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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Emissions minimization on road networks via Generic Second Order Models

In this paper we consider the problem of estimating emissions due to vehicular traffic on complex networks, and minimizing their effect by regulating traffic at junctions. For the traffic evolution, we consider a Generic Second Order Model, which encompasses the majority of two-equations (i.e., second-order) models available in the literature, and extend it to road networks with merge and diverge junctions. The dynamics on the whole network is determined by selecting a solution to the Riemann Problems at junctions, i.e., the Cauchy problems with constant initial data on each incident road. The latter are solved by assuming the maximization of the flow and assigning a traffic distribution coefficient for outgoing roads of diverges, and a priority rule for incoming roads of merges. A general emission model is considered and its parameters are tuned to the $ {\mathrm{NO_{x}}} $ emission rate. The minimization of emissions is then formulated in terms of the traffic distribution and priority parameters, taking into account travel times. A comparison is provided between roundabouts with optimized parameters and traffic lights, which correspond to time-varying traffic priorities. Our approach can be adapted to manage traffic in complex networks in order to reduce emissions while keeping travel time at acceptable levels.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Ultrafast Dynamics of Photosynthetic Light Harvesting: Strategies for Acclimation Across Organisms

Photosynthetic light harvesting exhibits near-unity quantum efficiency. The high efficiency is achieved through a series of energy and charge transfer steps within a network of pigment-containing proteins. Remarkably, high efficiency is conserved across many organisms despite differences in the protein structures and organization that allow each organism to respond to its own biological niche and the stressors within. In this review, we highlight recent progress toward understanding how organisms maintain optimal light-harvesting ability by acclimating to their environment. First, we review the building blocks of photosynthetic light harvesting, energy transfer, and time-resolved spectroscopic techniques. Then, we explore how three classes of photosynthetic organisms—purple bacteria, cyanobacteria, and green plants—optimize their light-harvesting apparatuses to their particular environment. Overall, research has shown that photosynthetic energy transfer is robust to changing environmental conditions, with each organism utilizing its own strategies to optimize photon capture in its particular biological niche.

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

Qualitative and quantitative analysis of neutron irradiation effects in SiC/SiC composites using X-ray computed tomography

Silicon carbide fiber-reinforced silicon carbide matrix (SiC/SiC) composites are candidate materials for cladding of light water reactor (LWR) fuels. Loss of fission product gas retention due to the formation of microcrack networks is considered a potential failure mechanism for SiC/SiC-cladded fuels. In this work, a variety of SiC/SiC composite tubes were irradiated with and without an LWR-relevant radial heat flux in the High Flux Isotope Reactor, followed by detailed characterization with X-ray computed tomography (XCT). This first set of XCT data for neutron-irradiated samples confirmed that the internal stresses arising from a combination of temperature gradients and irradiation-induced swelling act as the primary driver for cracking. Consequently, while the observed cracking patterns varied depending on the tube architectures, the sharp edges of relatively large pores were found to be the common stress concentrator. These findings are useful to help improve the design and manufacturing of SiC/SiC fuel claddings for reduced failure probability.

42 ENGINEERING↗
DOE OSTI2020

Microbial Communities Associated with Methylmercury Degradation in Paddy Soils

Bioaccumulation of the neurotoxin methylmercury (MeHg) in rice has raised worldwide concerns because of its risks to human health. Certain microorganisms are able to degrade MeHg in pure cultures, but the roles and diversities of the microbial communities in MeHg degradation in rice paddy soils are unknown. Using a series of microcosms, we investigated MeHg degradation in paddy soils from Hunan, Guizhou, and Hubei provinces, representing three major rice production regions in China, and further characterized one of the soils from the Hunan Province for microbial communities associated with MeHg degradation. Microbial demethylation was observed in all three soils, demonstrated by significantly more MeHg degraded in the unsterilized soils than in the sterilized controls. More demethylation occurred in water-saturated soils than in unsaturated soils, but the addition of molybdate and bromoethanesulfonic acid as the respective inhibitors of sulfate reducing bacteria and methanogens showed insignificant effects on MeHg degradation. However, the addition of Cu enhanced MeHg degradation and the enrichment of Xanthomonadaceae in the unsaturated soil. 16S rRNA Illumina sequencing and metatranscriptomic analyses of the Hunan soil consistently revealed that Catenulisporaceae, Frankiaceae, Mycobacteriaceae, and Thermomonosporaceae were among the most likely microbial taxa in influencing MeHg degradation in the paddy soil, and they were confirmed by combined analyses of the co-occurrence network, random forest modeling, and linear discriminant analysis of the effect size. Furthermore, our results shed additional light onto the roles of microbial communities in MeHg degradation in paddy soils and its subsequent bioaccumulation in rice grains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Metalloprotein catalysis: structural and mechanistic insights into oxidoreductases from neutron protein crystallography

Metalloproteins catalyze a range of reactions, with enhanced chemical functionality due to their metal cofactor. The reaction mechanisms of metalloproteins have been experimentally characterized by spectroscopy, macromolecular crystallography and cryo-electron microscopy. An important caveat in structural studies of metalloproteins remains the artefacts that can be introduced by radiation damage. Photoreduction, radiolysis and ionization deriving from the electromagnetic beam used to probe the structure complicate structural and mechanistic interpretation. Neutron protein diffraction remains the only structural probe that leaves protein samples devoid of radiation damage, even when data are collected at room temperature. Additionally, neutron protein crystallography provides information on the positions of light atoms such as hydrogen and deuterium, allowing the characterization of protonation states and hydrogen-bonding networks. Neutron protein crystallography has further been used in conjunction with experimental and computational techniques to gain insight into the structures and reaction mechanisms of several transition-state metal oxidoreductases with iron, copper and manganese cofactors. Here, the contribution of neutron protein crystallography towards elucidating the reaction mechanism of metalloproteins is reviewed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optimal Economic Dispatch and Load-Following Strategies for Nuclear Integrated Energy Systems

The need for distributed and adaptable energy resources that can handle the growing unpredictability in both supply and demand is rising as the power system continues to modernize. In order to satisfy those needs and maintain grid resilience, nuclear power plants can dynamically control their output, despite typically being used as baseload generators. By incorporating energy storage and renewable energy sources, nuclear integrated energy systems are designed to satisfy the electrical and thermal demands of different end-user applications while ensuring flexible power operation. These systems generate revenue by participating in both wholesale and ancillary services electricity markets, as well as commodity markets for various byproducts generated from coupled industrial processes. This study addresses the economic dispatch efficiency of a tightly coupled nuclear integrated energy system comprising a gigawatt-scale light water reactor, commercialized in the U.S., a high-temperature steam electrolysis unit, a district heating network, and specified electrical loads. To demonstrate the nuclear power plant’s flexibility within the day-ahead unit commitment and economic dispatch framework, while maintaining equilibrium even during periods of refueling outages, this paper develops a mixed-integer linear programming framework that models the subsystems and components of its nuclear steam supply system. A systematic comparative analysis of flexible versus baseload nuclear power plant operation under varying levels of renewable energy integration indicates that flexible operation enhances system profitability by more than 18% while also increasing energy storage utilization, improving reactor responsiveness to load fluctuations, and allowing for greater participation across numerous electricity markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Network construction of non-Abelian chiral spin liquids

We use a network of chiral junctions to construct a family of topological chiral spin liquids in two spatial dimensions. The chiral spin liquid phase harbors SU(2) _k k anyons, which stem from the underlying SU(2) _k k WZW models that describe the constituent spin chains of the network. The network exhibits quantized spin and thermal Hall conductances. We illustrate our construction by inspecting the topological properties of the SU(2) _2 2 model. We find that this model has emergent Ising anyons, with spinons acting as vortex excitations that bind Majorana zero modes. We also show that the ground state of this network is threefold degenerate on the torus, asserting its non-Abelian character. Our results shed new light on the stability of non-Abelian topological phases in artificial quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Coherent control of strongly interacting spins in the solid-state

The major goal of this project is to develop coherent interacting spin systems in the solid state, based on rare earth ions. By leveraging the ability to controllably incorporate rare earth ions such as Er into a solid-state host, and maintain individual-ion addressability below the diffraction limit based on inhomogeneous broadening, we aim to create strongly interacting electron spin clusters with individual-site control. Performing spectroscopy of these strongly interacting systems will shed light on their fundamental properties, as well as enable applications to quantum information science, in particular quantum networks that are also enabled by a telecom-band spin-photon interface in Er.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Disk Evolution Study through Imaging of Nearby Young Stars (DESTINYS): A Panchromatic View of DO Tau’s Complex Kilo-astronomical-unit Environment

While protoplanetary disks are often treated as isolated systems in planet formation models, observations increasingly suggest that vigorous interactions between Class II disks and their environments are not rare. DO Tau is a T Tauri star that has previously been hypothesized to have undergone a close encounter with the HV Tau system. As part of the DESTINYS ESO Large Programme, we present new Very Large Telescope (VLT)/SPHERE polarimetric observations of DO Tau and combine them with archival Hubble Space Telescope (HST) scattered-light images and Atacama Large Millimeter/submillimeter Array (ALMA) observations of CO isotopologues and CS to map a network of complex structures. The SPHERE and ALMA observations show that the circumstellar disk is connected to arms extending out to several hundred astronomical units. HST and ALMA also reveal stream-like structures northeast of DO Tau, some of which are at least several thousand astronomical units long. These streams appear not to be gravitationally bound to DO Tau, and comparisons with previous Herschel far-IR observations suggest that the streams are part of a bridge-like structure connecting DO Tau and HV Tau. We also detect a fainter redshifted counterpart to a previously known blueshifted CO outflow. While some of DO Tau's complex structures could be attributed to a recent disk–disk encounter, they might be explained alternatively by interactions with remnant material from the star formation process. These panchromatic observations of DO Tau highlight the need to contextualize the evolution of Class II disks by examining processes occurring over a wide range of size scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Results from an International Interlaboratory Study on Light- and Elevated Temperature-Induced Degradation (LETID) in Solar Modules

This presentation reports recently submitted results from an international interlaboratory comparison study on light- and elevated temperature-induced degradation (LETID) on crystalline silicon photovoltaic (PV) modules. A large global network of PV module manufacturers and PV testing laboratories collaborated to design a protocol for LETID detection, and screen a large and diverse set of prototype modules for LETID. We summarize the range of observed degradation and provide initial conclusions on the reproducibility of results across labs. In LETID-sensitive modules, both open-circuit voltage (VOC) and short-circuit current (ISC) degrade by a roughly similar magnitude. We observe, as do previous studies, that LETID affects each cell in a module differently. An investigation of the potential mismatch losses caused by nonuniform LETID degradation found that mismatch loss is insignificant compared to the direct LETID-related losses. We summarize the conclusions drawn from the study, provide an update on a forthcoming standard technical specification for LETID testing of PV modules (IEC TS 63342 ED1), and discuss unresolved questions and potential future work on LETID in PV modules.

degradation↗
DOE OSTI2024

Nonlinear encoding in diffractive information processing using linear optical materials

Nonlinear encoding of optical information can be achieved using various forms of data representation. Here, we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks. For a comprehensive evaluation, we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve, e.g., phase encoding, against data repetition-based nonlinear encoding strategies. We show that data repetition within a diffractive volume (e.g., through an optical cavity or cascaded introduction of the input data) causes the loss of the universal linear transformation capability of a diffractive optical processor. Therefore, data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks. However, they can still be effectively trained for specific inference tasks and achieve enhanced accuracy, benefiting from the nonlinear encoding of the input information. Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors. Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.

42 ENGINEERING↗
DOE OSTI2024

Hydrogen-induced tunable remanent polarization in a perovskite nickelate

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO 3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanometal-Interconnected Carbon Conductors (NICCS) for Advanced Electric Machines (RIT Final Technical Report)

Recent advancements in carbon nanotube (CNT) research have enabled lightweight, conductive wires as a transformative technology. Metal-carbon nanotube (CNT) hybrid conductors aim to combine the high conductivity of traditional metals with the low mass and temperature coefficient of resistance (TCR) of carbon nanotubes. The high conductivity of copper makes it a promising candidate to combine with CNTs in a hybrid structure, but there is limited physical and electrical interaction between copper and CNTs. The use of an interfacial layer offers one method of improving the interconnection of a Cu-CNT hybrid conductor. Over the course of this grant, a joule heating-driven chemical vapor deposition (CVD) technique was developed to deposit nanometal seeds throughout a porous, low-density (0.12 g/cm 3 , ~10 tex or mg/m) CNT roving template. Modification of the applied current to the CNT roving allows for the tuning of depositions towards either hot-spot site-specificity or overall uniformity. The effects of temperature, pressure, precursor mass, and the interval of applied current were investigated, demonstrating nanometal depositions ranging from less than 5 % w/w to over 85 % w/w. The versatility of CVD allows for a wide variety of metals to be deposited including copper, titanium, nickel, silver, tungsten, palladium, platinum, ruthenium, rhodium, and iridium. One preferred demonstration involved using platinum depositions to improve the electrical properties of metal-seeded CNTs across all mass loadings studied. Moreover, when the metal-seeded CNT wires were electroplated with copper, densified, and annealed under hydrogen/argon; the result was a Cu-CNT hybrid conductor with the highest conductivities reported to date. The good interconnection of the metal and CNT portions results in a stable conductor. An electrical conductivity of 16-20 MS/m was achieved for multiple Cu-CNT hybrid conductors at 150 °C, which exceeds the program goal for conductivity of greater than 15 MS/m for a 1 m long CNT wire. Overall, the research outcomes from the project showed improvements in CNT wire fabrication from roll-to-roll CVD grown carbon nanotube wires using nanometal interconnects to bridge CNT-to-CNT junctions, thus mitigating network contact resistances. Advanced nanometal interconnected carbon conductors (NICCs) were developed as a means to achieve novel light-weight wiring appropriate for applications that require the conductivity of metallic (i.e., Cu, Al, etc.) wires at elevated temperatures. High conductivity, low TCR electrical conductors such as the nanometal interconnected Cu-CNT hybrids have numerous future applications towards high efficiency motors, generators, and transformers. Specifically, the advanced wires have the ability to operate at lower resistance during conditions for standard electric motors at 150 °C, which would improve the electrical efficiency while lowering energy needs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Exploratory Approach Using Regression and Machine Learning in the Analysis of Mass Absorption Cross Section of Black Carbon Aerosols: Model Development and Evaluation

Mass absorption cross-section of black carbon (MAC BC ) describes the absorptive cross-section per unit mass of black carbon, and is, thus, an essential parameter to estimate the radiative forcing of black carbon. Many studies have sought to estimate MAC BC from a theoretical perspective, but these studies require the knowledge of a set of aerosol properties, which are difficult and/or labor-intensive to measure. We therefore investigate the ability of seven data analytical approaches (including different multivariate regressions, support vector machine, and neural networks) in predicting MAC BC for both ambient and biomass burning measurements. Our model utilizes multi-wavelength light absorption and scattering as well as the aerosol size distributions as input variables to predict MAC BC across different wavelengths. We assessed the applicability of the proposed approaches in estimating MAC BC using different statistical metrics (such as coefficient of determination (R 2 ), mean square error (MSE), fractional error, and fractional bias). Overall, the approaches used in this study can estimate MAC BC appropriately, but the prediction performance varies across approaches and atmospheric environments. Based on an uncertainty evaluation of our models and the empirical and theoretical approaches to predict MAC BC , we preliminarily put forth support vector machine (SVM) as a recommended data analytical technique for use. We provide an operational tool built with the approaches presented in this paper to facilitate this procedure for future users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Detecting Low-level Radiation Sources Using Border Monitoring Gamma Sensors

We consider a problem of detecting a low-level radiation source using a network of Gamma spectral sensors placed on the periphery of a monitored region. We propose a computationally light-weight, correlation-based method which is primarily intended for systems with limited computing capacity. Sensor measurements are combined at the fusion by first generating decisions at each time step and then taking their majority vote within a time widow. At each time step, decisions are generated using two strategies: (i) SUM method based on a threshold decision on a correlation statistic derived from measurements from all sensors, and (ii) OR method based on logical-OR of threshold decisions based on correlations statistics of individual sensor measurements. We derive analytical performance bounds for false alarm rates of SUM and OR methods, and show that their performance is enhanced by the temporal smoothing of majority vote within a time window. Using measurements from a test campaign, we generate a border monitoring scenario with twelve 2"x2" NaI Gamma sensors deployed on the periphery of 42m x 42m outdoor region. A Cs-137 source is moved in a straight-line across this region, starting several meters outside and finally moving away from it. We illustrate the performance of both correlation-based detection methods, and compare their performances with each other and with a particle filter method. Overall, under small false-alarm conditions, the OR fusion is found to produce better detection performance.

Sen, Satyabrata↗
DOE OSTI2021

Stripping away ion hydration shells in electrical double-layer formation: Water networks matter

Significance For centuries the double layer at the solid/electrolyte interface has been a central concept in electrochemistry. Today, it is still crucial for virtually all renewable energy storage and conversion technologies. Here, the double-layer formation is probed by THz spectroscopy with ultrabright synchrotron light as a source. Our results capture the molecular details of double-layer formation at positively/negatively charged Au electrodes for an NaCl electrolyte. We reveal a contrasting response applying positive versus negative bias, which is dictated by the interfacial water network and rationalized by accompanying molecular dynamics simulations and electronic-structure calculations. While Na + is directly attracted toward the negatively charged electrode, stripping of the Cl − hydration shell is observed only at larger potential values.

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

Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network

The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within ±1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.

43 PARTICLE ACCELERATORS↗