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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dopant Optimization of Donors in Semiconductor Opening Switches to Eliminate Prepulse

Semiconductor opening switches are solid-state devices capable of delivering nanosecond, hundreds of kilovolts pulses by interrupting kiloamps of current. The interruption of the current occurs in a moderately doped p-region when a high electric field region (HFR) is formed. The HFR occurs because the reverse pumping current cannot be supported by the saturation velocity and majority carrier concentration of the doping level. However, the donor profile also significantly affects the pulse performance. A secondary prepulse occurs if a secondary HFR is formed at the interface of the background n-doping and N+ doping (X n ) . By moving the location of X n deeper into the diode, the effect of the prepulse is reduced. This article investigates the effect of the donor doping profile on the performance metrics of semiconductor opening switches through technology computer-aided design (TCAD) simulations and experimental results. Through a SILVACO TCAD optimization, we designed a P + /p/n - base/n/N + where the intersection of the moderate p-region and intrinsic n-base region (X p ) is at 160 μm and X n is at 220 μm. This profile is fabricated via silicon epitaxy. Experimentally, it is shown that a deep X n (220 μm) compared with a shallow X n (300 μm) reduces the rise time by >5× . In addition, the magnitude of current density during interruption affects the prepulse foot and pulse shape. At lower current densities without the graded donor profile, high peak voltages are not achieved. Comparing the experimental results to the TCAD simulations shows that the model is predictive under high-current densities in the semiconductor opening switch (SOS) regime.

nanosecond pulse power↗
DOE OSTI2022

Background-Aware 3-D Point Cloud Segmentation With Dynamic Point Feature Aggregation

With the proliferation of LiDAR sensors and 3-D vision cameras, 3-D point cloud analysis has attracted significant attention in recent years. In this article, we propose a novel 3-D point cloud learning network, referred to as dynamic point feature aggregation network (DPFA-Net), by selectively performing the neighborhood feature aggregation (FA) with dynamic pooling and an attention mechanism. DPFA-Net has two variants for semantic segmentation and classification of 3-D point clouds. As the core module of the DPFA-Net, we propose an FA layer, in which features of the dynamic neighborhood of each point are aggregated via a self-attention mechanism. In contrast to other segmentation models, which aggregate features from fixed neighborhoods, our approach can aggregate features from different neighbors in different layers providing a more selective and broader view to the query points and focusing more on the relevant features in a local neighborhood. In addition, to further improve the performance of semantic segmentation, we exploit the background–foreground (BF) information and present two novel approaches, namely, two-stage BF-Net and BF regularization. Experimental results show that the proposed DPFA-Net achieves the state-of-the-art overall accuracy score of 89.22% for semantic segmentation on the Stanford large-scale 3-D Indoor Spaces (S3DIS) dataset and provides consistently satisfactory performance across different tasks of semantic segmentation, part segmentation, and 3-D object classification. Furthermore, our model achieves 93.1% accuracy on the ModelNet40 dataset and provides a mean shape intersection-over-union (IoU) value of 85.5% for part segmentation on the ShapeNet-Part dataset. It is a also computationally more efficient compared to other methods.

3-D↗
DOE OSTI2026

Characterization of Precipitation-Induced Radon Progeny Deposition Events Using a City-Scale Sensor Network

Networks of radiation detectors provide a platform for real-time radioactive source detection and identification in urban environments. Detection algorithms in these systems must adapt to naturally-occurring changes in background, which requires well-characterized relationships between precipitation events and their corresponding radiological signature. Here, we present a quantitative and qualitative description of rain-induced radon progeny deposition events occurring in Chicago from September 2023 to February 2024. We measure ambient gamma radiation levels, precipitation rate, temperature, pressure, and relative humidity in a network of sensor nodes. For each identified precipitation period, we decompose spectra into static- and radon-associated components as defined by a non-negative matrix factorization (NMF) algorithm. We find a consistent power-law relationship between a precipitation-dependent peak of the radon progeny proxy (RPP) and the peak strength of the radon-associated NMF component for most precipitation events. We conduct a case study of a rainfall period with abnormally high levels of implied radon progeny concentration and describe its temporal and spatial evolution. We hypothesize that this phenomenon is due to the air mass path that intersects a uranium-rich region of Wyoming. Finally, we cluster precipitation events into three distinct categories. One category roughly corresponds to events with deep low-pressure systems and high relative radon concentration, while another is characteristic of light stratiform rain with slightly higher temperatures and intermediate relative radon concentration. The third category appears to contain weak-gradient or lake breeze convection showers with intermittent precipitation and low relative radon concentration. These findings suggest that radiological anomaly detection could be improved by training unique background models corresponding to each category of meteorological event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Trust: Triangle Counting Reloaded on GPUs

Triangle counting is a building block for a wide range of graph applications. Here, traditional wisdom suggests that i) hashing is not suitable for triangle counting, ii) edge-centric triangle counting beats vertex-centric design, and iii) communication-free and workload balanced graph partitioning is a grand challenge for triangle counting. On the contrary, we advocate that i) hashing can help the key operations for scalable triangle counting on Graphics Processing Units (GPUs), i.e., list intersection and graph partitioning, ii) vertex-centric option reduces both hash table construction cost and memory consumption, which is limited on GPUs. In addition, iii) we exploit graph and workload collaborative, and hash-based 2D partitioning to scale vertex-centric triangle counting over 1,000 GPUs with sustained scalability. In this work, we present TRUST, which performs triangle counting with the hash operation and vertex-centric paradigm. To the best of our knowledge, TRUST is the first work that achieves over one trillion Traversed Edges Per Second (TEPS) rate for triangle counting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Press and Pulse of Climate Change: Extreme Events in the Colorado River Basin

Extremes in temperature and precipitation are associated with damaging floods, prolonged drought, destructive wildfires, agricultural challenges, compromised human health, vulnerable infrastructure, and threatened ecosystems and species. Often, the steady and progressive trends (or presses) of rising global temperature are the central focus in how climate impacts are described. However, observations of extreme weather events (or pulses) increasingly show that the intensity, duration and/or frequency of acute events are also changing, resulting in greater impacts on communities and the environment. Describing how the influence of extreme events may shape water management in the Colorado River Basin in clear terms is critical to sound future planning and efforts to manage risk. Three scenario planning workshops in 2019 and 2020 were held as part of a Colorado River Conversations series, identifying potential impacts from multiple intersecting extreme events. Water managers identified climate-related events of concern in the Colorado River Basin that necessitate greater attention and adaptive responses. To support efforts to include consideration of climate-change-driven extremes in water management and planning, we explore the current state of knowledge at the confluence of long-term climate shifts and extreme weather in the Colorado River Basin related to the events of concern that were identified by scenario planning participants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Identification of ancestral gnathostome Gli3 enhancers with activity in mammals

Abnormal expression of the transcriptional regulator and hedgehog (Hh) signaling pathway effector Gli3 is known to trigger congenital disease, most frequently affecting the central nervous system (CNS) and the limbs. Accurate delineation of the genomic cis-regulatory landscape controlling Gli3 transcription during embryonic development is critical for the interpretation of noncoding variants associated with congenital defects. Here, we employed a comparative genomic analysis on fish species with a slow rate of molecular evolution to identify seven previously unknown conserved noncoding elements (CNEs) in Gli3 intronic intervals (CNE15–21). Transgenic assays in zebrafish revealed that most of these elements drive activities in Gli3 expressing tissues, predominantly the fins, CNS, and the heart. Intersection of these CNEs with human disease associated SNPs identified CNE15 as a putative mammalian craniofacial enhancer, with conserved activity in vertebrates and potentially affected by mutation associated with human craniofacial morphology. Finally, comparative functional dissection of an appendage-specific CNE conserved in slowly evolving fish (elephant shark), but not in teleost (CNE14/hs1586) indicates co-option of limb specificity from other tissues prior to the divergence of amniotes and lobe-finned fish. In conclusion, these results uncover a novel subset of intronic Gli3 enhancers that arose in the common ancestor of gnathostomes and whose sequence components were likely gradually modified in other species during the process of evolutionary diversification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Method to Represent a Well in a Three‐Dimensional Discrete Fracture Network Model

Abstract In discrete fracture network (DFN) modeling, fractures are randomly generated and placed in the model domain. The rock matrix is considered impermeable. Small fractures and isolated fractures are often ignored to reduce computational expense. As a result, the rock matrix between fractures could be large and intersections may not be found between a well introduced in the model and the hydraulically connected fracture networks (fracture backbones). To overcome this issue, this study developed a method to conceptualize a well in a three‐dimensional (3D) DFN using two orthogonal rectangular fractures oriented along the well's axis. Six parameters were introduced to parameterize the well screen and skin zone, and to control the connectivity between the well and the fracture backbones. The two orthogonal fractures were discretized using a high‐resolution mesh to improve the quality of flow and transport simulations around and along the well. The method was successfully implemented within dfnWorks 2.0 (Hyman et al. 2015) to incorporate a well in a 3D DFN and to track particles leaving an injection well and migrating to a pumping well. Verification of the method against MODFLOW/MODPATH found a perfect match in simulated hydraulic head and particle tracking. Using three examples, the study showed that the method ensured the connectivity between wells and fracture backbones, and honored the physical processes of flow and transport along and around wells in DFNs. Recommendations are given for estimating the values of the six introduced well parameters in a real‐world case study.

Pham, Hai (ORCID:0000000310164394)↗
DOE OSTI2022

Let’s talk about sex: A biological variable in immune response against melanoma

As science culture gravitates toward a more holistic inclusion of both males and females in research design, the outlining of sex differences and their respective intersections with disease physiology and pathophysiology should see reciprocal expansion. Melanoma skin cancer, for example, has observed a female advantage in incidence, mortality, and overall survival since the early 1970s. The exact biological mechanism of this trend, however, is unclear and further complicated by a layering of clinical variables such as skin phototype, age, and body mass index. In this perspective, we highlight epidemiological evidence of sex differences in melanoma and summarize the landscape of their potential origin. Among several biological hallmarks, we make a note of sex-specific immune profiles—along with divergent hormonal regulation, social practices, DNA damage and oxidative stress responses, body composition, genetic variants, and X-chromosome expression—as probable drivers of disparity in melanoma initiation and progression. This review further focuses the conversation of sex as an influencing factor in melanoma development and its potential implication for disease management and treatment strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Multirange Vehicle Speed Prediction With Application to Model Predictive Control-Based Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Abstract Connectivity and automated driving technologies have opened up new research directions in the energy management of vehicles which exploit look-ahead preview and enhance the situational awareness. Despite this advancement, the vehicle speed preview that can be obtained from vehicle-to-vehicle/infrastructure (V2V/I) communications is often limited to a relatively short time-horizon. The vehicular energy systems, specifically those of the electrified vehicles, consist of multiple interacting power and thermal subsystems that respond over different time-scales. Consequently, their optimal energy management can greatly benefit from long-term speed prediction beyond that available through V2V/I communications. Accurately extending the look-ahead preview, on the other hand, is fundamentally challenging due to the dynamic nature of the traffic environment. To address this challenge, we propose a data-driven multirange vehicle speed prediction strategy for arterial corridors with signalized intersections, providing the vehicle speed preview for three different ranges, i.e., short-, medium-, and long-range. The short-range preview is obtained by V2V/I communications. The medium-range preview is realized using a neural network (NN), while the long-range preview is predicted based on a Bayesian network (BN). The predictions are updated in real-time based on the current state of traffic and incorporated into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city driving are reported.

Automation & Control Systems↗
DOE OSTI2022

Ecological Adaptive Cruise Control of Plug-In Hybrid Electric Vehicle With Connected Infrastructure and On-Road Experiments

Abstract This paper examines both mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. Human errors are typical sources of accidents in urban driving, which can be remedied by rigorous control theories. Designing an ECO-ACC is, therefore, a classical research problem to improve safety and energy efficiency. We add two main contributions to the literature. First, we propose a mathematical framework of an online ECO-ACC for plug-in hybrid electric vehicle (PHEV). Second, we demonstrate ECO-ACC in a real world, which includes other human drivers and uncertain traffic signals on a 2.6 (km) length of the corridor with eight signalized intersections in Southern California. The demonstration results show, on average, 30.98% of energy efficiency improvement and 8.51% additional travel time.

Automation & Control Systems↗
DOE OSTI2022

Teaching Quantum Computing to High School Students

Quantum computing is a growing field at the intersection of physics and computer science. The goal of this article is to highlight a successfully trialled quantum computing course for high school students between the ages of 15 and 18 years old. This course was designed to bridge the gap between popular science articles and advanced undergraduate textbooks. Conceptual ideas in the text are reinforced with active learning techniques, such as interactive problem sets and simulation-based labs at various levels. The course is freely available for use and download under the Creative Commons “Attribution-NonCommercial-ShareAlike 4.0 International” license.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Examining metastatic behavior within 3D bioprinted vasculature for the validation of a 3D computational flow model

Understanding the dynamics of circulating tumor cell (CTC) behavior within the vasculature has remained an elusive goal in cancer biology. To elucidate the contribution of hydrodynamics in determining sites of CTC vascular colonization, the physical forces affecting these cells must be evaluated in a highly controlled manner. To this end, we have bioprinted endothelialized vascular beds and perfused these constructs with metastatic mammary gland cells under physiological flow rates. By pairing these in vitro devices with an advanced computational flow model, we found that the bioprinted analog was readily capable of evaluating the accuracy and integrated complexity of a computational flow model, while also highlighting the discrete contribution of hydrodynamics in vascular colonization. This intersection of these two technologies, bioprinting and computational simulation, is a key demonstration in the establishment of an experimentation pipeline for the understanding of complex biophysical events.

42 ENGINEERING↗
DOE OSTI2024

Role of slip in hydrogen-assisted crack initiation in Ni-based alloy 725

We conduct in situ tensile straining experiments to investigate the role of hydrogen and slip in crack initiation in nickel-based alloy 725. Our experiments reveal no tendency for hydrogen to enhance localized slip and no necessity of slip for crack initiation. We use electrochemical charging to introduce hydrogen into samples, melt extraction to measure hydrogen content, and digital image correlation to analyze localized plastic strains during in situ tensile tests in a scanning electron microscope. Cracks initiate both in regions with and without nearby localized slip. Moreover, the fraction of cracks initiating with no nearby slip is greater at higher hydrogen content. Slip-assisted crack initiation generally occurs at locations where intergranular slip is arrested, especially at intersections of slipping coherent twin boundaries with thin twin lamellae. Cracks that initiate without nearby slip occur at a wider variety of microstructural features, including inclusions, triple junctions, and surface flaws.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomic-scale visualization of topological spin textures in the chiral magnet MnGe

Peeking into magnetic textures Topological spin textures hold promise as robust carriers of information and have been observed in bulk materials with a specific crystal structure. One of these materials, manganese germanide (MnGe), exhibits unusual textures in bulk form. Repicky et al . used spin-polarized scanning tunneling microscopy to study surface magnetism in thin films of MnGe. Achieving high spatial resolution, the researchers observed stripe-like features consistent with a helical state. In regions where the film was slightly curved due to strain, the intersection of domain walls led to characteristic closed patterns that could be manipulated with current/voltage pulses. —JS

Science & Technology - Other Topics↗
DOE OSTI2021

Crossover from hydrogen to chemical bonding

Hydrogen bonds (H-bonds) can be interpreted as a classical electrostatic interaction or as a covalent chemical bond if the interaction is strong enough. As a result, short strong H-bonds exist at an intersection between qualitatively different bonding descriptions, with few experimental methods to understand this dichotomy. The [F-H-F] − ion represents a bare short H-bond, whose distinctive vibrational potential in water is revealed with femtosecond two-dimensional infrared spectroscopy. It shows the superharmonic behavior of the proton motion, which is strongly coupled to the donor-acceptor stretching and disappears on H-bond bending. In combination with high-level quantum-chemical calculations, we demonstrate a distinct crossover in spectroscopic properties from conventional to short strong H-bonds, which identify where hydrogen bonding ends and chemical bonding begins.

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

Kink bands promote exceptional fracture resistance in a NbTaTiHf refractory medium-entropy alloy

Single-phase body-centered cubic (bcc) refractory medium- or high-entropy alloys can retain compressive strength at elevated temperatures but suffer from extremely low tensile ductility and fracture toughness. We examined the strength and fracture toughness of a bcc refractory alloy, NbTaTiHf, from 77 to 1473 kelvin. This alloy’s behavior differed from that of comparable systems by having fracture toughness over 253 MPa·m 1/2 , which we attribute to a dynamic competition between screw and edge dislocations in controlling the plasticity at a crack tip. Whereas the glide and intersection of screw and mixed dislocations promotes strain hardening controlling uniform deformation, the coordinated slip of <111> edge dislocations with {110} and {112} glide planes prolongs nonuniform strain through formation of kink bands. These bands suppress strain hardening by reorienting microscale bands of the crystal along directions of higher resolved shear stress and continually nucleate to accommodate localized strain and distribute damage away from a crack tip.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultrastructure of Organohalide-Respiring Dehalococcoidia Revealed by Cryo-Electron Tomography

Dehalococcoides mccartyi (Dhc) and Dehalogenimonas spp. (Dhgm) are members of the class Dehalococcoidia, phylum Chloroflexi, characterized by streamlined genomes and a strict requirement for organohalogens as electron acceptors. Here, we used cryo-electron tomography to reveal morphological and ultrastructural features of Dhc strain BAV1 and “Candidatus Dehalogenimonas etheniformans” strain GP cells at unprecedented resolution. Dhc cells were irregularly shaped discs (890 ± 110 nm long, 630 ± 110 nm wide, and 130 ± 15 nm thick) with curved and straight sides that intersected at acute angles, whereas Dhgm cells appeared as slightly flattened cocci (760 ± 85 nm). The cell envelopes were composed of a cytoplasmic membrane (CM), a paracrystalline surface layer (S-layer) with hexagonal symmetry and ~22-nm spacing between repeating units, and a layer of unknown composition separating the CM and the S-layer. Cell surface appendages were only detected in Dhc cells, whereas both cell types had bundled cytoskeletal filaments. Repetitive globular structures, ~5 nm in diameter and ~9 nm apart, were observed associated with the outer leaflet of the CM. We hypothesized that those represent organohalide respiration (OHR) complexes and estimated ~30,000 copies per cell. In Dhgm cultures, extracellular lipid vesicles (20 to 110 nm in diameter) decorated with putative OHR complexes but lacking an S-layer were observed. Furthermore, the new findings expand our understanding of the unique cellular ultrastructure and biology of organohalide-respiring Dehalococcoidia.

59 BASIC BIOLOGICAL SCIENCES↗