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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
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.

Utaegbulam, Hilary↗
DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗
DOE OSTI2023

Making coordination networks ionic: a unique strategy to achieve solution-processable hybrid semiconductors

The development of high-performance, solution-processable semiconducting materials is crucial for the advancement of emerging clean-energy technologies such as light-emitting diodes and photovoltaics. While hybrid perovskites have shown considerable promise for implementation in these technologies, their reliance on toxic metals and relatively low stability towards moisture and chemical environments remain to be addressed. In this Chemistry Frontiers article, we describe a unique strategy to build nontoxic, robust and solution-processable hybrid semiconductors based on copper halide by incorporating ionic bonds in coordination complexes (molecular or extended network structures). Specifically, these compounds are made of anionic copper(I) halide and cationic organic ligands that form both coordinate and ionic bonds at the inorganic/organic interfaces and are referred to as all-in-one (AIO)-type structures. Here, the unique bonding nature renders the AIO-type structures with greatly enhanced solubility, excellent optical tunability and remarkable framework stability, all highly desirable for thin-film based optoelectronic devices. We will highlight the most recent progress in the development of this material group, including their design strategies, important properties and potential for clean-energy related applications. We will also briefly discuss the existing challenges and future outlook of these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Reactive Extrusion of Waste Plastics with Compatibilizer and Lightly Pyrolyzed Crumb Rubber for Asphalt Modification

Modifying asphalt is a potentially high-value application for reusing waste plastics because of the high-volume usage of asphalt in highway construction. However, simply blending hot plastics and asphalt encounters difficulties related to the poor solubility of polymers, which limits the formation of a swollen network with asphalt molecules. The polymer phases also tend to coalesce and separate from asphalt during high-temperature storage in static conditions. The present study developed an innovative process to stabilize waste plastics in asphalt and improve binder storage stability by using lightly pyrolyzed crumb rubber together with a chemical compatibilizer. Both polymers were extruded to produce a thermoplastic elastomer (TPE) for asphalt modification. The mechanical performance and chemical reactions of TPEs were characterized via tension test and Fourier transform infrared spectroscopy. The storage stability and rheological properties of modified binder blends were evaluated through laboratory asphalt stability test and dynamic shear rheometer test. Polymer phases and network structures were characterized through optical microscopy. It was found that the pyrolyzed and reactive extrusion process improved the rubber solubility and polymer interaction, and therefore the storage stability of modified binder blends. The co-existence of rigid plastic and soft rubbery regimes in an entangled network provided a promising pathway to improve the mechanical performance of asphalt binders in both high- and low-temperature domains.

Ma, Yuetan↗
DOE OSTI2021

Spatial Mode Correction of Single Photons Using Machine Learning

Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Understanding the surface wave characteristics using 2D particle-in-cell simulation and deep neural network

Here, the characteristics of the surface waves along the interface between a plasma and a dielectric material have been investigated using kinetic particle-in-cell simulations. A microwave source of GHz frequency has been used to trigger the surface wave in the system. The outcome indicates that the surface wave gets excited along the interface of plasma and the dielectric tube and appears as light and dark patterns in the electric field profiles. The dependency of radiation pressure on the dielectric permittivity and supplied input frequency has been investigated. Further, we assessed the capabilities of neural networks to predict the radiation pressure for a given system. The proposed deep neural network model is aimed at developing accurate and efficient data-driven plasma surface wave devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

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

Cultural Shifts in High Energy Physics Collaboration from the Cold War to the Present: A Historical and Philosophical Perspective

Here, this article employs empirical history and the philosophy of science to study cultural convergences and divergences in international collaborations in high energy physics. We examine two cases: (1) E-36, an experiment on small angle proton-proton scattering conducted during the Cold War at the National Accelerator Laboratory (NAL) in the USA by Soviet and US scientists and (2) an ongoing collaborative experiment, NICA, at the Joint Institute for Nuclear Research (JINR, Dubna), which is a project devoted to heavy-ion physics. The JINR, particularly its Laboratory of High Energy Physics (formerly the “Laboratory of High Energies”) is the main mediating actor between these two cases (i.e., E-36 and NICA), as the majority of Soviet participants in E-36 were representatives of the Institute. Using empirical data collected through archival searches, field observations conducted at JINR in 2018–2019, and in-depth interviews, we tell a story of cultural differences in high energy physics by applying the concepts of ‘trading zones’ (P. Galison) and the translation of interests in actor-networks (B. Latour, M. Callon and others). We analyze three types of cultural diversity (specialization, nationality, and generational) in light of the implications of temporal context and the dichotomy between East and West, showing the roles cultural diversity plays in scientific collaboration (which is an integral part of as well as obstacle to scientific research that can nevertheless provide learning opportunities). Our study aims to demonstrate how disunity and diversity may function in scientific research and how high energy physics collaborations can remain productive despite sometimes deep divergences, including those between East and West.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

On an Extensive Late Hydrologic Event in Gale Crater as Indicated by Water‐Rich Fracture Halos

Abstract We analyze spatially pervasive, light‐toned “halos” associated with fractures in a sedimentary unit (Stimson) of Gale crater, Mars, and report a similar network of halos discovered in a separate geologic group (Bradbury). Through a dedicated active neutron measurement campaign, we provide independent confirmation of the water‐rich nature of these features. Together with mineralogical and geochemical data, these features are consistent with abundant hydrated amorphous silica (opal‐A). We suggest that the mineral and amorphous assemblages are indicative of formation under low‐temperature and predominantly low‐pH conditions (passive silica enrichment) with minor contribution of silica (active silica enrichment) from adjacent units. We show that there is significant amorphous silica in the array of sedimentary rocks in Gale crater, allowing them to play a role in an active silica enrichment phase of halo formation. We suggest that the involved alteration event was short lived and our finding of vast halo networks in a distant, older unit implies a more vast network of hydrologic subsurface conduits than previously known. This relatively recent subsurface hydrologic system was present long after the transition from a warm and wet to a cold and dry Martian environment, extending the habitability conditions on Mars to an epoch that is generally considered not favorable for life on the surface. Finally, our bulk H quantification of these features, which ranges from ∼3–6 wt% H 2 O‐equivalent‐H, suggests that the amorphous material in halos hosts ample supplies of readily released water, making them a considerable resource at the otherwise dry Martian equator.

Gabriel, Travis S. J.↗
DOE OSTI2021

Leveraging In-Network Computing and Programmable Switches for Streaming Analysis of Scientific Data

With the emergence of programmable network devices that match the performance of fixed function devices, several recent projects have explored in-network computing, where the processing that is traditionally done outside the network is offloaded to the network devices. In-network computing has typically been applied to network functions (e.g., load balancing, NAT, and DNS), caching, data reduction/aggregation, and coordination/consensus functions. In some cases it has been used to accelerate stream-processing tasks that involve small payloads and simple operations. In this work we focus on leveraging in-network computing for stream processing of scientific datasets with large payloads that require complex operations such as floating-point computations and logarithmic functions. We demonstrate in-network computing for a real-world scientific application performing streaming normalization of a 2-D image from a light source experiment. We discuss the challenges we encountered and potential approaches to address them.

Sankaran, Ganesh↗
DOE OSTI2024

Systems for Transducing Entanglement Between Photons and Electron Spins

The transfer of quantum properties and entanglement between photons and matter (transduction) is a major challenge in QIS, especially with regard to networking quantum information processing. In order to overcome this challenge, it is important to know how non-classical light (single or entangled photons) interacts with matter. This project specifically addresses fundamental questions about the interaction of single and entangled photons with molecules and nanostructures to produce electrons with prescribed spin polarizations and pairs of electrons with entangled spins, thus resulting in transduction by addressing two major objectives: (2) In Objective 1, we will investigate the formation of polarization-encoded radical (spin qubit) pairs and molecular triplet states photoexcited by single quantum emitter light sources. (2) In Objective 2, we will demonstrate the use of two entangled photons, generated by spontaneous parametric down conversion (SPDC) or by the coherent biexcitonic states of perovskite NPLs, to produce two entangled radical (spin qubit) pairs or molecular triplet states.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Covalent Triazine Framework-Derived Membranes: Engineered Sol–Gel Construction and Gas Separation Application

Covalent triazine frameworks (CTFs) represent one of the most extensively studied organic networks characterized by graphitic π-conjugated structures linked by aza-fused rings, possessing unique features such as compositions of light elements (e.g., C, H, and N), porous architectures abundant heteroatom involvement, and extensively conjugated structures. In addition, the textural and chemical structures of CTFs could be engineered via synthesis control to accommodate diverse applications. CTF materials with notable characteristics, including plentiful (ultra-)micropores, high surface areas, and the presence of CO 2 -philic functional groups involving nitrogen (N), oxygen (O), and fluorine (F), hold great promise as potential candidates for anthropogenic CO 2 capture and sequestration (CCS) applications. However, the conventional high-temperature involved ionothermal procedures and the solution-based coupling pathway only afforded CTF materials in powder form, which is difficult to be processed toward membrane formation. Successful fabrication of CTF-derived membranes will rely on the development of alternative polymerization approaches as well as structural engineering to afford membrane architectures with controllable porosity distribution and active interaction sites with CO 2 benefiting the CO 2 separation procedure. In this Account, a demonstration of the latest progress in the development of CTF-derived membranes was provided. The CTF membranes were mainly synthesized via a superacid (e.g., CF 3 SO 3 H)-promoted sol–gel approach involving the polymerization of aromatic nitrile monomers. The formation of the triazine unit through the trimerization of cyano groups served as the cross-linkers, resulting in the creation of π-conjugated networks alongside the arenes present in the starting materials. The aromatic nitrile monomers with rigid and sterically hindered structures were required to afford CTF membranes with nanoporous architectures. The acidity of the superacid and reactivity of the aromatic monomers played critical roles in the polymerization efficiency. The monomer diversity and synthesis tunability endowed the introduction of CO 2 -philic functionalities (e.g., pyrazole and fluorine) within the CTF skeletons, and integration of ionic moieties was achieved by adopting FSO 3 H with stronger acidity as the catalyst and aromatic nitrile monomers with pyrazine structures. To ensure the successful construction of fluorinated CTF membranes, it is important to avoid any fluorines on the ortho-position of the cyano groups on the benzene ring. Through control over the monomers and reaction conditions, flexible, transparent, and insoluble CTF membranes could be fabricated. The sol–gel method could be further expanded to membrane fabrication through acetyl-to-benzene transformation through synthesis control. The mild oxidation-exfoliation-filtration method was also demonstrated to fabricate substrate-supported CTF membranes. The as-afforded membranes are well characterized to determine the structural features and provide information to study the structure-performance relationship. Here, the application of CTF membranes in CO 2 separation was summarized, focusing on the approaches being developed to enhance CO 2 uptake and separation performance. In addition to utilizing the pristine CTF membranes for gas separation, functionalized carbon molecular sieve membranes could be obtained from the pyrolysis of thermally stable CTF membrane precursors toward efficient CO 2 separation, benefiting from the abundant ultramicropores being created during the pyrolysis/decomposition procedure and involvement of CO 2 -philic functionalities such as fluorine and nitrogen-containing moieties. Based on these achievements, unsolved issues in CTF membrane-related fabrication and applications, including the potential solution approaches, have been proposed to advance the application of CTF membranes.

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

Reconfigurable Intelligent Surfaces in Action for Nonterrestrial Networks

Next-generation communication technology will be made possible by cooperation between terrestrial networks with nonterrestrial networks (NTNs) composed of high-altitude platform stations (HAPSs) and satellites. Further, as humanity embarks on the long road to establish new habitats on other planets, the cooperation between NTNs and deep-space networks (DSNs) will be necessary. In this regard, we propose the use of reconfigurable intelligent surfaces (RISs) to improve coordination between these networks given that RISs perfectly match the size, weight, and power (SWaP) restrictions of operating in space. Here, a comprehensive framework of RIS-assisted nonterrestrial and interplanetary communications is presented that pinpoints challenges, use cases, and open issues. Furthermore, the performance of RIS-assisted NTNs under environmental effects, such as solar scintillation and satellite drag, is discussed in light of simulation results.

42 ENGINEERING↗
DOE OSTI2023

Analysis of Real-World Preignition Data Using Neural Networks

Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure. Further, this indicates that the alternating pattern of preignition cycles within clusters is influenced by the thermodynamic state as reflected in the pressure, but that the trigger for the initial preignition cycle is not thermodynamic in nature, but more likely tied to a critical threshold in the chemistry of the fuel/lubricant mixture in the upper crevice or other factors related to the presence of an ignition source.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Wavelength- and irradiance-dependent changes in intracellular nitric oxide level

Photobiomodulation (PBM) refers to beneficial effects of low energy light absorption. Although there is a large and growing body of literature describing down-stream physiological benefits of PBM, there is limited understanding of the molecular mechanisms that initiate and mediate these effects at the level of photon absorption. At present, the leading hypothesis is that light absorption induces release of nitric oxide (NO) from the active site of cytochrome c oxidase (COX), allowing it to bind O 2 instead. This is believed to increase mitochondrial respiration, and result in greater overall health of the cell due to increased ATP production. Aim: Although NO itself is a powerful signaling molecule involved in a host of biological responses, less attention has been devoted to the mechanisms of NO release and subsequent effects on cell signaling. The purpose of this work is to investigate wavelength-specific effects on intracellular NO release in living cells. Approach: We have conducted in depth dosimetry analyses of NO production and function in an in vitro retinal model in response to low energy exposure to one or more wavelengths of laser light. Results: We found statistically significant wavelength-dependent elevations (10-30%) in intracellular NO levels following laser exposures at 447, 532, 635 or 808 nm. Sequential or simultaneous exposures to light at two different wavelengths enhanced the NO modulation up to 50% of unexposed controls. Additionally, the immediate increases in cellular NO levels were independent of the function of nitric oxide synthase, depended greatly on the substrate source of electrons entering the electron transport chain, and did not result in increased levels of cGMP. Conclusions: This study concludes the simple model of light-mediated release of NO from COX is unlikely to explain the wide variety of PBM effects reported in the literature. Our multi-wavelength method provides a novel tool for studying immediate and early mechanisms of PBM, as well as exploring intracellular NO signaling networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An approach to nearest neighbor analysis of pigment-protein complexes using chemical cross-linking in combination with mass spectrometry

Herein, protein cross-linking is the process of chemically joining two amino acids in a protein or protein complex by a covalent bond. When combined with mass spectrometry, it becomes one of the structural mass spectrometry techniques gaining in importance for deriving valuable three-dimensional structural information on proteins and protein complexes. This platform complements existing structural methods, such as NMR spectroscopy, X-ray crystallography, and cryo-EM. Photosynthetic pigment protein complexes serve as light-energy harvesting systems and perform photochemical conversion as part of the “early events” of photosynthesis. This chapter outlines how to prepare cross-linking pigment protein complex samples for LC-MS/MS analysis, including identification of the cross-linked species, network analysis in a protein complex, and structural modeling and justification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO 2 between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO 2 release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO 2 fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co-acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data-driven approach based on combined neural networks (NN C-part ). NN C-part incorporates process knowledge by introducing a photosynthetic response based on the light-use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R 2 > .94) and RECO (R 2 > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NNC-part performed more realistic than the traditional methods for predicting additional patterns of gross CO 2 fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO 2 fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN C-part is a valid data-driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Calcium silicate hydrate colloid at different humidities: Microstructure, deformation mechanism, and mechanical properties

Calcium silicate hydrate (C-S-H) is the main hydration product of Portland cement, while fundamental questions persist regarding its colloidal structure and water content. In this work, we developed a full atomistic C-S-H colloid model and investigated the physical and mechanical properties at different gel water concentrations. Water confined in nanometer gel pores degrades the mechanical properties of C-S-H because of its hydrolysis effect. A “ductile to brittle” transition was observed in the C-S-H colloid model with increasing gel water contents, evolving from transgranular failure to intergranular fracture. The gel water confined in nanometer-sized pores displays glassy characteristics, and it acts as a lubricant and facilitates structure distortions during the deformation. We elucidated the topology effect of the hydrogen bond network on the evolution of the viscoelasticity of C-S-H at different humidities. In conclusion, this work sheds light on the role of water in C-S-H colloids from nanostructure perspectives.

36 MATERIALS SCIENCE↗