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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Updated resources for exploring experimentally-determined PDB structures and Computed Structure Models at the RCSB Protein Data Bank

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, RCSB.org), the US Worldwide Protein Data Bank (wwPDB, wwPDB.org) data center for the global PDB archive, provides access to the PDB data via its RCSB.org research-focused web portal. We report substantial additions to the tools and visualization features available at RCSB.org, which now delivers more than 227000 experimentally determined atomic-level three-dimensional (3D) biostructures stored in the global PDB archive alongside more than 1 million Computed Structure Models (CSMs) of proteins (including models for human, model organisms, select human pathogens, crop plants and organisms important for addressing climate change). In addition to providing support for 3D structure motif searches with user-provided coordinates, new features highlighted herein include query results organized by redundancy-reduced Groups and summary pages that facilitate exploration of groups of similar proteins. Newly released programmatic tools are also described, as are enhanced training opportunities.

Burley, Stephen K.↗
DOE OSTI2021

Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. Furthermore, the proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Two VHH Antibodies Neutralize Botulinum Neurotoxin E1 by Blocking Its Membrane Translocation in Host Cells

Botulinum neurotoxin serotype E (BoNT/E) is one of the major causes of human botulism, which is a life-threatening disease caused by flaccid paralysis of muscles. After receptor-mediated toxin internalization into motor neurons, the translocation domain (HN) of BoNT/E transforms into a protein channel upon vesicle acidification in endosomes and delivers its protease domain (LC) across membrane to enter the neuronal cytosol. It is believed that the rapid onset of BoNT/E intoxication compared to other BoNT serotypes is related to its swift internalization and translocation. We recently identified two neutralizing single-domain camelid antibodies (VHHs) against BoNT/E1 termed JLE-E5 and JLE-E9. Here, we report the crystal structures of these two VHHs bound to the LCHN domain of BoNT/E1. The structures reveal that these VHHs recognize two distinct epitopes that are partially overlapping with the putative transmembrane regions on HN, and therefore could physically block membrane association of BoNT/E1. This is confirmed by our in vitro studies, which show that these VHHs inhibit the structural change of BoNT/E1 at acidic pH and interfere with BoNT/E1 association with lipid vesicles. Therefore, these two VHHs neutralize BoNT/E1 by preventing the transmembrane delivery of LC. Furthermore, structure-based sequence analyses show that the 3-dimensional epitopes of these two VHHs are largely conserved across many BoNT/E subtypes, suggesting a broad-spectrum protection against the BoNT/E family. In summary, this work improves our understanding of the membrane translocation mechanism of BoNT/E and paves the way for developing VHHs as diagnostics or therapeutics for the treatment of BoNT/E intoxication.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Rational design of a uranyl metal-organic framework for the capture and colorimetric detection of organic dyes

A new uranyl containing metal-organic framework, RPL-1: [(UO2)2(C28H18O8)] · H2O (RPL for Radiochemical Processing Laboratory), was prepared, structurally characterized, and the solid-state photoluminescence properties explored. The single crystal X-ray diffraction data reveal the structure of RPL-1 consists of two crystallographically unique three dimensional, interpenetrating nets with a 4,3-connected tbo topology. Each net contains large pores with an average width of 22.8 Å and is formed from monomeric, hexagonal bipyramidal uranyl nodes that are linked via 1,2,4,5-tetrakis(4-carboxyphenyl)benzene (TCPB) linkers. The thermal and photophysical properties of RPL-1 were investigated using thermogravimetric analysis and absorbance, fluorescence, and lifetime spectroscopies. The material displays excellent thermal stability and temperature dependent uranyl and TCBP luminescence. The framework is stable in aqueous media and due to the large void space (constituting 76% of the unit cell by volume) can sequester organic dyes, the uptake of which induces a visible change to the color of the material.

Surbella, Robert G.↗
DOE OSTI2023

Scalable graphene sensor array for real-time toxins monitoring in flowing water

Abstract Risk management for drinking water often requires continuous monitoring of various toxins in flowing water. While they can be readily integrated with existing water infrastructure, two-dimensional (2D) electronic sensors often suffer from device-to-device variations due to the lack of an effective strategy for identifying faulty devices from preselected uniform devices based on electronic properties alone, resulting in sensor inaccuracy and thus slowing down their real-world applications. Here, we report the combination of wet transfer, impedance and noise measurements, and machine learning to facilitate the scalable nanofabrication of graphene-based field-effect transistor (GFET) sensor arrays and the efficient identification of faulty devices. Our sensors were able to perform real-time detection of heavy-metal ions (lead and mercury) and E. coli bacteria simultaneously in flowing tap water. This study offers a reliable quality control protocol to increase the potential of electronic sensors for monitoring pollutants in flowing water.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Three-dimensional paganica fault morphology obtained from hypocenter clustering (L'Aquila 2009 seismic sequence, Central Italy)

In seismic modelling, fault planes are normally assumed to be flat due to the lack of data which can constrain fault morphology. However, incorporating 3D fault morphology is important for modelling several phenomena, for example calculating mainshock induced stress changes. Here we utilize a data-analytical method to unveil the 3D rupture morphology of faults using unsupervised clustering techniques applied to earthquake hypocenters in seismic sequences. We apply this method to the 2009 L'Aquila seismic sequence which involved a M W 6.1 mainshock on April 6th. We use a dataset of about 50,000 relocated events, mostly microearthquakes, reaching magnitude of completeness equal to 0.7. Clustering distinguishes the earthquakes as occurring in three main clusters along with other minor fault segments. We then represent the morphology of the main Paganica fault system (responsible for the largest mainshock) using splines. This method shows promise as a step toward robustly and quickly obtaining 3D rupture morphologies where earthquake sequences have been monitored. The 3D model is presented interactively online, and the processing is presented in an interactive Jupyter Notebook (https://bit.ly/2MnCFdj).

58 GEOSCIENCES↗
DOE OSTI2024

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into “Beyond CMOS” and “More than Moore” paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. Finally, the outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nonlinear simulations of GAEs in NSTX-U

A set of nonlinear simulations has been performed in order to study the nonlinear evolution of unstable global Alfvén eigenmodes in the National Spherical Torus Experiment-Upgrade (NSTX-U). Results of the single toroidal mode number, n, simulations are compared with a full nonlinear simulation (all toroidal harmonics included). In single-n simulations, the conservation of two integrals of motion of a particle in a cyclotron resonance with a monochromatic wave is demonstrated, resulting in a one-dimensional evolution of the particle distribution in (E,μ,pϕ) phase-space. Nonlinear simulations (both single-n and full nonlinear) show a significant redistribution of the resonant fast ions, especially in the pitch parameter. Thus, the changes in the resonant particle's parallel and perpendicular energies can be several times larger than the total particle energy change, with only a small fraction transferring into the excitation of the mode itself. This implies that even a relatively small amplitude mode can significantly modify the beam distribution in the resonant region. For the NSTX-U case considered, the single-n simulation results are close to full nonlinear simulation only for the most unstable mode, in which case the saturation amplitudes and changes in the fast ion distribution are comparable. In contrast, peak amplitudes of subdominant modes in all-n simulations are smaller by a factor of 3–10 compared to single-n runs due to the flattening of the beam ion distribution by the fastest growing mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Structure of the immunoregulatory sialidase NEU1

Sialic acids linked to glycoproteins and glycolipids are important mediators of cell and protein recognition events. These sugar residues are removed by neuraminidases (sialidases). Neuraminidase-1 (sialidase-1 or NEU1) is a ubiquitously expressed mammalian sialidase located in lysosomes and on the cell membrane. Because of its modulation of multiple signaling processes, it is a potential therapeutic target for cancers and immune disorders. Genetic defects in NEU1 or in its protective protein cathepsin A (PPCA, CTSA) cause the lysosomal storage diseases sialidosis and galactosialidosis. To further our understanding of this enzyme’s function at the molecular level, we determined the three-dimensional structure of murine NEU1. The enzyme oligomerizes through two self-association interfaces and displays a wide substrate-binding cavity. A catalytic loop adopts an inactive conformation. We propose a mechanism of activation involving a conformational change in this loop upon binding to its protective protein. These findings may facilitate the development of selective inhibitor and agonist therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗
DOE OSTI2020

Treatment of Tilted Sonar Data for Salt Cavern Analysis

Structural modeling and visualization of salt caverns requires three-dimensional representations. These representations are typically produced from sonar surveys conducted by companies that then produce a report of depths, distances, and volumes. There are multiple formats that are vendor dependent, and, as technology improves, there have been changes from only horizontal surveys to inclined shots for ceilings and floors to mid-cavern inclined shots. For geomechanical modeling, leaching predictions, and cavern stability visualizations, Sandia has previously written in-house software, called SONAR8, that created a consistent geometry format from the processed sonar reports. However, the increase in the need for mid-cavern inclined surveys led to the discovery of certain limitations in that code. This report describes methods used to process the multiple different formats to handle inclined shots in a consistent and accurate manner in our modeling efforts. A set of file formats and a database schema that was developed for this work is also documented in the appendices.

02 PETROLEUM↗
DOE OSTI2021

Null geodesics and thermodynamic phase transition of four-dimensional Gauss–Bonnet AdS black hole

Highlights: • Modified gravity theories. • Null geodesics and the thermodynamic phase transition. • Four-dimensional Gauss–Bonnet AdS black hole. • Correlation between gravity and thermodynamics. Modified gravity theories are of great interest in both observational and theoretical studies. In this article, we study the correlation between the null geodesics and the thermodynamic phase transition of a four-dimensional Gauss–Bonnet AdS black hole. Firstly, we study the phase structure of the black hole, using the coexistence and spinodal curves, to understand the phase transition in an extended phase space. The imprints of these phase transition features can be clearly observed from the functional dependence of photon orbit radius and minimum impact parameter with respect to the Hawking temperature and pressure. The change in these two quantities during the phase transition serve as order parameters which characterise the critical behaviour. The correlation shows that thermodynamic phase transition can be studied by observing the effects of strong gravitational field on the photon orbit and vice versa.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Visualizing Orbital Content of Electronic Bands in Anisotropic 2D Semiconducting ReSe 2

Many properties of layered materials change as they are thinned from their bulk forms down to single layers, with examples including indirect-to-direct band gap transition in 2H semiconducting transition metal dichalcogenides as well as thickness-dependent changes in the valence band structure in post-transition-metal monochalcogenides and black phosphorus. Here, we use angle-resolved photoemission spectroscopy to study the electronic band structure of monolayer ReSe 2 , a semiconductor with a distorted 1T structure and in-plane anisotropy. By changing the polarization of incoming photons, we demonstrate that for ReSe 2 , in contrast to the 2H materials, the out-of-plane transition metal dz2 and chalcogen pz orbitals do not contribute significantly to the top of the valence band, which explains the reported weak changes in the electronic structure of this compound as a function of layer number. We estimate a band gap of 1.7 eV in pristine ReSe 2 using scanning tunneling spectroscopy and explore the implications on the gap following surface doping with potassium. Additionally, a lower bound of 1.4 eV is estimated for the gap in the fully doped case, suggesting that doping-dependent many-body effects significantly affect the electronic properties of ReSe 2 . Our results, supported by density functional theory calculations, provide insight into the mechanisms behind polarization-dependent optical properties of rhenium dichalcogenides and highlight their place among two-dimensional crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering

Single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low abundance proteins. Herein, we describe an ion mobility-enhanced mass spectrometry acquisition and peptide identification method, TIFF (Transferring Identification based on FAIMS Filtering), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Quantum Phase Engineering of Two-Dimensional Post-Transition Metals by Substrates: Toward a Room-Temperature Quantum Anomalous Hall Insulator

In this work, we propose a new strategy to engineer topological and magnetic properties of two-dimensional (2D) hexagonal lattices consisting of post-transition metals. Our first-principles calculations demonstrate that substrates serve as templates to form 2D lattices with high thermodynamic stability, where their topological properties as well as magnetic properties sensitively change as a function of lattice constants, i.e., the system undergoes a first-order phase transition from nonmagnetic to ferromagnetic state above a critical lattice constant. Consequently, substrates can be used to explore versatile magnetic, electronic, and quantum topological properties. We establish phase diagrams of versatile quantum phases in terms of exchange coupling and spin–orbit coupling effectively tuned by the lattice constants. We further reveal the first room-temperature quantum anomalous Hall (QAH) effect, i.e., Sn on 2√3 × 2√3 graphane is a QAH insulator with a large spin–orbit coupling gap of ~0.2 eV and a Curie temperature of ~380 K by using the 2D anisotropic Heisenberg model.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ultra-low-density digitally architected carbon with a strutted tube-in-tube structure

Porous materials with engineered stretching-dominated lattice designs, which offer attractive mechanical properties with ultra-light weight and large surface area for wide-ranging applications, have recently achieved near-ideal linear scaling between stiffness and density. Here, rather than optimizing the microlattice topology, we explore a different approach to strengthen low-density structural materials by designing tube-in-tube beam structures. We develop a process to transform fully dense, three-dimensional printed polymeric beams into graphitic carbon hollow tube-in-tube sandwich morphologies, where, similar to grass stems, the inner and outer tubes are connected through a network of struts. Compression tests and computational modelling show that this change in beam morphology dramatically slows down the decrease in stiffness with decreasing density. In situ pillar compression experiments further demonstrate large deformation recovery after 30–50% compression and high specific damping merit index. Lastly, our strutted tube-in-tube design opens up the space and realizes highly desirable high modulus–low density and high modulus–high damping material structures.

36 MATERIALS SCIENCE↗