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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗
DOE OSTI2020

Design and Development of a High-Efficiency Single Cylinder Natural Gas-Fueled Jet Ignition Engine

The current energy climate has created a push toward reducing consumption of fossil fuels and lowering emissions output in power generation applications. Combined with the desire for a more distributed energy grid, there is currently a need for small displacement, high efficiency engines for use in stationary power generation. An enabling technology for achieving high efficiencies with spark ignited engines for such applications is the use of jet ignition which enables ultra-lean (λ > ~1.6) combustion via air dilution.This paper provides a comprehensive review of the development of a 390cc, high efficiency single cylinder natural gas-fueled jet ignition engine operating ultra-lean. The engine was developed as part of the Department of Energy’s Advanced Research Projects Agency–Energy (DOE ARPA-E) GENSETS program. Design choices for minimizing friction are highlighted as well as test results showing further friction reduction through downspeeding. Extensive hardware optimization of the combustion system has been performed and results are presented for air-flow path optimization and the jet igniter. The efficiency benefits related to enleanment and downspeeding are analyzed using an efficiency loss breakdown based on the First Law of Thermodynamics. Through optimization efforts a peak brake thermal efficiency in excess of 34% was achieved, representing an increase of greater than 20% over the current state-of-the-industry for comparably sized CNG engines.

Peters, Nathan↗
DOE OSTI2021

Electron-beam energy reconstruction for neutrino oscillation measurements

Neutrinos exist in one of three types or ‘flavours’—electron, muon and tau neutrinos—and oscillate from one flavour to another when propagating through space. This phenomena is one of the few that cannot be described using the standard model of particle physics (reviewed in ref. 1), and so its experimental study can provide new insight into the nature of our Universe (reviewed in ref. 2). Neutrinos oscillate as a function of their propagation distance (L) divided by their energy (E). Therefore, experiments extract oscillation parameters by measuring their energy distribution at different locations. As accelerator-based oscillation experiments cannot directly measure E, the interpretation of these experiments relies heavily on phenomenological models of neutrino–nucleus interactions to infer E. Here we exploit the similarity of electron–nucleus and neutrino–nucleus interactions, and use electron scattering data with known beam energies to test energy reconstruction methods and interaction models. We find that even in simple interactions where no pions are detected, only a small fraction of events reconstruct to the correct incident energy. More importantly, widely used interaction models reproduce the reconstructed energy distribution only qualitatively and the quality of the reproduction varies strongly with beam energy. This shows both the need and the pathway to improve current models to meet the requirements of next-generation, high-precision experiments such as Hyper-Kamiokande (Japan) and DUNE (USA).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Cancer Incidence Trends in Successive Social Generations in the US

Importance: The incidence of some cancers in the US is increasing in younger age groups, but underlying trends in cancer patterns by birth year remain unclear. Objective: To estimate cancer incidence trends in successive social generations. Design, Setting, and Participants: In this cohort study, incident invasive cancers were ascertained from the Surveillance, Epidemiology, and End Results (SEER) program’s 13-registry database (November 2020 submission, accessed August 14, 2023). Invasive cancers diagnosed at ages 35 to 84 years during 1992 to 2018 within 152 strata were defined by cancer site, sex, and race and ethnicity. Exposure: Invasive cancer. Main Outcome and Measures: Stratum-specific semiparametric age-period-cohort (SAGE) models were fitted and incidence per 100 000 person-years at the reference age of 60 years was calculated for single-year birth cohorts from 1908 through 1983 (fitted cohort patterns [FCPs]). The FCPs and FCP incidence rate ratios (IRRs) were compared by site for Generation X (born between 1965 and 1980) and Baby Boomers (born between 1946 and 1964). Results: A total of 3.8 million individuals with invasive cancer (51.0% male; 8.6% Asian or Pacific Islander, 9.5% Hispanic, 10.4% non-Hispanic Black, and 71.5% non-Hispanic White) were included in the analysis. In Generation X vs Baby Boomers, FCP IRRs among women increased significantly for thyroid (2.76; 95% CI, 2.41-3.15), kidney (1.99; 95% CI, 1.70-2.32), rectal (1.84; 95% CI, 1.52-2.22), corpus uterine (1.75; 95% CI, 1.40-2.18), colon (1.56; 95% CI, 1.27-1.92), and pancreatic (1.39; 95% CI, 1.07-1.80) cancers; non-Hodgkins lymphoma (1.40; 95% CI, 1.08-1.82); and leukemia (1.27; 95% CI, 1.03-1.58). Among men, IRRs increased for thyroid (2.16; 95% CI, 1.87-2.50), kidney (2.14; 95% CI, 1.86-2.46), rectal (1.80; 95% CI, 1.52-2.12), colon (1.60; 95% CI, 1.32-1.94), and prostate (1.25; 95% CI, 1.03-1.52) cancers and leukemia (1.34; 95% CI, 1.08-1.66). Lung (IRR, 0.60; 95% CI, 0.50-0.72) and cervical (IRR, 0.71; 95% CI, 0.57-0.89) cancer incidence decreased among women, and lung (IRR, 0.51; 95% CI, 0.43-0.60), liver (IRR, 0.76; 95% CI, 0.63-0.91), and gallbladder (IRR, 0.85; 95% CI, 0.72-1.00) cancer and non-Hodgkins lymphoma (IRR, 0.75; 95% CI, 0.61-0.93) incidence decreased among men. For all cancers combined, FCPs were higher in Generation X than for Baby Boomers because gaining cancers numerically overtook falling cancers in all groups except Asian or Pacific Islander men. Conclusions and Relevance: In this model-based cohort analysis of incident invasive cancer in the general population, decreases in lung and cervical cancers in Generation X may be offset by gains at other sites. Generation X may be experiencing larger per-capita increases in the incidence of leading cancers than any prior generation born in 1908 through 1964. On current trajectories, cancer incidence could remain high for decades.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Ultradoping Boron on Si(100) via Solvothermal Chemistry

Ultradoping introduces unprecedented dopant levels into Si, which transforms its electronic behavior and enables its use as a next-generation electronic material. Commercialization of ultradoping is currently limited by gas-phase ultra-high vacuum requirements. Solvothermal chemistry is amenable to scale-up. However, an integral part of ultradoping is a direct chemical bond between dopants and Si, and solvothermal dopant-Si surface reactions are not well-developed. This work provides the first quantified demonstration of achieving ultradoping concentrations of boron (~1e14 cm 2 ) by using a solvothermal process. Surface characterizations indicate the catalyst cross-reacted, which led to multiple surface products and caused ambiguity in experimental confirmation of direct surface attachment. Density functional theory computations elucidate that the reaction results in direct B-Si surface bonds. Finally, this proof-of-principle work lays groundwork for emerging solvothermal ultradoping processes.

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

ppdx : Automated modeling of protein–protein interaction descriptors for use with machine learning

This paper describes ppdx, a python workflow tool that combines protein sequence alignment, homology modeling, and structural refinement, to compute a broad array of descriptors for characterizing protein–protein interactions. The descriptors can be used to predict various properties of interest, such as protein–protein binding affinities, or inhibitory concentrations (IC 50 ), using approaches that range from simple regression to more complex machine learning models. The software is highly modular. It supports different protocols for generating structures, and 95 descriptors can be currently computed. More protocols and descriptors can be easily added. The implementation is highly parallel and can fully exploit the available cores in a single workstation, or multiple nodes on a supercomputer, allowing many systems to be analyzed simultaneously. As an illustrative application, ppdx is used to parametrize a model that predicts the IC 50 of a set of antigens and a class of antibodies directed to the influenza hemagglutinin stalk.

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

Riverine bacterioplankton and phytoplankton assembly along an environmental gradient induced by urbanization

In the Anthropocene, human activities are intensifying stresses on biological communities across ecosystems. Knowledge on how environmental changes influence microbial community dynamics is crucial but currently limited. Here we unraveled ecological processes generating distribution patterns of bacterioplankton and phytoplankton communities in a river draining an urbanizing watershed in southern China. In this ecosystem, longitudinal environmental heterogeneity and directional flow potentially have counteracting effects on planktonic community assembly. Using simultaneously multiple approaches, we showed that the observed compositional patterns result from an interplay of stochastic and deterministic processes, indicating that dispersal via fluvial connectivity could not override local selective pressures. Successional shifts in the relative importance of the above processes were associated with trends in climatic factors. High diversity was observed at the intermediate levels of ecological processes alongside intense inter-species interactions maintained by a few keystone taxa. Altogether, interactions between climatic conditions, landscape and hydrology control plankton community dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Atomically Dispersed Ni‐N‐C Catalysts for Electrochemical CO 2 Reduction

Abstract The atomic dispersion of nickel in Ni‐N‐C catalysts is key for the selective generation of carbon monoxide through the electrochemical carbon dioxide reduction reaction (CO 2 RR). Herein, the study reports a highly selective, atomically dispersed Ni 1.0% ‐N‐C catalyst with reduced Ni loading compared to previous reports. Extensive materials characterization fails to detect Ni crystalline phases, reveals the highest concentration of atomically dispersed Ni metal, and confirms the presence of the proposed Ni‐N x active site at this reduced loading. The catalyst shows excellent activity and selectivity toward CO generation, with a faradaic efficiency for CO generation (FE CO ) of 97% and partial current density for CO (j co ) of ‐9.0 mA cm −2 at ‐0.9 V in an electrochemical H‐type cell. CO 2 RR activity and selectivity are also studied by rotating disk electrode (RDE) measurements where transport limitations can be suppressed. It is expected that the utility of these Ni‐N‐C catalysts will lie with tandem CO 2 RR reaction schemes to multi‐carbon (C 2+ ) products.

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

Moving small files in a networked environment

Globally distributed computing infrastructures, such as clouds and supercomputers, are currently used to manage data that is generated with an unprecedented speed from a variety of resources. Coping with this trend, the volume of data exchanged across distant sites increases substantially. To accelerate data transfer, high-speed networks are provided to connect remote sites. Most existing data movement solutions are optimized for moving large files. However, it is still challenging to transfer a large number of small files across networks. This disadvantage not only lowers data transfer performance, but also decreases overall system utilization. Here, we identify that moving small files is mainly constrained by degraded file system throughput, not just network performance as might be suspected. We have built a data transfer pipeline model to analyze the impact of small network I/O and storage I/O on data movement. Extending one of the widely used open source data movement solutions, GridFTP, we demonstrate several appropriate engineering approaches that mitigate the bottleneck and increase data transfer efficiency. We show optimizations that improve data transfer performance more than 5 times. In comparison to existing solutions, our approaches can save a significant amount of system resources for moving lots of small files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Energetics of oxidation and formation of uranium mononitride

Uranium mononitride (UN) is an advanced nuclear fuel currently being considered for use in several generation IV fast and thermal neutron spectrum core designs, with additional applications to thermal and electric nuclear propulsion reactors. Here, to better understand the thermal behavior and thermodynamic stability of UN, we investigated the bulk thermal oxidation process and thermochemical reactions, including the enthalpy of oxidation and standard enthalpy of formation, by conducting thermalgravimetric analysis – differential scanning calorimetry coupled with mass spectrometry (TGA-DSC-MS), and high temperature transposed temperature drop and oxide melt drop solution calorimetry. The bulk oxidation of UN (containing a small amount of α-UN 1.5+x ) in air was found to follow a step-wise process characterized by consecutive oxidative reactions UN-UN 1.5+x -UO 2 → UO 2 -UO 3 —N k → UO 3 —N k → UO 3 → U 3 O 8 . TGA results support that the UO 2 – U 2 N 3+x passivating layer delays the onset of rapid bulk oxidation of UN in air up to 662 K. Synchrotron X-ray diffraction (XRD) and extended X-ray absorption fine structure (EXAFS) analyses were performed to characterize UN and its final oxidized product. The standard enthalpy of formation (ΔH° f ) of UN was determined to be –144.4 ± 5.9 kJ/mol·atom, in good agreement with previously determined values from Pt encapsulation and bomb calorimetric experiments. Lastly, a negative linear correlation between ΔH° f and the N/U molar ratio was established based on the thermochemical data obtained in this work and previously reported enthalpies of formations of β-UN 1.5-x and α-UN 1.5+x .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Disposition of Solids from Hydrothermal Liquefaction of Biomass: Current Understanding, Research Gaps, and Opportunities

Characteristics of solid residuals generated during hydrothermal liquefaction (HTL) of biomass are reported to establish disposition options for these residuals to reduce liability or barriers to commercialization of HTL. HTL solids from pilot scale are reported and compared to existing HTL solids literature for a variety of biomass feedstocks and HTL configurations, noting differences among literature HTL solids due to solids collection methods. Reported analyses include CHNOS, moisture, ash, inorganics by Inductively Coupled Plasma (ICP), and High Heating Value (HHV). HTL solids are determined to be substantially compatible with U.S. Environmental Protection Agency (EPA) disposal regulations within existing data. Disposition and valorization routes are identified, yet combustion as valorization is determined to be not economically beneficial. Further, research gaps are identified, which include the need for future research to be performed on HTL solids that are representative of a continuous, commercializable flowsheet; verification that specific HTL solids meet EPA disposal requirements; exploration of valorization options; and the need for invention of continuous HTL solids separations/management.

09 BIOMASS FUELS↗
DOE OSTI2021

Visualizing the strongly reshaped skyrmion Hall effect in multilayer wire devices

Magnetic skyrmions are nanoscale spin textures touted as next-generation computing elements. When subjected to lateral currents, skyrmions move at considerable speeds. Their topological charge results in an additional transverse deflection known as the skyrmion Hall effect (SkHE). While promising, their dynamic phenomenology with current, skyrmion size, geometric effects and disorder remain to be established. Here we report on the ensemble dynamics of individual skyrmions forming dense arrays in Pt/Co/MgO wires by examining over 20,000 instances of motion across currents and fields. The skyrmion speed reaches 24 m/s in the plastic flow regime and is surprisingly robust to positional and size variations. Meanwhile, the SkHE saturates at ~22 ° , is substantially reshaped by the wire edge, and crucially increases weakly with skyrmion size. Particle model simulations suggest that the SkHE size dependence - contrary to analytical predictions - arises from the interplay of intrinsic and pinning-driven effects. These results establish a robust framework to harness SkHE and achieve high-throughput skyrmion motion in wire devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electrostatically controlled spin polarization in Graphene-CrSBr magnetic proximity heterostructures

Abstract The magnetic proximity effect can induce a spin dependent exchange shift in the band structure of graphene. This produces a magnetization and a spin polarization of the electron/hole carriers in this material, paving the way for its use as an active component in spintronics devices. The electrostatic control of this spin polarization in graphene has however never been demonstrated so far. We show that interfacing graphene with the van der Waals antiferromagnet CrSBr results in an unconventional manifestation of the quantum Hall effect, which can be attributed to the presence of counterflowing spin-polarized edge channels originating from the spin-dependent exchange shift in graphene. We extract an exchange shift ranging from 27 – 32 meV, and show that it also produces an electrostatically tunable spin polarization of the electron/hole carriers in graphene ranging from − 50% to + 69% in the absence of a magnetic field. This proof of principle provides a starting point for the use of graphene as an electrostatically tunable source of spin current and could allow this system to generate a large magnetoresistance in gate tunable spin valve devices.

Science & Technology - Other Topics↗
DOE OSTI2026

Dynamic magneto-chiral instability in photoexcited tellurium

In systems of charged chiral fermions out of equilibrium, an electric current parallel to a magnetic field can generate a dynamic instability that amplifies electromagnetic waves. Whether this mechanism also operates in chiral solid-state systems has remained uncertain. Here we observe signatures of a dynamic magneto-chiral instability in elemental tellurium, a structurally chiral crystal, using time-domain terahertz emission spectroscopy. Under transient photoexcitation in a moderate magnetic field, we observe terahertz radiation with coherent modes that grow in amplitude over time. We present a theoretical model that describes this behaviour based on a dynamic instability of electromagnetic waves interacting with infrared-active oscillators of acceptor states in tellurium, giving rise to an amplifying polariton. These results demonstrate that magneto-chiral instabilities can emerge in solid-state systems and establish a mechanism for terahertz-wave amplification in chiral materials.

42 ENGINEERING↗
DOE OSTI2022

Lossy compression of statistical data using quantum annealer

Abstract We present a new lossy compression algorithm for statistical floating-point data through a representation learning with binary variables. The algorithm finds a set of basis vectors and their binary coefficients that precisely reconstruct the original data. The optimization for the basis vectors is performed classically, while binary coefficients are retrieved through both simulated and quantum annealing for comparison. A bias correction procedure is also presented to estimate and eliminate the error and bias introduced from the inexact reconstruction of the lossy compression for statistical data analyses. The compression algorithm is demonstrated on two different datasets of lattice quantum chromodynamics simulations. The results obtained using simulated annealing show 3–3.5 times better compression performance than the algorithm based on neural-network autoencoder. Calculations using quantum annealing also show promising results, but performance is limited by the integrated control error of the quantum processing unit, which yields large uncertainties in the biases and coupling parameters. Hardware comparison is further studied between the previous generation D-Wave 2000Q and the current D-Wave Advantage system. Our study shows that the Advantage system is more likely to obtain low-energy solutions for the problems than the 2000Q.

97 MATHEMATICS AND COMPUTING↗