SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Here we report compression of turbulent plasma can amplify the turbulent kinetic energy, if the compression is fast compared to the viscous dissipation time of the turbulent eddies. A sudden viscous dissipation mechanism is demonstrated, whereby this amplified turbulent kinetic energy is rapidly converted into thermal energy, suggesting a new paradigm for fast ignition inertial fusion.
Time-resolved x-ray diffraction (XRD) of compressed liquid water shows transformation to ice VII in 6 nsec, revealing crystallization rather than amorphous solidification during compression freezing. Application of classical nucleation theory indicates heterogeneous nucleation and one-dimensional (e.g., needlelike) growth. In conclusion, these first XRD data demonstrate rapid growth kinetics of ice VII with implications for fundamental physics of diffusion-mediated crystallization and thermodynamic modeling of collision or impact events on ice-rich planetary bodies.
Herein we present the first demonstration of THz driven bunch compression and timing stabilization of a relativistic electron beam. Quasi-single-cycle strong field THz radiation is used in a shorted parallel-plate structure to compress a few-fC beam with 2.5 MeV kinetic energy by a factor of 2.7, producing a 39 fs rms bunch length and a reduction in timing jitter by more than a factor of 2 to 31 fs rms. This THz driven technique offers a significant improvement to beam performance for applications like ultrafast electron diffraction, providing a critical step towards unprecedented timing resolution in ultrafast sciences, and other accelerator applications using femtosecond-scale electron beams.
Equation-of-state (pressure, density, temperature, internal energy) and reflectivity measurements on shock-compressed CO 2 at and above the insulating-to-conducting transition reveal new insight into the chemistry of simple molecular systems in the warm-dense-matter regime. CO 2 samples were precompressed in diamond-anvil cells to tune the initial densities from 1.35 g/cm 3 (liquid) to 1.74 g/cm 3 (solid) at room temperature and were then shock compressed up to 1 TPa and 93 000 K. Lastly, variation in initial density was leveraged to infer thermodynamic derivatives including specific heat and Gruneisen coefficient, exposing a complex bonded and moderately ionized state at the most extreme conditions studied.
The ubiquitous nature and unusual properties of water have motivated many studies on its metastability under temperature- or pressure-induced phase transformations. Here, nanosecond compression by a high-power laser is used to create the nonequilibrium conditions where liquid water persists well into the stable region of ice VII. Through our experiments, as well as a complementary theoretical/computational analysis based on classical nucleation theory, we report that the metastability limit of liquid water under nearly isentropic compression from ambient conditions is at least 8 GPa, higher than the 7 GPa previously reported for lower loading rates.
Silicon (Si) exhibits a rich collection of phase transitions under ambient-temperature isothermal and shock compression. This report describes in-situ diffraction measurements of ramp compressed Si between 40 and 389 GPa. Angle-dispersive x-ray scattering reveals that Si assumes an hexagonal close-packed (hcp) structure between 40 and 93 GPa, and, at higher pressure, a face-centered cubic (fcc) structure which persists to at least 389 GPa, the highest pressure for which the crystal structure of Si has been investigated. Furthermore, the range of hcp stability extends to higher pressures and temperatures than predicted by theory.
Chemical compression effects on the ferroic orders in La substituted BiFeO 3 are studied by atomic pair distribution function analysis and structure modeling. While rhombohedral BiFeO 3 exhibits ferroelectricity and antiferromagnetism (AF) with a cycloidal Fe spin arrangement leading to zero magnetization, La substituted BiFeO 3 exhibits a reduced lattice polarization, strengthened AF order, and an apparently suppressed spin cycloid leading to nonzero magnetization. Furthermore, the observed changes in the ferroic orders arise from the chemical compression induced changes in the octahedral rotation and ferroelectric displacement of Bi atoms, which appear as lattice degrees of freedom entangling the electronic and magnetic orders in BiFeO 3 .
Characterizing the fundamental micromechanisms activated during plastic deformation is critical to explain the macroscopic shock response of materials and develop accurate material models. In this paper, we investigate the orientation dependence, and the mediated slip and twin systems on [100] and [111] bcc molybdenum single crystals shock compressed up to 18 GPa with real-time Laue x-ray diffraction measurements. We report that dislocation slip along the {110} < 111 > and {112} < 111 > systems is the governing deformation mechanism during compression with negligible anisotropy observed at the Hugoniot state. Here, we provide real-time evidence that molybdenum undergoes deformation twinning along {11¯2} < 111 > during shock release.
First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon ( e − ph ) interactions being a prime example. However, these techniques use large matrices encoding the interactions on dense momentum grids, which reduces computational efficiency and obscures interpretability. For e − ph interactions, existing interpolation techniques leverage locality in real space, but the high dimensionality of the data remains a bottleneck to balance cost and accuracy. Here we show an efficient way to compress e − ph interactions based on singular value decomposition (SVD), a widely used matrix and image compression technique. Leveraging (un)constrained SVD methods, we accurately predict material properties related to e − ph interactions—including charge mobility, spin relaxation times, band renormalization, and superconducting critical temperature—while using only a small fraction (1%–2%) of the interaction data. These findings unveil the hidden low-dimensional nature of e − ph interactions. Furthermore, they accelerate state-of-the-art first-principles e − ph calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of e − ph interactions can be readily generalized to electron-electron and electron-defect interactions, as well as to other couplings, advancing quantitative studies of condensed matter. Published by the American Physical Society 2024
We demonstrate a blue-detuned magneto-optical trap (MOT) of a polyatomic molecule, calcium monohydroxide (CaOH). We identify a novel MOT frequency configuration that produces high spatial compression of the molecular cloud. This high compression MOT achieves a cloud radius of 59(5) μm and a peak density of 8(2) ×10 8 cm −3 . We experimentally compare several blue-detuned MOT schemes for CaOH and find good agreement between our data and Monte Carlo simulations.
Polychromatic synchrotron undulator X-ray sources are useful for ultrafast single-crystal diffraction under shock compression. Here, simulations of X-ray diffraction of shock-compressed single-crystal tantalum with realistic undulator sources are reported, based on large-scale molecular dynamics simulations. Purely elastic deformation, elastic–plastic two-wave structure, and severe plastic deformation under different impact velocities are explored, as well as an edge release case. Transmission-mode diffraction simulations consider crystallographic orientation, loading direction, incident beam direction, X-ray spectrum bandwidth and realistic detector size. Diffraction patterns and reciprocal space nodes are obtained from atomic configurations for different loading (elastic and plastic) and detection conditions, and interpretation of the diffraction patterns is discussed.
Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-based state estimation approaches (matrix completion and compressive sensing) that have been proposed recently to address the challenge of unobservability. The proposed approach exploits both the low rank structure and a suitable transform domain representation to leverage the correlation structure of the spatio-temporal data matrix while incorporating the powerflow constraints of the distribution grid. Simulations are carried out on three phase unbalanced IEEE 37 test system to verify the effectiveness of the proposed approach. The performance results reveal - (1) the superiority over traditional matrix completion and (2) very low state estimation errors for high compression ratios representing very low observability.
Liquid argon time projection chambers (LArTPCs) have been proposed as neutrino detectors that combine both large sizes to maximize the number of neutrino interactions and detailed recording of the interaction. The readout of thousands of channels at MHz sampling rates produce images of the neutrino-nucleus interaction with millimeter-scale resolution, enabling the identification of the resulting particles and offering multiple handles to measure their energies at the expense of large data rates. Continuous acquisition of the LArTPC data is required to enable the use of high-latency triggers for capturing non-accelerator-beam events. We describe the case of the continuous readout of the MicroBooNE LArTPC, that grants the possibility of acquiring the neutrino burst from a supernova using the SNEWS (Supernova Early Warning System) alert as delayed trigger. The continuous data acquisition is accomplished by using real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA in the readout electronics.
Here, this study measures the voltage at which flashover occurs in compressed air for a variety of dielectric materials and lengths in a uniform field for DC voltages up to 100 kV. Statistical time lag is recorded and characterized, displaying a roughly exponential dependence on breakdown voltage. Of the materials tested, acrylic is observed to be the most resistant to flashover. These data are intended to facilitate the design of compressed-air insulated high voltage systems as an alternative to SF 6 insulated systems.
Despite advances in the programmable logic capabilities of modern trigger systems, a significant bottleneck remains in the amount of data to be transported from the detector to off-detector logic where trigger decisions are made. We demonstrate that a neural network (NN) autoencoder model can be implemented in a radiation-tolerant application-specific integrated circuit (ASIC) to perform lossy data compression alleviating the data transmission problem while preserving critical information of the detector energy profile. For our application, we consider the high-granularity calorimeter from the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider. The advantage of the machine learning approach is in the flexibility and configurability of the algorithm. By changing the NN weights, a unique data compression algorithm can be deployed for each sensor in different detector regions and changing detector or collider conditions. To meet area, performance, and power constraints, we perform quantization-aware training to create an optimized NN hardware implementation. The design is achieved through the use of high-level synthesis tools and the hls4ml framework and was processed through synthesis and physical layout flows based on a low-power (LP)-CMOS 65-nm technology node. The flow anticipates 200 Mrad of ionizing radiation to select gates and reports a total area of 3.6 mm 2 and consumes 95 mW of power. The simulated energy consumption per inference is 2.4 nJ. Furthermore, this is the first radiation-tolerant on-detector ASIC implementation of an NN that has been designed for particle physics applications.
Recent hydraulic bomb and confined sleeve tests on transparent armor glass materials such as borosilicate glass and soda-lime glass showed that the glass strength was a function of confinement pressure. The measured stress-strain relation is not a straight line as most brittle materials behave under little or no confinement. Moreover, borosilicate glass exhibited a stronger compressive strength when compared to soda-lime glass, even though soda-lime has higher bulk and shear moduli as well as apparent yield strength. To better understand these experimental findings, a mesoscale phase field model is developed to simulate the nonlinear stress versus strain behaviors under confinement by considering heterogeneity formation under triaxial compression and the energy barrier of a micro shear banding event (referred to as pseudo-slip hereafter) in the amorphous glass. With calibrated modeling parameters, the simulation results demonstrate that the developed phase field model can quantitatively predict the pressure-dependent strength, and it can also explain the difference between the two types of glasses from the perspective of energy barrier associated with a pseudo-slip event.
Because of its exceptional compressive resistance and crystal-clear appearance, lightweight glass has been traditionally used in transparent armor applications. However, due to its brittle nature, glass fails differently from ductile materials in the sense that glass fragmentation occurs instantly ahead of the projectile tip upon penetration. The effective residual strength of the armor glass then inevitably relies on the damaged glass strength within such comminuted zones with confinement from the surrounding intact materials. Physical understanding of damaged glass strength therefore becomes highly critical to the further development of armor designs. In the present study, a discrete element based modeling framework has been developed to understand and predict the evolution of compressive damages and residual strength of armor glasses. With the characteristic fragmentation and comminution failures explicitly resolved, their influences on the mechanical degradation of the loaded glass materials have been evaluated. The effects of essential loading conditions and material properties have also been investigated.
Abstract Here we show that compressive sensing allows 4‐dimensional (4‐D) STEM data to be obtained and accurately reconstructed with both high‐speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4‐D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal‐to‐noise ratio in the recovered phase using 0.3% of the total data. Lay abstract : Four‐dimensional scanning transmission electron microscopy (4‐D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2‐dimensional signal is acquired at each 2‐D probe location, equating to a 4‐D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4‐D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100‐1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4‐D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10‐100 times. The acquired data is then processed to fill‐in or inpaint the missing data, taking advantage of the inherently low‐complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4‐D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4‐D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100‐300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.