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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Emphasis on KSC ground processing operations, reduced spares up-mass lift requirements and campaign-level flexible path perspective for space systems support as Regolith-based ISM is achieved by; Network modeling for sequencing space logistics and in-space logistics nodal positioning to include feedstock. Economic modeling to assess ISM 3D printing adaption and supply chain risk.
Next-generation focal planes comprising dozens of kilopixel transition-edge sensor (TES) arrays require new methods to rapidly screen candidate arrays, evaluate array non-idealities in the field, identify outlier devices for removal, and optimize the array performance in the field. We demonstrate robust methods to estimate TES parameters (critical temperatures and thermal conductivity parameters) and their uncertainties using a custom Markov Chain Monte Carlo (MCMC) algorithm. We also constrain systematic effects in estimating the TES parameters from non-isothermal current-voltage curves (IVs) at approximately a ~3% level. Additionally, for the first time, we have applied Machine Learning (ML) algorithms to tune detector arrays and optimize their performance.
Planetary protection of Mars samples returned to Earth in a future NASA mission is a critical part of preventing uncontrolled biological materials being released from the samples. The planetary protection process requires addressing the potential risks and would involve “breaking the chain of contact (BTC)”, where any returned material reaching Earth for further analysis would have to be sealed inside a container with extremely high confidence. The sterilization process would require destroying any potential biological materials that may contaminate the external surface of the container. A novel process for containing the returned samples has been conceived and developed at JPL. The process consists of using induction heated brazing to synchronously sterilize, separate, seam and seal the container. In this case. the braze material is heated to the level of melting at temperatures higher than 500°C to assure sterilizing exposed areas since carbon bonds are broken above this temperature. The container that encloses the samples consists of double walls with interstitial space that is Earth-clean. The process consists of two-steps, where one was intended to be prepared on Earth and the second potentially executed on orbit around Mars. The latest results of this study that established the needed capability are described and discussed in this manuscript.
This presentation is a blockchain infrastructure use case on setting up a Secure Air Space Network for Autonomous Vehicles that are operating in an Urban Area and Secure the Data using Block Chain Technology.
Background: To date, there is no clear understanding of the effect of long-duration spaceflight on the major enzymes that govern the metabolism of omega-6 and omega-3 fatty acids. To address this gap in knowledge, we used data from the NASA Twins Study, which includes a multi-scale omic investigation of the changes that occurred during a year-long (340 days) human spaceflight. Embedded within the NASA Twins data are specific analytes associated with fatty acid metabolism. Objectives: To examine the long-chain fatty acid desaturases and elongases in a single human during one year in space. Method: One male twin was on board the International Space Station (ISS) for one year, while his monozygotic twin served as a genetically matched ground control. Longitudinal assessments included the genome, epigenome, transcriptome, proteome, metabolome, microbiome, and immunome during the mission, as well as six months before and after. The gene-specific fatty acid desaturase and elongase transcriptome data (FADS1, FADS2, ELOVL2 and ELOVL5) were extracted from untargeted RNA-seq measurements derived from white blood cell fractions. Results: Most data from the elongases and desaturases exhibited relatively similar expression profiles (R2>0.6) over time for the CD8, CD19, and LD cell fractions, indicating overall conservation of function within and between the subjects. Both cell-type and temporal specificity was observed in some cases, and some differences were also apparent between the poly-adenylated fraction (polyA) of processed RNAs vs. the ribo-depleted (ribo-) fraction. The flight subject showed a stronger enrichment of the Fatty Acid Metabolic processes pathway across almost all cell types (columns, CD4, CD8, CPT, LD), most especially in the ribodepleted fraction of RNA, but also with the polyA+ fraction of RNA. GSEA enrichment measures across three related Fatty Acid Metabolism pathways showed a differential between the ground and flight subject. Conclusions: There appears to be no persistent alteration of desaturase and elongase gene expression associated with one year in space. However, these data provide evidence that cellular lipid metabolism can be responsive and dynamic to spaceflight, even though it appears cell-type- and context-specific, most notably in terms of the fraction of RNA measured and the collection protocols. These results also provide new evidence of mid-flight spikes in expression of selected genes, which may indicate transient responses to specific insults during spaceflight.
Noise from multi-photon emissions can severely limit the use of probabilistic photon sources in quantum repeater chains. We present a Bell state measurement protocol that suppresses noise from multi-pair emissions in quantum repeaters.
Noise from multi-photon emissions can severely limit the use of probabilistic photon sources in quantum repeater chains. We present a Bell state measurement protocol that suppresses noise from multi-pair emissions in quantum repeaters.
As autonomous technology advances, unmanned aircraft systems are increasingly integrated into emergency response missions, such as wildfire response. These systems must be be safe with less risk than non-autonomous counter parts, yet quantifying the risk associated with present-day and future systems conventionally relies solely on expert opinion and little data. Instead, combining narrative mishap reports with probabilistic analysis can provide a method for evolutionary and timely risk analysis. In this paper, we present a framework for a data-driven probabilistic risk assessment style analysis, where hazard events and rates originate from documented UAS mishaps. The framework is applied to a UAS mapping mission in wildfire response, including a fault tree analysis, event tree analysis, and probabilistic analysis using Markov Chains. The analysis provides an enumeration of hazards in the system, hazard events that can lead to faults, the probability of a mission experiencing any fault, the probability of experiencing a specific fault, and the expected time spent until faulty states occur in present-day operations.
As autonomous technology advances, unmanned aircraft systems are increasingly integrated into emergency response missions, such as wildfire response. These systems must be be safe with less risk than non-autonomous counter parts, yet quantifying the risk associated with present-day and future systems conventionally relies solely on expert opinion and little data. Instead, combining narrative mishap reports with probabilistic analysis can provide a method for evolutionary and timely risk analysis. In this paper, we present a framework for a data-driven probabilistic risk assessment style analysis, where hazard events and rates originate from documented UAS mishaps. The framework is applied to a UAS mapping mission in wildfire response, including a fault tree analysis, event tree analysis, and probabilistic analysis using Markov Chains. The analysis provides an enumeration of hazards in the system, hazard events that can lead to faults, the probability of a mission experiencing any fault, the probability of experiencing a specific fault, and the expected time spent until faulty states occur in present-day operations.
Embodiments of the present invention are directed toward devices, systems, and methods for purifying nucleic acids to conduct polymerase chain reaction (PCR) assays. In one example, a method includes generating complexes of silica beads and nucleic acids in a lysis buffer, transporting the complexes through an immiscible fluid to remove interfering compounds from the complexes, further transporting the complexes into a density medium containing components required for PCR where the nucleic acids disassociate from the silica beads, and thermocycling the contents of the density medium to achieve PCR. Signal may be detected from labeling agents in the components required for PCR.
The project goal is to assess opportunities for value-adds in the supply chain through designing a feedstock logistics systems that uses moisture during the residence time in storage to protect and increase feedstock value.
Methods are described for using a combination of mass spectroscopic and proteomic approaches for identifying the specific pairing of heavy and light chains for an intact antibody, an antibody fragment, a mixture of intact antibodies, or a mixture of antibody fragments.
Provided are plants that express, or overexpress, a pPLAIIIδ protein. Constitutive or seed-specific expression of pPLAIIIδ protein in Arabidopsis increases seed oil content, the amount of C20 and C22 fatty acids, and the amount of C56, C58, and C60 triacylglycerols, effectively resulting in significantly higher oil yield per plant. Use of pPLAIIIδ is therefore an effective biotechnological tool to significantly increase plant yield, including oil, and the amount of high value long chain fatty acids in agricultural and horticultural crops, especially oilseed crops.
Demand for clean energy technologies such as wind turbines and batteries for electric vehicles has increased significantly as technology costs have plummeted over the last decade and countries seek to diversify their energy systems with more reliable clean energy sources to lower costs for businesses and consumers. The global clean energy market is expected to grow exponentially — reaching $23 trillion at a minimum by 2030. Without new domestic raw materials production and manufacturing capacity, the U.S. will continue to rely on clean energy imports, exposing the nation to supply chain vulnerabilities while simultaneously losing out on the enormous job opportunities associated with the energy transition. Yet, in many cases, the United States has untapped potential to support greater domestic production.
Semiconductors are a keystone technology that are essential for the operation of every electronic device, including those that are critical to a clean energy economy. The semiconductor industry has a complex, competitive, and highly integrated international supply chain in which the United States has historically enjoyed a dominant position, but where this position has been eroding over time. In 1995, 26% of global semiconductor manufacturing capacity was located in the United States; this had decreased to 10% by 2020. Investments in key semiconductor manufacturing technologies such as high-voltage power electronics, energy-efficient conventional devices, and advanced packaging point the way to secure a strong domestic semiconductor industrial base.
Land-based and offshore wind are expected to be a cornerstone for achieving U.S. clean electricity generation objectives, including 100% clean electricity by 2035 and an 30 gigawatts (GW) of offshore wind by 2030. Meeting these goals will require significant expansion of domestic supply chains and installation of unprecedented amounts of wind capacity.
The present disclosure relates to methods and compositions for making bio-based, biodegradable, and non-bioaccumulating lubricating base oils generated by esterifying alkoxylated polyols (average alkoxylation ≥3) with long-chain (≥C14) saturated and unsaturated fatty acids (FA) or fatty acids modified using industry recognized techniques.
Microbiome compositions and uses thereof. The microbiome compositions include a set of microbes. The sets of microbes contain members of Lactobacillaceae, Eubacteriaceae, Lachnospiraceae, and Coriobacteriaceae. The number of individual physical microbes in the set constitutes a certain percentage of the total number of individual physical microbes in the microbiome composition. The microbiome compositions can be used for producing medium-chain fatty acids from organic substrates through anaerobic fermentation in a medium. The medium can include lignocellulosic stillage.