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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The high level trigger and express data production at STAR

To meet the demands of the Beam Energy Scan phase-II (BES-II) program, the STAR experiment at the Relativistic Heavy Ion Collider (RHIC) developed a dual real-time framework consisting of a High Level Trigger (HLT) and an Express Data Production system (xProduction). The HLT operates online within the Data Acquisition (DAQ) chain on a dedicated multi-core CPU cluster with the option to offload compute-intensive kernels to Xeon Phi coprocessors. It uses parallelized algorithms, such as the Cellular Automaton (CA) Track Finder, to perform rapid tracking, vertexing, and event filtering. This allows it to select events of interest in real time and provide immediate feedback on detector and beam conditions. In contrast, the xProduction workflow runs concurrently and independently of the DAQ loop. It applies near offline-quality calibration and reconstruction within hours of data collection. The xProduction input is the express data stream, whose content can be enriched by HLT trigger/priority selections under DAQ/HLT resource constraints, and it uses the STAR calibration/conditions framework, incorporating online calibration/QA information when available. This enables early preliminary physics analysis, including the reconstruction of rare signals, such as hyperons and hypernuclei. It also provides collaboration-wide access to analysis-ready datasets. Together, the HLT and xProduction systems form a complementary architecture: the HLT performs online event selection while the xProduction chain delivers high-quality results within a short amount of time. This integrated framework has enabled the prompt reconstruction of the $^5_Λ$ He hypernucleus with high statistical significance and the efficient processing of hundreds of millions of heavy-ion collision events. In conclusion, its demonstrated scalability and robustness establish a model for future high-luminosity experiments requiring both online event filtering and rapid access to analysis-quality data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2027

Conceptual design of highly-constrained splitters for the FFA@CEBAF energy upgrade study

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is investigating a significant energy upgrade utilizing Fixed-Field Alternating-gradient (FFA) recirculating arcs. This upgrade requires the design of complex horizontal beam splitters to manage up to six concurrent beam passes. This paper presents the conceptual design of these splitters, which are subject to severe physical constraints imposed by the existing accelerator tunnel and multifaceted beam dynamics requirements for matching into the permanent-magnet FFA arcs. The design methodology, centered on multi-pass simulations in the Bmad toolkit, is detailed from the initial geometric layout through the advanced optics matching. Key results include a robust geometric arrangement that fits within the spatial boundaries and the development of multiple, flexible optics matching solutions. Furthermore, the design integrates a viable scheme for extracting high-energy beams for the experimental halls, a critical operational requirement. This work establishes a comprehensive and viable conceptual design, forming a baseline for future engineering and performance optimization studies.

Bodenstein, R.M. [Thomas Jefferson National Accele↗
DOE OSTI2024

Nuclear reactor radiation and temperature effects on piezoelectric surface acoustic wave devices

Surface acoustic wave (SAW) resonators were characterized in-situ in a nuclear reactor environment at high temperature. Devices based on lithium niobate (LiNbO 3 ), aluminum nitride (sc-AlN), and thin-film aluminum nitride on sapphire substrate (AlN/sapphire) were tested up to 400 °C temperature and 1.9 × 10 12 n/cm 2 s neutron flux. Shifts in device resonant frequency were detected in response to temperature and neutron flux. Devices undergo a frequency change when exposed to neutron flux. At 300 °C, AlN/sapphire produced the strongest neutron flux response about 1.02 ppm at 1.27 × 10 12 n/cm 2 s neutron flux (5.7 × 10 4 rad-Si/hr neutron dose rate), compared to 0.30 ppm for LiNbO 3 and 0.17 ppm for sc-AlN. While the transient kinetics in response to step change in neutron flux support the defect-accumulation mechanism, the concurrent measurement of device temperature using resistive temperature sensor suggests additional heating caused by absorption of gamma rays can also play a role. These results make SAW devices attractive candidates for sensor applications in extreme environments.

Aluminum nitride↗
DOE OSTI2024

A High-Performance Discrete-Element Framework for Simulating Flow and Jamming of Moisture Bearing Biomass Feedstocks

We developed and verified a high-performance open-source discrete element method (DEM) solver with simultaneously-supported feedstock-specific interaction models, including bonded-sphere, liquid bridge, cohesion, and non-linear contact models. Our solver uses parallel data structures on hybrid central and graphics processing unit (CPU/GPU) architectures, with favorable strong scaling performance observed for large problem sizes comprised of (100 M particles), and 4X single-node GPU speedup. The particles for corn stover feedstock were conceptualized and calibrated based on experimental measurements and results. Sensitivity analyses demonstrate that the mass flow rate from a wedge hopper is governed primarily by moisture content, friction coefficient, and cohesion energy density. The model is used to reproduce experimentally observed hopper jamming results, highlighting that the experimental no-flow trends can only be achieved by using non-spherical particles, liquid bridge and cohesion models, highlighting the importance of using concurrent feedstock specialized models for the effective representation of biomass material handling problems.

bioenergy↗
DOE OSTI2025

Hybrid classical-quantum communication networks

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum–classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications.

Fiber-optic communication↗
DOE OSTI2025

The effect on soot and its gas precursors of doping ethylene with 2,2,4,6,6-pentamethyl-heptane in the nitrogen-fuel stream of a laminar non-premixed Planar Mixing Layer Flame (PMLF)

Synthetic Aviation Turbine Fuels (SATFs) are promising for reducing soot emissions from the aviation sector and diversifying Jet Fuel (JF) sources. Accurately predicting the combustion and emissions behavior of SATFs (and other JFs) necessitates robust experimental databases to elucidate the chemistry of long-chain iso-paraffins, which can compose up to two-thirds of SATF blends and whose behavior is considered to be well-represented by that of iso-dodecane isomers. Here, this study characterizes two laminar non-premixed Planar Mixing Layer Flames (PMLFs) with mild soot loads fueled by nitrogen-diluted ethylene, pure and doped with 2,2,4,6,6-pentamethyl-heptane, respectively. The two PMLFs have the same stoichiometric mixture fraction and total hydrocarbon mole fraction in the fuel stream (X F,F =X C2H4,F +X C12H26,F = 0.260), resulting in nearly the same maximum temperature (T max ≈1800 K) and simple identification of the effects of doping. Importantly, any horizontal PMLF cross-section has a self-similar structure that can be modeled as an equivalent One-Dimensional Counterflow Flame (1D-CF) with vanishingly small strain rate (a). The cross-section at a Height Above the Burner (HAB) of 50 mm is characterized in terms of C 0 -C 18 gas species using capillary sampling followed by GC-MS analyses. Laser-Induced Emission Spectroscopy (LIES) quantifies the soot volume fraction (ƒ v ) profiles at HAB=25 and 50 mm where Elastic Laser Light Scattering (E-LLS) is performed to determine the a of the equivalent 1D-CFs and the profile of the E-LLS equivalent diameter ( d 6,3 ) of soot. The substitution of 1500 ppm of ethylene with 2,2,4,6,6-pentamethyl-heptane causes an increase of ≈1.5 in the concentrations of several polycyclic aromatic hydrocarbons and fv. Concurrently, the measured d 6,3 doubles in the oxidizer stream, yet remains the same in the fuel stream, at HAB=50 mm. Instead, at HAB= 25 mm, the iso-dodecane doping does not affect the d 6,3 profile in either stream. The experimental results partially validate the chemical reactions and soot formation kinetic model developed at Lawrence Livermore National Laboratory and provide directions to further improve its predictions.

Iso-dodecane (2,2,4,6,6-Pentamethyl-Heptane)↗
DOE OSTI2026

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗
DOE OSTI2025

Bayesian Entropy Neural Networks for physics-aware prediction

This article addresses the need for deep learning models to integrate well-defined constraints into their outputs, driven by their application in surrogate models, learning with limited data and partial information, and scenarios requiring flexible model behavior to incorporate non-data sample information. We introduce Bayesian Entropy Neural Networks (BENN), a framework grounded in Maximum Entropy (MaxEnt) principles, designed to impose constraints on Bayesian Neural Network (BNN) predictions. BENN is capable of constraining not only the predicted values but also their derivatives and variances, ensuring a more robust and reliable model output. To achieve simultaneous uncertainty quantification and constraint satisfaction, we employ the method of multipliers approach. This allows for the concurrent estimation of neural network parameters and the Lagrangian multipliers associated with the constraints. Our experiments, spanning diverse applications such as beam deflection modeling and microstructure generation, demonstrate the effectiveness of BENN. The results highlight significant improvements over traditional BNNs and showcase competitive performance relative to contemporary constrained deep learning methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Distributed optimization for multi-commodity urban traffic control

A distributed method for concurrent traffic signal and routing control of traffic networks is proposed. The method is based on the multi-commodity store-and-forward model, in which the destinations are the commodities. The system benefits from the communication between vehicles and infrastructure, providing optimal signal timings to intersections and routes to vehicles on a link-by-link basis. Using the augmented Lagrangian to model the constraints into the objective, the baseline centralized problem is decomposed into a set of objective-coupled subproblems, one for each intersection, enabling the solution to be computed by a distributed- gradient projection algorithm. Further, the intersection agents only need to communicate and coordinate with neighboring intersections to ensure convergence to the optimal solution while tolerating suboptimal iterations that offer more flexibility, unlike other distributed approaches. Through microsimulation, we demonstrate the effectiveness of the proposed algorithm in traffic networks with time-varying demand. Computational analysis shows that the distributed problem is suitable for real-time applications. A robustness analysis show that the distributed formulation enables a graceful degradation of the system in case of failure.

Augmented Lagrangian↗
DOE OSTI2024

Dynamics of precatalyst conversion and iron incorporation in nickel-based alkaline oxygen evolution reaction catalysts

The efficiency of alkaline water electrolyzers is limited by the oxygen evolution reaction (OER). The design of improved OER catalysts requires understanding of material changes induced by the electrolyte under oxidizing potentials. We compare four Ni-based thin-film precatalysts—Ni, NiO, Ni(OH) 2 , and NiS x —in 0.1 M KOH with and without Fe impurities. Precatalyst conversion to the active oxyhydroxide catalysts and their OER performance are induced and followed using cyclic voltammetry. Without Fe electrolyte impurities, the precatalysts convert at different rates to a similar, modestly active NiOOH catalyst. Added Fe impurities are incorporated concurrently with the oxyhydroxide formation leading to active Ni 1-x Fe x OOH catalysts. The NiS x and Ni(OH) 2 precatalysts rapidly convert to oxyhydroxides both with and without Fe, while conversion of Ni and especially NiO is slowed down by Fe impurities. Choice of the precatalyst and presence of Fe impurities are key factors in designing active Ni 1-x Fe x OOH OER catalysts for electrolyzers.

alkaline electrolysis↗
DOE OSTI2024

Cooling Mixed A-Site Halide Perovskites: Impact of Temperature on Optical and Structural Properties

The widespread utilization of perovskite-based photovoltaics requires probing both the structural and optical properties under extreme operating conditions to gain a holistic understanding of the material behavior under stressors. Here, in this study, we investigate the temperature-dependent behavior of mixed A-site cation lead triiodide perovskite thin films (85% methylammonium and 15% formamidinium) in the range from 300 to 20 K. Through a combination of optical and structural techniques, we find that the tetragonal-to-orthorhombic phase transition occurs at similar to 110 K for this perovskite composition, as indicated by the change in the diffraction pattern. With decreasing temperature, the quantum yield increases with a concurrent elongation of the carrier lifetimes, indicating suppression of nonradiative recombination pathways. Interestingly, in contrast to single A-site cation perovskites, an additional optical transition appears in the absorption spectrum when the phase transition is approached, which is also reflected in the emission spectrum. We propose that the splitting of the optical absorption and emission is due to local segregation of the mixed cation perovskite during the phase transition.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ether Cleavage Decreases the Ion Exchange Capacity of Anion Exchange Membranes

Anion exchange membranes (AEMs) are integral to fuel cells and water electrolysis systems but suffer from poor durability under alkaline conditions. Ether cleavage is an important failure pathway of poly(arylene ether)-based AEMs that compromises both mechanical stability and ion transport. While this degradation pathway is often studied in terms of polymer fragmentation, the role of newly formed hydrophilic groups has been largely overlooked. Here, we show that polymer scission leads to reduced mechanical rigidity, while the introduction of hydrophilic groups partially mitigates this loss. Under alkaline conditions, phenoxide groups formed during ether cleavage neutralize the polymer cations, leading to a previously unreported loss of ion exchange capacity (IEC). This IEC loss mechanism exacerbates the reduction in ionic conductivity, emphasizing the severity of ether cleavage as a degradation pathway. Recognizing that ether cleavage introduces significant chemical changes beyond polymer fragmentation provides critical insights into its interplay with other degradation mechanisms, such as the direct reduction of cationic sites by E2 and S N 2, and provides molecular-level interpretations for the concurrent effects of polymer scission and increased hydrophilicity on membrane performance.

crystal cleavage↗
DOE OSTI2024

Liquid–Liquid Equilibrium Prediction in Fast Pyrolysis Bio-Oil Systems: A Framework for Incorporating Bio-Oil Complexity

The study of mixtures of bio-oil, water and organic solvents in different proportions can serve as a cost-effective analysis of its content due to the formation of immiscible phases. This manuscript attempts to replicate experimentally determined partition coefficients (K OW ) of relevant species present in fast pyrolysis bio-oil (FPBO). A commercial flowsheeting simulator with surrogate bio-oil model representation is used. Concurrently, pyrolytic lignins in FPBO (‘pyrolignin’) do not have an agreed-upon structural representation, and the literature is ripe with wide variations of said representations. Thus, during the description of FPBO, this pyrolignin fraction was modeled using 20 possible structures (phenolic dimers to tetramers), with the goal of determining the structures for which the experimental data are best described. Two cases were considered: Case 1 normalized the reported experimental mass balance, while Case 2 included the unreported fraction in the mass balance to the total pyroligin. Please, add here a comment on the prediction of the Water oil equilibrium. The best KOW predictions for levoglucosan (LVG) were obtained when the system was modeled with no pyrolignin, presenting an MRE under 10% for both systems WO and BO. Among the possible structures, D2 (dimer), F1 (trimer) and I1, and I3 (tetramers) presented MRE ≤ 13% for both cases.

09 BIOMASS FUELS↗
DOE OSTI2025

Carbonation of MgO Single Crystals: Implications for Direct Air Capture of CO 2

Direct air capture (DAC) may be feasible to remove carbon dioxide (CO 2 ) from the atmosphere at the gigaton scale, holding promise to become a major contributor to climate change mitigation. Mineral looping using magnesium oxide (MgO) is potentially an economical, efficient, and sustainable pathway to gigaton-scale DAC. The hydroxylation and carbonation of MgO determine the efficiency of the looping process, but their rates and mechanisms remain uncertain. Here, in this work, MgO single crystals were reacted in air or CO 2 at varying humidities and characterized by X-ray scattering, microscopy, and vibrational spectroscopy. Results show that the hydroxylation formed a brucite (Mg(OH) 2 )-like layer immediately after crystal cleaving. Concurrently, the carbonation formed hydrated magnesium carbonate phases, including barringtonite (MgCO 3 ·2H 2 O) and nesquehonite (MgCO 3 ·2H 2 O), in the layer. Rapid initial growth of the layer is also manifested in short-range bending/warping of nanocrystallites, resulting in multiple orientations of the same phases on the surface. The layer growth slowed down over time, indicating surface passivation. The formation of barringtonite and nesquehonite with 1:1 CO 3 /Mg ratio indicates an efficient carbonation when compared to other magnesium carbonate phases of lower ratio. Our results are essential for understanding surface passivation mechanisms and tackling the passivation issue of mineral looping DAC technology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Potential and Cost of Carbon Dioxide Removal Using Direct Air Capture with Land-Based Wind and Utility-Scale Photovoltaics

The rapid deployment of direct air capture and storage (DACS) is critical for achieving emission targets, necessitating precise evaluation of the scale and cost of carbon dioxide removal. This study examines the availability of land, electricity generation, and geologic CO 2 storage within the United States, estimating a technical potential for low-temperature, adsorbent-based DACS to remove approximately 9 gigatonnes of CO 2 annually. By 2050, a substantial portion of this removal could be achieved at net-removed costs below $\$$300/tonneCO 2 , though costs are highly variable depending on factors such as facility scale, construction expenses, climate-dependent productivity and heating efficiency, and geologic storage conditions. In the short term, DACS deployment will help identify key research priorities for advancing technology and reducing removal costs. Concurrently, there is an urgent need for scientifically robust and standardized frameworks for monitoring, reporting, and verifying DACS performance across both established and emerging technologies and energy sources.

Carbon capture↗
DOE OSTI2024

Formation of Inorganic Sulfate and Volatile Nonsulfated Products from Heterogeneous Hydroxyl Radical Oxidation of 2-Methyltetrol Sulfate Aerosols: Mechanisms and Atmospheric Implications

Chemical transformation of 2-methyltetrol sulfates (2-MTS), key isoprene-derived secondary organic aerosol (SOA) constituents, through heterogeneous hydroxyl radical ( • OH) oxidation can result in the formation of previously unidentified atmospheric organosulfates (OSs). However, detected OSs cannot fully account for the sulfur content released from reacted 2-MTS, indicating the existence of sulfur in forms other than OSs, such as inorganic sulfates. This work investigated the formation of inorganic sulfates through heterogeneous • OH oxidation of 2-MTS aerosols. Remarkably, high yields of inorganic sulfates, defined as the moles of inorganic sulfates produced per mole of reacted 2-MTS, were observed in the range from 0.48 ± 0.07 to 0.68 ± 0.07. These could be explained by the production of sulfate (SO 4 •- ) and sulfite (SO 3 •- ) radicals through the cleavage of C-O(S) and (C)O-S bonds, followed by aerosol-phase reactions. Additionally, non-sulfated products resulting from bond cleavage were likely volatile and evaporated into gas phase, as evidenced by observed aerosol mass loss (up to 25%) and concurrent size reduction upon oxidation. This investigation highlights the significant transformation of sulfur from its organic to inorganic forms during the heterogeneous oxidation of 2-MTS aerosols, potentially influencing the physicochemical properties and environmental impacts of isoprene-derived SOA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning

Arsenene, a less-explored two-dimensional material, holds the potential for applications in wearable electronics, memory devices, and quantum systems. This study introduces a bond-order potential model with Tersoff formalism, the ML-Tersoff, which leverages multireward hierarchical reinforcement learning (RL), trained on an ab initio data set. This data set covers a spectrum of properties for arsenene polymorphs, enhancing our understanding of its mechanical and thermal behaviors without the complexities of traditional models requiring multiple parameter sets. Our RL strategy utilizes decision trees coupled with a hierarchical reward strategy to accelerate convergence in high-dimensional continuous search spaces. Unlike the Stillinger-Weber approach, which demands separate formalisms for buckled and puckered forms, the ML-Tersoff model concurrently captures multiple properties of the two polymorphs by effectively representing the local environment, thereby avoiding the need for different atomic types. Here, we apply the ML model to understand the mechanical and thermal properties of the arsenene polymorphs and nanostructures. We observe an inverse relationship between the critical strain and temperature in arsenene. Thermal conductivity calculations in nanosheets show good agreement with ab initio data, reflecting a decrease in thermal conductivity attributable to increased anharmonic effects at higher temperatures. We also apply the model to predict the thermal behavior of arsenene nanotubes.

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

Operando XPS for Plasma Process Monitoring: A Case Study on the Hydrogenation of Copper Oxide Confined under h-BN

Here, we demonstrate that ambient pressure x-ray photoelectron spectroscopy (APXPS) can be used for in situ studies of dynamic changes in surface chemistry in a plasma environment. This opens a new and vast application space for XPS and greatly complements modern spectroscopy techniques to probe plasma-solid/liquid interactions relevant to process monitoring in the semiconductor industry, bio-medical plasma applications and plasma remediation technologies. Hexagonal boron nitride (h-BN) grown on Cu was used in this study as a well-defined model system for plasma process monitoring and because of its unique chemical, optical and electrical properties that make it a prospective material for advanced electronics. To better understand the stability and surface chemistry of h-BN during plasma assisted processing, we track in real time the plasma-induced chemical state changes of B, N and the underlying Cu substrate using APXPS equipped with an AC discharge plasma source operating at 13 Pa. Residual gas analysis (RGA) mass-spectra were concurrently collected during plasma-XPS to track reaction products formed during plasma exposure. A clear reduction of Cu x O is seen, while an h-BN layer remains intact, suggesting hydrogen radical (H • ) species can attack the exposed and h-BN covered Cu oxide patches and partially reduce the underlying substrate without significantly damaging the overlaying h-BN, which is of practical importance for development of h-BN encapsulated devices and interfaces. In addition to demonstration of plasma-XPS capabilities we discuss the observed challenges (e.g., parasitic plasma-chamber walls reactions and charging effects) and propose potential solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗