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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Experimental demonstration of novel beam characterization using a polarizable X-band transverse deflection structure

The PolariX TDS (Polarizable X-Band Transverse Deflection Structure) is an innovative TDS-design operating in the X-band frequency-range. The design gives full control of the streaking plane, which can be tuned in order to characterize the projections of the beam distribution onto arbitrary transverse axes. This novel feature opens up new opportunities for detailed characterization of the electron beam. In this paper we present first measurements of the Polarix TDS at the FLASHForward beamline at DESY, including three-dimensional reconstruction of the charge-density distribution of the bunch and slice emittance measurements in both transverse directions. The experimental results open the path toward novel and more extensive beam characterization in the direction of multi-dimensional-beam-phase-space reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Accurate real space iterative reconstruction (RESIRE) algorithm for tomography

Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at https://zenodo.org/record/7273314.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Real Time implementation of Artificial Intelligence compression algorithm for High-Speed Streaming Readout signals

The new generation of high-energy physics experiments plans to acquire data in streaming mode. With this approach, it is possible to access the information of the whole detector (organized in time slices) for optimal and lossless triggering of data acquisitions. With this approach, data rates, especially in large detectors, are often very high, and the network is likely to be the bottleneck for the entire Streaming Read Out system. The aim of this work is to study the implementation of a lossy compression algorithm based on Artificial Intelligence: an Autoencoder. With Machine Learning it is possible to achieve a high compression ratio and fast inference time with only a small degradation of the signals, almost negligible for the specific application. This work explores different configurations of the Autoencoder and the implementation on different hardware. Different Autoencoder configurations are explored to find the best trade-off between compression ratio and reconstruction loss, both for signals and energy spectrum. Different hardware implementations are also explored to find the best platform to achieve real-time performance for the specific application.

Rossi, Fabio (ORCID:0009000385713885)↗
DOE OSTI2020

Deep convolutional neural networks for multi-scale time-series classification and application to tokamak disruption prediction using raw, high temporal resolution diagnostic data

In this paper we discuss recent advances in deep convolutional neural networks (CNN) for sequence learning, which allow identifying long-range, multi-scale phenomena in long sequences, such as those found in fusion plasmas. We point out several benefits of these deep CNN architectures, such as not requiring experts such as physicists to hand-craft input data features, the ability to capture longer range dependencies compared to the more common sequence neural networks (recurrent neural networks like long short-term memory (LSTM) networks), and the comparative computational efficiency. We apply this neural network architecture to the popular problem of disruption prediction in fusion energy tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. Initial results trained on a large ECEi dataset show promise, achieving an F 1 -score of ~91% on individual time-slices using only the ECEi data. This indicates the ECEi diagnostic by itself can be sensitive to a number of pre-disruption markers useful for predicting disruptions on timescales not only for mitigation but also avoidance. Future opportunities for utilizing these deep CNN architectures with fusion data are outlined, including impact of recent upgrades to the ECEi diagnostic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Imaging phonon dynamics with ultrafast electron microscopy: Kinematical and dynamical simulations

Ultrafast x-ray and electron scattering techniques have proven to be useful for probing the transient elastic lattice deformations associated with photoexcited coherent acoustic phonons. Indeed, femtosecond electron imaging using an ultrafast electron microscope (UEM) has been used to directly image the influence of nanoscale structural and morphological discontinuities on the emergence, propagation, dispersion, and decay behaviors in a variety of materials. Here, we describe our progress toward the development of methods ultimately aimed at quantifying acoustic-phonon properties from real-space UEM images via conventional image simulation methods extended to the associated strain-wave lattice deformation symmetries and extents. Using a model system consisting of pristine single-crystal Ge and a single, symmetric Lamb-type guided-wave mode, we calculate the transient strain profiles excited in a wedge specimen and then apply both kinematical- and dynamical-scattering methods to simulate the resulting UEM bright-field images. While measurable contrast strengths arising from the phonon wavetrains are found for optimally oriented specimens using both approaches, incorporation of dynamical scattering effects via a multi-slice method returns better qualitative agreement with experimental observations. Contrast strengths arising solely from phonon-induced local lattice deformations are increased by nearly an order of magnitude when incorporating multiple electron scattering effects. We also explicitly demonstrate the effects of changes in global specimen orientation on the observed contrast strength, and we discuss the implications for increasing the sophistication of the model with respect to quantification of phonon properties from UEM images.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Laser-heated capillary discharge plasma waveguides for electron acceleration to 8 GeV

A plasma channel created by the combination of a capillary discharge and inverse Bremsstrahlung laser heating enabled the generation of electron bunches with energy up to 7.8 GeV in a laser-driven plasma accelerator. The capillary discharge created an initial plasma channel and was used to tune the plasma temperature, which optimized laser heating. Although optimized colder initial plasma temperatures reduced the ionization degree, subsequent ionization from the heater pulse created a fully ionized plasma on-axis. The heater pulse duration was chosen to be longer than the hydrodynamic timescale of ≈ 1 ns, such that later temporal slices were more efficiently guided by the channel created by the front of the pulse. Here, simulations are presented which show that this thermal self-guiding of the heater pulse enabled channel formation over 20 cm. The post-heated channel had lower on-axis density and increased focusing strength compared to relying on the discharge alone, which allowed for guiding of relativistically intense laser pulses with a peak power of 0.85 PW and wakefield acceleration over 15 diffraction lengths. Electrons were injected into the wake in multiple buckets and times, leading to several electron bunches with different peak energies. To create single electron bunches with low energy spread, experiments using localized ionization injection inside a capillary discharge waveguide were performed. A single injected bunch with energy 1.6 GeV, charge 38 pC, divergence 1 mrad, and relative energy spread below 2% full-width half-maximum was produced in a 3.3 cm-long capillary discharge waveguide. This development shows promise for mitigation of energy spread and future high efficiency staged acceleration experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

15.9% organic tandem solar cell with extended near-infrared absorption

Stacking single-junction organic solar cells is effective in increasing the power conversion efficiency (PCE) by reducing the thermalization loss and increasing the open circuit voltage. Current developments of non-fullerene acceptors (NFAs) offer a range of materials whose energy gaps are suited for absorbing relatively narrow slices of the solar spectrum, thus easing requirements for current balance between sub-elements in the multijunction stacks. In this report, we demonstrate a solution-processed tandem organic solar cell comprising a binary, visible-absorbing sub-cell and a ternary near-infrared (NIR) absorbing sub-cell. The ternary NIR sub-cell utilizes a narrow energy gap NFA acceptor that enables a broadened and increased absorption compared to a binary NIR sub-cell. An isopropanol surface treatment is developed to connect the hydrophilichydrophobic surfaces in the charge recombination zone (CRZ) located between the sub-cells. The nearly optically and electrically lossless CRZ combined with an anti-reflection coating results in a tandem OPV with PCE = 15.9 ± 0.2 % under AM 1.5G simulated illumination.

14 SOLAR ENERGY↗
DOE OSTI2020

Looking at the bigger picture: Identifying the photoproducts of pyruvic acid at 193 nm

Here, photodissociation of pyruvic acid (PA) was studied in the gas-phase at 193 nm using two complementary techniques. The time-sliced velocity map imaging arrangement was used to determine kinetic energy release distributions of fragments and estimate dissociation timescales. The multiplexed photoionization mass spectrometer setup was used to identify and quantify photoproducts, including isomers and free radicals, by their mass-to-charge ratios, photoionization spectra, and kinetic time profiles. Using these two techniques, it is possible to observe the major dissociation products of PA photodissociation: CO 2 , CO, H, OH, HCO, CH 2 CO, CH 3 CO, and CH 3 . Acetaldehyde and vinyl alcohol are minor primary photoproducts at 193 nm, but products that are known to arise from their unimolecular dissociation, such as HCO, H 2 CO, and CH 4 , are identified and quantified. A multivariate analysis that takes into account the yields of the observed products and assumes a set of feasible primary dissociation reactions provides a reasonable description of the photoinitiated chemistry of PA despite the necessary simplifications caused by the complexity of the dissociation. These experiments offer the first comprehensive description of the dissociation pathways of PA initiated on the S 3 excited state. Most of the observed products and yields are rationalized on the basis of three reaction mechanisms: (i) decarboxylation terminating in CO 2 + other primary products (~50%); (ii) Norrish type I dissociation typical of carbonyls (~30%); and (iii) O—H and C—H bond fission reactions generating the H atom (~10%). The analysis shows that most of the dissociation reactions create more than two products. This observation is not surprising considering the high excitation energy (~51 800 cm –1 ) and fairly low energy required for dissociation of PA. We find that two-body fragmentation processes yielding CO 2 are minor, and the expected, unstable primary co-fragment, methylhydroxycarbene, is not observed because it probably undergoes fast secondary dissociation and/or isomerization. Norrish type I dissociation pathways generate OH and only small yields of CH 3 CO and HOCO, which have low dissociation energies and further decompose via three-body fragmentation processes. Experiments with d 1 -PA (CH 3 COCOOD) support the interpretations. The dissociation on S 3 is fast, as indicated by the products’ recoil angular anisotropy, but the roles of internal conversion and intersystem crossing to lower states are yet to be determined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Measuring the electron temperature and identifying plasma detachment using machine learning and spectroscopy

A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from operation of the DIII-D tokamak using extreme ultraviolet/vacuum ultraviolet emission spectroscopy matched with high-accuracy divertor Thomson scattering measurements of the electron temperature, T e . This NN is shown to be particularly good at predicting T e at low temperatures (T e < 10 eV) where the NN demonstrated a mean average error of less than 1 eV. Trained to detect plasma detachment in the tokamak divertor, a NN classifier was able to correctly identify detached states (T e < 5 eV) with a 99% accuracy (an F 1 score of 0.96) at an acquisition rate 10× faster than the Thomson scattering measurement. The performance of the model is understood by examining a set of 4800 theoretical spectra generated using collisional radiative modeling that was also used to predict the performance of a low-cost spectrometer viewing nitrogen emission in the visible wavelengths. Furthermore, these results provide a proof-of-principle that low-cost spectrometers leveraged with machine learning can be used to boost the performance of more expensive diagnostics on fusion devices and be used independently as a fast and accurate T e measurement and detachment classifier.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Stochastic density functional theory: Real- and energy-space fragmentation for noise reduction

Stochastic density functional theory (sDFT) is becoming a valuable tool for studying ground-state properties of extended materials. The computational complexity of describing the Kohn-Sham orbitals is replaced by introducing a set of random (stochastic) orbitals leading to linear and often sub-linear scaling of certain ground-state observables at the account of introducing a statistical error. Schemes to reduce the noise are essential, for example, for determining the structure using the forces obtained from sDFT. Recently, we have introduced two embedding schemes to mitigate the statistical fluctuations in the electron density and resultant forces on the nuclei. Both techniques were based on fragmenting the system either in real space or slicing the occupied space into energy windows, allowing for a significant reduction in the statistical fluctuations. For chemical accuracy, further reduction of the noise is required, which could be achieved by increasing the number of stochastic orbitals. However, the convergence is relatively slow as the statistical error scales as 1 / N &#x3C7; according to the central limit theorem, where N χ is the number of random orbitals. In this paper, we combined the embedding schemes mentioned above and introduced a new approach that builds on overlapped fragments and energy windows. The new approach significantly lowers the noise for ground-state properties, such as the electron density, total energy, and forces on the nuclei, as demonstrated for a G-center in bulk silicon.

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

Quantitative spatiotemporal density evolution of aluminum heated purely by monochromatic electrons

A spatially resolved air-wedge shearing interferometer and shadowgraph diagnostic provides measurements of electron density with a resolution of ∼40 μm. A ∼100-ns-long, monoenergetic electron bunch at 19.8 MeV and a current of 1.4 kA (8.5×1014 e−) heats 100-μm-thick aluminum (Al) foils in a 1-mm-spot to Te∼1 eV. A 5-ns-long, ∼60 mJ, frequency doubled Nd:YAG laser probes the dense Al plasma. Electron densities up to 1020cm−3 are resolved; the maximum resolvable density is limited by opacity, transmission, and spatial fringe density achievable with the detector. This diagnostic provides measurements of the total phase shift, transmission, and electron density. Several measurements at different time slices provide the ability to determine the velocity of the leading edge of the shadowgraph and compare it to the motion of different density shells. These measurements are also compared to radiation hydrodynamics simulations. A rough quantitative agreement is shown between the hydro simulations and the measurements; there are differences in the exact density distributions.

Coleman, J. E. (ORCID:0000000308873757)↗
DOE OSTI2023

On the importance of three-dimensional modeling for high-energy-density physics experiments

Laser-driven cylindrical implosion experiments enable direct measurements of hydrodynamic instability growth in convergent geometries, providing a wealth of validation data in the high-energy-density regime. These experiments are designed to be nearly axially invariant, allowing for modeling with complementary two-dimensional slices of the cylinder. Two distinct hydrodynamics codes are employed to model a subset of these experiments, and the results are shown to be in very good agreement with each other and the available experimental data. While this 2D modeling approach adequately captures most of the physics of the implosion and ensuing instability growth, there are crucial aspects from the three-dimensional nature of the experiments that are missed in 2D. The first fully 3D simulations of these experiments are presented, and small but significant differences are found to arise from both the axial and azimuthal non-uniformity in the laser drive. Recent experimental results confirming the drive asymmetry are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Uncovering the three-dimensional structure of upconverting core–shell nanoparticles with multislice electron ptychography

In photon upconverting core–shell nanoparticles, structure strongly dictates performance. Typical imaging in scanning transmission electron microscopy has sufficient resolution to probe the atomic structure of these nanoparticles, but contrast, dose, and projection limitations make conventional methods insufficient for fully characterizing these structures. Phase retrieval techniques provide a promising alternative imaging mode, and, in particular, multislice electron ptychography can recover depth-dependent information. Here, we study beam-sensitive photon upconverting core–shell nanoparticles with a multislice ptychography approach using a low electron dose to avoid damage. Large strain fields arise in these heterostructures due to the mismatch in lattice parameter between the core and the shell. We reconstruct both a nanoparticle that appears defect-free and one that has a large break in the side and map the distribution of strain in 3D by computing distortion fields from high-resolution potential images of each slice. In the defect-free nanoparticle, we observe twisting of the shell, while in the broken nanoparticle, we measure the 3D position of the crack, the core, and dislocations. These results highlight the advantage of multislice electron ptychography to recover 3D information from a single scan, even under strict electron dose requirements from beam-sensitive samples.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

A multi-mass and multi-hit two-camera 3D ion momentum imaging system

We demonstrate an improved two-camera system for multi-mass and multi-hit three-dimensional (3D) momentum imaging of ions. The imaging system employs two conventional complementary metal–oxide–semiconductor cameras. We have shown previously that the system can time slice ion Newton spheres with a time resolution of 8.8 ns, limited by camera timing jitter [J. Chem. Phys., 158, 191104 (2023)]. In this work, a jitter correction method was developed to suppress the camera jitter and improve the time resolution to better than 2 ns. With this resolution, full 3D momentum distributions of ions can be obtained. We further show that this method can detect two ions with different masses when utilizing both the rising and falling edges of the cameras.

Instruments & Instrumentation↗
DOE OSTI2025

New generation bunch shape monitor for ion accelerators

Measuring longitudinal beam parameters is important for operation and development of high intensity linear accelerators, but it is notoriously difficult for proton and ion beams at non-relativistic energies. The Bunch Shape Monitor (BSM) is a device used for measuring the longitudinal bunch distribution in ion linacs. The existing BSM models have poor electron collection efficiency from the wire and are limited to one-dimensional measurements of the phase coordinate. In response to this problem, we have developed a new generation BSM with improved performance. The proposed design incorporates three major innovations: First, the collection efficiency was improved by adding a focusing field between the wire and the entrance slit, which will also allow measurements over a much wider dynamic range. Second, an improvement in the measurement speed was achieved by sampling longitudinal profiles of multiple energy slices simultaneously, where the BSM wire is placed at the exit of an ion spectrometer so that ions with different energies hit the wire at different horizontal coordinates along the wire. Finally, the design incorporates a motion system that can shift the wire and deflecting cavity together, enabling transverse profile measurements like a wire scanner. Here, in this paper, we will provide the design of the new BSM and report on its beam test results at the Spallation Neutron Source facility in Oak Ridge National Laboratory.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Sculpting crystals one Burgers vector at a time: Toward colloidal lattice robot swarms

Plastic deformation of crystalline materials with isotropic particle attractions proceeds by the creation and migration of dislocations under the influence of external forces. If dislocations are produced and migrated under the action of local forces, then material shape change can occur without the application of surface forces. We investigate how particles with variable diameters can be embedded in colloidal monolayers to produce dislocations on demand. Additionally, we find in simulation that when embedded clusters of variable diameter particles are taken through multiple cycles of swelling and shrinking, large cumulative plastic slip is produced by the creation and biased motion of dislocation pairs in the solid for embedded clusters of particular geometries. In this way, dislocations emitted by these clusters (biased “dislocation emitters”) can be used to reshape colloidal matter. Our results are also applicable to larger-scale swarms of robotic particles that organize into dense ordered two-dimensional (2D) arrangements. We conclude with a discussion of how dislocations fulfill for colloids the role sought by “metamodules” in lattice robotics research and show how successive applications of shear as a unit operation can produce shape change through slicing and swirling.

36 MATERIALS SCIENCE↗