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Compiler frameworks are crucial for the widespread use of FPGA-based deep learning accelerators. They allow researchers and developers, who are not familiar with hardware engineering, to harness the performance attained by domain-specific logic. There exists a variety of frameworks for conventional artificial neural networks. However, not much research effort has been put into the creation of frameworks optimized for spiking neural networks (SNNs). This new generation of neural networks becomes increasingly interesting for the deployment of AI on edge devices, which have tight power and resource constraints. Our end-to-end framework E3NE automates the generation of efficient SNN inference logic for FPGAs. Based on a PyTorch model and user parameters, it applies various optimizations and assesses trade-offs inherent to spike-based accelerators. Multiple levels of parallelism and the use of an emerging neural encoding scheme result in an efficiency superior to previous SNN hardware implementations. For a similar model, E3NE uses less than 50% of hardware resources and 20% less power, while reducing the latency by an order of magnitude. Furthermore, scalability and generality allowed the deployment of the large-scale SNN models AlexNet and VGG. [ABSTRACT FROM AUTHOR]

For n ≥ 2 , we obtain Liouville type theorems for the minimal surface equation in half space R + n with constant Neumann boundary value or linear Dirichlet boundary value. [ABSTRACT FROM AUTHOR]

A conspicuous emission phenomenon of luminous particles from the liquid anode surface of an atmospheric pressure DC glow discharge is reported. The emission has been shown to occur when the plasma forms a pattern on the surface of the liquid electrolyte. The spatial-temporal evolutions of the trajectories of emitted particles were studied using a high-speed imaging system. Particles were sampled in flight using a witness plate for analysis. Critical particle characteristics were examined using electron microscope technologies. The morphology of the resulting splats and compositions suggest that they are molten droplets with a great deal of structure, including evidence of nanoprecipitation. A theoretical model was employed to estimate the particle size from the measured splats, which provides a radius range within a hundred micrometers. This experiment leads to the postulation of a mechanism in which particle emission at the plasma liquid interface is likely driven by the Taylor cone effect. [ABSTRACT FROM AUTHOR]

Background: Hypertension and diabetes mellitus are two of the major risk factors for cardio-cerebrovascular diseases (CVDs). Although prior studies have confirmed that the coexistence of the two can markedly increase the risk of CVDs, few studies investigated whether potential interaction effects of hypertension and diabetes can result in greater cardio-cerebrovascular damage. We aimed to investigate the prevalence of hypertension and diabetes and whether they both affect synergistically the risk of CVDs.Methods: A cross-sectional study was conducted by using a multistage stratified random sampling among communities in Changsha City, Hunan Province. Study participants aged > = 18 years were asked to complete questionnaires and physical examinations. Multivariate logistic regression models were performed to evaluate the association of diabetes, hypertension, and their multiplicative interaction with CVDs with adjustment for potential confounders. We also evaluated additive interaction with the relative excess risk ratio (RERI), attribution percentage (AP), synergy index (SI).Results: A total of 14,422 participants aged 18-98 years were collected (men = 5827, 40.7%). The prevalence was 22.7% for hypertension, 7.0% for diabetes, and 3.8% for diabetes with hypertension complication, respectively. Older age, women, higher educational level, unmarried status, obesity (central obesity) were associated with increased risk of hypertension and diabetes. We did not find significant multiplicative interaction of diabetes and hypertension on CVDs, but observed a synergistic additive interaction on coronary heart disease (SI, 1.43; 95% CI, 1.03-1.97; RERI, 1.94; 95% CI, 0.05-3.83; AP, 0.26; 95% CI, 0.06-0.46).Conclusions: Diabetes and hypertension were found to be associated with a significantly increased risk of CVDs and a significant synergistic additive interaction of diabetes and hypertension on coronary heart disease was observed. Participants who were old, women, highly educated, unmarried, obese (central obese) had increased risk of diabetes and hypertension. [ABSTRACT FROM AUTHOR]

Subpicosecond coincidence timing from nonlocal intensity interference of entangled photons allows quantum interferometry for plasmas. Using a warm plasma dispersion relation, we correlate phase measurement sensitivity with different plasma properties or physics mechanisms over six orders of magnitude. Due to N α (α ≤ − 1 / 2) scaling with the photon number N, quantum interferometry using entangled light can probe small signals in plasmas not previously accessible. As an example, it is predicted that plasmas will induce shifts to a Gaussian dip, a well-known quantum optics phenomenon that is yet to be demonstrated for plasmas. [ABSTRACT FROM AUTHOR]

The continuing improvement in quantum efficiency (above 90% for single visible photons), reduction in noise (below 1 electron per pixel), and shrink in pixel pitch (less than 1 μm) enable billion-pixel x-ray cameras (BiPC-X) based on commercial complementary metal–oxide–semiconductor (CMOS) imaging sensors. We describe BiPC-X designs and prototype construction based on flexible tiling of commercial CMOS imaging sensors with millions of pixels. Device models are given for direct detection of low energy x rays (<10 keV) and indirect detection of higher energies using scintillators. Modified Birks's law is proposed for light yield non-proportionality in scintillators as a function of x-ray energy. Single x-ray sensitivity and spatial resolution have been validated experimentally using a laboratory x-ray source and the Argonne Advanced Photon Source. Possible applications include wide field-of-view or large x-ray aperture measurements in high-temperature plasmas, the state-of-the-art synchrotron, x-ray free electron laser, and pulsed power facilities. [ABSTRACT FROM AUTHOR]

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization. [ABSTRACT FROM AUTHOR]

With the increasing popularity of data-intensive applications in data centers, the switching fabric in the internode network becomes significant. Silicon-photonic switching fabrics have a bright future in data centers, which offer high bandwidth, high energy efficiency, and low latency. However, integrating a high radix multistage switching fabric in a single chip faces challenges. A large number of waveguide crossings on the silicon photonic die causes massive power loss and introduces a tremendous amount of crosstalk noise. In this article, we propose a chip partition optimization platform (POP), which can decrease the number of waveguide crossings and shorten the on-chip traversal distance of optical signals. Our algorithms can effectively reduce the power loss and crosstalk noise in silicon-photonic multistage switching fabrics, and help to improve the signal integrity. For example, compared with the common design, POP can achieve 33-dB improvement on average power loss, 42-dB improvement on the worst-case power loss, and 39-dB improvement on the worst-case signal to noise ratio, in a $1024\times1024$ butterfly based silicon-photonic switching fabric. [ABSTRACT FROM AUTHOR]

While many new applications prefer manycore processor with a large number of cores, the exploding communications among multiple cores, caches, and off-chip memories is posing a fundamental challenge on manycore designs. Silicon photonics-based interconnection network promises high bandwidth, low latency, and high energy efficiency, and can potentially meet the communication requirements of manycore processors. In this paper, we propose CAMON, a small low-cost silicon photonic chiplet integrated into the manycore processor package. CAMON chiplet can effectively alleviate the communication bottlenecks of manycore processors and improve the energy efficiency of data movement, especially for large-scale systems. We develop a distributed arbitration system, a low-power low-latency optical interface, and an off-chip laser preactivation mechanism for CAMON. The experimental results show that compared with the electrical network, CAMON can improve the full-system performance per energy by $4.6\times $ , speedup the manycore processor by $2.7\times $ , and save the area of the processor die by 3%, in a 512-core system. [ABSTRACT FROM AUTHOR]

Rack-scale computing systems are promising to undertake the emerging large-scale applications by distributing massive tasks to processing cores. The communication and coordination efficiency of these tasks and resources directly affect the system performance and energy consumption. Silicon photonic interconnects are expected to address the communication and system power consumption challenges imposed on rack-scale systems. However, the control for optical interconnects can cause server performance degradation if not properly designed, especially for the complicated and time-consuming multidomain networks. In this paper, we study the optical interconnects for rack-scale computing systems and propose a new communication flow and control scheme for the efficient coordination of distributed resources. Particularly, we first propose a forward propagation strategy that parallels the path reservation process with the distributed tasks connection setup. Second, we develop a pre-emptive chain feedback (PCF) scheme to optimize multidomain path reservation. The PCF scheme pre-emptively allocates network resources with the help of multicell reservation window and quickly releases resources with a feedback mechanism. This solution increases the network resources utilization and task coordination efficiency while minimizing path reservation overheads. Comparing to the baseline InfiniBand network fabric and handshake scheme, PCF can improve network throughput greatly under uniform and hotspot traffic patterns. Realistic benchmark results show that the PCF scheme on average reduces 52% and 60% energy consumption per unit system performance than InfiniBand and the handshake scheme for a 256-node rack system. [ABSTRACT FROM AUTHOR]

Oceans of image and particle track data encountered in plasma interactions with microparticle clouds motivate development and applications of machine-learning (ML) algorithms. A local-constant-velocity tracker, a Kohonen neural network or self-organizing map, the feature tracking kit, and U-Net are described and compared with each other for microparticle cloud datasets generated from exploding wires, dusty plasmas, and atmospheric plasmas. Particle density and the signal-to-noise ratio have been identified as two important factors that affect the tracking accuracy. Fast Fourier transform is used to reveal how U-Net, a deep convolutional neural network developed for non-plasma applications, achieves the improvements for noisy scenes. Viscous effects are revealed in the ballistic motions of the particles from the exploding wires and atmospheric plasmas. Subdiffusion of microparticles satisfying Δ r 2 ∝ t k (k = 0.84 ± 0.02) is obtained from the dusty plasma datasets. Microparticle cloud imaging and tracking, when enhanced with data and ML models, present new possibilities for plasma physics. [ABSTRACT FROM AUTHOR]

Anti-miR21 and resveratrol (RSV)-loaded mesoporous silica nanoparticles (MSNs) conjugated with hyaluronic acid (HA) were developed to enhance therapeutic efficacy in gastric carcinoma. The surface conjugation of HA, which acts as a targeting ligand to the overexpressed CD44 receptor on gastric cancer cells, was clearly identified by the presence of a greyish shell on the dark MSNs. Confocal laser-scanning microscopy and flow cytometry analysis showed higher cellular internalisation of HA/RSVmirNP compared to RSVmirNP. In vitro cytotoxicity and apoptosis assays confirmed the superior anticancer effect of the optimised formulation and synergistic effects of anti-miR21 and RSV in gastric cancer cells. Importantly, HA/RSVmirNP showed significant (p <.001) reductions in the tumour burden compared to the other group. Indeed, HA/RSVmirNP showed a threefold higher tumour regression effect compared to that of free RSV and a twofold tumour regression effect compared to that of RSVmirNP, indicating its anticancer efficacy. The percentage of TUNEL-positive cells was significantly higher in HA/RSVmirNP-treated cells compared to any other group, indicating that the mechanism underlying the superior anticancer efficacy of HA/RSVmirNP included apoptosis and cell necrosis. Thus, a combination of anti-miR21 and RSV in a targeted nanocarrier might be a promising drug delivery system for gastric cancer therapy. [ABSTRACT FROM AUTHOR]

Let Ω ⊊ R n (n ≥ 2) be an unbounded convex domain. We study the minimal surface equation in Ω with boundary value given by the sum of a linear function and a bounded uniformly continuous function in R n. If Ω is not a half space, we prove that the solution is unique. If Ω is a half space, we prove that graphs of all solutions form a foliation of Ω × R. This can be viewed as a stability type theorem for Edelen-Wang's Bernstein type theorem in [10]. We also establish a comparison principle for the minimal surface equation in Ω. [ABSTRACT FROM AUTHOR]

Let γ be the Gauss measure on ℝ: We establish a Calderón-Zygmund type decomposition and a John-Nirenberg type inequality in terms of the local sharp maximal function and the median value of function over cubes. As an application, we obtain an equivalent characterization of known BMO space with Gauss measure. [ABSTRACT FROM AUTHOR]

In this paper, the efficiency of catalysis of nickel acetylacetonate in the thermal cure and ceramization of a new liquid polymeric precursor (methyl-terminated vinyl-containing oligomethylsilane, PSI) of SiC was investigated. The new liquid PSI was prepared by Wurtz condensation method using lithium as reductant. Under nitrogen atmosphere, the thermal cure was preformed through the mechanism of hydrosilylation, dehydrogen and vinyl polymerization; with the addition of Ni(acac) 2 or Co(acac) 3 as catalyst, the cure reaction was promoted to proceed at credibly decreased temperature, especially when using Ni(acac) 2 as catalyst. With the increase of Ni(acac) 2 amount, the thermal curing exotherm of PSI precursor shifted to lower temperatures gradually. Upon pyrolysis, the ceramic yield of PSI precursor was highly improved by catalysis of Ni(acac) 2 . With the increase of Ni(acac) 2 amount, the ceramic yield of PSI precursor was highly increased from 53% to 77%; the growth of crystalline phase was accelerated at the same time. The elements in the pyrolyzed β-SiC were observed to distribute uniformly at micro-scale. The results showed that the catalyst Ni(acac) 2 could accelerate thermal cure, promote ceramic crystallization and improve the SiC ceramic yield of PSI precursor. [ABSTRACT FROM AUTHOR]

A multilayer surface detector for ultracold neutrons (UCNs) is described. The top 10 B layer is exposed to vacuum and directly captures UCNs. The ZnS:Ag layer beneath the 10 B layer is a few microns thick, which is sufficient to detect the charged particles from the 10 B(n,α) 7 Li neutron-capture reaction, while thin enough that ample light due to α and 7 Li escapes for detection by photomultiplier tubes. A 100-nm thick 10 B layer gives high UCN detection efficiency, as determined by the mean UCN kinetic energy, detector materials, and other parameters. Low background, including negligible sensitivity to ambient neutrons, has also been verified through pulse-shape analysis and comparison with other existing 3 He and 10 B detectors. This type of detector has been configured in different ways for UCN flux monitoring, development of UCN guides and neutron lifetime research. [ABSTRACT FROM AUTHOR]

Chip multiprocessor (CMP) is becoming increasingly popular in the processor industry. Efficient network-on-chip (NoC) that has similar performance to the processor cores is important in CMP design. Fat-tree-based on-chip network has many advantages over traditional mesh or torus-based networks in terms of throughput, power efficiency, and latency. It has a bright future in the development of CMP. However, the floorplan design of the fat-tree-based NoC is very challenging because of the complexity of topology. There are a large number of crossings and long interconnects, which cause severe performance degradation in the network. In electronic NoCs, the parasitic capacitance and inductance will be significant. In optical ones, large crosstalk noise and power loss will be introduced. The novel contribution of this paper is to propose a method to optimize the fat-tree floorplan, which can effectively reduce the number of crossings and minimize the interconnect length. Two types of floorplans are proposed, which could be applied to fat-tree-based networks of arbitrary size. Compared with the traditional one, our floorplans could reduce more than 87% of the crossings. Since the traversal distance for signals is related to the aspect ratio of the processor cores, we also present a method to calculate the optimum aspect ratio of the processor cores to minimize the traversal distance. [ABSTRACT FROM AUTHOR]

Abstract: Both neutron absorption and elastic scattering can be used to measure neutron momentum. Based on elastic collisions, the linear momentum of a fast neutron can be measured from as few as two consecutive recoil ion tracks plus the vertex position of the third collision, or ‘two and half’ ion tracks. If the time delay between the first two consecutive ion tracks is also measured, the number of ion tracks can be reduced to one and a half. The angular and magnitude resolutions are limited by ion range straggling to about 10%. Multi-wire proportional chambers and light-field imaging can be used for fast neutron tracking. Light-field imaging is free of charge-diffusion-induced image blur, but the limited number of photons available can be a challenge. 1H, 2H and 3He could be used for the initial development of fast neutron trackers based on light-field imaging. [Copyright &y& Elsevier]

Abstract: A detector efficiency model based on energy extraction from neutrons is described and used to compare 4He detectors with liquid scintillators (EJ301/NE-213). Detector efficiency can be divided into three regimes: single neutron scattering, multiple neutron scattering, and a transition regime in-between. For an average fission neutron of 2MeV, the amount of 4He needed would be about 1/4 of the amount of the mass of EJ301/NE-213 in the single-scattering regime. For about 50% neutron energy extraction (1MeV out of 2MeV), the two types of detectors (4He in the transition regime, EJ301 still in the single-scattering regime) have comparable mass, but 4He detectors can be much larger depending on the number density. A six-tube 11-bar-pressure 4He detector prototype is built and tested. Individual electrical pulses from the detector are recorded using a 12-bit digitizer. Differences in pulse rise time and amplitudes, due to different energy loss of neutrons and gamma rays, are used for neutron/gamma separation. Several energy spectra are also obtained and analyzed. [Copyright &y& Elsevier]

A convenient method to accelerate simultaneously hundreds of micron-size dust particles to a few km/s over a distance of about 1 m is based on plasma drag. Plasma jets which can deliver sufficient momentum to the dust particles need to have speeds of at least several tens of km/s, densities of the order of 1022 m-3 or higher, and low temperature ∼1 eV, in order to prevent dust destruction. An experimental demonstration of dust particles acceleration to hypervelocities by plasma produced in a coaxial gun is presented here. The plasma flow speed is deduced from photodiode signals while the plasma density is measured by streaked spectroscopy. As a result of the interaction with the plasma jet, the dust grains are also heated to high temperatures and emit visible light. A hypervelocity dust shower is imaged in situ with a high speed video camera at some distance from the coaxial gun, where light emission from the plasma flow is less intense. The bright traces of the flying microparticles are used to infer their speed and acceleration by employing the time-of-flight technique. A simple model for plasma drag which accounts for ion collection on the grain surface gives predictions for dust accelerations which are in good agreement with the experimental observations. [ABSTRACT FROM AUTHOR]

This Special Issue of the IEEE Transactions on Plasma Science (TPS) follows the first American Physical Society Division of Plasma Physics (APS-DPP) mini-conference on Machine Learning, Data Science, and Artificial Intelligence in Plasma Research held during the 60th APS-DPP Meeting in Portland, OR, USA (November 5–9, 2018). It contains selected highlights from not only the mini-conference but also the broader plasma physics community. Although data science has a long and rich history in plasma physics, dating back at least three decades, it is experiencing a renaissance, thanks in large part to the advances outside of plasma physics. Novel algorithms, hardware, and analytic techniques (buoyed by the open source software ecosystem) have led plasma scientists to explore ways in which the data revolution could accelerate and inform scientific discovery. Emerging data-driven methods could have a transformative effect across the full spectrum of plasma research. For fusion energy research, some areas of opportunities [item 1) in the Appendix] include using machine learning (ML) or data methods for scientific discoveries, augmented instrumentation, accelerated model development and simulations, data-informed intelligent controls of the experiment, and data-enhanced predictions. The DPP mini-conference and the articles herein represent only a tiny cross section of contemporary research on data-driven plasma science. The 3rd International Conference on Data-Driven Plasma Science (ICDDPS-3) will be held in Okinawa, Japan, in April 2020 [item 2) in the Appendix], with expected presentations on fusion plasmas and low-temperature plasmas and beyond. Furthermore, Plasma Science is not unique in its exploration of Scientific Machine Learning: the Second Workshop on Machine Learning and the Physical Sciences (NeurIPS 2019, Vancouver, BC, Canada, December 2019) and it illustrates a trend in cross disciplinary collaboration with contributions from plasma research. [ABSTRACT FROM AUTHOR]

The physics of microparticle motion in flowing plasmas is studied in detail for plasmas with electron and ion densities ne,i∼1019 m-3, electron and ion temperatures of no more than 15 eV, and plasma flows on the order of the ion thermal speed, vf∼vti. The equations of motion due to Coulomb interactions and direct impact with ions and electrons, of charge variation, as well as of heat exchange with the plasma, are solved numerically for isolated particles (or dust grains) of micron sizes. It is predicted that microparticles can survive in plasma long enough, and can be dragged in the direction of the local ion flow. Based on the theoretical analysis, we describe a new plasma flow measurement technique called microparticle tracer velocimetry (mPTV), which tracks microparticle motion in a plasma with a high-speed camera. The mPTV can reveal the directions of the plasma flow vectors at multiple locations simultaneously and at submillimeter scales, which is hard to achieve by most other techniques. Thus, mPTV can be used to study plasma flows produced in the laboratory. [ABSTRACT FROM AUTHOR]

A Penning-assisted 20 MW coaxial plasma source (plasma gun), which can achieve breakdown at sub-kV voltages, is described. The minimum breakdown voltage is about 400 V, significantly lower than previously reported values of 1–5 kV. The Penning region for electrons is created using a permanent magnet assembly, which is mounted to the inside of the cathode of the coaxial plasma source. A theoretical model for the breakdown is given. A 900 V 0.5 F capacitor bank supplies energy for gas breakdown and plasma sustainment from 4 to 6 ms duration. Typical peak gun current is about 100 kA and gun voltage between anode and cathode after breakdown is about 200 V. A circuit model is used to understand the current-voltage characteristics of the coaxial gun plasma. Energy deposited into the plasma accounts for about 60% of the total capacitor bank energy. This plasma source is uniquely suitable for studying multi-MW multi-ms plasmas with sub-MJ capacitor bank energy. [ABSTRACT FROM AUTHOR]

The Chandrasekhar equilibria form a class of stationary ideal magnetohydrodynamics equilibria stabilized by magnetic-field-aligned Alfvénic flows. Analytic solutions of the Chandrasekhar equilibria are explicitly constructed for both field-reversed configurations and spheromaks. Favorable confinement property of nested closed flux surfaces and the ideal magnetohydrodynamic stability of the compact toroids are of interest for both magnetic trapping of high energy electrons in astrophysics and confinement of high temperature plasmas in laboratory. © 2004 American Institute of Physics. [ABSTRACT FROM AUTHOR]

The temperature-induced swelling and deswelling of thin layers of poly(N-isopropylacrylamide) gels in water was measured as a function of cross-link density and thickness. The collapse behavior was probed via an in situ combination of a quartz-crystal microbalance (QCM) and a surface plasmon resonance (SPR) spectrometer. The shifts in the SPR coupling angle are explained in terms of decrease of the refractive index inside the film. The evanescent optical wave mostly probes the film's interior properties. The acoustic shear wave emanating from the quartz resonator, on the other hand, propagates to the outer surface of the film, unless the film is very dilute. The acoustic data are dominated by the changes in thickness, rather than in its viscosity. The combination of acoustic and optical measurements, therefore, provides complementary information on the film that can be exploited for sensing applications. [ABSTRACT FROM AUTHOR]

Injecting neutral atoms into high-temperature plasmas forms the basis for several important diagnostics, such as motional Stark effect and charge exchange recombination spectroscopy. We describe an alternative approach to seeding the plasma with neutrals, via "hypervelocity dust beam injection" (HDBI), using micron-sized dusts. Among its many potential applications, HDBI mapping of two-dimensional internal magnetic fields inside medium-sized (50-500 eV) plasmas is discussed in detail. Electrostatic acceleration at ∼100-200 kV will launch a stream of (0.2-10 µm-sized) dust grains of lithium or carbon to hypervelocities (1-10 km/s). Each dust grain, acting as a "microcomet" in the plasma, forming a plume (tail), which if photographed, will reveal the direction of the local magnetic field, with anywhere from 10-100 microcomets in the plasma at any time, a full profile of the B-field direction could be obtained per high resolution image. Due to the small dust grain size, the perturbation to the plasma will be minimal. HDBI could be a simple low cost approach to obtain internal magnetic field information in plasmas with magnetic field structures that are significantly different than vacuum fields, such as in spherical tokamaks, FRC's, RFP's, and spheromaks. [ABSTRACT FROM AUTHOR]

A new kind of dynamo utilizing flowing laboratory plasmas has been identified. The conversion of plasma kinetic energy to magnetic energy is verified numerically by kinematic dynamo simulations for magnetic Reynolds numbers above 210. As opposed to intrinsically-turbulent liquid-sodium dynamos, the proposed plasma dynamo corresponds to laminar flow topology. Modest plasma parameters (1–20 eV temperatures, 10[sup 19]–10[sup 20] m[sup -3] densities in 0.3–1.0 m scale-lengths driven by velocities on the order of the Alfve´n critical ionization velocity) self-consistently satisfy the conditions needed for the magnetic field amplication. Growth rates for plasma dynamos are obtained numerically with different geometry and magnetic Reynolds numbers. Magnetic-field-free coaxial plasma guns can be used to sustain the plasma flow and the dynamo. © 2002 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Exact analytic solutions for steady-state magnetized plasma flow (MPF) using ideal magnetohydrodynamics formalism are presented. Several cases are considered. When plasma flow is included, a finite plasma pressure gradient ∇p can be maintained in a force-free state JxB=0 by the velocity gradient. Both incompressible and compressible MPF examples are discussed for a Taylor-state spheromak B field. A new magnetized nozzle solution is given for compressible plasma when U||B. Transition from a magnetized nozzle to a magnetic nozzle is possible when the B field is strong enough. No physical nozzle would be needed in the magnetic nozzle case. Diverging-, drum- and nozzle-shaped MPF solutions when U⊥B are also given. The electric field is needed to balance the UxB term in Ohm's law. The electric field can be generated in the laboratory with the proposed conducting electrodes. If such electric fields also exist in stars and galaxies, such as through a dynamo process, then these solutions can be candidates to explain single and double jets. [ABSTRACT FROM AUTHOR]

A newly installed density diagnostic using CO[sub 2] laser interferometry and an H[sub α] diagnostic using interference filters and photomultiplier tubes for the recently constructed sustained spheromak physics experiment (SSPX) are described. First diagnostic results of the H[sub α] diagnostic were useful to understand the breakdown physics in the new SSPX experiments. Low-noise density data validates techniques to reduce vibration and electronic pickup. The data-processing electronics of the new interferometer can yield unambiguous density data that is equivalent to 16 fringe shifts. Density data is also critical to understand the particle source, and the J/n[sub e] parameter for SSPX. [ABSTRACT FROM AUTHOR]

Fast neutron identification and spectroscopy is of great interest to nuclear physics experiments. Using the neutron elastic scattering, the fast neutron momentum can be measured. Wang and Morris introduced the theoretical concept that the initial fast neutron momentum can be derived from up to three consecutive elastic collisions between the neutron and the target, including the information of two consecutive recoil ion tracks and the vertex position of the third collision or two consecutive elastic collisions with the timing information. Here, we also include the additional possibility of measuring the deposited energies from the recoil ions. In this paper, we simulate the neutron elastic scattering using the Monte Carlo N-Particle Transport Code (MCNP) and study the corresponding neutron detection and tracking efficiency. The corresponding efficiency and the scattering distances are simulated with different target materials, especially natural silicon (92.23% 28 Si, 4.67% 29 Si, and 3.1% 30 Si) and helium-4 ( 4 He). The timing of collision and the recoil ion energy are also investigated, which are important characters for the detector design. We also calculate the ion traveling range for different energies using the software, "The Stopping and Range of Ions in Matter (SRIM)", showing that the ion track can be most conveniently observed in 4 He unless sub-micron spatial resolution can be obtained in silicon. [ABSTRACT FROM AUTHOR]

Abstract: Intrinsic efficiencies of multi-layer boron-10 thin-film detectors were studied theoretically and experimentally. For multi-layer schemes based on an optimized single-layer film thickness, the practical efficiency is limited to about 42% for thermal neutrons. This is about half the efficiency of a moderated 3He detectors in commercial use for portal monitoring. The efficiency limitation is due to charged particle loss in the boron layers and substrates. The same loss mechanism will prevent all substrate-based boron detectors from ever reaching the intrinsic efficiencies of high-pressure 3He tubes, independent of substrate geometry and material composition. Experimental data also indicate that the multi-layer detector configuration can have an efficiency approaching the theoretical limit. Excellent discrimination has also been achieved using an ionization chamber. [Copyright &y& Elsevier]

Abstract: The design, construction, and performance of a type of sealed 3He drift tubes for neutron detection are presented. Because the 3He pressure is in the 25–300mbar range, the detector costs are not dominated by the 3He gas. Intrinsic neutron detection efficiencies up to 5% have been observed by using high-density polyethylene moderation. Sensitive measurements of the detector lifetime are achieved by monitoring the full-energy peak of the 3He(n, p)3H reaction as a function of time. The neutron peak position shows a 24-h cycle that may be explained by the physical adsorption of gases onto the wall. The estimated lifetimes of the detectors are sufficiently long and therefore, the design and the construction are robust and practical for applications such as fissile material detection. [Copyright &y& Elsevier]

Dust varies from a few nanometers to a fraction of a millimeter in size. Dust also offers essentially unlimited choices in material composition and structure. The potential of dust for high-temperature plasma diagnostic is largely unfulfilled yet. The principles of dust spectroscopy to measure internal magnetic field, microparticle tracer velocimetry to measure plasma flow, and dust photometry to measure heat flux are described. Two main components of the different dust diagnostics are a dust injector and a dust imaging system. The dust injector delivers a certain number of dust grains into a plasma. The imaging system collects and selectively detects certain photons resulted from dust-plasma interaction. One piece of dust gives the local plasma quantity, a collection of dust grains together reveals either two-dimensional (using only one or two imaging cameras) or three-dimensional (using two or more imaging cameras) structures of the measured quantity. A generic conceptual design suitable for all three types of dust diagnostics is presented. [ABSTRACT FROM AUTHOR]

Silicon detectors have been widely used in high energy physics (HEP) experiments. The outstanding properties of silicon detectors include radiation hardness, small material budget, fine spatial resolution, high speed and low cost. Here we report initial results of using a single-bit Monolithic Active Pixel Sensor (MAPS), a leading candidate for the next generation trackers in high luminosity colliders, for hard X-ray imaging. The MAPS responses to X-ray with different energies are obtained and compared with simulation. The observed cluster sizes are larger than that predicted by the Continuous Slowing Down Approximation (CSDA) model, indicating that the charge diffusion process might play an important in the MAPS response to low energy electrons. This work paves the way towards multiple layer ultrafast silicon sensor applications in synchrotrons and XFEL beamlines. [ABSTRACT FROM AUTHOR]

The rocket equation breaks down for micron grains because the number of particles per grain is small compared with that within macroscopic objects. Therefore, the discrete rocket effect replaces the classical continuous rocket effect for micron grains. The discrete rocket effect is due to the fact that ejected mass from a micron grain can be comparable to the total mass for these intermediate size objects. Electron beam and laser ablation are possible means to accelerate micron grains to 10[sup 6] m/s and higher velocity. © 2002 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Recent advances in ghost imaging techniques and X-ray sources such as synchrotrons and, more recently, X-ray free-electron lasers (XFEL) have made X-ray ghost imaging a growing topic of interest. One specific type of ghost imaging utilizes thermal radiation and the measurement of intensity fluctuation correlation to form a true image without the need of a lens. This technique allows for much higher resolution than traditional X-ray imaging for a mesoscopic or even a microscopic object. In addition to this benefit of not requiring a lens, a surprising experiment has shown that, when set up correctly, this type of ghost imaging can provide clear images through the measurement of intensity fluctuation correlation when traditional images through measurements of intensity are blurred due to optical turbulence and vibrations. This turbulence-free technique will help maintain the high resolution of X-ray ghost imaging. How is an image formed from fluctuations in light? And what makes it turbulence-free? Using the concept of two-photon interference, this article provides an introduction to these fundamentally interesting concepts and X-ray ghost imaging. • Point-to-point ghost imaging is a result of two-photon interference. • X-ray ghost imaging provides higher resolution images than traditional imaging. • A correct setup may allow for turbulence-free X-ray ghost imaging. [ABSTRACT FROM AUTHOR]

The use of machine learning (ML) models toward development of validated structure-property relationships for two fundamental properties of activated inorganic scintillators for high energy radiation detection, namely the light yield (LY) and the decay time constant, is explored. The ML models are built on easily accessible proxies of materials—interchangeably referred to as features, descriptors or fingerprints—that are carefully selected on the basis of a physical understanding of the scintillation mechanism. Our study indicates that the developed physics-based ML models employing kernel ridge regression (KRR) and AdaBoost algorithm applied on top of a decision tree-based regression are able to "learn" the underlying design rules in a multi-dimensional feature space and thereby enable reasonably accurate predictions of the two target properties on unseen compounds (i.e., on a held-out test set). For instance, within a set of twenty-five cerium- or europium-doped scintillator materials, our analysis reveals a strong correlation between the average ionic part of the dielectric constant and the LY, irrespective of the specific chemistry of the compounds, indicating that the average ionic part of the dielectric constant is a particularly relevant descriptor toward prediction of the LY. Our results also demonstrate that, despite the use of small training datasets, the developed models are able to quickly distinguish high performing chemistries from those with relatively poor performance and therefore can play a crucial role in screening of new compounds with an attractive combination of targeted properties. The present study provides necessary motivation for future efforts involving ML models with relatively large training datasets, vast feature space explorations, and experimental design in search of promising novel scintillator chemistries. [ABSTRACT FROM AUTHOR]

Images of plasma jets launched in vacuum from a coaxial plasma accelerator are presented. The turbulent plasma jet which includes a multitude of filaments arbitrarily oriented along the propagation direction self-organizes into a more laminar flow later in time. The captured pictures of the flow have exposures of 1 \mu\s or less and were acquired at 45 to 130 \mu\s after firing the coaxial gun. [ABSTRACT FROM AUTHOR]

Biomass-based aerogel materials have many advantages, such as low thermal conductivity and non-toxicity. These materials are environmentally friendly and have broad development potential in the fields of packaging, cushioning and green building insulation. However, defects, such as low mechanical strength and poor fire safety, greatly limit the application of these materials. In this work, the agar/polyvinyl alcohol composite aerogel modified by the magnesium hydroxide (MH)/sodium alginate (SA) composite flame retardant system was developed by using a freeze-dried technology and the strategy of in-situ generation of MH and crosslinking of SA. The results showed that the MH/SA dramatically enhanced the mechanical and thermal stability of the composites. The compression modulus of AP-M35S15 was 2.37 MPa, which was 152.13 % higher than that of AP-M50. The limiting oxygen index value of AP-M35S15 was 34.1 % and reached V -0 level in the vertical burning test, which was better than those of the samples with a single MH effect. The cone calorimetric test showed that the MH/SA composite flame retardant system performed better in extending the ignition time, slowing down the heat release rate and reducing the total heat release and had a more complete dense carbon structure after burning. [ABSTRACT FROM AUTHOR]

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general. [ABSTRACT FROM AUTHOR]

Gigahertz (GHz) imaging using hard x-rays (>=10 keV) can be useful to high-temperature plasma experiments, as well as research and applications using coherent photons from synchrotron radiation and x-ray free electron lasers. GHz framing rate can be achieved by using multiple cameras through multiplexing. The advantages and trade-offs of single-photon detection mode, when no more than one x-ray photon is detected per pixel, are given. Two possible paths towards x-ray imaging at GHz frame rates using a single camera are: (a) avalanche photodiode arrays of high-Z materials and (b) microchannel plate photomultipliers in conjunction with materials with large indices of refraction. [ABSTRACT FROM AUTHOR]

Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei and young stellar objects commonly emit plasma jets in various forms. With the availability of data from plasma jet experiments resembling astrophysical plasma jets, classification of such data would potentially aid in not only investigating the underlying physics of the experiments but also the study of astrophysical jets. In this work we use deep learning to process all of the laboratory plasma images from the Caltech Spheromak Experiment spanning two decades. We found that cosine similarity can aid in feature selection, classify images through comparison of feature vector direction and be used as a loss function for the training of AlexNet for plasma image classification. We also develop a simple vector direction comparison algorithm for binary and multi-class classification. Using our algorithm we demonstrate 93 % accurate binary classification to distinguish unstable columns from stable columns and 92 % accurate five-way classification of a small, labelled data set which includes three classes corresponding to varying levels of kink instability. [ABSTRACT FROM AUTHOR]

Resistive magnetohydrodynamics (MHD) is used to model the electromagnetic acceleration of plasmas in coaxial channels. When the Hall effect is considered, the inclusion of resistivity is necessary to obtain physically meaningful solutions. In resistive MHD with the Hall effect, if and only if the electric current and the plasma flow are orthogonal (J·U=0), then there is a conserved quantity, in the form of U[sup 2]/2+w+e&Fgr;/M, along the flow, where U is the flow velocity, &Fgr; is the electric potential, w is the enthalpy, and M is the ion mass. New solutions suggest that in coaxial geometry the Hall effect along the axial plasma flow can be balanced by proper shaping of conducting electrodes, with acceleration then caused by an electrostatic potential drop along the streamlines of the flow. The Hall effect separation of ion and electron flow then just cancels the electrostatic charge separation. Assuming particle ionization increases with energy density in the system, the resulting particle flow rates (J[sub p]) scales with accelerator bias (V[sub bias]) as J[sub p]∝V[sub bias][sup 2], exceeding the Child–Langmuir limit. The magnitude of the Hall effect (as determined by the Morozov Hall parameter, &Ygr;, which is defined as the ratio of electric current to particle current) is related to the energy needed for the creation of each ion–electron pair. © 2001 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Mixtures of Ce‐doped rare‐earth aluminum perovskites are drawing a significant amount of attention as potential scintillating devices. However, the synthesis of complex perovskite systems leads to many challenges. Designing the A‐site cations with an equiatomic ratio allows for the stabilization of a single‐crystal phase driven by an entropic regime. This work describes the synthesis of a highly epitaxial thin film of configurationally disordered rare‐earth aluminum perovskite oxide (La0.2Lu0.2Y0.2Gd0.2Ce0.2)AlO3 and characterizes the structural and optical properties. The thin films exhibit three equivalent epitaxial domains having an orthorhombic structure resulting from monoclinic distortion of the perovskite cubic cell. An excitation of 286.5 nm from Gd3+ and energy transfer to Ce3+ with 405 nm emission are observed, which represents the potential for high‐energy conversion. These experimental results also offer the pathway to tunable optical properties of high‐entropy rare‐earth epitaxial perovskite films for a range of applications. [ABSTRACT FROM AUTHOR]

Novel polyzirconosilane resin, prepared by Wurtz-Fittig copolymerization, was applied as a single source precursor for SiC-ZrC ceramics preparation. It could be rheologically much easily tailored catering to the precursor-infiltration-pyrolysis process in the production of ceramic composites. Polyzirconosilane resin could be thermally cured at 110-200 °C to form a solidified monolith and finally transformed at 1000-1400 °C to SiC-ZrC monoliths at a yield of around 65 wt%. The polyzirconosilane derived SiC-ZrC exhibited ultra-high thermo-oxidation resistance up to 1200 °C. The polyzirconosilane preceramic resin was an ideal candidate for SiC-ZrC multi-component ceramic under ultra-high temperature oxidation conditions. Graphical Abstract: [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Phenylethynyloligosilane (PEPSI), prepared by lithium condensation, was stable in liquid state after a bench life over one year, and PEPSI can be used as precursor of SiC-C ceramic. The thermal cure occurred readily through polymerization reaction of ethynyl groups and hydrosilylation of Si-H with ethynyl at 230-330 °C. Thermal cure was dramatically accelerated by catalyst addition; among the investigated catalysts of Fe(acac), Co(acac) and Ni(acac), the highest catalysis performance was achieved for Ni(acac). The effect of catalyst amount [1, 2 and 3 % Ni(acac), respectively] on thermal cure and ceramization was studied using DSC, TGA, XRD, and SEM-EDS, etc. The results show: 1 % weight of catalyst Ni(acac) was enough for catalytic thermal cure and pyrolysis; the thermal cure process showed a decrease in the initiation crosslinking temperature from 230 to 120 °C and the peak temperature from 280 to 155 °C; the ceramic yield was improved from 58 to 71 %; the ceramic crystallization was accelerated by catalytic sintering of Ni(acac). [ABSTRACT FROM AUTHOR]