AlphaFold was used to predict functions of transcriptionally active yet poorly annotated genes, revealing feruloyl esterases that likely play an important role in lignocellulose degradation by anaerobic fungi. The combination of this strain's genomic and transcriptomic characterization, omics-informed structural prediction, and robustness in microbial co-culture make it a well-suited platform to conduct future investigations into bioprocessing and enzyme discovery.

CAZymes↗