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At least 289 records · Page 16

Shower thoughts: why scientists should spend more time in the rain

Abstract Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists’ human sensory and cognitive systems during storms.

ecosystem functioning↗

Diagnosis of PV Cell Antireflective Coating Degradation Resulting From Hot-Humid High-Voltage Potential Aging

Corrosion of the antireflective coating on a photovoltaic cell ("ARc corrosion") has previously been observed in studies using hot-humid test conditions with external high-voltage (HV) bias. This study primarily focuses on known vulnerable legacy aluminum back surface field cells in mini-modules (MiMos) put through comparative stepped stress tests. Each cell type had MiMos at +1500 V, -1500 V, or unbiased ("Voc") potential, which were sequentially subjected to test conditions of 60 degrees C/60% relative humidity (RH) for 96 h, as in International Electrotechnical Commission Technical Specification 62804-1; 70 degrees C/70% RH for 200 h; and 85 degrees C/85% RH for 200 h. Characterizations at each step included visual camera and electroluminescence (EL) imaging, colorimetry, and current-voltage curve tracing. Final characterizations included: Suns-Voc, spatial mapping of external quantum efficiency, high-resolution photoluminescence, EL, and dark lock-in thermography imaging. Forensics were performed on extracted cores, including scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy, and scanning Auger microscopy (SAM). Forensics were also conducted on MiMos from previous studies that underwent stepped HV aging and separate outdoor aged full-sized modules. ARc corrosion was specifically seen for the glass/encapsulant/cell side of the +1500 V (HV+) stressed MiMos and modules. Appearance, color, and reflectance were the most distinguishing characteristics relative to glass corrosion, gridline corrosion and delamination, and other concurrent degradation modes. SEM/EDS and SAM identified the conversion of silicon nitride to hydrated silica, hydrous silica, or hydrated amorphous silica, which preferentially occurred at the edges and tips of the pyramidal textured cell surface.

14 SOLAR ENERGY↗

Diagnosis of PV Cell Antireflective Coating Degradation Resulting from Hot-Humid, High Voltage Potential Aging

Corrosion of the antireflective coating on a photovoltaic cell ("ARc corrosion") has previously been observed in studies using hot-humid test conditions with external high-voltage (HV) bias. This study primarily focuses on known vulnerable, legacy aluminum back surface field (Al-BSF) cells in mini-modules (MiMos) put through comparative stepped stress tests. Each cell type had MiMos at +1500 V, -1500 V, or unbiased ("Voc") potential, which were sequentially subjected to test conditions of 60deg C/60% relative humidity (RH) for 96 h, as in International Electrotechnical Commission (IEC) Technical Specification 62804-1; 70 deg C/70% RH for 200 h; and 85 deg C/85% RH for 200 h. Characterizations at each step included visual camera and electroluminescence (EL) imaging, colorimetry, and current-voltage (I-V) curve tracing. Final characterizations included: Suns-Voc; spatial mapping of external quantum efficiency (EQE); high-resolution photoluminescence (PL), EL, and dark lock-in thermography (DLIT) imaging. Forensics were performed on extracted cores, including scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and scanning Auger microscopy (SAM). Forensics were also conducted on MiMos from previous studies that underwent stepped HV aging and separate outdoor aged full-sized modules. ARc corrosion was specifically seen for the glass/encapsulant/cell side of the +1500V (HV+) stressed MiMos and modules. Appearance, color, and reflectance were the most distinguishing characteristics relative to glass corrosion, gridline-corrosion and -delamination as well as other concurrent degradation modes. SEM/EDS and SAM identified conversion of silicon nitride to hydrated silica, hydrous silica, or hydrated amorphous silica, which preferentially occurred at the edges and tips of the pyramidal textured cell surface.

14 SOLAR ENERGY↗

Liquid to crystal Si growth simulation using machine learning force field

Machine learning force field (ML-FF) has emerged as a potential promising approach to simulate various material phenomena for large systems with ab initio accuracy. However, most ML-FFs have been used to study the phenomena relatively close to the equilibrium ground states. In this work, we have studied a far from equilibrium system of liquid to crystal Si growth using ML-FF. Here, we found that our ML-FF based on ab initio decomposed atomic energy can reproduce all the aspects of ab initio simulated growth, from local energy fluctuations to transition temperatures, to diffusion constant, and growth rates. We have also compared the growth simulation with the Stillinger-Weber classical force field and found significant differences. A procedure is also provided to correct a systematic fitting bias in the ML-FF training process, which exists in all training models, otherwise critical results like transition temperature will be wrong.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatial profiles of photon chemical potential in near-field thermophotovoltaic cells

Emitted photons stemming from the radiative recombination of electron–hole pairs carry chemical potential in radiative energy converters. This luminescent effect can substantially alter the local net photogeneration in near-field thermophotovoltaic cells. Several assumptions involving the luminescent effect are commonly made in modeling photovoltaic devices; in particular, the photon chemical potential is assumed to be zero or a constant prescribed by the bias voltage. The significance of photon chemical potential depends upon the emitter temperature, the semiconductor properties, and the injection level. Hence, these assumptions are questionable in near-field thermophotovoltaic devices with nanoscale separation distances between the emitter and the cell. In the present work, an iterative solver that combines fluctuational electrodynamics with the drift-diffusion model is developed to tackle the coupled photon and charge transport problem, enabling the determination of the spatial profile of photon chemical potential beyond the detailed balance approach. Here, the difference between the results obtained by allowing the photon chemical potential to vary spatially and by assuming a constant value demonstrates the limitations of the conventional approaches. This study is critically important for performance evaluation of near-field thermophotovoltaic systems with nanoscale vacuum gaps.

30 DIRECT ENERGY CONVERSION↗

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Controlling reversible phase transitions in rare-earth nickelates for novel memory devices

Resistive switching in correlated complex oxides is lucrative for emerging applications in neuromorphic computing, and densely scaled non-volatile memory. Electrical conductance of such complex oxides can be controllable switched across multiple orders of magnitude by either (a) electroforming a conduction channel (e.g., in tungsten oxide), or (b) inducing Mott-Hubbard transition (e.g., in rare-earth nickelates)– both via controlled migration of defects (such as oxygen vacancies) under applied bias. Nevertheless, the promise of such defect-driven electronic transitions are far from realized due to a lack of fundamental understanding of the atomic-scale processes that underlie migration and spatiotemporal evolution of oxygen vacancies over nano-to-mesoscopic length/timescales under applied electric field. In this project, we employ a synergistic integration of density functional theory (DFT) calculations, ab initio/classical molecular dynamics (AIMD/CMD) simulations, machine learning (ML), precision synthesis, and multi-modal X-ray imaging experiments to address this knowledge gap. Such an integrated approach offers to elucidate the correlations between subtle structural distortion and oxidation states; treat localized charge carriers; describe defect/ion transport in the presence of electric field; and, in turn, greatly advance the current understanding of microstructural evolution in complex oxides under applied bias. The fundamental knowledge gained from this work will enable precise control over hierarchical defect structures and unravel new routes to manipulate resistance states in complex oxides. This, in turn, will accelerate design of novel devices with desired set of neural functionalities, and high-speed densely-scaled resistive random access memory technologies.

36 MATERIALS SCIENCE↗

Manipulating the insulator–metal transition through tip-induced hydrogenation

Manipulating the insulator–metal transition in strongly correlated materials has attracted a broad range of research activity due to its promising applications in, for example, memories, electrochromic windows and optical modulators. Electric-field-controlled hydrogenation using ionic liquids and solid electrolytes is a useful strategy to obtain the insulator–metal transition with corresponding electron filling, but faces technical challenges for miniaturization due to the complicated device architecture. Here, in this work, we demonstrate reversible electric-field control of nanoscale hydrogenation into VO 2 with a tunable insulator–metal transition using a scanning probe. The Pt-coated probe serves as an efficient catalyst to split hydrogen molecules, while the positive-biased voltage accelerates hydrogen ions between the tip and sample surface to facilitate their incorporation, leading to non-volatile transformation from insulating VO 2 into conducting H x VO 2 . Remarkably, a negative-biased voltage triggers dehydrogenation to restore the insulating VO 2 . This work demonstrates a local and reversible electric-field-controlled insulator–metal transition through hydrogen evolution and presents a versatile pathway to exploit multiple functional devices at the nanoscale.

36 MATERIALS SCIENCE↗

Bias-hardened estimators of patchy screening profiles

Detecting anisotropic screening of the cosmic microwave background (CMB) holds the promise of revealing the distribution of gas in the Universe, characterizing the complex processes of galaxy formation and feedback, and studying the epoch of reionization. Estimators for inhomogeneous screening, including some recently proposed small-scale (stacked) estimators, are quadratic or higher order in the CMB temperature or polarization fields and are therefore subject to contamination from CMB lensing. We review the origin of this lensing bias and show that, when stacking on unWISE galaxies, the expected lensing bias dominates the signal if left unmitigated. Hardening techniques that null the lensing bias have been proposed for standard quadratic estimators, whereas only approximate methods have been proposed for stacked estimators. In conclusion, we review these techniques and apply the former to stacked estimators, presenting several strategies (including the optimal strategy) to null lensing contamination when stacking on any large-scale structure tracer.

Cosmic microwave background↗

Constrained patterning of orientated metal chalcogenide nanowires and their growth mechanism

One-dimensional metallic transition-metal chalcogenide nanowires (TMC-NWs) hold promise for interconnecting devices built on two-dimensional (2D) transition-metal dichalcogenides, but only isotropic growth has so far been demonstrated. Here we show the direct patterning of highly oriented Mo 6 Te 6 NWs in 2D molybdenum ditelluride (MoTe 2 ) using graphite as confined encapsulation layers under external stimuli. The atomic structural transition is studied through in-situ electrical biasing the fabricated heterostructure in a scanning transmission electron microscope. Atomic resolution high-angle annular dark-field STEM images reveal that the conversion of Mo 6 Te 6 NWs from MoTe 2 occurs only along specific directions. Combined with first-principles calculations, we attribute the oriented growth to the local Joule-heating induced by electrical bias near the interface of the graphite-MoTe 2 heterostructure and the confinement effect generated by graphite. Using the same strategy, we fabricate oriented NWs confined in graphite as lateral contact electrodes in the 2H-MoTe 2 FET, achieving a low Schottky barrier of 11.5 meV, and low contact resistance of 43.7 Ω µm at the metal-NW interface. Our work introduces possible approaches to fabricate oriented NWs for interconnections in flexible 2D nanoelectronics through direct metal phase patterning.

36 MATERIALS SCIENCE↗

Aboveground woody biomass estimation of young bioenergy plantations of Populus and its hybrids using mobile (backpack) LiDAR remote sensing

Woody aboveground biomass (AGB) including short-rotation Populus is used as a feedstock for renewable and carbon-neutral bioenergy. While woody AGB can be estimated with allometric equations requiring labor-intensive field data, remote sensing technologies like mobile terrestrial light detection and ranging (LiDAR) can estimate woody AGB quickly and accurately. Therefore, the goals of this study were to develop a model to predict woody AGB of 2-year-old Populus spp. from three taxa (P. deltoides, P. deltoides × P. maximowiczii and P. deltoides × P. trichocarpa) using allometric (height and diameter at breast height (DBH)) or LiDAR-derived metrics from a mobile terrestrial (backpack) system. Likewise, we sought to compare LiDAR-estimated tree height and DBH with field-measured values. We found that a taxa-specific model containing LiDAR-measured tree height, crown volume, and taxa interactions with the height of the 10 th percentile, and the density of the lowest interval (density metric 0) explained 84 % of the variation in woody AGB with a root mean square error (RMSE) of 28.7 % and performed slightly better than the allometric model. The best model excluding taxa had a slightly higher RMSE but lower bias than the allometric model. LiDAR-derived tree heights were highly correlated with field-measured heights, but DBH could not be estimated accurately. Therefore, terrestrial mobile LiDAR systems can accurately estimate woody AGB and tree height of Populus in short rotation systems to aid in the fast and efficient quantification of woody bioenergy production and renewable energy resources.

AGB↗

Large-volume CdZnTe bar detectors characterized by laser-induced transient currents

In this work, we studied the free-carrier transport properties and space-charge formation/polarization in a CdZnTe bar-shaped radiation detector using the Laser-Induced Transient Current technique. We found out that a steady-state space charge ranging from 8 x 10 8 to 2.1 x 10 9 cm -3 is formed throughout the detector at about 0.5 s following biasing. The measured current waveforms were modeled by Monte Carlo simulations after taking into account the electric and weighting fields inside the detector and shielding box. Modeling of the unpolarized waveforms revealed an exceptionally high electron mobility-lifetime product μ e τ e ≥0.095cm 2 V -1 . The observed formation of positive space charge in the biased detector and linear scaling of the current waveform shapes on applied bias revealed that the detector polarization is attributed to carrier injection at the anode. In conclusion, measurements in pulsed and DC bias in modified electrode geometry proved the surface-charge formation.

47 OTHER INSTRUMENTATION↗

Carbon flux estimates are sensitive to data source: a comparison of field and lab temperature sensitivity data

Abstract A large literature exists on mechanisms driving soil production of the greenhouse gases CO 2 and CH 4 . Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. These data are used to parameterize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO 2 and CH 4 measurements. We use Q 10 of greenhouse gas flux (temperature sensitivity) for our analyses because this metric is commonly used in biological and Earth system sciences and is an important parameter in many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q 10 values calculated from lab-based measurements of CO 2 fluxes, because lab experiments explore extremes rarely seen in situ , and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q 10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q 10 , these values showed almost identical distributions across laboratory ( n = 1110) and field ( n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH 4 Q 10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata.

54 ENVIRONMENTAL SCIENCES↗

Droplet-Gas Interactions in Nanoelectrospray Multiphase Flow

Electrospray (ES) is production of a charged droplet plume that transits from an electrically biased supply capillary to a counter electrode under the influence of an electric field. Drag interactions with the surrounding gas decelerate the droplets while transferring the momentum from droplets to accelerate the surrounding gas, resulting in an induced gas flow. This work seeks to characterize the structure of the resulting gas jet and identify the key mechanisms defining the flow structure. The phenomenon of gas jets produced by momentum transfer from nano-electrospray (nES) plumes is explored with schlieren visualization, thermal anemometry, and numerical simulations. Schlieren visualization experiments provide information on the flow structure in support of simulation predictions, and the hot thermistor anemometry measurements of gas velocities outside the spray demonstrate quantitatively validated simulation results. The study reveals the formation of a moderately high velocity coaxial gas jet within the nES plume and provides insight into the overall flow structure of the induced flow. The multiphase electrohydrodynamic simulations enable numerical experimentation to explore the fundamental physics of coupled droplet-gas transport and the resulting flow structure. The simulations, confirmed by the experiments, reveal gas jetting induced by nES with a narrow (sub hundred micrometers in diameter) core originating from the nES liquid-jet breakup region and a surrounding larger-in-extent zone (several hundred micrometers in diameter) of lower velocity gas flow within the electrospray plume. This behavior is due to nES ejecting a stream of droplets from the tip of a narrow liquid cone-jet, where the combined effect of many small droplets transferring momentum to a confined region of gas yields a narrow but high-velocity gas stream. Furthermore, the micro-jets produced by nES have practical utility for mass spectrometry, 3D printing and fabrication, and thermal management.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Uranium Oxide Synthetic Pathway Discernment through Unsupervised Morphological Analysis

We present a novel unsupervised machine learning method for quantitative representation of scanning electron micrographs and its applications and performance for nuclear forensic analysis of uranium ore concentrates. The method uses a vector quantizing variational autoencoder followed by a histogram operation to encode a micrograph into a single dimensional representation, called the latent vector. The method requires no extant labeling of the data and can be applied over large datasets of micrographs with minimal human interaction. The representations generated are broadly descriptive of each micrograph and the microstructure of the material imaged. In the case of uranium ore concentrate analysis, the representations were amenable to processing reagent and ore concentrate species classification with accuracy of 81:8%, which is competitive with state-of-the-art supervised networks. The representations were also used to classify previously unseen processing routes, were able to classify imaging parameters such as magnification (to 76:0% accuracy), were able to classify fine grained process parameters such as calcining temperature (to 74:4% accuracy), and their informatic properties indicate that they are generally descriptive of the image represented. This method can be applied across microstructure analysis fields to perform quantitative analysis without the need for labor intensive and possibly biased human analysis.

Scanning Electron Microscopy, Vector Quantizing Va↗

Diocotron modes in pure electron plasmas in the APEX levitating dipole trap

Abstract Observations of persistent toroidal modes in dipole-trapped pure electron plasmas are presented. Non-neutral electron plasmas were confined by the poloidal magnetic field of the APEX (A Positron Electron eXperiment) levitating dipole trap. The negative bias of the electron emitter was gated to control the filling time. Large amplitude, narrow-band oscillations were consistently observed in wall probe measurements after the fill. The oscillatory image-charge currents induced by the trapped electron plasma typically persisted for many seconds with fundamental frequencies, f 0 = 50 to 500 kHz, that scale with the E → × B → drift velocity. We attribute this feature to the dipole-equivalent of the diocotron mode that is commonly observed in non-neutral plasmas in linear traps.

Deller, A. (ORCID:0000000234301501)↗

The DESI Early Data Release white dwarf catalogue

The Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) comprises spectroscopy obtained from 2020 December 14 to 2021 June 10. White dwarfs were targeted by DESI both as calibration sources and as science targets and were selected based on Gaia photometry and astrometry. Here, we present the DESI EDR white dwarf catalogue, which includes 2706 spectroscopically confirmed white dwarfs of which approximately 60 per cent have been spectroscopically observed for the first time, as well as 66 white dwarf binary systems. We provide spectral classifications for all white dwarfs, and discuss their distribution within the Gaia Hertzsprung–Russell diagram. We provide atmospheric parameters derived from spectroscopic and photometric fits for white dwarfs with pure hydrogen or helium photospheres, a mixture of those two, and white dwarfs displaying carbon features in their spectra. We also discuss the less abundant systems in the sample, such as those with magnetic fields, and cataclysmic variables. The DESI EDR white dwarf sample is significantly less biased than the sample observed by the Sloan Digital Sky Survey, which is skewed to bluer and therefore hotter white dwarfs, making DESI more complete and suitable for performing statistical studies of white dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗

Terahertz Second-Harmonic Generation from Lightwave Acceleration of Symmetry-Breaking Nonlinear Supercurrents

We report terahertz (THz) light-induced second harmonic generation, in superconductors with inversion symmetry that forbid even-order nonlinearities. The THz second harmonic emission vanishes above the superconductor critical temperature and arises from precession of twisted Anderson pseudospins at a multicycle, THz driving frequency that is not allowed by equilibrium symmetry. We explain the microscopic physics by a dynamical symmetry breaking principle at sub-THz-cycle by using quantum kinetic modeling of the interplay between strong THz-lightwave nonlinearity and pulse propagation. In this work, the resulting nonzero integrated pulse area inside the superconductor leads to light-induced nonlinear supercurrents due to subcycle Cooper pair acceleration, in contrast to dc-biased superconductors, which can be controlled by the band structure and THz driving field below the superconducting gap.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗