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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas↗
DOE OSTI2023

Tomography of ultrarelativistic nuclei with polarized photon-gluon collisions

A linearly polarized photon can be quantized from the Lorentz-boosted electromagnetic field of a nucleus traveling at ultrarelativistic speed. When two relativistic heavy nuclei pass one another at a distance of a few nuclear radii, the photon from one nucleus may interact through a virtual quark-antiquark pair with gluons from the other nucleus, forming a short-lived vector meson (e.g., ρ 0 ). In this experiment, the polarization was used in diffractive photoproduction to observe a unique spin interference pattern in the angular distribution of ρ 0 → π + π – decays. The observed interference is a result of an overlap of two wave functions at a distance an order of magnitude larger than the ρ0 travel distance within its lifetime. The strong-interaction nuclear radii were extracted from these diffractive interactions and found to be 6.53 ± 0.06 fm ( 197 Au) and 7.29 ± 0.08 fm ( 238 U), larger than the nuclear charge radii. The observable is demonstrated to be sensitive to the nuclear geometry and quantum interference of nonidentical particles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Single-mode squeezed-light generation and tomography with an integrated optical parametric oscillator

Quantum optical technologies promise advances in sensing, computing, and communication. A key resource is squeezed light, where quantum noise is redistributed between optical quadratures. We introduce a monolithic, chip-scale platform that exploits the χ (2) nonlinearity of a thin-film lithium niobate (TFLN) resonator device to efficiently generate squeezed states of light. Our system integrates all essential components—except for the laser and two detectors—on a single chip with an area of one square centimeter, reducing the size, operational complexity, and power consumption associated with conventional setups. Using the balanced homodyne measurement subsystem that we implemented on the same chip, we measure a squeezing of 0.55 decibels and an anti-squeezing of 1.55 decibels. We use 20 milliwatts of input power to generate the parametric oscillator pump field by using second harmonic generation on the same chip. Our work represents a step toward compact and efficient quantum optical systems posed to leverage the rapid advances in integrated nonlinear and quantum photonics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Time-resolved atomic-resolution Brownian tomography of single nanocrystals reveals size-dependent dynamics

Atomic-resolution structure identification of nanocrystals by graphene liquid cell electron microscopy (GLC-EM) has revealed that small, solubilized platinum nanocrystals consist of an ordered crystalline core surrounded by mobile surface atoms, which dissociate during oxidative etching, resulting in distinct temporal structural states. Requirements imposed by the 3D reconstruction algorithm limit the number of structural states that can be resolved. We introduce a regularized 3D reconstruction algorithm that exploits the redundancy inherent in the experimental data, allowing us to improve the time resolution. Our developments provide a comprehensive molecular picture at unprecedented spatial and temporal resolution of the nonlinear, linear, and fluctuating dynamic phenomena that single nanocrystals undergo during the GLC-EM experiment. We determined atomic structures of 66 temporal structural states, extracted from 15 time trajectories of individual nanocrystals. Large (478 to 698 atoms) and small (<300 atoms) nanocrystals show etching that preserves a stable core, whereas mid-sized (351 to 571 atoms) nanocrystals present dynamics that change the coordination of the core.

Meana-Pañeda, Rubén↗
DOE OSTI2021

Fireball tomography from bottomonia elliptic flow in relativistic heavy-ion collisions

Abstract We calculate the elliptic flow of bottomonia produced in Pb $$\,+\,$$ + Pb collisions at $$\sqrt{s_{\mathrm{NN}}}=5.02$$ s NN = 5.02 TeV. We consider temperature-dependent decay widths for the anisotropic escape of various bottomonium states and observe that the transverse momentum dependence of bottomonia elliptic flow provides a tomographic information about the QGP fireball at different stages of its evolution. For the space-time evolution of the fireball, we employ simulation results from the 3 + 1 D quasiparticle anisotropic hydrodynamic model. We find that our results for transverse momentum dependence of bottomonia elliptic flow are in reasonable agreement with experimental results from the ALICE and CMS collaborations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Neutrino tomography of the Earth with ORCA detector

Abstract Using PREM as a reference model for the Earth density distribution we investigate the sensitivity of ORCA detector to deviations of the Earth (i) outer core (OC) density, (ii) inner core (IC) density, (iii) total core density, and (iv) mantle density, from their respective PREM densities. The analysis is performed by studying the effects of the Earth matter on the oscillations of atmospheric $$\nu _{\mu }$$ ν μ , $$\nu _e$$ ν e , $${\bar{\nu }}_\mu $$ ν ¯ μ and $${\bar{\nu }}_e$$ ν ¯ e . We present results which illustrate the dependence of the ORCA sensitivity to the OC, IC, core and mantle densities on the type of systematic uncertainties used in the analysis, on the value of the atmospheric neutrino mixing angle $$\theta _{23}$$ θ 23 , on whether the Earth mass constraint is implemented or not, and on the way it is implemented, and on the type – with normal ordering (NO) or inverted ordering (IO) – of the light neutrino mass spectrum. We show, in particular, that in the “most favorable” NO case of implemented Earth mass constraint, “minimal” systematic errors and $$\sin ^2\theta _{23}=0.58$$ sin 2 θ 23 = 0.58 , ORCA can determine, e.g., the OC (mantle) density at $$3\sigma $$ 3 σ C.L. after 10 years of operation with an uncertainty of (− 18%)/+ 15% (of (− 6%)/+ 8%). In the “most disfavorable” NO case of “conservative” systematic errors and $$\sin ^2\theta _{23}=0.42$$ sin 2 θ 23 = 0.42 , the uncertainty on OC (mantle) density reads (− 43%)/+ 39% ((− 17%/+ 20%), while for for $$\sin ^2\theta _{23} = 0.50$$ sin 2 θ 23 = 0.50 and 0.58 it is noticeably smaller: (− 37)%/+ 30% and (− 30%)/+ 24% ((− 13%)/+ 16% and (− 11%/+ 14%)). We find also that the sensitivity of ORCA to the OC, core and mantle densities is significantly worse for IO neutrino mass spectrum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗
DOE OSTI2025

Livermore Computed Tomography Input/Output library

Read, write, and connect visualizers to data for LLNL radiography and CT tools (e.g. LTT: https://softwarelicensing.llnl.gov/product/livermore-tomography-tools-ltt).

Vardar-Irrgang, MichaelE [Lawrence Livermore Natio↗
DOE OSTI2022

Physics-driven learning of Wasserstein GAN for density reconstruction in dynamic tomography

Object density reconstruction from projections containing scattered radiation and noise is of critical importance in many applications. Existing scatter correction and density reconstruction methods may not provide the high accuracy needed in many applications and can break down in the presence of unmodeled or anomalous scatter and other experimental artifacts. Incorporating machine-learning models could prove beneficial for accurate density reconstruction, particularly in dynamic imaging, where the time evolution of the density fields could be captured by partial differential equations or by learning from hydrodynamics simulations. In this work, we demonstrate the ability of learned deep neural networks to perform artifact removal in noisy density reconstructions, where the noise is imperfectly characterized. Here, we use a Wasserstein generative adversarial network (WGAN), where the generator serves as a denoiser that removes artifacts in densities obtained from traditional reconstruction algorithms. We train the networks from large density time-series datasets, with noise simulated according to parametric random distributions that may mimic noise in experiments. The WGAN is trained with noisy density frames as generator inputs, to match the generator outputs to the distribution of clean densities (time series) from simulations. A supervised loss is also included in the training, which leads to an improved density restoration performance. In addition, we employ physics-based constraints such as mass conservation during the network training and application to further enable highly accurate density reconstructions. Our preliminary numerical results show that the models trained in our frameworks can remove significant portions of unknown noise in density time-series data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗