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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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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adaptive Laboratory Evolution for Enhanced Performance of Cupriavidus necator on Formic Acid

The need to decarbonize our economy is becoming ever more pressing. CO2, can be electrochemically reduced to formic acid, a soluble C1 molecule that can be used to store carbon and energy. Cupriavidus necator H16, a soil bacterium, capable of consuming and growing on formic acid as its sole carbon source, is well positioned to upgrade CO2-derived formic acid into value added chemicals such as sustainable aviation fuel. To improve the performance of C. necator on formic acid adaptive laboratory evolution (ALE), a proven tool for improving microbial fitness, has been conducted using continuous pH-stat bioreactors. The system works on the basis that consumption of formic acid raises the pH and triggers the addition of more formic acid to maintain the pH at 6.7, such that formic acid is provided at the same rate as it is consumed. This system has been coupled with level control to achieve continuous fermentation where cells acquiring mutations that improve growth on formic acid become more abundant in the population, from which they can be isolate and characterized. This configuration where the dilution rate is controlled by pH-stat has been found to seek out a dilution rate that matches the exponential growth rate of the organism. During developmental experiments it was discovered that formic acid accumulated to inhibitory levels. It was determined that the nitrogen source, ammonium hydroxide, must be tailored to the carbon consumption to avoid formic acid accumulation. ALE has run in three lineages for 2000+ hours and 300+ generations. Growth of evolved isolates derived from all lineages will be evaluated on formic acid and those with improved growth rates or biomass yield will be subjected to whole genome sequencing to identify potentially causative mutations. These mutations will be evaluated individually and in combination to identify those that improve growth on formic acid.

adaptive laboratory evolution↗
NASA NTRS2021

Results from the ASTERIA CubeSat Extended Mission Experiments

Over the past two years, JPL has used the ASTERIA (Arcsecond Space Telescope Enabling Research In Astrophysics) CubeSat as an in-flight test platform during extended missions. ASTERIA successfully completed its prime mission in early 2018, and continued to operate in low Earth orbit (LEO) for an additional twenty months. This paper describes demonstrations that were performed on the spacecraft and on the ground-based testbed during the extended mission. These demonstrations fall into three categories: Autonomy technology maturation, hardware characterization, and science discovery. Autonomy technology maturation supported three development efforts. The first shifted the spacecraft commanding paradigm from time-based sequences to Task Networks (tasknets), which allow simpler commanding and more robust onboard execution. The second demonstrated onboard orbit determination in Low Earth Orbit (LEO) without GPS. This activity used a fully-independent means of spacecraft orbit determination for Earth orbiters using only passive imaging. The third technology provided in situ hardware health state estimation using a model-based reasoning technique. These three technologies were demonstrated either in flight or on the testbed individually, and then were combined to demonstrate the capability to perform autonomous navigation on board without ground intervention, even in the presence of anomalies. Hardware characterization involved both onboard and ground-based activities. On board, nonstandard attitude control modes were commanded to characterize the spacecraft pointing jitter as a function of target brightness, reaction wheel speed, controller gain, and the number of guide stars. The results provide insights into the contribution of jitter to the ASTERIA photometry and inform the feasibility of future astrophysics small satellite missions for which jitter control is an enabling technology. On the ground, the ASTERIA Operations Team coordinated with Amazon Web Services (AWS) to configure their new ground stations to communicate with ASTERIA to prove out their viability. ASTERIA used AWS ground stations for nominal operations for the last four months of the mission. Finally, ASTERIA continued to perform exoplanet science as the spacecraft was well-suited to execute long-term monitoring of stars such as alpha Centauri to search for small transiting planets. The science team also imaged a number of interesting objects including a comet, an asteroid, cities at night, and the moon, and coordinated with other projects on Targets of Opportunity for follow-up confirmations and co-observations. Throughout the prime and the extended missions, the ASTERIA spacecraft proved to be a mighty platform that “will go into history as an innovative milestone.”[1 - Zurbuchen]

Doran, Patrick↗
DOE OSTI2021

Viruses infecting a warm water picoeukaryote shed light on spatial co-occurrence dynamics of marine viruses and their hosts

The marine picoeukaryote Bathycoccus prasinos has been considered a cosmopolitan alga, although recent studies indicate two ecotypes exist, Clade BI (B. prasinos) and Clade BII. Viruses that infect Bathycoccus Clade BI are known (BpVs), but not that infect BII. We isolated three dsDNA prasinoviruses from the Sargasso Sea against Clade BII isolate RCC716. The BII-Vs do not infect BI, and two (BII-V2 and BII-V3) have larger genomes (~210 kb) than BI-Viruses and BII-V1. BII-Vs share ~90% of their proteins, and between 65% to 83% of their proteins with sequenced BpVs. Phylogenomic reconstructions and PolB analyses establish close-relatedness of BII-V2 and BII-V3, yet BII-V2 has 10-fold higher infectivity and induces greater mortality on host isolate RCC716. BII-V1 is more distant, has a shorter latent period, and infects both available BII isolates, RCC716 and RCC715, while BII-V2 and BII-V3 do not exhibit productive infection of the latter in our experiments. Global metagenome analyses show Clade BI and BII algal relative abundances correlate positively with their respective viruses. The distributions delineate BI/BpVs as occupying lower temperature mesotrophic and coastal systems, whereas BII/BII-Vs occupy warmer temperature, higher salinity ecosystems. Accordingly, with molecular diagnostic support, we name Clade BII Bathycoccus calidus sp. nov. and propose that molecular diversity within this new species likely connects to the differentiated host-virus dynamics observed in our time course experiments. Overall, the tightly linked biogeography of Bathycoccus host and virus clades observed herein supports species-level host specificity, with strain-level variations in infection parameters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition

Abstract Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed laser deposition (PLD) is emerging as a viable autonomous synthesis tool, and so the need arises to develop machine learning (ML) techniques that are capable of extracting information from in situ diagnostics. Here, we demonstrate that intensified-CCD image sequences of the plasma plume generated during PLD can be used for anomaly detection and the prediction of thin film growth kinetics. We develop multi-output (2 + 1)D convolutional neural network regression models that extract deep features from plume dynamics that not only correlate with the measured chamber pressure and incident laser energy, but more importantly, predict parameters of an auto-catalytic film growth model derived from in situ laser reflectivity experiments. Our results demonstrate how ML with in situ plume diagnostics data in PLD can be utilized to maintain deposition conditions in an optimal regime. Further, the predictive capabilities of plume dynamics on the kinetics of film growth or other film properties prior to deposition provides a means for rapid pre-screening of growth conditions for the non-expert, which promises to accelerate materials optimization with PLD.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Parallel structures in human and computer memory

If one thinks of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library. One recognizes a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. A computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do is constructed. Such a memory is remarkably similiar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. It is concluded that the frame problem of artificial intelligence could be solved by the use of such a memory if one were able to encode information about the world properly.

Kanerva, P.↗
NASA NTRS2025

The Microbiome of A Tomato Crop Grown Under Different Lighting Regimes on the International Space Station

The VEG-05 experiment presented here investigated the effect of red-rich and blue-rich light recipes in Veggie on the microbiome of the Veggie facility and the plant tissues of a dwarf tomato variety, Solanum lycopersicum cv. Red Robin. For food safety, the plants were screened using culture-based methods for potential human pathogens that may cause infection by consumption of the fruit. The microbiome was investigated using bacterial 16S and fungal ITS sequencing methods to enumerate and identify bacterial and fungal communities on tomato fruit, roots, leaves, rooting substrate, and Veggie facility surfaces grown under blue-rich or red-rich lighting. Comparisons of microbial communities were made between lighting treatments, as well as for flight and ground controls. This analysis determined the core microbiome and microbiological composition for tomato plants grown under a blue-rich or red-rich lighting treatment and microgravity conditions. Culture-based pathogen screening, corroborated by 16S and ITS sequencing, yielded negative results. Bacterial and fungal counts were lower for ground controls than in-flight samples. However, there were no differences in microbial counts between lighting treatments. Regardless of lighting treatment, plant components shared a core microbiome, although some differences were observed in genera between lighting treatments.

Veggie↗
NASA NTRS1977

Establishing effective working relations with a potential user community - NASA Lewis Research Center experience

The NASA Lewis Research Center has held a series of six major and unique technology utilization conferences which were major milestones in planned structured efforts to establish effective working relationships with specific technology user communities. These efforts were unique in that the activities undertaken prior to the conference were extensive, and effectively laid the groundwork for productive technology transfer following, and as a direct result of, the conferences. The effort leading to the conference was in each case tailored to the characteristics of the potential user community, however, the common factors comprise a basic framework applicable to similar endeavors. The process is essentially a planned sequence of steps that constitute a technical market survey and a marketing program for the development of beneficial applications of aerospace technology beyond the aerospace field.

Foster, P.↗
DOE OSTI2019

Solid-state NMR experiments have been developed to probe crystallization behavior fluoropolymers (Progress Summary)

The FK-800 fluoropolymer elastomer is being developed as a replacement material for the Kel-F 800 binder in the plastic bonded explosive PBX-9502. These polymers are a random co-polymer of poly-vinylidene fluoride (PVDF) and poly-chlorotrifluoroetheylene (PCTFE) in nominal 1:3 ratio. Initial characterizations of the FK-800 replacement show similar characteristics as the legacy Kel-F 800. However, differences in bulk crystallinity and crystallization kinetics have been observed. These differences may be driven by small differences in the distribution of the monomers on the polymer backbone (sequence distribution).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays

Using a maskless photolithography method, we produced DNA oligonucleotide microarrays with probe sequences tiled throughout the genome of the plant Arabidopsis thaliana. RNA expression was determined for the complete nuclear, mitochondrial, and chloroplast genomes by tiling 5 million 36-mer probes. These probes were hybridized to labeled mRNA isolated from liquid grown T87 cells, an undifferentiated Arabidopsis cell culture line. Transcripts were detected from at least 60% of the nearly 26,330 annotated genes, which included 151 predicted genes that were not identified previously by a similar genome-wide hybridization study on four different cell lines. In comparison with previously published results with 25-mer tiling arrays produced by chromium masking-based photolithography technique, 36-mer oligonucleotide probes were found to be more useful in identifying intron-exon boundaries. Using two-dimensional HPLC tandem mass spectrometry, a small-scale proteomic analysis was performed with the same cells. A large amount of strongly hybridizing RNA was found in regions "antisense" to known genes. Similarity of antisense activities between the 25-mer and 36-mer data sets suggests that it is a reproducible and inherent property of the experiments. Transcription activities were also detected for many of the intergenic regions and the small RNAs, including tRNA, small nuclear RNA, small nucleolar RNA, and microRNA. Expression of tRNAs correlates with genome-wide amino acid usage.

Arabidopsis/genetics↗
DOE OSTI2017

Origin and Evolution of Magnetic Field in PMS Stars: Influence of Rotation and Structural Changes

During stellar evolution, especially in the pre-main-sequence phase, stellar structure and rotation evolve significantly, causing major changes in the dynamics and global flows of the star. We wish to assess the consequences of these changes on stellar dynamo, internal magnetic field topology, and activity level. To do so, we have performed a series of 3D HD and MHD simulations with the ASH code. We choose five different models characterized by the radius of their radiative zone following an evolutionary track computed by a 1D stellar evolution code. These models characterized stellar evolution from 1 to 50 Myr. By introducing a seed magnetic field in the fully convective model and spreading its evolved state through all four remaining cases, we observe systematic variations in the dynamical properties and magnetic field amplitude and topology of the models. The five MHD simulations develop a strong dynamo field that can reach an equipartition state between the kinetic and magnetic energies and even superequipartition levels in the faster-rotating cases. We find that the magnetic field amplitude increases as it evolves toward the zero-age main sequence. Moreover, the magnetic field topology becomes more complex, with a decreasing axisymmetric component and a nonaxisymmetric one becoming predominant. The dipolar components decrease as the rotation rate and the size of the radiative core increase. The magnetic fields possess a mixed poloidal-toroidal topology with no obvious dominant component. Moreover, the relaxation of the vestige dynamo magnetic field within the radiative core is found to satisfy MHD stability criteria. Hence, it does not experience a global reconfiguration but slowly relaxes by retaining its mixed stable poloidal-toroidal topology.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Failure of the ERBE scanner instrument aboard NOAA 10 spacecraft and results of failure analysis

The Earth Radiation Budget Experiment (ERBE) scanner instrument on the NOAA 10 spacecraft malfunctioned on May 22, 1989, after more than 4 years of in-flight operation. After the failure, all instrument operational mode commands were tested and the resulting data analyzed. Details of the tests and analysis of output data are discussed therein. The radiometric and housekeeping data appear to be valid. However, the instrument will not correctly execute operational scan mode commands or the preprogrammed calibration sequences. The data indicate the problem is the result of a failure in the internal address decoding circuity in one of the ROM (read only memory) chips of the instrument computer.

Miller, J. B.↗
NASA NTRS2005

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

Review↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Automated theoretical chemical kinetics: Predicting the kinetics for the initial stages of pyrolysis

Large scale implementation of high level computational theoretical chemical kinetics offers the prospect for dramatically improving the fidelity of combustion chemical modeling. To facilitate such efforts, we have developed a suite of codes, collectively referred to as AutoMech, that allow for the automatic prediction of the kinetics for large sets of reactions via ab initio transition-state-theory based master-equation calculations. The primary input is simply the mechanism, a dictionary relating chemically identifiable species descriptors (e.g., SMILES or InChIs) to species labels in the mechanism, and a specification of the electronic structure and transition state theory models to be implemented. Here we illustrate the current utility of AutoMech through a study of the initial stages of pyrolysis for 3 sets of fuels: sequences of alkanes, alcohols, and aldehydes. For simplicity, the analysis focuses on abstractions from the fuel by H, CH 3 , and OH, and the decomposition of the resulting radicals. Altogether, there are a total of 166 input channels in these sets (more than 363 forward reactions when expanded to the full set of elementary reactions). The code successfully produces high quality rate estimates (with apparent uncertainties less than a factor of two in limited comparisons with experiment) for > 95% of these. For the radical decomposition reactions, the analysis includes predictions for the pressure dependence of the kinetics. This wide-ranging exploration illustrates (i) the effect of different levels of prediction on the expected accuracy, (ii) the branching between abstractions at different sites for different abstractors, (iii) the dependence of the rates on the chemical structure, and (iv) the variation in radical stabilities across chemical families. These results, as well as the demonstrated feasibility of the methodology, should find further utility in the development of accurate rate expressions for arbitrary fuels. (c) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Elliott, Sarah N.↗
DOE OSTI2018

Multi-omic elucidation of aromatic catabolism in adaptively evolved Rhodococcus opacus

Lignin utilization has been identified as a key factor in biorefinery profitability. However, lignin depolymerization generates heterogeneous aromatic mixtures that inhibit microbial growth and conversion of lignocellulose to biochemicals. Rhodococcus opacus is a promising aromatic-catabolizing, oleaginous bacterium, but mechanisms for its aromatic tolerance and utilization remain undercharacterized. To better understand these mechanisms, we adaptively evolved R. opacus for improved utilization of 32 combinations of diverse aromatic compounds. Evolved R. opacus mutants showed up to 1900% growth improvement in the utilization of phenol, guaiacol, 4-hydroxybenzoate, vanillate, and benzoate compared to the wild-type strain. Whole genome sequencing revealed several redox-related genes with mutations shared across multiple adapted mutants. PVHG6, the mutant with the most improved growth on a mixture of multiple aromatic compounds, showed 56% lower superoxide dismutase activity than the wild-type strain, suggesting that redox reactions are important for aromatic tolerance and utilization. Comparative transcriptomics revealed by-product detoxification pathways and five aromatic funneling pathways that were upregulated in response to specific aromatic compounds. Gene knockout experiments confirmed the two degradation routes of the β-ketoadipate pathway for five aromatic compounds. Finally, these results provide an improved understanding of aromatic bioconversion and facilitate development of R. opacus as a biorefinery host.

09 BIOMASS FUELS↗
DOE OSTI2023

Characterization and Diversification of AraC/XylS Family Regulators Guided by Transposon Sequencing

In this study, we explored the development of engineered inducible systems. Publicly available data from previous transposon sequencing assays were used to identify regulators of metabolism in Pseudomonas putida KT2440. For AraC family regulators (AFRs) represented in these data, we posited AFR/promoter/inducer groupings. Twelve promoters were characterized for a response to their proposed inducers in P. putida, and the resultant data were used to create and test nine two-plasmid sensor systems in Escherichia coli. Several of these were further developed into a palette of single-plasmid inducible systems. From these experiments, we observed an unreported inducer response from a previously characterized AFR, demonstrated that the addition of a P. putida transporter improved the sensor dynamics of an AFR in E. coli, and identified an uncharacterized AFR with a novel potential inducer specificity. Finally, targeted mutations in an AFR, informed by structural predictions, enabled the further diversification of these inducible plasmids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Automated experimental design of safe rampdowns via probabilistic machine learning

Abstract Typically the rampdown phase of a shot consists of a decrease in current and injected power and optionally a change in shape, but there is considerable flexibility in the rate, sequencing, and duration of these changes. On the next generation of tokamaks it is essential that this is done safely as the device could be damaged by the stored thermal and electromagnetic energy present in the plasma. This works presents a procedure for automatically choosing experimental rampdown designs to rapidly converge to an effective rampdown trajectory. This procedure uses probabilistic machine learning methods paired with acquisition functions taken from Bayesian optimization. In a set of 2022 experiments at DIII-D, the rampdown designs produced by our method maintained plasma control down to substantially lower current and energy levels than are typically observed. The actions predicted by the model significantly improved as the model was able to explore over the course of the experimental campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗