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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

VHH antibody loop guides design of a synthetic macrocyclic peptide that potently blocks influenza virus membrane fusion

Abstract Miniaturizing biologically complex structural motifs to produce synthetic functional mimetics holds significant promise for development of new therapeutic modalities. Here, we demonstrate a unique approach using the key binding loop of the single variable domain of a heavy chain (V H H) llama antibody as a starting point for peptide design. V H H antibodies of camelids and sharks generally have longer, but more ligand-efficient complementarity determining region 3 (CDR3) loops and are relatively stable structures. We harnessed these attributes as templates for design of a series of synthetic macrocyclic peptides. The designed peptides exhibit nanomolar binding to influenza hemagglutinin (HA) and heterosubtypic in vitro neutralization breadth against influenza A viruses by inhibiting the low pH mediated HA conformational changes that lead to membrane fusion. X-ray structures of peptide-HA complexes reveal high structural mimicry with the parent V H H antibody. One such macrocycle peptide candidate is promising for further development of broad protection against influenza A group 1 viruses.

Kadam, Rameshwar U.↗
DOE OSTI2021

System-on-chip upgrade of millimeter-wave imaging diagnostics for fusion plasma

Monolithic, millimeter wave “system-on-chip” technology has been employed in chip heterodyne radiometers in a newly developed Electron Cyclotron Emission Imaging (ECEI) system on the DIII-D tokamak for 2D electron temperature and fluctuation diagnostics. The system employs 20 horn-waveguide receiver modules each with customized W-band (75–110 GHz) monolithic microwave integrated circuit chips comprising a W-band low noise amplifier, a balanced mixer, a ×2 local oscillator (LO) frequency doubler, and two intermediate frequency amplifier stages in each module. Compared to previous quasi-optical ECEI arrays with Schottky mixer diodes mounted on planar antennas, the upgraded W-band array exhibits >30 dB additional gain and 20× improvement in noise temperature; an internal eight times multiplier chain is used to provide LO coupling, thereby eliminating the need for quasi-optical coupling. The horn-waveguide shielding housing avoids out-of-band noise interference on each module. The upgraded ECEI system plays an important role for absolute electron temperature and fluctuation measurements for edge and core region transport physics studies. An F-band receiver chip (up to 140 GHz) is under development for additional fusion facilities with a higher toroidal magnetic field. Visualization diagnostics provide multi-scale and multi-dimensional data in plasma profile evolution. Finally, a significant aspect of imaging measurement is focusing on artificial intelligence for science applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Using millimeter-sized carbon–deuterium foils for high-precision deuterium–tritium neutron spectrum measurements in direct-drive inertial confinement fusion at the OMEGA laser facility

Millimeter-sized CD foils fielded close (order mm) to inertial confinement fusion (ICF) implosions have been proposed as a game-changer for improving energy resolution and allowing time-resolution in neutron spectrum measurements using the magnetic recoil technique. This paper presents results from initial experiments testing this concept for direct drive ICF at the OMEGA Laser Facility. Additionally, while the foils are shown to produce reasonable signals, inferred spectral broadening is seen to be high (~5 keV) and signal levels are low (by ~20%) compared to expectation. Before this type of foil is used for precision experiments, the foil mount must be improved, oxygen uptake in the foils must be better characterized, and impact of uncontrolled foil motion prior to detection must be investigated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

An x-ray penumbral imager for measurements of electron–temperature profiles in inertial confinement fusion implosions at OMEGA

Hot-spot shape and electron temperature (T e ) are key performance metrics used to assess the efficiency of converting shell kinetic energy into hot-spot thermal energy in inertial confinement fusion implosions. X-ray penumbral imaging offers a means to diagnose hot-spot shape and T e , where the latter can be used as a surrogate measure of the ion temperature (T i ) in sufficiently equilibrated hot spots. We have implemented a new x-ray penumbral imager on OMEGA. We demonstrate minimal line-of-sight variations in the inferred T e for a set of implosions. Furthermore, we demonstrate spatially resolved T e measurements with an average uncertainty of 10% with 6 μm spatial resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Neural network for 3D inertial confinement fusion shell reconstruction from single radiographs

In inertial confinement fusion (ICF), x-ray radiography is a critical diagnostic for measuring implosion dynamics, which contain rich three-dimensional (3D) information. Traditional methods for reconstructing 3D volumes from 2D radiographs, such as filtered backprojection, require radiographs from at least two different angles or lines of sight (LOS). In ICF experiments, the space for diagnostics is limited, and cameras that can operate on fast timescales are expensive to implement, limiting the number of projections that can be acquired. To improve the imaging quality as a result of this limitation, convolutional neural networks (CNNs) have recently been shown to be capable of producing 3D models from visible light images or medical x-ray images rendered by volumetric computed tomography. Here, we propose a CNN to reconstruct 3D ICF spherical shells from single radiographs. We also examine the sensitivity of the 3D reconstruction to different illumination models using preprocessing techniques such as pseudo-flatfielding. To resolve the issue of the lack of 3D supervision, we show that training the CNN utilizing synthetic radiographs produced by known simulation methods allows for reconstruction of experimental data as long as the experimental data are similar to the synthetic data. We also show that the CNN allows for 3D reconstruction of shells that possess low mode asymmetries. Further comparisons of the 3D reconstructions with direct multiple LOS measurements are justified.

3D Reconstruction↗
DOE OSTI2021

Robust analysis of space-, time-, and energy-resolved soft x-ray measurements of magnetically confined fusion plasmas (invited)

A novel compact multi-energy soft x-ray (ME-SXR) diagnostic based on the PILATUS3 100K x-ray detector has been developed in collaboration between the Princeton Plasma Physics Laboratory and the University of Wisconsin-Madison and tested on the Madison Symmetric Torus (MST) reversed-field pinch. This solid-state photon-counting detector consists of a two-dimensional array of ~100 000 pixels for which the lower photon absorption cutoff energy can be independently set, allowing it to be configured for a unique combination of simultaneous spatial, spectral, and temporal resolution of ~1 cm, 100 eV, and 500 Hz, respectively. The diagnostic is highly versatile and can be readily adapted to diverse plasma operating conditions and scientific needs without any required downtime. New results from improved-confinement and quasi-single helicity plasmas in the MST demonstrate how the detector can be applied to study multiple aspects of the evolution of magnetically confined fusion-grade plasmas. These include observing the evolution of thermal emissivity, characterizing the energy of mid-Z excitation lines, extracting the T e profile, and observing the evolution of non-thermal populations. A technique for integrating the ME-SXR diagnostic into an integrated data analysis framework based on Bayesian inference is also presented. As a result, this allows ME-SXR measurements to be combined with data for complementary diagnostics in order to simultaneously infer Te and nZ from all available information.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Toward exascale whole-device modeling of fusion devices: Porting the GENE gyrokinetic microturbulence code to GPU

GENE solves the five-dimensional gyrokinetic equations to simulate the development and evolution of plasma microturbulence in magnetic fusion devices. The plasma model used is close to first principles and computationally very expensive to solve in the relevant physical regimes. In order to use the emerging computational capabilities to gain new physics insights, several new numerical and computational developments are required. Here, we focus on the fact that it is crucial to efficiently utilize GPUs (graphics processing units) that provide the vast majority of the computational power on such systems. In this paper, we describe the various porting approaches considered and given the constraints of the GENE code and its development model, justify the decisions made, and describe the path taken in porting GENE to GPUs. We introduce a novel library called gtensor that was developed along the way to support the process. Performance results are presented for the ported code, which in a single node of the Summit supercomputer achieves a speed-up of almost 15× compared to running on central processing unit (CPU) only. Typical GPU kernels are memory-bound, achieving about 90% of peak. Our analysis shows that there is still room for improvement if we can refactor/fuse kernels to achieve higher arithmetic intensity. We also performed a weak parallel scalability study, which shows that the code runs well on a massively parallel system, but communication costs start becoming a significant bottleneck.

Germaschewski, K. (ORCID:0000000284956354)↗
DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗
DOE OSTI2021

Volumetric recombination in EMC3-EIRENE: Implementation and first application to the pre-fusion power operation phase in ITER

An upgrade to the 3D plasma boundary model EMC3-EIRENE for detached divertor plasmas is introduced and evaluated. Stabilization of the iterative approximation of a self-consistent plasma–neutral gas solution is required at low divertor plasma temperatures, and this has been achieved by linearization of the energy loss term associated with the electron–neutral gas interaction. An implicit method for volumetric recombination has been implemented, which improves agreement with SOLPS-ITER results for the pre-fusion power operation phase in ITER. Resonant magnetic perturbations for control of edge localized modes are found to result in a partially detached divertor plasma with a significantly broader reduction of particle loads in the traditional strike zone, which is attributed to volumetric recombination. The additional non-axisymmetric far scrape-off layer strike points, on the other hand, remain attached at relatively high temperature so that volumetric recombination is not effective there.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A laser powder bed fusion system for operando synchrotron x-ray imaging and correlative diagnostic experiments at the Stanford Synchrotron Radiation Lightsource

Laser powder bed fusion (LPBF) is a highly dynamic multi-physics process used for the additive manufacturing (AM) of metal components. Improving process understanding and validating predictive computational models require high-fidelity diagnostics capable of capturing data in challenging environments. Synchrotron x-ray techniques play a vital role in the validation process as they are the only in situ diagnostic capable of imaging sub-surface melt pool dynamics and microstructure evolution during LPBF-AM. In this article, a laboratory scale system designed to mimic LPBF process conditions while operating at a synchrotron facility is described. The system is implemented with process accurate atmospheric conditions, including an air knife for active vapor plume removal. Significantly, the chamber also incorporates a diagnostic sensor suite that monitors emitted optical, acoustic, and electronic signals during laser processing with coincident x-ray imaging. The addition of the sensor suite enables validation of these industrially compatible single point sensors by detecting pore formation and spatter events and directly correlating the events with changes in the detected signal. Experiments in the Ti–6Al–4V alloy performed at the Stanford Synchrotron Radiation Lightsource using the system are detailed with sufficient sampling rates to probe melt pool dynamics. X-ray imaging captures melt pool dynamics at frame rates of 20 kHz with a 2 µm pixel resolution, and the coincident diagnostic sensor data are recorded at 470 kHz. Furthermore, this work shows that the current system enables the in situ detection of defects during the LPBF process and permits direct correlation of diagnostic signatures at the exact time of defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bootstrap estimation of the effect of instrument response function uncertainty on the reconstruction of fusion neutron sources

Neutron imagers are important diagnostics for the inertial confinement fusion implosions at the National Ignition Facility. They provide two- and three-dimensional reconstructions of the neutron source shape that are key indicators of the overall performance. To interpret the shape results properly, it is critical to estimate the uncertainty in those reconstructions. There are two main sources of uncertainties: limited neutron statistics, leading to random errors in the reconstructed images, and incomplete knowledge of the instrument response function (the pinhole-dependent point spread function). While the statistical errors dominate the uncertainty for lower yield deuterium-tritium (DT) shots, errors due to the instrument response function dominate the uncertainty for DT yields on the order of 10 16 neutrons or higher. In this work, a bootstrapping method estimates the uncertainty in a reconstructed image due to the incomplete knowledge of the instrument response function. The main reconstruction is created from the fixed collection of pinhole images that are best aligned with the neutron source. Additional reconstructions are then built using subsets of that collection of images. Variations in the shapes of these additional reconstructions originate solely from uncertainties in the instrument response function, allowing us to use them to provide an additional systematic uncertainty estimate.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Constraining time-dependent ion temperature measurements in inertial confinement fusion (ICF) implosions with an intermediate distance neutron time-of-flight (nToF) detector

A concept for using an intermediate distance (0.3–3.0 m) neutron time-of-flight (nToF) to provide a constraint on the measurement of the time-dependence of ion temperature in inertial confinement fusion implosions is presented. Simulated nToF signals at different distances are generated and, with a priori knowledge of the burn-averaged quantities and burn history, analyzed to determine requirements for a future detector. Results indicate a signal-to-noise ratio >50 and time resolution <20 ps to constrain the ion temperature gradient to ∼±25% (0.5 keV/100 ps).

Moore, A. S. (ORCID:0000000221258882)↗
DOE OSTI2022

Instrument design for an inertial confinement fusion ion temperature imager

A mix of contaminant mass is a known, performance-limiting factor for laser-driven inertial confinement fusion (ICF). It has also recently been shown that the contaminant mass is not necessarily in thermal equilibrium with the deuterium–tritium plasma. Contaminant mass temperature is one of the dominant uncertainties in contaminant mass estimates. The MixIT diagnostic is a new and potentially transformative diagnostic, capable of spatially resolving ion temperature. The approach combines principles of neutron time-of-flight and neutron imaging diagnostics. The information from the MixIT diagnostic can be used to optimize ICF target and laser drive designs as well as provide key constraints on ICF radiation-hydrodynamic simulations that are critical to contaminant mass estimates. This work details the design and optimization of the major components of the MixIT diagnostic: the neutron aperture, the neutron detector (scintillator), and the recording system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The Vacuum Cherenkov Detector (VCD) for γ-ray measurements in inertial confinement fusion experiments

Inertial confinement fusion experiments at both the National Ignition Facility (NIF) and the Laboratory for Laser Energetics OMEGA laser facility currently utilize Cherenkov detectors, with fused silica as the Cherenkov medium. At the NIF, the Quartz Cherenkov Detectors improve the precision of neutron time-of-flight measurements; and at OMEGA, the Diagnostic for Areal Density provides measurements of capsule shell areal densities. An inherent property of fused silica is the radiator’s relatively low energy threshold for Cherenkov photon production (E threshold < 1 MeV), making it advantageous over gas-based Cherenkov detectors for experiments requiring low-energy γ detection. The Vacuum Cherenkov Detector (VCD) has been specifically designed for efficient detection of low energy γ’s. Its primary use is in implosion experiments, which will study reactions relevant to stellar and big-bang nucleosynthesis, such as T( 4 He,γ) 7 Li, 4 He( 3 He,γ) 7 Be, and 12 C(p,γ) 13 N. Further, the VCD is compatible with LLE’s standard Ten-Inch Manipulator diagnostic insertion module. This work will outline the design and characterization of the VCD as well as provide results from recent experiments conducted at the OMEGA laser facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Observation and diagnostic application of Kr K-shell emission in magnetized liner inertial fusion experiments at Z

In a series of Magnetized Liner Inertial Fusion (MagLIF) experiments performed at the Z pulsed power accelerator of Sandia National Laboratories, beryllium liners filled with deuterium gas pressures in the 4–8 atm range and a tracer amount of krypton were imploded. At the collapse of the cylindrical implosion, temperatures in the 1–3 keV range and atom number densities of ∼1023 cm−3 were expected. The plasma was magnetized with a 10 T axial magnetic field. Krypton was added to the fuel for diagnosing implosion plasma conditions. Krypton K-shell line emission was recorded with the CRITR time-integrated transmission crystal x-ray spectrometer. The observation shows n = 2 to n = 1 line emissions in B-, Be-, Li-, and He-like Kr ions and is characteristic of the highest electron temperatures achieved in the thermonuclear plasma. Detailed modeling of the krypton atomic kinetics and radiation physics permits us to interpret the composite spectral feature, and it demonstrates that the spectrum is temperature sensitive. We discuss temperatures extracted from the krypton data analysis for experiments performed with several filling pressures.

Clapp, J. T. (ORCID:0000000219928146)↗
DOE OSTI2023

Quantum computing for fusion energy science applications

This is a review of recent research exploring and extending present-day quantum computing capabilities for fusion energy science applications. We begin with a brief tutorial on both ideal and open quantum dynamics, universal quantum computation, and quantum algorithms. Then, we explore the topic of using quantum computers to simulate both linear and nonlinear dynamics in greater detail. Because quantum computers can only efficiently perform linear operations on the quantum state, it is challenging to perform nonlinear operations that are generically required to describe the nonlinear differential equations of interest. In this work, we extend previous results on embedding nonlinear systems within linear systems by explicitly deriving the connection between the Koopman evolution operator, the Perron–Frobenius evolution operator, and the Koopman–von Neumann evolution (KvN) operator. We also explicitly derive the connection between the Koopman and Carleman approaches to embedding. Extension of the KvN framework to the complex-analytic setting relevant to Carleman embedding, and the proof that different choices of complex analytic reproducing kernel Hilbert spaces depend on the choice of Hilbert space metric are covered in the appendixes. Finally, we conclude with a review of recent quantum hardware implementations of algorithms on present-day quantum hardware platforms that may one day be accelerated through Hamiltonian simulation. We discuss the simulation of toy models of wave–particle interactions through the simulation of quantum maps and of wave–wave interactions important in nonlinear plasma dynamics.

Joseph, I. (ORCID:0000000255400840)↗
DOE OSTI2023

Advanced data analysis in inertial confinement fusion and high energy density physics

Bayesian analysis enables flexible and rigorous definition of statistical model assumptions with well-characterized propagation of uncertainties and resulting inferences for single-shot, repeated, or even cross-platform data. This approach has a strong history of application to a variety of problems in physical sciences ranging from inference of particle mass from multi-source high-energy particle data to analysis of black-hole characteristics from gravitational wave observations. The recent adoption of Bayesian statistics for analysis and design of high-energy density physics (HEDP) and inertial confinement fusion (ICF) experiments has provided invaluable gains in expert understanding and experiment performance. In this Review, we discuss the basic theory and practical application of the Bayesian statistics framework. We highlight a variety of studies from the HEDP and ICF literature, demonstrating the power of this technique. Due to the computational complexity of multi-physics models needed to analyze HEDP and ICF experiments, Bayesian inference is often not computationally tractable. Two sections are devoted to a review of statistical approximations, efficient inference algorithms, and data-driven methods, such as deep-learning and dimensionality reduction, which play a significant role in enabling use of the Bayesian framework. We provide additional discussion of various applications of Bayesian and machine learning methods that appear to be sparse in the HEDP and ICF literature constituting possible next steps for the community. We conclude by highlighting community needs, the resolution of which will improve trust in data-driven methods that have proven critical for accelerating the design and discovery cycle in many application areas.

47 OTHER INSTRUMENTATION↗