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At least 361 records · Page 20

Long-Lived Photocatalysis Centers Created in ZnO via Resonant Exciton Excitation

ZnO together with TiO{sub 2} is a main photocatalyst for various redox reactions to convert light energy into a chemical one and to purify the environment. Intrinsic surface defects in ZnO—the vacancies in anionic and cationic sublattices (F-type and V-type centers)—allow creation of long-lived (up to 10{sup 3} s) photocatalysis centers and, therefore, tenfold increase in quantum yield of reactions. Slow surface states—the photocatalysis centers—appear via diffusion of electrons and holes generated during the interband transitions in the bulk of a photoactivated sample. The transfer efficiency, however, decreases sharply because of recombination of charge carriers and losses during overcoming the surface Schottky barrier. Neutral energy carriers—excitons—were used in this work to decrease these losses during the energy transfer to a surface. High exciton binding energy in ZnO (60 meV) allows it to move at room temperature without decay. The exciton energy loss for radiation is effectively decreased in our experiments via formation of a 2D surface structure. The results confirm high efficiency of exciton channel to form surface long-lived photocatalysis F-centers and V‑centers during the photoadsorption and photodesorption processes of oxygen, which simulate full cycle of a redox photocatalytic reaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On-Orbit Calibration and Performance of NOAA-20 VIIRS Reflective Solar Bands

The NOAA-20 (N20) satellite was launched on November 18, 2017 carrying the second Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. Immediately following the launch, the VIIRS passed a series of intensive calibration and validation tests, after which regular calibration and operation activities have continued successfully for more than three years. The production of NASA Collection 2 Level 1B (C2 L1B) for N20 VIIRS began in summer 2019. In this article, we evaluate the early mission performance of the N20 VIIRS reflective solar bands (RSB) covering the first three full years of operation. The calibrated RSB gains are calculated primarily from the onboard solar diffuser (SD) and used in generating the C2 L1B reflectance and radiance products. We also show the on-orbit performance of the instrument noise, signal-to-noise ratio (SNR), and a reflectance uncertainty assessment. Comparisons are made to the first three years of operation of the first VIIRS instrument, aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We evaluate the long-term stability of the calibrated N20 RSB reflectance product by looking at the long-term trends of lunar observations and data from the pseudo-invariant Libya 4 desert site. The N20 RSB have had excellent early mission performance, with changes in the gain of less than 0.5% in the first three years across all detectors, stable L1B reflectance, and very stable values of detector SNR and reflectance uncertainty.

calibration↗

Cosmic rays and MHD turbulence generation in interstellar giant molecular clouds

The diffusive propagation of nonrelativistic cosmic ray (CR) protons undergoing energy losses by ionization in a dense homogeneous infinitely extended interstellar molecular cloud (MC) is investigated. The steady-state transport equation for the differential number density of nonrelativistic CR protons is solved with the boundary condition that at the edge of cloud it agrees with the interstellar CR number density. It is shown that giant interstellar MCs with column depths much greater than about 7⋅10{sup 22} cm{sup −2} are an efficient sink of nonrelativistic CRs. At small penetration depths the CRs lose energy by ionizing and heating the molecular gas, whereas at large penetration depths they are collectively dissipated by the streaming instability, which transfers one-half of the energy density of the incoming interstellar nonrelativistic CRs to Alfvénic magnetic field turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗

Cathodic electrocatalyst layer for electrochemical generation of hydrogen peroxide

A cathodic gas diffusion electrode for the electrochemical production of aqueous hydrogen peroxide solutions. The cathodic gas diffusion electrode comprises an electrically conductive gas diffusion substrate and a cathodic electrocatalyst layer supported on the gas diffusion substrate. A novel cathodic electrocatalyst layer comprises a cathodic electrocatalyst, a substantially water-insoluble quaternary ammonium compound, a fluorocarbon polymer hydrophobic agent and binder, and a perfluoronated sulphonic acid polymer. An electrochemical cell using the novel cathodic electrocatalyst layer has been shown to produce an aqueous solution having between 8 and 14 weight percent hydrogen peroxide. Furthermore, such electrochemical cells have shown stable production of hydrogen peroxide solutions over 1000 hours of operation including numerous system shutdowns.

Rhodes, Christopher P.↗

Characterization of statistical prior image constrained compressed sensing (PICCS): II. Application to dose reduction

Purpose: The ionizing radiation imparted to patients during computed tomography exams is raising concerns. This paper studies the performance of a scheme called dose reduction using prior image constrained compressed sensing (DR-PICCS). The purpose of this study is to characterize the effects of a statistical model of x-ray detection in the DR-PICCS framework and its impact on spatial resolution. Methods: Both numerical simulations with known ground truth and in vivo animal dataset were used in this study. In numerical simulations, a phantom was simulated with Poisson noise and with varying levels of eccentricity. Both the conventional filtered backprojection (FBP) and the PICCS algorithms were used to reconstruct images. In PICCS reconstructions, the prior image was generated using two different denoising methods: a simple Gaussian blur and a more advanced diffusion filter. Due to the lack of shift-invariance in nonlinear image reconstruction such as the one studied in this paper, the concept of local spatial resolution was used to study the sharpness of a reconstructed image. Specifically, a directional metric of image sharpness, the so-called pseudopoint spread function (pseudo-PSF), was employed to investigate local spatial resolution. Results: In the numerical studies, the pseudo-PSF was reduced from twice the voxel width in the prior image down to less than 1.1 times the voxel width in DR-PICCS reconstructions when the statistical model was not included. At the same noise level, when statistical weighting was used, the pseudo-PSF width in DR-PICCS reconstructed images varied between 1.5 and 0.75 times the voxel width depending on the direction along which it was measured. However, this anisotropy was largely eliminated when the prior image was generated using diffusion filtering; the pseudo-PSF width was reduced to below one voxel width in that case. In the in vivo study, a fourfold improvement in CNR was achieved while qualitatively maintaining sharpness; images also had a qualitatively more uniform noise spatial distribution when including a statistical model. Conclusions: DR-PICCS enables to reconstruct CT images with lower noise than FBP and the loss of spatial resolution can be mitigated to a large extent. The introduction of statistical modeling in DR-PICCS may improve some noise characteristics, but it also leads to anisotropic spatial resolution properties. A denoising method, such as the directional diffusion filtering, has been demonstrated to reduce anisotropy in spatial resolution effectively when it was combined with DR-PICCS with statistical modeling.

60 APPLIED LIFE SCIENCES↗

Double-diffusive effects during solidification

When a fluid contains two diffusing components with different molecular diffusivities, such as heat and solute concentration, convective motion may be generated when potential energy is released owing to differential diffusion. In the solidification of binary alloys and doped semiconductors, temperature and concentration gradients do exist simultaneously. If these gradients are aligned in a suitable manner, convection may ensue. In the case of the binary alloy, such convection may extend through the mushy zone and may be the cause of macrosegregations. In the case of doped semiconductors, the convective motion may cause the nonuniform distribution of dopant in the product. In this paper, the fundamentals of double-diffusive convection will be reviewed, and its effect on solidification will be discussed.

Chen, C. F.↗

An Atmospheric Cloud Physics Laboratory for the Space Laboratory

Results of research and engineering analyses to date show that it is feasible to develop and fly on the first Spacelab mission a multipurpose laboratory in which experiments can be performed on the microphysical processes in atmospheric clouds. The paper presents a series of tables on the Atmospheric Cloud Physics Laboratory, with attention given to experiment classes, the preliminary equipment list (particle generators, optical and imaging devices, particle detectors and characterizers, etc.), initial equipment (scientific equipment subsystems and flight support subsystems), and scientific functional requirements (the expansion chamber, the continuous flow diffusion chamber, the static diffusion chamber, the humidifier, and particle generators).

Smith, R.↗

Solid-State, Single-Ion Conducting, Polymer Blend Electrolytes with Enhanced Li + Conduction, Electrochemical Stability, and Limiting Current Density

The development of solid-state polymer electrolytes with high lithium conductivity is crucial to improve lithium-ion battery performance and ameliorate the safety challenges associated with current solvent-based electrolytes. Unfortunately, sluggish polymer segmental dynamics are known to constrain conductivity enhancements in solid-state polymer electrolyte systems, limiting overall performance. In this work, a glassy single-ion-conducting polymer, poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate] (PLiMTFSI), was blended with a flexible polymer, poly(oligo-oxyethylene methyl ether methacrylate) (POEM), and the impact of PLiMTFSI molecular weight and ion concentration on the thermal and ion-conducting behavior of blend electrolytes was investigated. High ionic conductivities approaching 1 × 10 -2 S/cm at 150 °C were realized in this polymer blend electrolyte system as a result of decoupling Li + transport from polymer segmental dynamics. The decoupled ion transport was attributed to the packing frustration of the glassy PLiMTFSI – sufficient percolating free volume was generated to produce effective ion diffusion pathways. This decoupling was tunable as the ion transport could be altered from being closely coupled to the polymer segmental dynamics (Vogel–Tammann–Fulcher-like) to hopping (Arrhenius-like) by increasing the PLiMTFSI molecular weight and ion concentration. Moreover, the immobilized TFSI anion resulted in high Li + selectivity (Li + transference number = 0.9), high electrochemical stability (up to 4.7 V against Li + / Li), and limiting current density of 1.8 mA/cm 2 (electrolyte thickness = 0.05 cm). These features suggest that this single-ion-conducting, polymer blend electrolyte might be a promising alternative to a benchmark system – salt-doped polyethylene oxide. Moreover, the above characteristics can support the battery operation at higher voltages using energy-dense Li metal anodes, with faster charging rates and enhanced energy/power densities. Altogether, the results suggest that polymer chain packing frustration can be exploited to overcome the constraints of slow polymer segmental relaxations to achieve rapid and highly selective ion transport and enhanced performance in solid-state polymer electrolytes.

36 MATERIALS SCIENCE↗

Stabilized Oxygen Vacancy Chemistry toward High-Performance Layered Oxide Cathodes for Sodium-Ion Batteries

Anionic redox has emerged as a transformative paradigm for high-energy layered transition-metal (TM) oxide cathodes, but it is usually accompanied by the formation of anionic redox-mediated oxygen vacancies (OVs) due to irreversible oxygen release. Additionally, external factor-induced OVs (defined as intrinsic OVs) also play a pivotal role in the physicochemical properties of layered TM oxides. However, an in-depth understanding of the interplay between intrinsic and anionic redox-mediated OVs and the corresponding regulation mechanism of the dynamic evolution of OVs is still missing. Herein, we disclose the strong interrelationship between these OVs and demonstrate that the presence of intrinsic OVs in the TMO2 layers could induce weak integrity of the TM-O frameworks and unlock additional diffusion paths to trigger the generation and migration of anionic redox-mediated OVs. Accordingly, an OV stabilization strategy is proposed by deliberately introducing high-valence Nb5+, which could serve as an important building block in anchoring the oxygen sublattice and preventing the formation of a percolating OV migration network, thereby suppressing the formation/diffusion of anionic redox-mediated OVs. Consequently, superb structural integrity and improved electrochemical performance with reversible anionic redox chemistry are achieved. This work advances our understanding of the role of OVs for developing high-performance energy storage systems utilizing anionic redox.

anionic redox↗

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

54 ENVIRONMENTAL SCIENCES↗

Neuromorphic scaling advantages for energy-efficient random walk computations

Neuromorphic computing, which aims to replicate the computational structure and architecture of the brain in synthetic hardware, has typically focused on artificial intelligence applications. What is less explored is whether such brain-inspired hardware can provide value beyond cognitive tasks. Here we show that the high degree of parallelism and configurability of spiking neuromorphic architectures makes them well suited to implement random walks via discrete-time Markov chains. Overall, these random walks are useful in Monte Carlo methods, which represent a fundamental computational tool for solving a wide range of numerical computing tasks. Using IBM’s TrueNorth and Intel’s Loihi neuromorphic computing platforms, we show that our neuromorphic computing algorithm for generating random walk approximations of diffusion offers advantages in energy-efficient computation compared with conventional approaches. We also show that our neuromorphic computing algorithm can be extended to more sophisticated jump-diffusion processes that are useful in a range of applications, including financial economics, particle physics and machine learning.

97 MATHEMATICS AND COMPUTING↗

The multiple roles of small-angle tilt grain boundaries in annihilating radiation damage in SiC

Lattice defects generated by radiation damage can diffuse to grain boundaries (GBs) and be annihilated at GBs. However, the precise role of GBs in annihilating the segregated defects remains unclear. Here, we employed multi-scale models to determine how interstitials are annihilated at small-angle tilt GBs (STGBs) in SiC. First of all, we found the pipe diffusion of interstitials in STGBs is slower than bulk diffusion. This is because the increased interatomic distance at dislocation cores raises the migration barrier of interstitial dumbbells. Furthermore, we found both the annihilation of interstitials at jogs and jog nucleation from clusters are diffusion-controlled and can occur under off-stoichiometric interstitial fluxes. Finally, a dislocation line model is developed to predict the role of STGBs in annihilating radiation damage. This model includes defect flux to GBs, pipe diffusion in STGBs, and the interaction of defects with jogs. The model predicts the role of STGBs in annihilating defects depends on the rate of defects segregation to and diffusion along STGBs. STGBs mainly serve as diffusion channel for defects to reach other sinks when defect diffusivity is high at boundaries. As a result, when defect diffusivity is low, most of the defects segregated to STGBs are annihilated by dislocation climb.

36 MATERIALS SCIENCE↗

Proton in SRF Niobium

Hydrogen is a difficult impurity to physically deal with in superconducting radio frequency (SRF) niobium, therefore, its properties in the metals should be well understood to allow the metal's superconducting properties to be optimized for minimum loss in the construction of resonant accelerator cavities. It is known that hydrogen is a paramagnetic impurity in niobium from NMR studies. This paramagnetism and its effect on superconducting properties are important to understand. To that end analytical induction measurements aimed at isolating the magnetic properties of hydrogen in SRF niobium are introduced along with optical reflection spectroscopy which is also sensitive to the presence of hydrogen. From the variety, magnitude and rapid kinetics found in the optical and magnetic properties of niobium contaminated with hydrogen forced a search for an atomic model. This yielded quantum mechanical description that correctly generates the activation energy for diffusion of the proton and its isotopes not only in niobium but the remaining metals for which data is available. This interpretation provides a frame work for understanding the individual and collective behavior of protons in metals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Mach 5 bow shock control by a nanosecond pulse surface dielectric barrier discharge

Bow shock perturbations in a Mach 5 air flow, produced by low-temperature, nanosecond pulse, and surface dielectric barrier discharge (DBD), are detected by phase-locked schlieren imaging. A diffuse nanosecond pulse discharge is generated in a DBD plasma actuator on a surface of a cylinder model placed in air flow in a small scale blow-down supersonic wind tunnel. Discharge energy coupled to the actuator is 7.3-7.8 mJ/pulse. Plasma temperature inferred from nitrogen emission spectra is a few tens of degrees higher than flow stagnation temperature, T = 340 {+-} 30 K. Phase-locked Schlieren images are used to detect compression waves generated by individual nanosecond discharge pulses near the actuator surface. The compression wave propagates upstream toward the baseline bow shock standing in front of the cylinder model. Interaction of the compression wave and the bow shock causes its displacement in the upstream direction, increasing shock stand-off distance by up to 25%. The compression wave speed behind the bow shock and the perturbed bow shock velocity are inferred from the Schlieren images. The effect of compression waves generated by nanosecond discharge pulses on shock stand-off distance is demonstrated in a single-pulse regime (at pulse repetition rates of a few hundred Hz) and in a quasi-continuous mode (using a two-pulse sequence at a pulse repetition rate of 100 kHz). The results demonstrate feasibility of hypersonic flow control by low-temperature, repetitive nanosecond pulse discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Single-shot high aspect ratio bulk nanostructuring of fused silica using chirp-controlled ultrafast laser Bessel beams

We report single-shot, high aspect ratio nanovoid fabrication in bulk fused silica using zeroth order chirp-controlled ultrafast laser Bessel beams. We identify a unique laser pulse length and energy dependence of the physical characteristics of machined structures over which nanovoids of diameter in the range 200–400 nm and aspect ratios exceeding 1000 can be fabricated. A mechanism based on the axial energy deposition of nonlinear ultrashort Bessel beams and subsequent material densification or rarefaction in fused silica is proposed, intricating the non-diffractive nature with the diffusing character of laser-generated free carriers. Fluid flow through nanochannel is also demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Calculating potential energy curves with fixed-node diffusion Monte Carlo: CO and N 2

This study reports on the prospect for the routine use of Quantum Monte Carlo (QMC) for the electronic structure problem, applying fixed-node Diffusion Monte Carlo (DMC) to generate highly accurate Born-Oppenheimer potential energy curves (PECs) for small molecular systems. The singlet ground electronic states of CO and N 2 were used as test cases. The PECs obtained by DMC employing multiconfigurational trial wavefunctions were compared with those obtained by conventional high-accuracy electronic structure methods such as multireference configuration interaction and/or the best available empirical spectroscopic curves. The goal was to test whether a straightforward procedure using available QMC codes could be applied robustly and reliably. Results obtained with DMC codes were found to be in close agreement with the benchmark PECs, and the n 3 scaling with the number of electrons (compared with n 7 or worse for conventional high-accuracy quantum chemistry) could be advantageous depending on the system size. Due to a large pre-factor in the scaling, for the small systems tested here, it is currently still much more computationally intensive to compute PECs with QMC. Nevertheless, QMC algorithms are particularly well-suited to large-scale parallelization and are therefore likely to become more relevant for future massively parallel hardware architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-classical ion-indiffusion processes in quasi-one-dimensional ionic conductor KTiOPO4

Developments in coercive field engineering and waveguide writing via ion-exchange in the ferroelectric ionic-conductor KTiOPO4 (KTP) have led to breakthroughs within the field of nonlinear optics and quantum photonics. However, the microscopic diffusion dynamics of ion-exchange in KTP are poorly understood and show signs of non-classical diffusion dynamics. The precise control of ion-exchange gradients is critical for developing KTP into a mature, integrated nonlinear optical material but requires a level of control that, in turn, demands a deeper understanding of the ion-exchange process. We employ direct ToF-SIMS mapping to untangle the complex diffusion dynamics of the commonly used ion-exchange dopant ions: Rb, Ba, and K. We map periodic diffusion gradients of two exchanges, one dominated by Rb-ions and the other by Ba-ions. For the first time, we show the interdependent nature of the Ba- and Rb ion in the ion-exchange diffusion gradient. The low incorporation of the Ba ion is mapped and quantified, and dopant–crystal interactions are identified. This work highlights the complex diffusion dynamics of dopants in the KTP structure and lays the foundation for deterministic control of diffusion gradients for the next generation of integrated nonlinear and quantum photonic devices.

Barrett, Laura [ORNL]↗

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗