Search NASA⌕ Search

SEARCH · Search NASA

Results for “marcelling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider

The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the “glue” that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5 T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Herein our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Detector requirements and simulation results for the EIC exclusive, diffractive and tagging physics program using the ECCE detector concept

This article presents a collection of simulation studies using the ECCE detector concept in the context of the EIC’s exclusive, diffractive, and tagging physics program, which aims to further explore the rich quark–gluon structure of nucleons and nuclei. To successfully execute the program, ECCE proposed to utilize the detector system close to the beamline to ensure exclusivity and tag ion beam/fragments for a particular reaction of interest. Preliminary studies confirm the proposed technology and design satisfy the requirements. Further, the projected physics impact results are based on the projected detector performance from the simulation at 10 or 100 fb -1 of integrated luminosity. Additionally, insights related to a potential second EIC detector are documented, which could serve as a guidepost for future development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Evaluation of longitudinal double-spin asymmetry measurements in semi-inclusive deep-inelastic scattering from the proton for the ECCE detector design

The evaluation of the measurement of double-spin asymmetries for charge-separated pions and kaons produced in deep-inelastic scattering from the proton using the ECCE detector design concept is presented, for the combinations of lepton and hadron beam energies of 5 × 41 GeV 2 and 18 × 275 GeV 2 . The study uses unpolarised simulated data that are processed through a full GEANT simulation of the detector. These data are then reweighted at the parton level with DSSV helicity distributions and DSS fragmentation functions, in order to generate the relevant asymmetries, and subsequently analysed. Furthermore, the performed analysis shows that the ECCE detector concept provides the resolution and acceptance, with a broad coverage in kinematic phase space, needed for a robust extraction of asymmetries. This, in turn, allows for a precise extraction of sea-quark helicity distributions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Design of the ECCE detector for the Electron Ion Collider

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. Finally, this detector concept has been selected to be the basis for the EIC project detector.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Complex exposure-burial history and Pleistocene sediment recycling in the dead sea rift with implications for the age of the Acheulean site of ‘Ubeidiya

Here, we present early Pleistocene burial ages of the ‘Ubeidiya Formation sediments in the Jordan Valley, a segment of the Dead Sea Rift Valley. A minimum age of ∼1.1 Ma is constrained both by paleomagnetic analysis and U-Pb dating of Melanopsis shells. Simple cosmogenic burial ages (i.e., one very long exposure period followed by one period of burial) calculated from the ratios of 26 Al to 10 Be and 10 Be concentrations indicate ages of ∼3 Ma, contradicting the geological and paleomagnetic constraints as well as a reasonable age of the ‘Ubeidiya archeological site, as it contains human remains. A more sophisticated way of treating the results, by combining numerical modeling of cosmogenic nuclide build up during repeated burial-exposure cycles, paleomagnetic analysis (indicating reverse polarity) and a minimum burial age of 1.1 Ma set by U-Pb dating of Melanopsis shells, suggests two most probable time slots (1.19-1.77 and 1.93- 2.14 Ma) for the absolute age of the ‘Ubeidiya Formation. However, the skewed distribution of cosmogenic isotope burial ages, with a median age of 2.05 Ma, indicates a much higher probability of the older ages, most likely >1.9 Ma. The exposure-burial history that emerges from the model implies recycling of sediments previously deposited and buried in the rift valley, between 4.5 and 3.2 Ma, and subsequently exhumed, eroded, transported and then redeposited along the ‘Ubeidiya paleo lake shoreline.

Acheulean↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
DOE OSTI2021

Influence of shrub willow buffers strategically integrated in an Illinois corn-soybean field on soil health and microbial community composition

We report soil serves many important ecological functions and is an integral part of our existence as a society. However, concerns for soil health are growing globally, in part due to the negative impacts of agricultural management on soil resources. The production of perennial bioenergy crops on marginal land in row-crop production systems is one solution that could improve land-use efficiency and address the sustainability of cropland management. Because the relationship between crop management and the environment is complex, more research is needed to evaluate the potential benefits perennial bioenergy crop production has on soil health, as well as other ecosystem services. In this study, shrub willow buffers were strategically integrated into a corn-soybean cropping system with the main objective of reducing nitrate-N leaching from grain crop production while producing biomass for bioenergy. Two buffer systems (defined by landscape positions) were included for comparison, one on marginal land with exposure to nitrate-N leaching from upslope grain (southern plots) and one on fertile soils with less nitrate-N leaching potential (northern plots). Evaluation of soil (chemistry, bulk density, microbial community) and shrub willow vegetation properties ( fine roots, leaf litter decomposition, and nutrient uptake dynamics), showed that landscape position plays an important role in (1) the dynamics of soil chemical properties, (2) shrub willow's influence and productivity, and (3) the provision of additional ecosystem services such as reductions in nitrous oxide emissions and nitrate-N leaching. In addition, the combination of crop type and landscape position (N-grain, N-willow, S-grain, and S-willow) influenced the species composition of the soil microbial community, resulting in unique and identifiable communities. These results highlight the potential application of shrub willow buffers for ecosystem service provision and support of ecosystem processes; however, understanding the relationship between the microbial community, crop type, and landscape is important for understanding the sustainability of the design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Expanding the genomic encyclopedia of Actinobacteria with 824 isolate reference genomes

The phylum Actinobacteria includes important human pathogens like Mycobacterium tuberculosis and Corynebacterium diphtheriae and renowned producers of secondary metabolites of commercial interest, yet only a small part of its diversity is represented by sequenced genomes. Here, we present 824 actinobacterial isolate genomes in the context of a phylum-wide analysis of 6,700 genomes including public isolates and metagenome-assembled genomes (MAGs). We estimate that only 30%–50% of projected actinobacterial phylogenetic diversity possesses genomic representation via isolates and MAGs. A comparison of gene functions reveals novel determinants of host-microbe interaction as well as environment-specific adaptations such as potential antimicrobial peptides. We identify plasmids and prophages across isolates and uncover extensive prophage diversity structured mainly by host taxonomy. Analysis of >80,000 biosynthetic gene clusters reveals that horizontal gene transfer and gene loss shape secondary metabolite repertoire across taxa. Our observations illustrate the essential role of and need for high-quality isolate genome sequences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Three-Dimensional Reconstruction Algorithm for Scanning Transmission Electron Microscopy Data from a Single Sample Orientation

Abstract Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal series of four-dimensional scanning transmission electron microscopy (4D-STEM) data. We apply the approach to a lead iridate, PbIrO, and yttrium-stabilized zirconia, YZrO, heterostructure from data acquired with the specimen in a single plan-view orientation, with the epitaxial layers stacked along the beam direction. We demonstrate that Pb–Ir atomic columns are visible in the uppermost layers of the reconstructed volume. We compare this approach to the alternative techniques of depth sectioning using differential phase contrast scanning transmission electron microscopy (DPC-STEM) and multislice ptychographic reconstruction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Incorporation and Assembly of a Light-Emitting Enzymatic Reaction into Model Protein Condensates

Eukaryotic cells partition enzymes and other cellular components into distinct subcellular compartments to generate specialized biochemical niches. A subclass of these compartments form in the absence of lipid membranes, via liquid-liquid phase separation of proteins to form biomolecular condensates or “membraneless organelles” such as nucleoli, stress granules, and P-bodies. Because of their ability to form compartments from simple starting materials, membraneless organelles are an attractive target for engineering new functionalities in both living cells and protocells. In this work, we demonstrate incorporation of novel enzymatic activity in protein coacervates with a light-generating enzyme, NanoLuc, to produce bioluminescence. Using condensates comprised of the disordered RGG domain of C. elegans LAF-1, we show functionalization of condensates with enzymatic activity in vitro and that localization to protein coacervates enhances the assembly and activity of split enzymes. To build condensates that function as light emitting reactors, we designed a NanoLuc enzyme flanked by RGG domains. Furthermore, the resulting condensates concentrated NanoLuc by 10-fold over bulk solution and display significantly increased net reaction rates. We further show that condensate viscosity impacts light emission due to diffusion-limited behavior. By splitting NanoLuc enzyme into its constituent components, we demonstrate that NanoLuc activity can be reconstituted via co-condensation. Further, we demonstrate control of the spatial localization of enzyme within condensates by targettng NanoLuc to the surface of in vitro condensates. Collectively, this work demonstrates that membraneless organelles can be endowed with localized enzymatic activity, and that this activity can be spatially and temporally controlled via enzyme reconstitution and design of protein surfactants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Forces from Stochastic Density Functional Theory under Nonorthogonal Atom-Centered Basis Sets

We develop a formalism for calculating forces on the nuclei within the linear-scaling stochastic density functional theory (sDFT) in a nonorthogonal atom-centered basis set representation (Fabian et al. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2019, 9, e1412, 10.1002/wcms.1412) and apply it to the Tryptophan Zipper 2 (Trp-zip2) peptide solvated in water. We use an embedded-fragment approach to reduce the statistical errors (fluctuation and systematic bias), where the entire peptide is the main fragment and the remaining 425 water molecules are grouped into small fragments. We analyze the magnitude of the statistical errors in the forces and find that the systematic bias is of the order of 0.065 eV/Å (~1.2 × 10 -3 E h / a 0 ) when 120 stochastic orbitals are used, independently of system size. This magnitude of bias is sufficiently small to ensure that the bond lengths estimated by stochastic DFT (within a Langevin molecular dynamics simulation) will deviate by less than 1% from those predicted by a deterministic calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗