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At least 919 records · Page 51

Regional Impacts of Woodland Expansion on Nitrogen Oxide Emissions from Texas Savannahs: Combining Field, Modeling and Remote Sensing Approaches

Woody encroachment has contributed to documented changes world-wide and locally in the southwestern U.S. Specifically, in North Texas rangelands encroaching mesquite (Prosopis glandulosa var. glandulosa) a known N-fixing species has caused changes in aboveground biomass. While measurements of aboveground plant production are relatively common, measures of soil N availability are scarce and vary widely. N trace gas emissions (nitric and nitrous oxide) flom soils reflect patterns in current N cycling rates and availability as they are stimulated by inputs of organic and inorganic N. Quantification of N oxide emissions from savanna soils may depend upon the spatial distribution of woody plant canopies, and specifically upon the changes in N availability and cycling and subsequent N trace gas production as influenced by the shift from herbaceous to woody vegetation type. The main goal of this research was to determine whether remotely sensible parameters of vegetation structure and soil type could be used to quantify biogeochemical changes in N at local, landscape and regional scales. To accomplish this goal, field-based measurements of N trace gases were carried out between 2000-2001, encompassing the acquisition of imaging spectrometer data from the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) on September 29, 2001. Both biotic (vegetation type and soil organic N) and abiotic (soil type, soil pH, temperature, soil moisture, and soil inorganic N) controls were analyzed for their contributions to observed spatial and temporal variation in soil N gas fluxes. These plot level studies were used to develop relationships between spatially extensive, field-based measurements of N oxide fluxes and remotely sensible aboveground vegetation and soil properties, and to evaluate the short-term controls over N oxide emissions through intensive field wetting experiments. The relationship between N oxide emissions, remotely-sensed parameters (vegetation cover, and soil type), and physical controls (soil moisture, and temperature) permitted the regional scale quantification of soil N oxides emissions. Landscape scale analysis linking N oxide emissions with cover change revealed an alleviation from N limitation following mesquite invasion. This study demonstrated the advantage of using N trace gases as a measure of ecosystem N availability combined with remote sensing to characterize the spatial heterogeneity in ecosystem parameters at a scale commensurate with field-based measurements of these properties. Woody vegetation encroachment provided an opportunity to capitalize on detection of the remotely-sensible parameter of woody cover as it relates to belowground biogeochemical processes that determine N trace gas production. The first spatially-explicit estimates of NO flux were calculated based on Prosopis fractional cover derived from high resolution remote sensing estimates of fractional woody cover (< 4 m) for a 120 sq km region of North Texas. An assessment of both N stocks and fluxes from the study revealed an alleviation of N limitation at this site experiencing recent woody encroachment. Many arid and semi-arid regions of the world are experiencing woody invasions, often of N-fixing species. The issue of woody encroachment is in the center of an ecological and political debate. Improving the links between biogeochemical processes and remote sensing of ecosystem properties will improve our understanding of biogeochemical processes at the regional scale, thus providing a means to address issues of land-use and land-cover change.

Asner, Gregory P.↗

Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes.

60 APPLIED LIFE SCIENCES↗

Imaging and spatially resolved mass spectrometry applications in nephrology

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. Further, the complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

60 APPLIED LIFE SCIENCES↗

Lapse-Rate Feeback: The Key to Reconciling TOA and Surface Attributions of Surface Warming

The impact of climate feedbacks on surface warming is conventionally evaluated using a decomposition of the top-of-atmosphere (TOA) energy budget. Alternatively, the climate feedback analysis can also be carried out using the surface energy budget. However, the two perspectives do not provide the same interpretation of process contributions to surface warming, particularly when executing a spatial analysis. The TOA energy budget is equal to the sum of the surface and atmospheric energy budgets. Using the CMIP5 RCP 8.5 model projections, we show that the major discrepancies between the surface and TOA climate feedback attributions of surface warming are due to non-negligible changes in the atmospheric energy budget that differ from their counterparts at the surface. Individual radiative and non-radiative processes cause vertically non-uniform energy flux perturbations, in response to an external forcing, that naturally lead to a vertically non-uniform temperature change. The TOA lapse-rate feedback is the manifestation of these multiple processes that produce a vertically non-uniform warming response such that it accounts for the asymmetry between the changes in the atmospheric and surface energy budgets. Using the climate feedback-response analysis method, we can decompose the lapse-rate feedback into contributions by individual processes. The negative lapse-rate feedback in the tropics is due to greater moist convection and condensational heating along with ocean heat storage. On the other hand, the positive lapse-rate feedback in polar regions is primarily due to the surface albedo and water vapor feedbacks. Combining the process contributions that are hidden within the lapse-rate feedback with their respective direct impacts on the TOA energy budget allows for a very consistent picture of process contributions to surface warming and its inter-model spread as that given by the surface energy budget approach. With the modified approach, both perspectives indicate water vapor feedback is the largest contributor in the tropics, while surface albedo feedback is the greatest contributor in polar regions. Dynamics and ocean heat storage are the main suppressors of surface warming, except over Antarctica. Both perspectives show there is large inter-model uncertainty in the contributions of water vapor, clouds, albedo, and dynamics plus ocean heat storage.

Sergio A Sejas↗

Unveiling defect-mediated carrier dynamics in monolayer semiconductors by spatiotemporal microwave imaging

The optoelectronic properties of atomically thin transition-metal dichalcogenides are strongly correlated with the presence of defects in the materials, which are not necessarily detrimental for certain applications. For instance, defects can lead to an enhanced photoconduction, a complicated process involving charge generation and recombination in the time domain and carrier transport in the spatial domain. Here, we report the simultaneous spatial and temporal photoconductivity imaging in two types of WS 2 monolayers by laser-illuminated microwave impedance microscopy. The diffusion length and carrier lifetime were directly extracted from the spatial profile and temporal relaxation of microwave signals, respectively. Time-resolved experiments indicate that the critical process for photoexcited carriers is the escape of holes from trap states, which prolongs the apparent lifetime of mobile electrons in the conduction band. As a result, counterintuitively, the long-lived photoconductivity signal is higher in chemical-vapor deposited (CVD) samples than exfoliated monolayers due to the presence of traps that inhibits recombination. Overall, our work reveals the intrinsic time and length scales of electrical response to photoexcitation in van der Waals materials, which is essential for their applications in optoelectronic devices.

42 ENGINEERING↗

A three-dimensional viscous flow analysis for the helicopter tip vortex generation problem

The tip vortex flow field occurring in the vicinity of the tip region of a a helicopter rotor blade is a very complicated three-dimensional, viscous flow phenomenon. The details of the flow in the tip region can have a major effect in determining the generated rotor noise and can significantly affect the performance and dynamic loading of the rotor blade. The three-dimensional viscous subsonic tip vortex generation processes is investigated by a numerical procedure which allows spatial forward-marching integration, utilizing flow approximations from the velocity-decomposition approach of Briley and McDonald. The approach has been applied to compute the laminar and turbulent tip vortex flows for a constant thickness slab airfoil with a square tip, a constant thickness slab airfoil with a half round tip and a NACA 0012 airfoil with a half round tip. The basic mechanism of the tip vortex generation process as well as the prediction of vortex appearance, strength and secondary flow shown by the calculations are in qualitative agreement with experimental results.

Lin, S. J.↗

A three-dimensional viscous flow analysis for the helicopter tip vortex generation process about square and round tipped blades

The tip vortex flow field occurring in the vicinity of the tip region of a helicopter rotor blade is a very complicated three-dimensional, viscous flow phenomenon. The details of the flow in the tip region can have a major effect in determining the generated rotor noise and can significantly effect the performance and dynamic loading of the rotor blade. The three-dimensional viscous subsonic tip vortex generation processes is investigated by a numerical procedure which allows spatial forward-marching integration, utilizing flow approximations from the velocity-decomposition approach of Briley and McDonald. The approach has been applied to compute the laminar and turbulent tip vortex flows for a constant thickness slab airfoil with a square tip, a constant thickness slab airfoil with a half round tip and a NACA 0012 airfoil with a half round tip. The basic mechanism of the tip vortex generation process as well as the prediction of vortex appearance, strength and secondary flow shown by the calculations are in qualitative agreement with experimental results.

Lin, S.-J.↗

Chemical Mapping of Vesta

Vesta s surface mineralogy and composition have been studied for decades via telescopic spectroscopy and laboratory analyses of the howardite, eucrite, and diogenite (HED) meteorites, which are thought to originate from Vesta. Visible and infrared reflectance measurements by Dawn have broadly confirmed the paradigm established by Earth-based work, strengthening the Vesta-HED connection. The Dawn mission has achieved a milestone by completing the first chemical measurements of a main-belt asteroid using nuclear spectroscopy. Dawn s Gamma Ray and Neutron Detector (GRaND) has globally mapped the composition of Vesta, including the portions of the northern hemisphere not illuminated by solar radiation. GRaND is sensitive to the composition of the bulk regolith to depths of several decimeters. Abundances and/or detection limits for specific elements and elemental ratios, such as H, Fe, Si, Fe/O, Fe/Si, and K, have been measured. Variations in the average atomic mass and neutron macroscopic absorption cross section have been characterized. The measurements constrain the relative proportions of HED whole-rock end-members, providing measurements of the pyroxene and plagioclase content of the regolith, thereby constraining the processes underlying Vesta s differentiation and crustal evolution. The spatial resolution of GRaND is sufficient to determine basin-average compositions of Veneneia and Rheasilvia, which may contain outcrops of Vesta s olivine-rich mantle. While the elemental composition of Vesta s regolith is similar to the meteorites, there are notable departures from HED whole-rock compositions. While these differences are not sufficient to topple the Vesta-HED paradigm, they provide insight into global-scale processes that have shaped Vesta s surface. Questions addressed by the analysis of GRaND data include: (i) Is Vesta the source of the Fe-rich mesosiderites? (ii) Are evolved, igneous lithologies present on Vesta s surface? (iii) What are the origins of exogenic materials found in Vesta s regolith? (iv) Is the vestan mantle exposed within the southern basins?

Prettyman, Thomas H.↗

Discovering invariant spatial features in electron energy loss spectroscopy images on the mesoscopic and atomic levels

Over the last two decades, Electron Energy Loss Spectroscopy (EELS) imaging with a scanning transmission electron microscope has emerged as a technique of choice for visualizing complex chemical, electronic, plasmonic, and phononic phenomena in complex materials and structures. The availability of the EELS data necessitates the development of methods to analyze multidimensional data sets with complex spatial and energy structures. Traditionally, the analysis of these data sets has been based on analysis of individual spectra, one at a time, whereas the spatial structure and correlations between individual spatial pixels containing the relevant information of the physics of underpinning processes have generally been ignored and analyzed only via the visualization as 2D maps. Here, we develop a machine learning-based approach and workflows for the analysis of spatial structures in 3D EELS data sets using a combination of dimensionality reduction and multichannel rotationally invariant variational autoencoders. This approach is illustrated for the analysis of both the plasmonic phenomena in a system of nanowires and in the core excitations in functional oxides using low loss and core-loss EELS, respectively. The code developed in this manuscript is open sourced and freely available and provided as a Jupyter notebook for the interested reader.

36 MATERIALS SCIENCE↗

GMI-IPS: Processing & Visualization Software Used in ATom DC-8 Aircraft Studies

NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Damon, M. R.↗

A Personal Journey in Nanoscience via Developing and Applying Liquid Phase TEM

Liquid phase TEM has attracted widespread attention in recent years as a groundbreaking tool to address various fundamental problems in nanoscience. It has provided the opportunity to reveal many unseen dynamic phenomena of nanoscale materials in solution processes by direct imaging through liquids with high spatial and temporal resolution. After my earlier work on real-time imaging of the nucleation, growth, and dynamic motion of nanoparticles in liquids by developing high-resolution liquid phase transmission electron microscopy (TEM) down to the sub-nanometer level, I established my own research group at Lawrence Berkeley National Lab in 2010. My group focuses on developing and applying liquid phase TEM to investigate complex systems and reactions. We have studied a set of scientific problems centered on understanding how atomic level heterogeneity and fluctuations at solid-liquid interfaces impact nanoscale materials transformations using advanced liquid phase TEM. This article describes my personal journey in nanoscience, highlighting the main discoveries of my research group using liquid phase TEM as a unique tool. Some perspectives on the impacts of liquid phase TEM and the future opportunities in nanoscience and nanotechnology enabled by liquid phase TEM are also included.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of hybrid rocket solid fuel regression rate for a slab burner using deep learning

This study presents an imaging-based deep learning tool to measure the fuel regression rate in a 2D slab burner experiment for hybrid rocket fuels. The slab burner experiment is designed to verify mechanistic models of reacting boundary layer combustion in hybrid rockets by the measurement of fuel regression rates. A DSLR camera with a high intensity flash is used to capture images throughout the burn and the images are then used to find the fuel boundary to calculate the regression rate. A U-net convolutional neural network architecture is explored to segment the fuel from the experimental images. Here, a Monte-Carlo Dropout process is used to quantify the regression rate uncertainty produced from the network. The U-net computed regression rates are compared with values from other techniques from literature and show error less than 10%. An oxidizer flux dependency study is performed and shows the U-net predictions of regression rates are accurate and independent of the oxidizer flux, when the images in the training set are not over-saturated. Training with monochrome images is explored and is not successful at predicting the fuel regression rate from images with high noise. The network is superior at filtering out noise introduced by soot, pitting, and wax deposition on the chamber glass as well as the flame when compared to traditional image processing techniques, such as threshold binary conversion and spatial filtering. U-net consistently provides low error image segmentations to allow accurate computation of the regression rate of the fuel.

42 ENGINEERING↗

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗

Incorporating space and time into random forest models for analyzing geospatial patterns of drug-related crime incidents in a major U.S. metropolitan area

The opioid crisis has hit American cities hard, and research on spatial and temporal patterns of drug-related activities including detecting and predicting clusters of crime incidents involving particular types of drugs is useful for distinguishing hot zones where drugs are present that in turn can further provide a basis for assessing and providing related treatment services. In this study, we investigated spatiotemporal patterns of more than 52,000 reported incidents of drug-related crime at block group granularity in Chicago, IL between 2016 and 2019. We applied a space-time analysis framework and machine learning approaches to build a model using training data that identified whether certain locations and built environment and sociodemographic factors were correlated with drug-related crime incident patterns, and establish the top contributing factors that underlaid the trends. Space and time, together with multiple driving factors, were incorporated into a random forest model to analyze these changing patterns. We accommodated both spatial and temporal autocorrelation in the model learning process to assist with capturing the changes over time and tested the capabilities of the space-time random forest model by predicting drug-related activity hot zones. Overall, we focused particularly on crime incidents that involved heroin and synthetic drugs as these have been key drug types that have highly impacted cities during the opioid crisis in the U.S.

97 MATHEMATICS AND COMPUTING↗

X-ray computed tomography-based porosity analysis: Algorithms and application for porous woody biomass

The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.

42 ENGINEERING↗

Deposition-controlled phase separation in CuNb metallic alloys

Vapor co-deposited metal nanocomposites with immiscible components have shown to have several superior properties including mechanical performance, radiation tolerance, and enhanced functionalities. The morphology and structural design of these nanocomposites are important in determining the expression of these properties. The conditions used to deposit thin film nanocomposites are the governing factors in determining the final nanostructure. In this work, we link the effects of process gas pressure, substrate temperature, and sputtering target power on resultant Cu/Nb thin film nanostructures. Here, we find that for films with equiatomic phase fractions of Cu and Nb, inhomogeneous precipitate segregation dominated the structure at lower substrate temperature depositions while higher temperatures distributed the Cu and Nb phases more uniformly. Increasing process gas pressure during deposition lead to a spatially homogeneous, nanocrystalline structure of Cu/Nb. In situ annealing of this sample shows that the phase separated morphology of the two immiscible materials depends on the initial composition. Finally, compositions of Cu and Nb that were highly disparate lead to interface segregation of the minority phase. The morphological evolution observed in the Cu/Nb system is compatible with modified structural zone models for immiscible thin film systems.

36 MATERIALS SCIENCE↗

Four Theories of the Madden‐Julian Oscillation

Abstract Studies of the Madden‐Julian Oscillation (MJO) have progressed considerably during the past decades in observations, numerical modeling, and theoretical understanding. Many theoretical attempts have been made to identify the most essential processes responsible for the existence of the MJO. Criteria are proposed to separate a hypothesis from a theory (based on the first principles with quantitative and testable assumptions, able to predict quantitatively the fundamental scales and eastward propagation of the MJO). Four MJO theories are selected to be summarized and compared in this article: the skeleton theory, moisture‐mode theory, gravity‐wave theory, and trio‐interaction theory of the MJO. These four MJO theories are distinct from each other in their key assumptions, parameterized processes, and, particularly, selection mechanisms for the zonal spatial scale, time scale, and eastward propagation of the MJO. The comparison of the four theories and more recent development in MJO dynamical approaches lead to a realization that theoretical thinking of the MJO is diverse and understanding of MJO dynamics needs to be further advanced.

58 GEOSCIENCES↗

Investigation of Coupled Processes in Fractures and the Bordering Matrix via a Micro‐Continuum Reactive Transport Model

Abstract In multi‐mineral fractured rocks, the altered porous layer on the fracture surface resulting from preferential dissolution of the fast‐reacting minerals can have profound impacts on subsequent chemical‐physical alteration of the fractures. This study adopts the micro‐continuum approach to provide further understanding of reactive transport processes in the altered layer (AL), and mass exchanges with the bordering matrix and fracture. The modeling framework couples the Darcy‐Brinkman‐Stokes (DBS) solver in COMSOL Multiphysics and the geochemical modeling capability of CrunchFlow. Three‐dimensional steady state simulations with systematically varied chemical‐physical parameters of the AL were performed to examine the impacts of individual factors and processes. Our simulation results confirm previous observations that dissolution of the fast‐reacting mineral (i.e., calcite) is largely controlled by diffusion across the AL. We also show that dissolution of the slow‐reacting mineral (i.e., dolomite), which controls AL development and fracture enlargement, increases with surface area and has a complex dependence on different local rate‐limiting processes. In particular, advection can result in evident spatial variations in the local dissolution rates of dolomite, although it does not affect the bulk chemistry significantly. The difference in the spatial patterns between simulations with and without advection in the AL is more noticeable in the locations with smaller apertures, with up to 20% difference in local reaction rates. Therefore, it is important to include a full depiction of advection, diffusion, and reactions for accurately capturing local dynamics that control long‐term fracture evolution.

58 GEOSCIENCES↗