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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed

This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.

Elwasif, Wael↗
DOE OSTI2024

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Incorporating FLEX Strategies in Multi-Unit Probabilistic Risk Assessment

The catastrophic Fukushima nuclear accident reminded nuclear community about the possibilities of extreme accident scenarios, including those involving multiple reactor units on the same site. As the responses to the Fukushima accident, the nuclear power industry developed and implemented a series of strategies, including the Diverse and Flexible Coping Strategies (FLEX), to enhance the coping capacities of nuclear power plants (NPPs) under extreme accidents. This study intends to examine the impact of FLEX strategies on the risk from all the reactor units on the same NPP site, including risks from accidents involving a single unit and from accidents involving multiple units. The fundamental, methodological element of this study is Multi-Unit Probabilistic Risk Assessment (MUPRA), which requires a shift in Probabilistic Risk Assessment (PRA) from a “one-reactor-at-a-time” mindset to a “considering all reactors sharing a site as a unity” one. An integrated modeling approach for multi-unit event sequence development will be leveraged to develop MUPRA model and address the intra-unit and inter-unit dependencies. Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), a PRA software developed and maintained by Idaho National Laboratory (INL) for the U.S. Nuclear Regulatory Commission (NRC), will serve as the platform for MUPRA modeling. This study selects Loss Of Offsite Power (LOOP) as a representative initiating event, which may occur on a generic two-unit NPP site and impacts both reactor units on the site. First, an MUPRA model, including multi-unit event trees, will be developed to obtain single-unit and multi-unit accident scenarios. Next, different FLEX strategies will be assumed, including FLEX equipment for a unit cannot be used for another unit, FLEX equipment for multiple units can be used in a cross-connected manner, etc. Lastly, the effectiveness of each postulated FLEX strategy will be evaluated by incorporating the corresponding FLEX equipment and deployment logic in the MUPRA model.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS)

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. Overall, this protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

HyperKube: A Kubernetes Based System for the Automation of Processing and Analysis of Hyperspectral Data Obtained from Multiple Hyperspectral Imaging Systems

Hyperspectral imagery is an emerging field of technology that has enormous potential for remote and proximal sensing in numerous areas of research. The plant phenotyping community is applying this technology to advance the throughput and accuracy of plant phenotypes based on airborne and lab-based hyperspectral imaging technology. Here we report an automated processing and analysis pipeline for four different hyperspectral imaging platforms, discuss the data issues involved, and present a strategy for computing and data architecture to handle hyperspectral data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Synthesis and application of thermally responsive nanofiber coatings for overtemperature monitoring

This study presents a one-pot synthesis route to organometallic nanofibers based on copper thiolate, exhibiting distinctive chemical and physical characteristics. Electron microscopy analysis of morphology and composition revealed 2-10 μm-long, 50-90 nm-diameter hollow and non-hollow fibers composed of copper, sulfur, oxygen, hydrocarbon, and chlorine. Thermogravimetric analysis showed a pronounced mass loss within 120°C-135°C. To elucidate the thermal responsive pathways, the nanofibers were characterized before and after heating. X-ray photoelectron spectroscopy indicates that an initially mixed Cu(I)/Cu(II) oxidation states transition to predominantly Cu(I) upon heating. A layer of nanofiber was coated on battery pouch foil and evaluated as a candidate thermally sensitive coating. At elevated temperature (100-130°C), nanofiber coating released volatile organic compounds, sulfide and sulfur dioxide as detected using multiple gas sensors. This thermally responsive gas release/sensing approach provides a potential large-area temperature monitoring strategy, which is particularly relevant where direct temperature measurements of individual batteries is impractical. The results established proof of concept for nanofiber-coated battery pouch foil as overtemperature warning platform that can provide alerts when surface temperatures exceed a critical threshold. More broadly, the ability to form interconnected fiber networks positions copper thiolate nanofiber coatings as promising materials for advanced applications.

Ihala Gamaralalage, Chanaka [ORNL] (ORCID:00000002↗
DOE OSTI2022

Exploring mechanistic routes for light alkane oxidation with an iron–triazolate metal–organic framework

In this work, we computationally explore the formation and subsequent reactivity of various iron-oxo species in the iron–triazolate framework Fe 2 (m-OH) 2 (bbta) (H2bbta = 1H,5H-benzo(1,2-d:4,5- d0)bistriazole) for the catalytic activation of strong C–H bonds. With the direct conversion of methane to methanol as the probe reaction of interest, we use density functional theory (DFT) calculations to evaluate multiple mechanistic pathways in the presence of either N 2 O or H 2 O 2 oxidants. These calculations reveal that a wide range of transition metal-oxo sites – both terminal and bridging – are plausible in this family of metal–organic frameworks, making it a unique platform for comparing the electronic structure and reactivity of different proposed active site motifs. Based on the DFT calculations, we predict that Fe 2 (m-OH)2(bbta) would exhibit a relatively low barrier for N 2 O activation and energetically favorable formation of an [Fe(O)] 2+ species that is capable of oxidizing C–H bonds. In contrast, the use of H 2 O 2 as the oxidant is predicted to yield an assortment of bridging iron-oxo sites that are less reactive. We also find that abstracting oxo ligands can exhibit a complex mixture of both positive and negative spin density, which may have broader implications for relating the degree of radical character to catalytic activity. In general, we consider the coordinatively unsaturated iron sites to be promising for oxidation catalysis, and we provide several recommendations on how to further tune the catalytic properties of this family of metal–triazolate frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Conflation of Geospatial POI Data and Ground-level Imagery via Link Prediction on Joint Semantic Graph

With the proliferation of smartphone cameras and social networks, we have rich, multi-modal data about points of interest (POIs) - like cultural landmarks, institutions, businesses, etc. - within a given areas of interest (AOI) (e.g., a county, city or a neighborhood) available to us. Data conflation across multiple modalities of data sources is one of the key challenges in maintaining a geographical information system (GIS) which accumulate data about POIs. Given POI data from nine different sources, and ground-level geo-tagged and scene-captioned images from two different image hosting platforms, in this work we explore the application of graph neural networks (GNNs) to perform data conflation, while leveraging a natural graph structure evident in geospatial data. The preliminary results demonstrate the capacity of a GNN operation to learn distributions of entity (POIs and images) features, coupled with topological structure of entity's local neighborhood in a semantic nearest neighbor graph, in order to predict links between a pair of entities.

Gurav, Rutuja↗
DOE OSTI2022

Transactive Campus Energy Systems: An R&D Testbed for Renewables, Integration, Efficiency, and Grid Services (CRADA 356 / Amendment 1)

The Clean Energy and Transactive Campus (CETC) work described in this report was done as part of Amendment 1 to Campus Cooperative Research and Development Agreement (CRADA) 356, the Transactive Campus CRADA with the Washington State Department of Commerce (Commerce) between the U.S. Department of Energy’s (DOE’s), Pacific Northwest National Laboratory (PNNL) and the Commerce through the Clean Energy Fund (CEF). The original project team consisted of PNNL, the University of Washington (UW) and Washington State University (WSU), to connect the PNNL, UW, and WSU campuses to construct and operate the testbed as both a regional flexibility resource and as a platform for research and development (R&D) for buildings/grid integration. Building on the foundational transactive system established by the Pacific Northwest Smart Grid Demonstration (PNWSGD), the purpose of the project was to construct the testbed as both a regional flexibility resource and as a platform for R&D on buildings/grid integration and information-based energy efficiency. The testbed supports the integration of renewables and other regional needs, using the flexibility provided by building loads, energy storage, and smart inverters for batteries and photovoltaic (PV) solar systems, at four physical scales: multiple campuses, campus, microgrid and building.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Proton Conducting Sulfonated Poly(Ionic Liquid) Block Copolymers

Herein, we report the synthesis of proton-conducting sulfonated poly(ionic liquid) block copolymers (S-PILBCPs) containing one block with sulfonic acid (sulfonated styrene, SS) and the other with an IL moiety (vinylbenzylmethylimidazolium bis(trifluoromethylsulfonyl)imide, VBMIm-TFSI) using reversible addition–fragmentation chain-transfer (RAFT) polymerization and post-polymerization modifications (i.e., functionalization, anion exchange reactions, and sulfonation). The S-PILBCPs uniquely conjoin the SS block with mobile protons (H + ) and the PIL block with mobile anions (TFSI – ), where multiple highly desired properties, including high proton conductivity (from the SS block), and high IL-philicity and oxygen solubility (from the PIL block) can exist compartmentally within a microphase separated morphology (evidenced by differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS)). High ion conductivity of 79.7 mS/cm at a PIL block composition of 21.6 mol % was observed at 80 °C and 90% relative humidity (RH) (comparable to the benchmark Nafion ionomer). This work successfully demonstrates the design of S-PILBCPs as a new material platform and showcases its promise as an ionomer for proton exchange membrane fuel cells (PEMFCs) as they simultaneously and compartmentally combine proton conductivity and oxygen solubility. Furthermore, these benefits have recently been leveraged to achieve substantial improvement in oxygen reduction reaction (ORR) activity and subsequently fuel cell performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Heterotrimetallic Mixed‐Valent Molecular Precursors Containing Periodic Table Neighbors: Assignment of Metal Positions and Oxidation States

Abstract A known trinuclear structure was used to design the heterobimetallic mixed‐valent, mixed‐ligand molecule [Co II (hfac) 3 −Na−Co III (acac) 3 ] ( 1 ). This was used as a template structure to develop heterotrimetallic molecules [Co II (hfac) 3 −Na−Fe III (acac) 3 ] ( 2 ) and [Ni II (hfac) 3 −Na−Co III (acac) 3 ] ( 3 ) via isovalent site‐specific substitution at either of the cobalt positions. Diffraction methods, synchrotron resonant diffraction, and multiple‐wavelength anomalous diffraction were applied beyond simple structural investigation to provide an unambiguous assignment of the positions and oxidation states for the periodic table neighbors in the heterometallic assemblies. Molecules of 2 and 3 are true heterotrimetallic rather than a statistical mixture of two heterobimetallic counterparts. Trinuclear platform 1 exhibits flexibility in accommodating a variety of di‐ and trivalent metals, which can be further utilized in the design of molecular precursors for the NaMM′O 4 functional oxide materials.

Han, Haixiang↗
DOE OSTI2025

Autonomous direct freeform fabrication strategy for multi-axis additive manufacturing

Multi-axis additive manufacturing (M-AM) enables precise material deposition along both planar and curved layers, eliminating the need for support structures through a continuous material deposition approach. In contrast to conventional 2-dimensional planar layers constrained to a fixed building orientation, the deposition on freeform layers demands the specification of guided curves to determine material deposition directions which are no longer to be fixed to a build direction. There are challenges that arise when fabricating components with multiple “build” directions, necessitating the decomposition of geometries and the specification of guided curves for the resulting volumes. Furthermore, multi-axis systems introduce heightened challenges due to an increased degree of freedom in motion. Consequently, the potential risks of collision between the deposited geometry and the motion platform become a notable concern. This research proposes a freeform layering algorithm to address the challenge of seamless transitions between planar and curved layers in the process planning of M-AM. The algorithm computes 3D “printable” layers by leveraging topological information derived from the geometry to be built and integrates collision-free manufacturability considerations into the computational process. These accumulated volumes serve as a “substrate” and support volumes for subsequent deposition, allowing later layers to be built without the need for additional support material. In conclusion, the proposed method successfully devises a freeform layering approach suitable for intricate models that demand substantial support, thus enabling the fabrication of diverse geometries in a manner previously unachievable.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electromagnetic response and emergent topological orders in transition metal dichalcogenide MoTe 2 bilayers

Twisted bilayer transition metal dichalcogenides, such as MoTe 2 , provide a versatile platform for exploring correlated topological phases. This work investigates the interplay between perpendicular magnetic and electric fields in tuning the electronic structure and emergent topological orders of twisted bilayer MoTe 2 (t-MoTe 2 ) across two distinct regimes: a low-twist-angle phase (θ ≈ 2.1°) hosting multiple Chern bands of identical Chern numbers per valley, and a higher-angle phase (θ ≈ 3.89°) featuring Haldane-like bands with opposite Chern numbers. Using a continuum model incorporating moiré potentials up to second harmonics, we compute the Hofstadter fractal spectra under applied fields, revealing Landau fan structures and magnetic-flux-dependent band topology. These fractal spectra are useful in studying emergent topological orders in terms of the composite fermion picture, where the statistical Chern-Simons flux is approximated as a uniform gauge field. We demonstrate that the system hosts both Jain-sequence fractional Chern insulators (FCIs) and non-Jain fractal FCIs with higher Chern numbers. As a result, the electric field suppresses composite fermion gaps and induces topological quantum phase transitions. Furthermore, our analysis extends to valley-contrasting flux attachment, proposing pathways to describe fractional quantum spin Hall states.

Anyons↗
DOE OSTI2022

Bicircular Light Floquet Engineering of Magnetic Symmetry and Topology and Its Application to the Dirac Semimetal Cd 3 As 2

Here, we show that bicircular light (BCL) is a versatile way to control magnetic symmetries and topology in materials. The electric field of BCL, which is a superposition of two circularly polarized light waves with frequencies that are integer multiples of each other, traces out a rose pattern in the polarization plane that can be chosen to break selective symmetries, including spatial inversion. Using a realistic low-energy model, we theoretically demonstrate that the three-dimensional Dirac semimetal Cd 3 As 2 is a promising platform for BCL Floquet engineering. Without strain, BCL irradiation induces a transition to a noncentrosymmetric magnetic Weyl semimetal phase with tunable energy separation between the Weyl nodes. In the presence of strain, we predict the emergence of a magnetic topological crystalline insulator with exotic unpinned surface Dirac states that are protected by a combination of twofold rotation and time reversal (2') and can be controlled by light.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

Qiu, Yin (ORCID:0009000900948794)↗
DOE OSTI2020

Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV)

The subject matter described herein includes a modular and extensible approach to integrate noisy measurements from multiple heterogeneous sensors that yield either absolute or relative observations at different and varying time intervals, and to provide smooth and globally consistent estimates of position in real time for autonomous flight. We describe the development of the algorithms and software architecture for a new 1.9 kg MAV platform equipped with an IMU, laser scanner, stereo cameras, pressure altimeter, magnetometer, and a GPS receiver, in which the state estimation and control are performed onboard on an Intel NUC 3rd generation i3 processor. We illustrate the robustness of our framework in large-scale, indoor-outdoor autonomous aerial navigation experiments involving traversals of over 440 meters at average speeds of 1.5 m/s with winds around 10 mph while entering and exiting buildings.

42 ENGINEERING↗
DOE OSTI2023

Magnetic Field-Stabilized Wigner Crystal States in a Graphene Moiré Superlattice

ABC-stacked trilayer graphene on boron nitride (ABC-TLG/hBN) moiré superlattices provides a tunable platform for exploring Wigner crystal states in which the electron correlation can be controlled by electric and magnetic fields. Here, in this work, we report the observation of magnetic field-stabilized Wigner crystal states in a ABC-TLG/hBN. We show that correlated insulating states emerge at multiple fractional and integer fillings corresponding to ν = 1/3, 2/3, 1, 4/3, 5/3, and 2 electrons per moiré lattice site under a magnetic field. These correlated insulating states can be attributed to generalized Mott states for the integer fillings and generalized Wigner crystal states for the fractional fillings. The generalized Wigner crystal states are stabilized by a vertical magnetic field and are strongest at one magnetic flux quantum per three moiré superlattices. The ν = 2 insulating state persists up to 30 T, which can be described by a Mott–Hofstadter transition at a high magnetic field.

77 NANOSCIENCE AND NANOTECHNOLOGY↗