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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Measurement of the azimuthal anisotropy of charged particles in $\sqrt{s_{\mathrm{NN}}}=5.36$ TeV $^{16}$O$+^{16}$O and $^{20}$Ne$+^{20}$Ne collisions with the ATLAS detector

This paper presents the first measurements of the azimuthal anisotropy coefficients $v_{n}$, which quantify the $n^{\mathrm{th}}$-order Fourier modulation of charged-particle azimuthal distributions, for $n=2$-4 in $\sqrt{s_{\mathrm{NN}}}=5.36$ TeV $\mathrm{^{16}O}+\mathrm{^{16}O}$ and $\mathrm{^{20}Ne}+\mathrm{^{20}Ne}$ collisions recorded with the ATLAS detector at the Large Hadron Collider in 2025. The $v_{n}$ coefficients are measured as a function of transverse momentum ($p_{\mathrm{T}}$), collision centrality, and event multiplicity. They are extracted using two complementary methods: two-particle correlations with a template-fit subtraction of short-range non-flow contributions, and four-particle subevent cumulants, which intrinsically suppress non-flow effects and provide sensitivity to flow fluctuations. The results show a clear hierarchy $v_{2} > v_{3} > v_{4}$ and a non-monotonic dependence on $p_{\mathrm{T}}$, reaching a maximum around 2 GeV, consistent with trends observed in heavy-ion collisions. Detailed comparisons between the two collision systems reveal an enhanced $v_{2}$ in central $\mathrm{^{20}Ne}+\mathrm{^{20}Ne}$ collisions, consistent with theory expectations based on the predicted prolate deformation of neon nuclei, in contrast to the slightly tetrahedral structure predicted for oxygen. The four-particle cumulant results highlight strong event-by-event fluctuations and provide the greatest sensitivity to nuclear shape effects. These measurements can place new constraints on the initial geometry and the hydrodynamic response in light-ion collisions, offering valuable input for models of nuclear structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Using DAPPER to extract the photon strength function of 58Fe using the inverse Oslo and shape methods

The photon strength function of 58 Fe has been extracted using both the Oslo and Shape methods from particle-γ coincidence data measured using the Detector Array for Photons, Protons, and Exotic Residues, which probes nuclei utilizing (d,p) reactions in inverse kinematics. Four particle-γ coincidence matrices, each constructed with different treatments of the γ-ray energies, are explored in order to observe the impact on the resulting nuclear level density and photon strength. The final photon strength function reported is found to agree well with previous Oslo measurements of other iron isotopes. Systematic uncertainties are included, using different model parameters and their reported errors to perform the Oslo method normalization. The model-independent Shape method is explored and the functional form of the photon strength function obtained is in agreement with the Oslo method results. A low-energy enhancement is not reported for 58 Fe in this work given possible subtraction issues originating from strongly populated states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Angular Dependence of Drell-Yan in the SeaQuest Experiment using Deep Neural Network-Based Reconstruction

The SeaQuest and SpinQuest experiments at Fermilab were designed to probe the internal dynamics of protons and neutrons via the angular dependence of muons created by colliding 120 GeV protons into stationary targets. To do this, it is necessary to translate the detector data into coherent information about the particles detected in the experiment. This dissertation describes the development and implementation of QTracker, a neural network-based algorithm designed to reconstruct muons. The application of QTracker to experimental data yields improved reconstruction of muon tracks, allowing for a more precise investigation of the transverse momentum distributions and angular modulations in the Drell-Yan process. This work highlights the potential of neural network-based methods to advance particle tracking and enhance our understanding of nucleon structure.

Conover, Arthur↗
DOE OSTI2021

Modelling a Heaving Point-Absorber with a Closed-Loop Control System Using the DualSPHysics Code

The present work addresses the need for an efficient, versatile, accurate and open-source numerical tool to be used during the design stage of wave energy converters (WECs). The device considered here is the heaving point-absorber developed and tested by Sandia National Laboratories. The smoothed particle hydrodynamics (SPH) method, as implemented in DualSPHysics, is proposed since its meshless approach presents some important advantages when simulating floating devices. The dynamics of the power take-off system are also modelled by coupling DualSPHysics with the multi-physics library Project Chrono. A satisfactory matching between experimental and numerical results is obtained for: (i) the heave response of the device when forced via its actuator; (ii) the vertical forces acting on the fixed device under regular waves and; (iii) the heave response of the WEC under the action of both regular waves and the actuator force. This proves the ability of the numerical approach proposed to simulate accurately the fluid–structure interaction along with the WEC’s closed-loop control system. In addition, radiation models built from the experimental and WAMIT results are compared with DualSPHysics by plotting the intrinsic impedance in the frequency domain, showing that the SPH method can be also employed for system identification.

42 ENGINEERING↗
DOE OSTI2022

Photoelectron spectroscopy in molecular physical chemistry

Photoelectron spectroscopy has long been a powerful method in the toolbox of experimental physical chemistry and molecular physics. Recent improvements in coincidence methods, charged-particle imaging, and electron energy resolution have greatly expanded the variety of environments in which photoelectron spectroscopy can be applied, as well as the range of questions that can now be addressed. In this Perspectives Article, we focus on selected recent studies that highlight these advances and research areas. Furthermore, the topics include reactive intermediates and new thermochemical data, high-resolution comparisons of experiment and theory using methods based on pulsed-field ionisation (PFI), and the application of photoelectron spectroscopy as an analytical tool to monitor chemical reactions in complex environments, like model flames, catalytic or high-temperature reactors.

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

CO2 mass transfer enhancement of aqueous amine solvents by particle additives

The present invention relates to methods for improving carbon capture by providing particles within an amine solvent. The particles provide for increased turbulence at the interface between the counter-flowing gas and solvent, which allows for increased amine and carbamate salt diffusion between the liquid film and bulk.

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

EUTERPE: A global gyrokinetic code for stellarator geometry

The current state of the EUTERPE code is described with emphasis on the implemented models and their numerical implementation. The code solves the multi-species electromagnetic gyrokinetic equations in the full volume of a three-dimensional domain. Noise reduction of the particle-in-cell method is achieved by using a δf-method and Fourier filters. The field equations are discretized with B-splines and the resulting system of equations is solved iteratively. For linear simulations a phase-factor transformation is applied in order to strongly reduce the necessary grid resolution. Apart from the full gyrokinetic model, other numerically less expensive hybrid models are also implemented. They are mainly tailored for comparison with fluid theory and for studying the interaction of the bulk plasma with fast particles. The code is parallelized for CPUs by particle and domain decomposition. Good scalability up to several thousand nodes is demonstrated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Using Machine Learning to Understand Electric and Hybrid Vehicles Ownership in Burdened and Nonburdened Communities

Transitioning to electric and hybrid vehicles (EHVs) for all communities is a pivotal step toward sustainable transportation and environmental conservation. This paper aims to understand the adoption of EHVs, focusing on burdened communities (BCs) in the United States. The EHV ownership-based analysis combines two datasets—behavioral data from the Puget Sound Regional Travel Survey integrated with BCs (Justice40) data covering transportation insecurity, environmental burden, social vulnerability, health vulnerability, and climate and disaster risk burden. After creating this unique database, descriptive analysis and modeling are used to analyze the data and predict EHV ownership in the future. Specifically, we use a new method that combines particle swarm optimization (PSO) with a stacking model named PSO-Stacking, which incorporates heterogeneous base learners of machine learning and deep learning. PSO applies a customized objective function to select the optimal hyperparameters for heterogeneous learners within the stacking model, effectively addressing challenges such as multicollinearity, data imbalance, nonlinearity, and overfitting. The proposed solution covers more accurate results than standard benchmark models for EHV ownership in BCs and non-BCs. In addition, the results of the PSO-Stacking method are explained using the local interpretable model-agnostic explanations technique. Results show a negative correlation between the BCs indicators, that is, higher transportation insecurity associated with lower EHV ownership. Furthermore, BCs have higher future climate risk scores, diesel particulate matter levels, and PM2.5 in the air than non-BCs because of higher conventional vehicle ownership. These communities are at higher risk and can benefit from electrification, EV infrastructure, and EV policies to address environmental challenges.

Aslam, Zeeshan [ORNL]↗
DOE OSTI2020

Simulation of and Antenna Design for a Reflector-based Broadband Axion Search

The axion is a theoretical particle that presents a solution to the Strong CP problem in the Standard Model and is a strong candidate for dark matter. Axions convert to photons in the presence of a strong magnetic field. Searches for the axion capitalize on this property, but the unknown mass of the axion means the frequency of oscillation of the photons is also unknown. This work explores a broadband reflector-based experiment with a conical horn antenna and circular waveguide as a new potential search method for this particle.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Acoustic focusing of microplastics in microfabricated and steel tube devices: An experimental study on the effects from particle size and medium density

The contamination of aquatic systems with microplastics is becoming a severe threat to living organisms. Microplastics found in the environment consist of a wide range of particle sizes thus give rise to several challenges to current purification methods. Acoustic focusing has been utilized as a particle concentrating method in biological and non-biological applications. In this study, we investigate the feasibility of using acoustic focusing technology to isolate microplastics in aqueous samples and find that a two-stage mechanism is essential to concentrate microplastics of wide size ranges of the same material. We demonstrate for the first time experimentally that when the particle size is comparable to the resonance wavelength, they deviate from typical pressure nodal focusing and show pressure antinodal focusing. Further, we have expanded microplastics isolation beyond microfluidic systems and demonstrate their extraction capabilities relatively at higher flow rates using microplastics of polystyrene, polyethylene, and polymethyl methacrylate ranging from 6 µm to 300 µm diameter and in devices fabricated with cylindrical steel tubes. We could extract 70% of microplastics smaller than 180 µm and 82% of microplastics greater than 180 µm in diameter from an aqueous sample at a flow rate of 12 mL/min. In conclusion, we demonstrate that small microplastics focus on acoustic pressure nodes regardless of the medium density. However, focusing of large microplastics of the same material depends on the medium density.

42 ENGINEERING↗
DOE OSTI2022

System and method for repeated metal deposition-dewetting steps to form a nano-particle etching mask producing thicker layer of engraved metasurface

A method and system is disclosed for creating an optical component having a spatially controlled refractive index and uniform anti-reflective layer. The method may involve alternately depositing and dewetting two or more thin metal material layers on the substrate to form a mask having a spatially varying nano-particle distribution, and with an increased thickness beyond what could be achieved using a single, thick layer of the same material. The substrate may then be etched, using the mask, to imprint a spatially patterned nanostructure pattern on a surface the substrate in accordance with the mask.

Feigenbaum, Eyal↗
DOE OSTI2025

Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code TRIFORCE

The ability to accurately model burn propagation in inertial confinement fusion plasmas is crucial for advancing fusion energy research. This work presents enhancements to the triforce hybrid fluid-kinetic multiphysics code, focusing on its kinetic half, which employs the particle-in-cell (PIC) method with Monte Carlo collisions (MCC). We use a moment-preserving collision model that mitigates numerical noise, particularly in spherical geometries where particle weights vary significantly. Additionally, we refine the treatment of inverse bremsstrahlung to account for electron–ion collision frequency reductions in degenerate plasmas and incorporate a blackbody radiation source to enable realistic photon injection. These improvements enable the simulation of 1-dimensional (1D) spherical fusion burn propagation in deuterium–tritium plasmas. Benchmark comparisons with the hydra radiation-hydrodynamics code confirm that triforce accurately captures the dynamics of hot-spot expansion and burn propagation, demonstrating sensitivity to ignition thresholds consistent with theoretical models. Findings show the ignition cliff to be less steep in our work compared to radiation-hydrodynamic modeling. These results highlight the role of kinetic effects in fusion ignition physics and underscore the necessity of hybrid fluid-kinetic models for advancing predictive capabilities in high-energy-density plasma systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Unveiling Morphology and Crystallinity Dynamics in Ni x Mn 1– x CO 3 Cathode Precursors through Batch-Mode Coprecipitation

This study delves into the synthesis and control of Ni x Mn 1–x CO 3 , a critical class of Mn-rich, Co-free precursors vital for cathode-oxide materials in energy storage and conversion technologies. Employing batch-mode coprecipitation, we systematically generated samples with varying Ni concentrations (x = 0, 0.1, 0.3, 0.5, 0.7, and 0.9) and conducted a comprehensive analysis of their compositions, crystallinities, transition-metal distributions, and particle morphologies through both experimental and computational methods. A significant variation in particle size and crystallinity was observed, contingent on the Ni content. Further, a pivotal transition emerged at Ni concentrations above x = ~0.5, transforming uniform morphologies, such as spherical, monodisperse, pseudo-single-crystalline particles, into bimodal, polycrystalline structures. Furthermore, the study highlights the role of Ni–ammonia complexes leading to Ni-deficient precipitates and underscores the importance of ammonia concentration in achieving precise Ni content control. This study unveils critical reaction conditions governing Mn-rich precursor properties that are vital for cathode-oxides, emphasizing the need for meticulous synthetic control and offering the potential for practical applications in advanced energy storage and conversion systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Aerosol Hygroscopic Growth, Mixing State, and Cloud Condensation Nuclei Activity during TRACER (Field Campaign Report)

Convective clouds play a critical role in the Earth’s climate system. Recent research has shown that a realistic representation of convective processes is critical to constraining climate sensitivity in global climate models. Theoretical and modeling studies showed that aerosols could have strong dynamic feedback to convection in warm and humid environments through enhancing ice-related processes and condensational growth. A few observation-based studies also suggested the influence of aerosols on convective cloud and precipitation properties. However, robust observational quantification of an aerosol effect on convective clouds isolated from other factors remains elusive. Understanding the impact of aerosol on convective clouds requires knowledge of the cloud condensation nuclei (CCN) spectrum, which represents the number of particles that uptake water and form cloud droplets as a function of supersaturation. The water uptake by aerosol is also of critical importance for the direct interaction of aerosol with radiation (i.e., aerosol direct effect) due to light scattering and absorption by aerosol. While both droplet activation under supersaturated conditions (i.e., relative humidity RH > 100%) and the hygroscopic growth under sub-saturated conditions (i.e., RH < 100%) are strongly influenced by particle hygroscopicity, the thermodynamic regimes and measurement methods are quite different. Aerosol particles, especially organic particles, can exhibit higher hygroscopicity for droplet activation than that for hygroscopic growth. In the subsaturated regime, the hygroscopicity of organic particles can also vary strongly with RH. However, global climate models usually treat organic species in aerosols with a constant hygroscopicity, potentially introducing substantial uncertainties in the quantification of aerosol radiative effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hollow Silica Particles: Recent Progress and Future Perspectives

Hollow silica particles (or mesoporous hollow silica particles) are sought after for applications across several fields, including drug delivery, battery anodes, catalysis, thermal insulation, and functional coatings. Significant progress has been made in hollow silica particle synthesis and several new methods are being explored to use these particles in real-world applications. This review article presents a brief and critical discussion of synthesis strategies, characterization techniques, and current and possible future applications of these particles.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An unconditionally stable, time-implicit algorithm for solving the one-dimensional Vlasov–Poisson system

The development of an implicit, unconditionally stable, numerical method for solving the Vlasov–Poisson system in one dimension using a phase-space grid is presented. The algorithm uses the Crank–Nicolson discretization scheme and operator splitting allowing for direct solution of the finite difference equations. This method exactly conserves particle number, enstrophy and momentum. A variant of the algorithm which does not use splitting also exactly conserves energy but requires the use of iterative solvers. This algorithm has no dissipation and thus fine-scale variations can lead to oscillations and the production of negative values of the distribution function. We find that overall, the effects of negative values of the distribution function are relatively benign. We consider a variety of test cases that have been used extensively in the literature where numerical results can be compared with analytical solutions or growth rates. We examine higher-order differencing and construct higher-order temporal updates using standard composition methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Transforming jet flavour tagging at ATLAS

Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton–proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. Designed to classify jets based on the flavour of their constituent particles, GN2 processes low-level tracking information in an end-to-end architecture and incorporates physics-informed auxiliary training objectives to enhance both interpretability and performance. Its performance is validated in both simulation and collision data. The measured c-jet (light-jet) rejection in data is improved by a factor of 3.5 (1.8) for a 70% b-jet tagging efficiency, compared to the previous algorithm. GN2 provides substantial benefits for physics analyses involving heavy-flavour jets, such as measurements of Higgs boson pair production and the couplings of bottom and charm quarks to the Higgs boson, and demonstrates the impact of advanced machine learning methods in experimental particle physics.

Characterization and analytical techniques↗