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Abstract Debris flows pose a significant hazard to communities in mountainous areas, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. In certain situations, such as scenarios following wildfire, where there could be an abrupt increase in the likelihood and size of debris flows that necessitates a rapid hazard assessment, the computational demands of inundation models play a role in their utility. The inability to efficiently determine the downstream effects of anticipated debris-flow events remains a critical gap in our ability to understand, mitigate, and assess debris-flow hazards. To better understand the downstream effects of debris flows, we introduce a computationally efficient, reduced-complexity inundation model, which we refer to as the Progressive Debris-Flow routing and inundation model (ProDF). We calibrate ProDF against mapped inundation from five watersheds near Montecito, CA, that produced debris flows shortly after the 2017 Thomas Fire. ProDF reproduced 70% of mapped deposits across a 40 km 2 study area. While this study focuses on a series of post-wildfire debris flows, ProDF is not limited to simulating debris-flow inundation following wildfire and could be applied to any scenario where it is possible to estimate a debris-flow volume. However, given its ability to reproduce mapped debris-flow deposits downstream of the 2017 Thomas Fire burn scar, and the modest run time associated with a simulation over this 40 km 2 study area, results suggest ProDF may be particularly promising for post-wildfire hazard assessment applications. 

Reconfigurable arrays of 2D nanomaterials are essential for the realization of switchable and intelligent material systems. Using liquid crystals (LCs) as a medium represents a promising approach, in principle, to enable such control. In practice, however, this approach is hampered by the difficulty of achieving stable dispersions of nanomaterials. Here, we report on good dispersions of pristine CdSe nanoplatelets (NPLs) in LCs, and reversible, rapid control of their alignment and associated anisotropic photoluminescence, using a magnetic field. We reveal that dispersion stability is greatly enhanced using polymeric, rather than small molecule, LCs and is considerably greater in the smectic phases of the resulting systems relative to the nematic phases. Aligned composites exhibit highly polarized emission that is readily manipulated by field-realignment. Such dynamic alignment of optically-active 2D nanomaterials may enable the development of programmable materials for photonic applications and the methodology can guide designs for anisotropic nanomaterial composites for a broad set of related nanomaterials.

 

A highly adaptable and robust terahertz (THz) energy meter is designed and implemented to detect energetic THz pulses from high-intensity (>1018 W/cm2) laser–plasma interactions on the OMEGA EP. THz radiation from the laser driven target is detected by a shielded pyrometer. A second identical pyrometer is used for background subtraction. The detector can be configured to detect THz pulses in the 1 mm to 30 μm (0.3- to 10-THz) range and pulse energies from joules to microjoules via changes in filtration, aperture size, and position. Additional polarization selective filtration can also be used to determine the THz pulse polarization. The design incorporates significant radiation and electromagnetic pulse shielding to survive and operate within the OMEGA EP radiation environment. We describe the design, operational principle, calibration, and testing of the THz energy meter. The pyrometers were calibrated using a benchtop laser and show linear sensitivity to up to 1000 nJ of absorbed energy. The initial results from four OMEGA EP THz experiments detected up to ∼15μJ at the detector, which can correspond to hundreds of mJ depending on THz emission and reflection models.

 

Intensively managed forest plantations often require fertilization to maintain site fertility and to improve growth and yield over successive rotations. We applied urea-based “enhanced-efficiency fertilizers” (EEF) containing 0.5 atom% 15N at a rate of 224 kg N ha−1 to soils under mid-rotation black walnut (Juglans nigra L.) plantations to track the fate of applied 15N within aboveground ecosystem components during the 12-month period after application. Treatments included Agrotain Ultra (urea coated with a urease inhibitor), Arborite EC (urea coated with water-soluble boron and phosphate), Agrium ESN (polymer-coated urea), uncoated urea, and an unfertilized control. Agrotain Ultra and Arborite EC increased N concentrations of competing vegetation within one month after fertilization, while neither Agrium ESN nor uncoated urea had any effect on competing vegetation N concentrations during the experiment. Agrotain Ultra and Arborite EC increased δ15N values in leaves of crop trees above those of controls at one and two months after fertilization, respectively. By contrast, Agrium ESN and uncoated urea had no effect on δ15N values in leaves of crop trees until three months after fertilization. Fertilizer N recovery (FNR) varied among ecosystem components, with competing vegetation acting as a sink for applied nutrients. There were no significant differences in FNR for all the urea-based EEF products compared to uncoated urea. Agrium ESN was the only EEF that exhibited controlled-release activity in this study, with other fertilizers behaving similarly to uncoated urea. 

Abstract The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/ c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 $$\pm 0.6$$ ± 0.6 % and 84.1 $$\pm 0.6$$ ± 0.6 %, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.