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Accurate and timely inland waterbody extent and location data are foundational information to support a variety of hydrological applications and water resources management. Recently, the Cyclone Global Navigation Satellite System (CYGNSS) has emerged as a promising tool for delineating inland water due to distinct surface reflectivity characteristics over dry versus wet land which are observable by CYGNSS’s eight microsatellites with passive bistatic radars that acquire reflected L-band signals from the Global Positioning System (GPS) (i.e., signals of opportunity). This study conducts a baseline 1-km comparison of water masks for the contiguous United States between latitudes of 24°N-37°N for 2019 using three Earth observation systems: CYGNSS (i.e., our baseline water mask data), the Moderate Resolution Imaging Spectroradiometer (MODIS) (i.e., land water mask data), and the Landsat Global Surface Water product (i.e., Pekel data). Spatial performance of the 1-km comparison water mask was assessed using confusion matrix statistics and optical high-resolution commercial satellite imagery. When a mosaic of binary thresholds for 8 sub-basins for CYGNSS data were employed, confusion matrix statistics were improved such as up to a 34% increase in F1-score. Further, a performance metric of ratio of inland water to catchment area showed that inland water area estimates from CYGNSS, MODIS, and Landsat were within 2.3% of each other regardless of the sub-basin observed. Overall, this study provides valuable insight into the spatial similarities and discrepancies of inland water masks derived from optical (visible) versus radar (Global Navigation Satellite System Reflectometry, GNSS-R) based satellite Earth observations.

 

Charge transfer is a fundamental interface process that can be harnessed for light detection, photovoltaics, and photosynthesis. Recently, charge transfer was exploited in nanophotonics to alter plasmon polaritons by involving additional non-polaritonic materials to activate the charge transfer. Yet, direct charge transfer between polaritonic materials has not been demonstrated. We report the direct charge transfer in pure polaritonic van der Waals (vdW) heterostructures of α-MoO3/graphene. We extracted the Fermi energy of 0.6 eV for graphene by infrared nano-imaging of charge transfer hyperbolic polaritons in the vdW heterostructure. This unusually high Fermi energy is attributed to the charge transfer between graphene and α-MoO3. Moreover, we have observed charge transfer hyperbolic polaritons in multiple energy–momentum dispersion branches with a wavelength elongation of up to 150%. With the support from the density functional theory calculation, we find that the charge transfer between graphene and α-MoO3, absent in mechanically assembled vdW heterostructures, is attributed to the relatively pristine heterointerface preserved in the epitaxially grown vdW heterostructure. The direct charge transfer and charge transfer hyperbolic polaritons demonstrated in our work hold great promise for developing nano-optical circuits, computational devices, communication systems, and light and energy manipulation devices. 

Tandem mass spectrometry (MS/MS) using fragmentation has become one of the most effective methods for gaining sequence and structural information of biomolecules. Ion/ion reactions are competitive reactions where either proton transfer (PT) or electron transfer (ET) can occur from interactions between multiply charged cations and singly charged anions. Utilizing ion/ion reactions with fluoranthene has offered a unique method of fragment formation for structural elucidation of biomolecules. Fluoranthene is considered an ideal anion reagent because it selectively causes electron transfer dissociation (ETD) and minimizes PT when interacting with peptides. However, limited investigations have sought to understand how fluoranthene – the primary, commercially available anion reagent – interacts with other biomolecules. Here, we apply deuterium labeling to investigate ion/ion reaction mechanisms between fluoranthene and divalent, metal-adducted carbohydrates (Ca2+, Mg2+, Co2+, and Ni2+). Deuterium labeling of carbohydrates allowed us to observe evidence of hydrogen/deuterium exchange (HDX) occurring after ion/ion dissociation reactions. The extent of deuterium loss is dependent on several factors, including the physical properties of the metal ion and the fragment structure. Based on the deuterium labeling data, we have proposed ETD, PTD, and intermolecular PT – also described as HDX - mechanisms. This research provides a fundamental perspective of ion/ion and ion/molecule reaction mechanisms and illustrates properties that impact ion/ion and ion/molecule reactions for carbohydrates. Together, this could improve the capability to distinguish complex and heterogenous biomolecules, such as carbohydrates. 

Electroadhesive devices with dielectric films can electrically program changes in stiffness and adhesion, but require hundreds of volts and are subject to failure by dielectric breakdown. Recent work on ionoelastomer heterojunctions has enabled reversible electroadhesion with low voltages, but these materials exhibit limited force capacities and high detachment forces. It is a grand challenge to engineer electroadhesives with large force capacities and programmable detachment at low voltages (<10 V). In this work, tough ionoelastomer/metal mesh composites with low surface energies are synthesized and surface roughness is controlled to realize sub‐ten‐volt clutches that are small, strong, and easily detachable. Models based on fracture and contact mechanics explain how clutch compliance and surface texture affect force capacity and contact area, which is validated over different geometries and voltages. These ionoelastomer clutches outperform the best existing electroadhesive clutches by fivefold in force capacity per unit area (102 N cm^-2), with a 40‐fold reduction in operating voltage (± 7.5 V). Finally, the ability of the ionoelastomer clutches to resist bending moments in a finger wearable and as a reversible adhesive in an adjustable phone mount is demonstrated. 

The stimuli-responsive self-folding structure is ubiquitous in nature, for instance, the mimosa folds its leaves in response to external touch or heat, and the Venus flytrap snaps shut to trap the insect inside. Thus, modeling self-folding structures has been of great interest to predict the final configuration and understand the folding mechanism. Here, we apply a simple yet effective method to predict the folding angle of the temperature-responsive nanocomposite hydrogel/elastomer bilayer structure manufactured by 3D printing, which facilitates the study of the effect of the inevitable variations in manufacturing and material properties on folding angles by comparing the simulation results with the experimentally measured folding angles. The defining feature of our method is to use thermal expansion to model the temperature-responsive nanocomposite hydrogel rather than the nonlinear field theory of diffusion model that was previously applied. The resulted difference between the simulation and experimentally measured folding angle ( i.e. , error) is around 5%. We anticipate that our method could provide insight into the design, control, and prediction of 3D printing of stimuli-responsive shape morphing ( i.e. , 4D printing) that have potential applications in soft actuators, robots, and biomedical devices. 

Supervised training of optical flow predictors generally yields better accuracy than unsupervised training. However, the improved performance comes at an often high annotation cost. Semi-supervised training trades off accuracy against annotation cost. We use a simple yet effective semi-supervised training method to show that even a small fraction of labels can improve flow accuracy by a significant margin over unsupervised training. In addition, we propose active learning methods based on simple heuristics to further reduce the number of labels required to achieve the same target accuracy. Our experiments on both synthetic and real optical flow datasets show that our semi-supervised networks generally need around 50% of the labels to achieve close to full-label accuracy, and only around 20% with active learning on Sintel. We also analyze and show insights on the factors that may influence active learning performance. Code is available at https://github.com/duke-vision/ optical-flow-active-learning-release. 

Observations of the young solar wind by the Parker Solar Probe (PSP) mission reveal the existence of intense plasma wave bursts with frequencies between 0.05 and 0.20f_ce(tens of hertz up to ∼300 Hz) in the spacecraft frame. The wave bursts are often collocated with inhomogeneities in the solar wind magnetic field, such as local dips in magnitude or sudden directional changes. The observed waves are identified as electromagnetic whistler waves that propagate either sunward, anti-sunward, or in counter-propagating configurations during different burst events. Being generated in the solar wind flow, the waves experience significant Doppler downshift and upshift of wave frequency in the spacecraft frame for sunward and anti-sunward waves, respectively. Their peak amplitudes can be larger than 2 nT, where such values represent up to 10% of the background magnetic field during the interval of study. The amplitude is maximum for propagation parallel to the background magnetic field. We (i) evaluate the properties of these waves by reconstructing their parameters in the plasma frame, (ii) estimate the effective length of the PSP electric field antennas at whistler frequencies, and (iii) discuss the generation mechanism of these waves.

 

Room-temperature, pulsed-operation lasing of 8.5  μm-emitting InP-based quantum cascade lasers (QCLs), with low threshold-current density and watt-level output power, is demonstrated from structures grown on (001) GaAs substrates by metal-organic chemical vapor deposition. Prior to growing the laser structure, which contains a 35-stage In 0.53 Ga 0.47 As/In 0.52 Al 0.48 As lattice-matched active-core region, a ∼2  μm-thick nearly fully relaxed InP buffer with strained 1.6 nm-thick InAs quantum-dot-like dislocation-filter layers was grown. A smooth terminal buffer-layer surface, with roughness as low as 0.4 nm on a 10 × 10  μm 2 scale, was obtained, while the estimated threading-dislocation density was in the mid-range × 10 8  cm −2 . A series of measurements, on lasers grown on InP metamorphic buffer layers (MBLs) and on native InP substrates, were performed for understanding the impact of the buffer-layer's surface roughness, residual strain, and threading-dislocation density on unipolar devices such as QCLs. As-cleaved devices, grown on InP MBLs, were fabricated as 25  μm × 3 mm deep-etched ridge guides with lateral current injection. The results are pulsed maximum output power of 1.95 W/facet and a low threshold-current density of 1.86 kA/cm 2 at 293 K. These values are comparable to those obtained from devices grown on InP: 2.09 W/facet and 2.42 kA/cm 2 . This demonstrates the relative insensitivity of the device-performance metrics on high residual threading-dislocation density, and high-performance InP-based QCLs emitting near 8  μm can be achieved on lattice-mismatched substrates.