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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Tunable Multivariate Metal–Organic Framework as a Platform for Designing Photocatalysts

Catalysts for photochemical reactions underlie many foundations in our lives, from natural light harvesting to modern energy storage and conversion, including processes such as water photolysis by TiO 2 . Recently, metal–organic frameworks (MOFs) have attracted large interest within the chemical research community, as their structural variety and tunability yield advantages in designing photocatalysts to address energy and environmental challenges. Here, we report a series of novel multivariate metal–organic frameworks (MTV-MOFs), denoted as MTV-MIL-100. They are constructed by linking aromatic carboxylates and AB 2 OX 3 bimetallic clusters, which have ordered atomic arrangements. Synthesized through a solvent-assisted approach, these ordered and multivariate metal clusters offer an opportunity to enhance and fine-tune the electronic structures of the crystalline materials. Moreover, mass transport is improved by taking advantage of the high porosity of the MOF structure. Combining these key advantages, MTV-MIL-100(Ti,Co) exhibits a high photoactivity with a turnover frequency of 113.7 mol H2 gcat. –1 min –1 , a quantum efficiency of 4.25%, and a space time yield of 4.96 × 10 –5 in the photocatalytic hydrolysis of ammonia borane. Bridging the fields of perovskites and MOFs, this work provides a novel platform for the design of highly active photocatalysts.

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

MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Reply to “Comment on ‘How a Formate Dehydrogenase Responds to Oxygen: Unexpected O 2 Insensitivity of an Enzyme Harboring Tungstopterin, Selenocysteine, and [4Fe–4S] Clusters’”

For the past 15 years, researchers have asserted that the ability to split a pair of electrons by an enzyme-bound redox cofactor called flavin can occur only in a particular way. In addition, they have claimed that this process known as flavin-based electron bifurcation (FBEB) was only discovered in 2008. Here, my laboratory's work not only demonstrates that these claims are untrue, but also illustrates how the research community has failed to responsibly reference key precedents for FBEB dating back to the early 1970s. Furthermore, our research places EB in the proper context, thus allowing for significant new bifurcating systems to be discovered and characterized.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fine-Tuning of Pt Dispersion on Al 2 O 3 and Understanding the Nature of Active Pt Sites for Efficient CO and NH 3 Oxidation Reactions

Fine-tuning the dispersion of active metal species on widely used supports is a research hotspot in the catalysis community, which is vital for achieving a balance between the atomic utilization efficiency and the intrinsic activity of active sites. In this work, using bayerite Al(OH) 3 as support directly or after precalcination at 200 or 550 °C, Pt/Al 2 O 3 catalysts with distinct Pt dispersions from single atoms to clusters (ca. 2 nm) were prepared and evaluated for CO and NH 3 removal. Richer surface hydroxyl groups on AlO x (OH) y support were proved to better facilitate the dispersion of Pt. However, Pt/Al 2 O 3 with relatively lower Pt dispersion could exhibit better activity in CO/NH 3 oxidation reactions. Further reaction mechanism study revealed that the Pt sites on Pt/Al 2 O 3 with lower Pt dispersion could be activated to Pt 0 species much easier under the CO oxidation condition, on which a higher CO adsorption capacity and more efficient O 2 activation were achieved simultaneously. Compared to Pt single atoms, PtO x clusters could also better activate NH 3 into –NH 2 and –HNO species. The higher CO adsorption capacity and the more efficient NH 3 /O 2 activation ability on Pt/Al 2 O 3 with relatively lower Pt dispersion well explained its higher CO/NH 3 oxidation activity. This study emphasizes the importance of avoiding a singular pursuit of single-atom catalyst synthesis and instead focusing on achieving the most effective Pt species on Al 2 O 3 support for targeted reactions. Finally, this approach avoids unnecessary limitations and enables a more practical and efficient strategy for Pt catalyst fabrication in emission control applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Inflight Parachute Measurement Challenge

The Purpose of the Inflight Parachute Measurement Challenge is to solicit potential measurement solutions that can result in successful parachute loading assumption validation, along with validation of Fluid-Structure Interaction (FSI) simulations. A parachute system contains many components which see various loading conditions including tension and aerodynamic pressure forces. While measurements can be made in wind tunnels, significant limitations exist as compared to flight testing which include scaling, dynamic pressure time history, and cluster behavior. Traditional flight test instrumentation is difficult due the flexible nature of parachute components, packing requirements, and high forces and chaos during deployment. The Objectives of this challenge are to (1) describe the anatomy and behavior of parachute systems, (2) identify measurements of particular interest to the parachute design and analysis community, (3) identify additional uses of measurements such as FSI validation.

Daum, Jared↗
DOE OSTI2020

Leisingera sp. ANG59 & Pseudoalteromonas sp. JC28 Genomes Overview

The Hawaiian bobtail squid, Euprymna scolopes, has a symbiotic bacterial consortium in the accessory nidamental gland (ANG), a female reproductive organ that protects eggs against fouling microorganisms. To test the antibacterial activity of ANG community members, 19 bacterial isolates were screened for their ability to inhibit Gram-negative and Gram-positive bacteria, of which two strains were inhibitory. These two antibacterial isolates, Leisingera sp. ANG59 and Pseudoalteromonas sp. JC28, were subjected to further genomic characterization. Genomic analysis of Leisingera sp. ANG59 revealed a biosynthetic gene cluster encoding the antimicrobial compound indigoidine. The genome of Pseudoalteromonas sp. JC28 had a 14-gene cluster with >95% amino acid identity to a known bromoalterochromide (BAC) cluster. Chemical analysis confirmed production of known BACs, BAC-A/A′ (compounds 1a/1b), as well as two new derivatives, BAC-D/D′ (compounds 2a/2b). Extensive nuclear magnetic resonance (NMR) analyses allowed complete structural elucidation of compounds 2a/2b, and the absolute stereochemistry was unambiguously determined using an optimized Marfey’s method. The BACs were then investigated for in vitro antibacterial, antifungal, and nitric oxide (NO) inhibitory activity. Compounds 1a/1b were active against the marine bacteria Bacillus algicola and Vibrio fischeri, while compounds 2a/2b were active only against B. algicola. Compounds 1a/1b inhibited NO production via lipopolysaccharide (LPS)-induced inflammation in RAW264.7 macrophage cells and also inhibited the pathogenic fungus Fusarium keratoplasticum, which, coupled with their antibacterial activity, suggests that these polyketide-nonribosomal peptides may be used for squid egg defense against potential pathogens and/or fouling microorganisms. These results indicate that BACs may provide Pseudoalteromonas sp. JC28 an ecological niche, facilitating competition against nonsymbiotic microorganisms in the host’s environment.​

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Investigating the Determinants of Household Capabilities Burden During Power Outages: The Case of Winter Storm Uri

Existing research primarily uses census data to identify the vulnerability of communities to hazards. These vulnerability indices provide aggregated data and are not hazard-specific nor well-validated with post-event data. In contrast, our study uses household survey data (n=1065) to understand which Texan households suffered the greatest loss of their capabilities due to power outages and other utility service disruptions during Winter Storm Uri. Inspired by the Capabilities Approach, our measures of burden include the number of household capability types disrupted during the outages (e.g., cooking, heating, refrigeration), the severity of impact for each disrupted capability, and the additional time and financial costs of coping with these disruptions. We perform a clustering analysis, and find two distinct groups in our data, consisting of ‘lesser burden' and ‘heavier burden' households. Results indicate that the households experiencing the heaviest capabilities burden were most likely to experience longer power outages and the loss of water services. They were also more likely to have a Hispanic-Latino household member, lack access to a generator, live in a rented home, have larger households with more young children, fewer adults over 65, lower household incomes, been impacted by the COVID-19 pandemic, and more family characteristics that made life harder. We also fit a logistic regression model to assess the role of outage, household, and community characteristics in predicting differences in capabilities burden. Our results offer insights into enumerating the consequences of utility service disruptions on households, which can inform more targeted and equitable resilience strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

The Carousel Lens: A Well-modeled Strong Lens with Multiple Sources Spectroscopically Confirmed by VLT/MUSE

Over the past few years alone, the lensing community has discovered thousands of strong lens candidates, and spectroscopically confirmed hundreds of them. In this time of abundance, it becomes pragmatic to focus our time and resources on the few extraordinary systems, in order to most efficiently study the Universe. In this paper, we present such a system: DESI-090.9854-35.9683, a cluster-scale lens at z l = 0.49, with seven observed lensed sources around the core, and additional lensed sources further out in the cluster. From the number and the textbook configuration of the lensed images, a tight constraint on the mass potential of the lens is possible. This would allow for detailed analysis on the dark and luminous matter content within galaxy clusters, as well as a probe into dark energy and high-redshift galaxies. We present our spatially resolved kinematic measurements of this system from the Very Large Telescope Multi Unit Spectroscopic Explorer, which confirm five of these source galaxies (in ascending order, at z s = 0.962, 0.962, 1.166, 1.432, and 1.432). With previous Hubble Space Telescope imaging in the F140W and F200LP bands, we also present a simple flux-based lens model consisting of two power-law profiles that, for a cluster lens, well models the five lensed arc families with redshifts. We determine the mass to be M(< θ E ) = 4.78 × 10 13 M ⊙ for the primary mass potential. From the model, we extrapolate the redshift of one of the two source galaxies not yet spectroscopically confirmed to be at $z_s = 4.52^{+1.03}_{-0.71}$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Deep unsupervised learning using spike-timing-dependent plasticity

Abstract Spike-timing-dependent plasticity (STDP) is an unsupervised learning mechanism for spiking neural networks that has received significant attention from the neuromorphic hardware community. However, scaling such local learning techniques to deeper networks and large-scale tasks has remained elusive. In this work, we investigate a Deep-STDP framework where a rate-based convolutional network, that can be deployed in a neuromorphic setting, is trained in tandem with pseudo-labels generated by the STDP clustering process on the network outputs. We achieve 24.56% higher accuracy and 3.5 × faster convergence speed at iso-accuracy on a 10-class subset of the Tiny ImageNet dataset in contrast to a k -means clustering approach.

Lu, Sen↗
NASA NTRS1994

Analysis of the request patterns to the NSSDC on-line archive

NASA missions, both for earth science and for space science, collect huge amounts of data, and the rate at which data is being gathered is increasing. For example, the EOSDIS project is expected to collect petabytes per year. In addition, these archives are being made available to remote users over the Internet. The ability to manage the growth of the size and request activity of scientific archives depends on an understanding of the access patterns of scientific users. The National Space Science Data Center (NSSDC) of NASA Goddard Space Flight Center has run their on-line mass storage archive of space data, the National Data Archive and Distribution Service (NDADS), since November 1991. A large world-wide space research community makes use of NSSDC, requesting more than 20,000 files per month. Since the initiation of their service, they have maintained log files which record all accesses the archive. In this report, we present an analysis of the NDADS log files. We analyze the log files, and discuss several issues, including caching, reference patterns, clustering, and system loading.

Johnson, Theodore↗
NASA NTRS2003

The Ionization History of The Intergalactic Medium:

The funded project seeked a unified description of the ionization, physical structure, and evolution of the intergalactic medium (IGM) and quasar intervening absorption systems. We proposed to conduct theoretical studies of the IGM and QSO absorbers in the context of current theories of galaxy formation, developing and using numerical and analytical techniques aimed at a detailed modeling of cosmological radiative transfer, gas dynamics, and thermal and ionization evolution. The ionization history of the IGM has important implications for the metagalactic UV background, intergalactic helium absorption 21-cm tomography, metal absorption systems, fluctuations in the microwave background, and the cosmic rate of structure and star formation. All the original objectives of our program have been achieved, and the results widely used and quoted by the community. Indeed, they remain relevant as the level and complexity of research in this area has increased substantially since our proposal was submitted, due to new discoveries on galaxy formation and evolution, a flood of high-quality data on the distant universe, new theoretical ideas and direct numerical simulations of structure formation in hierarchical clustering theories.

Madau, Piero↗
DOE OSTI2024

Molecular architecture and functional dynamics of the pre-incision complex in nucleotide excision repair

Nucleotide excision repair (NER) is vital for genome integrity. Yet, our understanding of the complex NER protein machinery remains incomplete. Combining cryo-EM and XL-MS data with AlphaFold2 predictions, we build an integrative model of the NER pre-incision complex(PInC). Here TFIIH serves as a molecular ruler, defining the DNA bubble size and precisely positioning the XPG and XPF nucleases for incision. Using simulations and graph theoretical analyses, we unveil PInC’s assembly, global motions, and partitioning into dynamic communities. Remarkably, XPG caps XPD’s DNA-binding groove and bridges both junctions of the DNA bubble, suggesting a novel coordination mechanism of PInC’s dual incision. XPA rigging interlaces XPF/ERCC1 with RPA, XPD, XPB, and 5' ssDNA, exposing XPA’s crucial role in licensing the XPF/ERCC1 incision. Mapping disease mutations onto our models reveals clustering into distinct mechanistic classes, elucidating xeroderma pigmentosum and Cockayne syndrome disease etiology.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2009

Multiscale Computer Simulation of Tensile and Compressive Strain in Polymer- Coated Silica Aerogels

While the low thermal conductivities of silica aerogels have made them of interest to the aerospace community as lightweight thermal insulation, the application of conformal polymer coatings to these gels increases their strength significantly, making them potentially useful as structural materials as well. In this work we perform multiscale computer simulations to investigate the tensile and compressive strain behavior of silica and polymer-coated silica aerogels. Aerogels are made up of clusters of interconnected particles of amorphous silica of less than bulk density. We simulate gel nanostructure using a Diffusion Limited Cluster Aggregation (DLCA) procedure, which produces aggregates that exhibit fractal dimensions similar to those observed in real aerogels. We have previously found that model gels obtained via DLCA exhibited stress-strain curves characteristic of the experimentally observed brittle failure. However, the strain energetics near the expected point of failure were not consistent with such failure. This shortcoming may be due to the fact that the DLCA process produces model gels that are lacking in closed-loop substructures, compared with real gels. Our model gels therefore contain an excess of dangling strands, which tend to unravel under tensile strain, producing non-brittle failure. To address this problem, we have incorporated a modification to the DLCA algorithm that specifically produces closed loops in the model gels. We obtain the strain energetics of interparticle connections via atomistic molecular statics, and abstract the collective energy of the atomic bonds into a Morse potential scaled to describe gel particle interactions. Polymer coatings are similarly described. We apply repeated small uniaxial strains to DLCA clusters, and allow relaxation of the center eighty percent of the cluster between strains. The simulations produce energetics and stress-strain curves for looped and nonlooped clusters, for a variety of densities and interaction parameters.

Good, Brian↗
DOE OSTI2023

Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Abstract Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic and viral multi-omics from either short- or long-read sequencing

Abstract The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA’s versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1974

ERTS-1 imagery and native plant distributions

A method is developed for using ERTS spectral signature data to determine plant community distribution and phenology without resolving individual plants. An Exotech ERTS radiometer was used near ground level to obtain spectral signatures for a desert plant community, including two shrub species, ground covered with live annuals in April and dead ones in June, and bare ground. It is shown that comparisons of scene types can be made when spectral signatures are expressed as a ratio of red reflectivity to IR reflectivity or when they are plotted as red reflectivity vs. IR reflectivity, in which case the signature clusters of each component are more distinct. A method for correcting and converting the ERTS radiance values to reflectivity values for comparison with ground truth data is appended.

Musick, H. B.↗
NASA NTRS1989

On developing the local research environment of the 1990s - The Space Station era

A requirements analysis for the Space Station's polar platform data system has been performed. Based upon this analysis, a cluster, layered cluster, and layered-modular implementation of one specific module within the Eos Data and Information System (EosDIS), an active data base for satellite remote sensing research has been developed. It is found that a distributed system based on a layered-modular architecture and employing current generation work station technologies has the requisite attributes ascribed by the remote sensing research community. Although, based on benchmark testing, probabilistic analysis, failure analysis and user-survey technique analysis, it is found that this architecture presents some operational shortcomings that will not be alleviated with new hardware or software developments. Consequently, the potential of a fully-modular layered architectural design for meeting the needs of Eos researchers has also been evaluated, concluding that it would be well suited to the evolving requirements of this multidisciplinary research community.

Chase, Robert↗