R-F Simulator for a Long-pulse Radar
X-band target simulator with spectral purity for long radar echo pulses
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X-band target simulator with spectral purity for long radar echo pulses
Radio echo technique applied to measurement of electron line density in ionization trains of intermediate type
Turbulence in upper atmosphere according to radio echo observations of meteor trains
Modulator transfer functions for fixed and ramp input waveforms, and nonlinear homomorphic system for echo removal
Radar echo measurements of increased meteor counts during middle months of 1963
Oblique echo presence during winter nights on auroral and subauroral latitudes ionograms, analyzing electron number density of nighttime F region in midlatitude trough vicinity
Radar experiments of sun at 38 mc/s, presenting results on echo variation with sunspot number, coronal irregularities, etc
Stratospheric aerosol concentrations observed by optical radar echoes compared with expected return from molecular atmosphere to obtain vertical profile
Planetary radar astronomy is the study of solar system entities (the moon, asteroids, and comets, as well as the major planets and their satellites and ring systems) by transmitting radio signals towards a target and receiving and analyzing the echoes.
Understanding the spatial heterogeneity beneath Thwaites Glacier, West Antarctica, is vital to projecting its impact on future sea levels. Radar-echo sounding (RES) is commonly used to infer subglacial conditions, but these data can be challenging to interpret. We assess basal heterogeneity across Thwaites Glacier by comparing RES returns to a radar backscattering simulator for over 400 km of RES data. The modeled variations in bed returned power exhibited a strong correlation with actual RES data in 40% of our simulated flight segments, which we consider evidence for a relatively homogeneous glacier bed. Other sites (40%) demonstrated improved fit quality when hydrology or substrate transitions were introduced in the bed material model. The remaining simulated segments (20%) were diagnosed as having more complex basal heterogeneity. The spatial distribution of complex heterogeneity appears to coincide with asymmetric patterns in the RES specularity content, which has been interpreted in previous studies as a signature for channelized hydrology. Conversely, the homogeneous substrate locations coincide with areas of fast-moving ice in western Thwaites. Our simulation method can isolate power variations induced by material heterogeneity vs topography, which is an important limitation of existing RES analysis methods.
Stabilizing oil-water interfaces in emulsions by plant-based proteins provides sustainable and tunable ways for designing emulsions with specific properties, for food, healthcare, and pharmaceuticals. Cruciferin, a protein from rapeseed, has great potential as green emulsifier, but details about its structure and mobility at oil-water interfaces are largely unknown. Here, these properties are studied with small angle neutron and x-ray scattering, and neutron spin echo spectroscopy, analyzed by atomistic modelling of scattering curves and coarse-grained modelling, to gain insight into interface coverage, and molecular conformation and mobility at the interface. Cruciferin assumes trimeric conformations at the interface, as in solution, but with its protrusions from the central core of the subunits (“arms”) more compressed. Interfacial mobility is only marginally lower than in solution, indicating the arms still transiently extend and preserve a network, for the first time revealing the mechanism how cruciferin forms highly elastic 2d gel-like oil-water interfaces, as observed in macroscopic rheology. The high interfacial mobility may help in self-repairing non-stabilized interfacial fractions, reducing coalescence. These findings provide a deeper molecular level understanding of proteins at oil-water interfaces, which can stimulate development of new plant-based emulsion products, and contribute to the global protein transition.
Micro-tomography (μCT) and nuclear magnetic resonance (NMR) have been used to characterize porous media for decades. Here, Magnetic Resonance Imaging (MRI) enables direct visualization of pore architecture and many pulse sequences exist. In this work, we tested the MRI pulse sequence Zero Echo Time (ZTE) to study sandstone and carbonate for its ability to address short relaxation times. We aimed at resolving two fluid conduit scales, i.e. pores and fractures. In this research, we study tighter porous systems than those previously reported using ZTE. Additionally, Pore Cluster Analysis (PCA), combined with ZTE, can be used to analyze pore-fracture connectivity of relatively large core plugs. We show that ZTE can resolve two-scale pore systems simultaneously, i.e. fractures and pores. By combining Time-Domain NMR pore-size analysis and PCA, we show that careful selection of resolution is necessary to understand transport in porous media.
Physical reservoir computing is a framework that enables energy‐efficient information processing by using physical systems. Nonlinear dynamics in physical systems provide a computational capability that is unique to reservoirs. It is, however, difficult to find an appropriate task for a reservoir because of the complexity of nonlinear information processing. The information processing capacity has recently been used to clarify systematically the tasks that are solved by reservoirs; it quantifies the memory capacity of reservoirs in accordance with the order of nonlinearity. Herein, an experimental evaluation of the information processing capacity of a spintronic oscillator consisting of nanostructured ferromagnets is reported. The spintronic reservoir state is electrically manipulated by adding a delayed‐feedback circuit. The total capacity reaches a maximum of 5.6 at the edge of the echo state property. A trade‐off between the linear and nonlinear components of the capacity is also found. The result can be used to better understand the nonlinear information processing in reservoirs and to find good matches between reservoirs and tasks. As an example, a function‐approximation task is performed and it is found that it can be efficiently solved when the reservoir state is appropriately tuned so that its information processing capacity matches that of the task.
Nesquehonite is a magnesium carbonate mineral relevant to carbon sequestration envisioned for carbon capture and storage of CO 2 . Its chemical formula remains controversial today, assigned as either a hydrated magnesium carbonate [MgCO 3 · 3H 2 O], or a hydroxy- hydrated- magnesium bicarbonate [Mg(HCO 3 )OH · 2H 2 O]. Here, the resolution of this controversy is central to understanding this material‘s thermodynamic, phase, and chemical behavior. In an NMR crystallography study, using rotational-echo double-resonance 13 C{ 1 H} (REDOR), 13 C- 1 H distances are determined with precision, and the combination of 13 C static NMR lineshapes and density functional theory (DFT) calculations are used to model different H atomic coordinates. [MgCO 3 · 3H 2 O] is found to be accurate, and evidence from neutron powder diffraction bolsters these assignments. Refined H positions can help understand how H-bonding stabilizes this structure against dehydration to MgCO 3 . More broadly, these results illustrate the power of NMR crystallography as a technique for resolving questions where X-ray diffraction is inconclusive.
Machine learning (ML) has become a central focus of the computational chemistry community. In this paper, I will first discuss my personal history in the field. Then I will provide a broader view of how this resurgence in ML interest echoes and advances upon earlier efforts. Although numerous changes have brought about this latest wave, one of the most significant is the increased accuracy and efficiency of low-cost methods (e.g., density functional theory or DFT) that have made it possible to generate large data sets for ML models. ML has also been used to bypass, guide, or improve DFT. The field of computational chemistry thus finds itself at a crossroads as ML both augments and supersedes traditional efforts. I will present what I believe the role of the computational chemist will be in this evolving landscape, with specific focus on my experience in the development of autonomous workflows in computational materials discovery for open-shell transition-metal chemistry.
Although nanometer-sized aluminum hydroxide clusters (i.e., ϵ-Al 13 , [Al 13 O 4 (OH) 24 (H 2 O) 12 ] 7+ ) command a central role in aluminum ion speciation and transformations between minerals, measurement of their translational diffusion is often limited to indirect methods. Here, in this work, 27 Al pulsed field gradient stimulated echo nuclear magnetic resonance (PFGSTE NMR) spectroscopy has been applied to the AlO 4 core of the ϵ-Al 13 cluster with complementary theoretical simulations of the diffusion coefficient and corresponding hydrodynamic radii from a boundary element-based calculation. The tetrahedral AlO 4 center of the ϵ-Al 13 cluster is symmetric and exhibits only weak quadrupolar coupling, which results in favorable T 1 and T 2 27 Al NMR relaxation coefficients for 27 Al PFGSTE NMR studies. Stokes–Einstein relationship was used to relate the 27 Al diffusion coefficient of the ϵ-Al 13 cluster to the hydrodynamic radius for comparison with theoretical simulations, dynamic light scattering from literature, and previously published 1 H PFGSTE NMR studies of chelated Keggin clusters. This first-of-its-kind observation proves that 27 Al PFGSTE NMR diffusometry can probe symmetric Al environments in polynuclear clusters of greater molecular weight than previously considered.
Solid-state NMR experiments on 2 H, 31 P, 13 C, and 1 H nuclei, including 31 P T 1 , 1 H T 1 , and 1 H T 1ρ measurements, as well as on the kinetics of proton-phosphorus cross-polarization have been performed to characterize the crystalline and amorphous α-zirconium phosphates, which were intercalated with D 2 O and/or CD 3 OD. The 13 C{ 1 H} CP MAS NMR experiment performed for compound 1-CD 3 OD (Zr (HPO 4 ) 2 .0.2CD 3 OD) with carbon cross-polarization via protons of phosphate groups has provided a prove that the methanol was intercalated into the interlayer spaces of this compound. The variable-temperature 2 H solid-echo MAS NMR spectra of intercalated compounds demonstrated that the methanol molecules, in contrast to the mobile water, were immobile, keeping, however, free CD 3 rotations around the C 3 -axis. It has been demonstrated that the intercalated species, D 2 O and CD 3 OD, do not affect the high-frequency motions of the phosphate groups. By utilizing local structural models that satisfy the constraints of the experimental data, it has been suggested that the immobile methanol molecules are located in the cavity between two neighboring layers of the zirconium phosphates. Here, the present work illustrates the reliable criteria in a comprehensive NMR approach to structural and dynamic studies of such systems.
We consider the fate of a massless (or ultra-relativistic massive) string probe propagating down the BTZ-like throat of a microstate geometry in the D1-D5 system. Far down the throat, the probe encounters large tidal forces that stretch and excite the string. The excitations are limited by the very short transit time through the region of large tidal force, leading to a controlled approximation to tidal stretching. We show that the amount of stretching is proportional to the incident energy, and that it robs the probe of the kinetic energy it would need to travel back up the throat. As a consequence, the probe is effectively trapped far down the throat and, through repeated return passes, scrambles into the ensemble of nearby microstates. We propose that this tidal trapping may lead to weak gravitational echoes.