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At least 1,045 records · Page 58

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

Electron Energy-Loss Spectroscopy and Differential Phase Contrast Imaging with Active Decision in Multimodal Electron Microscopy: Isotopic detection at the atomic scale

Isotopic engineering provides a powerful route to control phonon behavior in crystalline solids, enabling fundamental studies of lattice dynamics and heat transport at the atomic scale. Here, we directly visualize isotope-dependent phonon propagation in epitaxial Cr 2 O 3 using aberration-corrected scanning transmission electron microscopy (STEM) combined with monochromated, high-energy-resolution electron energy-loss spectroscopy (EELS). Guided by ab initio phonon calculations, we demonstrate that optical phonon modes above 70 meV are predominantly oxygen-derived and exhibit measurable redshifts upon substitution of natural 16 O by enriched 18 O. Spatially resolved vibrational spectrum imaging reveals isotope-enriched tracer layers within Cr 2 O 3 thin films, correlating isotope concentration with phonon intensity variations and vibrational energy shifts. At the nanometer and atomic scales, vibrational EELS mapping uncovers coherent phonon propagation across isotopic interfaces, consistent with theoretical phonon density of states and dispersion relations. These results establish vibrational EELS as a quantitative probe for isotope-dependent phonon transport in materials, opening new possibilities for studying energy dissipation and lattice dynamics.

36 MATERIALS SCIENCE↗

Extended X-Ray Monitoring of Gravitational Lenses with Chandra and Joint Constraints on X-Ray Emission Regions

We present an X-ray photometric analysis of six gravitationally lensed quasars, with observation campaigns spanning from 5 to 14 years, measuring the total (0.83–21.8 keV restframe), soft- (0.83–3.6 keV), and hard- (3.6–21.8 keV) band image flux ratios for each epoch. Using the ratios of the model-predicted macro-magnifications as baselines, we build differential microlensing light curves and obtain joint likelihood functions for the average X-ray emission region sizes. Our analysis yields a probability distribution function for the average half-light radius of the X-ray emission region in the sample that peaks slightly above 1 gravitational radius and with nearly indistinguishable 68% confidence (one-sided) upper limits of 17.8 and 18.9 gravitational radii for the soft and hard X-ray emitting regions, assuming a mean stellar mass of 0.3 M {sub ⊙}. We see hints of energy dependent microlensing between the soft and hard bands in two of the objects. In a separate analysis on the root-mean-square (rms) of the microlensing variability, we find significant differences between the soft and hard bands, but the sign of the difference is not consistent across the sample. This suggests the existence of some kind of spatial structure to the X-ray emission in an otherwise extremely compact source. We also discover a correlation between the rms microlensing variability and the average microlensing amplitude.

79 ASTRONOMY AND ASTROPHYSICS↗

A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log

Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.

Park, Byung↗

Building spatial symmetries into parameterized quantum circuits for faster training

Abstract Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much research has been devoted to devising adequate gate-sets, typically respecting some symmetries of the problem, very little is known about how their parameters should be structured. In this work, we show that an ideal parameter structure naturally emerges when carefully considering spatial symmetries (i.e. the symmetries that are permutations of parts of the system under study). Namely, we consider the automorphism group of the problem Hamiltonian, leading us to develop a circuit construction that is equivariant under this symmetry group. The benefits of our novel circuitstructure, called ORB, are numerically probed in several ground-state problems. We find a consistent improvement (in terms of circuit depth, number of parameters required, and gradient magnitudes) compared to literature circuit constructions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spatial Mode Correction of Single Photons Using Machine Learning

Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Relationship between surface μ‐roughness and interface slurry particle spatial distribution during glass polishing

Abstract During optical glass polishing, a number of interactions between the workpiece (i.e., glass), polishing slurry, and pad can influence the resulting workpiece roughness at different spatial scale lengths. In our previous studies, the particle size distribution of the slurry, the pad topography, and the amount of material removed by a single particle on the workpiece were shown to strongly correlate with roughness at AFM scale lengths (nm‐μm) and weakly at μ‐roughness scale lengths (μm‐mm). In this study, the polishing slurry pH and the generation of glass removal products are shown to influence the slurry particle spatial and height distribution at the polishing interface and the resulting μ‐roughness of the glass workpiece. A series of fused silica and phosphate glass samples were polished with various ceria and colloidal silica slurries over a range of slurry pH , and the resulting AFM roughness and μ‐roughness were measured. The AFM roughness was largely invariant with pH , suggesting that the removal function of a single particle is unchanged with pH . However, the μ‐roughness changed significantly, increasing linearly with pH for phosphate glass and having a maximum at an intermediate pH for fused silica. In addition, the spatial and height distribution of slurry particles on the pad (as measured by laser confocal microscopy) was determined to be distinctly different at low and high pH during phosphate glass polishing. Also, the zeta potential as a function of pH was measured for the workpiece, slurry, and pad with and without surrogate glass products (K 3 PO 4 for phosphate glass and Si( OH ) 4 for silica) to assess the role of interfacial charge during polishing. The addition of K 3 PO 4 significantly raised the zeta potential, whereas addition of Si( OH ) 4 had little effect on the zeta potential. An electrostatic DLVO three‐body force model, using the measured zeta potentials, was used to calculate the particle–particle, particle–workpiece, and particle–pad attractive and repulsive forces as a function of pH and the incorporation of glass products at the interface. The model predicted an increase in particle–pad attraction with an increase in pH and phosphate glass products consistent with the measured slurry distribution on the pads during phosphate glass polishing. Finally, a slurry “island” distribution gap ( IDG ) model has been formulated which utilizes the measured interface slurry distributions and a load balance to determine the interface gap, the contact area fraction, and the load on each slurry “island”. The IDG model was then used to simulate the workpiece surface topography and μ‐roughness; the results show an increase in roughness with pH similar to that observed experimentally.

Suratwala, Tayyab↗

Microscopic origins of hydrodynamic transport in the type-II Weyl semimetal WP 2

A microscopic understanding of hydrodynamic transport in Dirac and Weyl semimetals has remained elusive in theoretical descriptions and experimental measurements. We investigate the structure and microscopic properties of transport in WP 2 , a type-II Weyl semimetal exhibiting hydrodynamic transport. Here, we characterize the nature of the microscopic properties of WP 2 as a function of temperature through ab initio calculations of the relevant scattering processes, including electron-phonon and electron-electron lifetimes, and provide equivalent calculations for copper as a point of reference. Additionally, we present an approach to calculate phonon drag, a mechanism invoked in recent experiments, through predictions of a phonon-mediated electron-electron lifetime. We show that the resistivity is very well described by the electron-phonon interaction alone, indicating WP 2 exhibits conventional metallic electrical behavior in which strong electron-electron correlations do not play a significant role. After establishing the zone-averaged behavior of the calculated lifetimes, we further investigate specific features of the spatial distribution of the electron-phonon lifetime across the Fermi surfaces of WP 2 to study possible scattering channels involved in hydrodynamic transport and quantify the degree of lifetime anisotropy in electron and hole pockets. This description of microscopic dynamics in WP 2 prompts additional investigation of specific scattering channels and indicates the importance of phonon interactions in understanding connections between transport in hydrodynamic materials and strongly correlated systems including unconventional metals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Trade-offs between microbiome diversity and productivity in a stratified microbial mat

Productivity is a major determinant of ecosystem diversity. Microbial ecosystems are the most diverse on the planet yet very few relationships between diversity and productivity have been reported as compared to macro-ecological studies. Here we evaluated the spatial relationships of productivity and microbiome diversity in a laboratory-cultivated photosynthetic mat. The goal was to determine how spatial diversification of microorganisms drives localized carbon and energy acquisition rates. We measured sub-millimeter depth profiles of net primary-productivity and gross oxygenic photosynthesis in the context of the localized microenvironment and community structure and observed negative correlations between species richness and productivity within the energy-replete, photic zone. Variations between localized community structures were associated with distinct taxa as well as environmental profiles describing a continuum of biological niches. Spatial regions corresponding to high primary productivity and photosynthesis rates had relatively low species richness and high evenness. Hence, this system exhibited negative species-productivity and species–energy relationships. These negative relationships may be indicative of photosynthetically-driven, light-controlled mat ecosystems that are able to be the most productive with a relatively smaller, even distributions of species that specialize within the highly-oxic, photic zones.

59 BASIC BIOLOGICAL SCIENCES↗

Test to Extract Soil Properties Using the Seismic HammerTM Active Seismic Source

Geologic material properties are necessary parameters for ground motion modeling and are difficult and expensive to obtain via traditional methods. Alternative methods to estimate soil properties require a measurement of the ground's response to a force. A possible method of obtaining these measurements is active-source seismic surveys, but measurements of the ground response at the source must also be available. The potential of seismic sources to obtain soil properties is limited, however, by the repeatability of the source. Explosives, and hammer surveys are not repeatable because of variable ground coupling or swing strength. On the other hand, the Seismic Hammer TM (SH) is consistent in the amount of energy it inputs into the ground. In addition, it leaves large physical depressions as a result of ground compaction. The volume of ground compaction varies by location. Here, we hypothesize that physical depressions left in the earth by the SH correlate to energy recorded by nearby geophones, and therefore are a measurement of soil physical properties. Using measurements of the volume of shot holes, we compare the spatial distribution of the volume of ground compacted between the different shot locations. We then examine energy recorded by the nearest 50 geophones and compare the change in amplitude across hits at the same location. Finally, we use the percent difference between the energy recorded by the first and later hits at a location to test for a correlation to the volume of the shot depressions. We find that: * Ground compaction at the shot-depression does cluster geographically, but does not correlate to known surface features. * Energy recorded by nearby geophones reflects ground refusal after several hits. * There is no correlation to shot volume and changes in energy at particular shot locations. Deeper material properties (i.e. below the depth of surface compaction) may be contributing to the changes in energy propagation. * Without further processing of the data, shot-depression volumes are insufficient to understanding ground response to the SH. Without an accurate understanding of the ground response, we cannot extract material properties in conjunction with the SH survey. Additional processing including picking direct arrivals and static corrections may yield positive results.

58 GEOSCIENCES↗

Good and proper: self-similarity of N -body simulations with proper force softening

ABSTRACT Analysis of self-similarity in scale-free N-body simulations reveals the spatial and temporal scales for which statistics measured in cosmological simulations are converged to the physical continuum limit. We examine how the range of scales in which the two-point correlation function is converged depends on the force softening length and whether it is held constant in comoving or proper coordinates. We find that a proper softening that reaches roughly 1/30th of the inter-particle spacing by the end of the simulation resolves the same spatial and temporal scales as a comoving softening of the same length while using a third fewer time-steps, for a range of scale factors typical to Lambda cold dark matter (ΛCDM) simulations. We additionally infer an inherent resolution limit, set by the particle mass and scaling as a−1/2, beyond which reducing the softening does not improve the resolution. We postulate a mapping of these results with spectral index n = −2 to ΛCDM simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Sharp, high numerical aperture (NA), nanoimprinted bare pyramid probe for optical mapping

The ability to correlate optical hyperspectral mapping and high resolution topographic imaging is critically important to gain deep insight into the structure–function relationship of nanomaterial systems. Scanning near-field optical microscopy can achieve this goal, but at the cost of significant effort in probe fabrication and experimental expertise. To overcome these two limitations, we have developed a low-cost and high-throughput nanoimprinting technique to integrate a sharp pyramid structure on the end facet of a single-mode fiber that can be scanned with a simple tuning-fork technique. The nanoimprinted pyramid has two main features: (1) a large taper angle (~70°), which determines the far-field confinement at the tip, resulting in a spatial resolution of 275 nm, an effective numerical aperture of 1.06, and (2) a sharp apex with a radius of curvature of ~20 nm, which enables high resolution topographic imaging. Optical performance is demonstrated through evanescent field distribution mapping of a plasmonic nanogroove sample, followed by hyperspectral photoluminescence mapping of nanocrystals using a fiber-in-fiber-out light coupling mode. Through comparative photoluminescence mapping on 2D monolayers, we also show a threefold improvement in spatial resolution over chemically etched fibers. These results show that the bare nanoimprinted near-field probes provide simple access to spectromicroscopy correlated with high resolution topographic mapping and have the potential to advance reproducible fiber-tip-based scanning near-field microscopy.

47 OTHER INSTRUMENTATION↗

Formulation of a one-dimensional electrostatic plasma model for testing the validity of kinetic theory

Here, we present a one-dimensional (1-D) model composed of aligned, electrostatically interacting charged disks, conceived to address in a computable model the validity of the Bogoliubov assumption on the decay of particle correlations in the Born–Bogoliubov–Green–Kirkwood–Yvon hierarchy. This assumption is a basic premise of plasma kinetic theory. The disk model exhibits spatially 1-D features at short distances, but retains 3-D features at large distances. Here the collective dynamics of this model plasma is investigated by solving the corresponding Vlasov equation. In addition, the implementation of the model for the numerical validation of the Bogoliubov assumption is formulated.

1-D plasma model↗

Treatment of Nonuniform Temperature Distribution by Subgroup Method

The subgroup method divides an energy group into several subgroups according to the magnitude of the cross section. The subgroup fixed source equation is formulated on the energy range of a subgroup, the ratio of which to the energy range of an energy group is defined as subgroup probability. Typically the physical probability table or the mathematical probability table is applied. However, both of the tables are not guaranteed to share the same set of subgroup probabilities for a resonant nuclide at different temperatures. This means that the subgroup fixed source equation cannot be formulated and the subgroup method will not work when the temperature distribution is nonuniform. To overcome this defect, the subgroup method based on partial cross section fit scheme (PXSFS) and the simplified partial cross section fit scheme (SPXSFS) are proposed. These methods fit the cross sections at different temperatures as partial cross sections to share a same set of subgroup probabilities. The new methods is compared to the conventional subgroup method (CSM) based on physical probability table and the preexisting methods: the correlation model (CM), the subgroup level adjustment scheme (SLAS) and the number density adjustment scheme (NDAS). The numerical results show that the new methods can better predict the spatial dependent reaction rate than preexisting methods. Within these two methods, the simplified scheme consumes less time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A COUPLED 2 × 2D BABCOCK–LEIGHTON SOLAR DYNAMO MODEL. II. REFERENCE DYNAMO SOLUTIONS

In this paper we complete the presentation of a new hybrid 2 × 2D flux transport dynamo (FTD) model of the solar cycle based on the Babcock–Leighton mechanism of poloidal magnetic field regeneration via the surface decay of bipolar magnetic regions (BMRs). This hybrid model is constructed by allowing the surface flux transport (SFT) simulation described in Lemerle et al. to provide the poloidal source term to an axisymmetric FTD simulation defined in a meridional plane, which in turn generates the BMRs required by the SFT. A key aspect of this coupling is the definition of an emergence function describing the probability of BMR emergence as a function of the spatial distribution of the internal axisymmetric magnetic field. We use a genetic algorithm to calibrate this function, together with other model parameters, against observed cycle 21 emergence data. We present a reference dynamo solution reproducing many solar cycle characteristics, including good hemispheric coupling, phase relationship between the surface dipole and the BMR-generating internal field, and correlation between dipole strength at cycle maximum and peak amplitude of the next cycle. The saturation of the cycle amplitude takes place through the quenching of the BMR tilt as a function of the internal field. The observed statistical scatter about the mean BMR tilt, built into the model, acts as a source of stochasticity which dominates amplitude fluctuations. The model thus can produce Dalton-like epochs of strongly suppressed cycle amplitude lasting a few cycles and can even shut off entirely following an unfavorable sequence of emergence events.

79 ASTRONOMY AND ASTROPHYSICS↗

Direct measurements of slip irreversibility in a nickel-based superalloy using high resolution digital image correlation

Fatigue crack nucleation in crystalline materials typically develops due to highly localized cyclic slip. During a fatigue cycle, reverse slip differs locally from slip in the forward direction particularly in precipitate-containing materials such as superalloys. In this paper we report the first direct measurements of irreversibility at the scale of individual slip bands by high-resolution digital image correlation (DIC) in a polycrystalline nickel-based superalloy. Quantitative measurements of the slip irreversibility are challenging for regions of material that have a size that captures the microstructure and its variability. High spatial resolution at the nanometer scale during experimental measurements is needed to observe slip localization during deformation. Moreover, large fields are also needed to obtain the material response over statistically representative populations of microstructural configurations. Recently, high resolution scanning electron microscope (SEM) digital image correlation (DIC) has been extended for quantitative analysis of discontinuities induced by slip events using the Heaviside-DIC method. Therefore, this novel method provides quantitative measurements of slip localization at the specimen surface. In this paper, the Heaviside-DIC method is used to measure slip irreversibility and plastic strain accumulation in a nickel-based superalloy. The method detects bands with high levels of irreversibility early in cycling that ultimately form fatigue cracks upon further cycling. The local microstructural configurations that induce large amounts of plasticity and slip irreversibility are correlated to crack nucleation locations.

36 MATERIALS SCIENCE↗