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DOE OSTI2020

Validation of selection function, sample contamination and mass calibration in galaxy cluster samples

ABSTRACT We construct and validate the selection function of the MARD-Y3 galaxy cluster sample. This sample was selected through optical follow-up of the 2nd ROSAT faint source catalogue with Dark Energy Survey year 3 data. The selection function is modelled by combining an empirically constructed X-ray selection function with an incompleteness model for the optical follow-up. We validate the joint selection function by testing the consistency of the constraints on the X-ray flux–mass and richness–mass scaling relation parameters derived from different sources of mass information: (1) cross-calibration using South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) clusters, (2) calibration using number counts in X-ray, in optical and in both X-ray and optical while marginalizing over cosmological parameters, and (3) other published analyses. We find that the constraints on the scaling relation from the number counts and SPT-SZ cross-calibration agree, indicating that our modelling of the selection function is adequate. Furthermore, we apply a largely cosmology independent method to validate selection functions via the computation of the probability of finding each cluster in the SPT-SZ sample in the MARD-Y3 sample and vice versa. This test reveals no clear evidence for MARD-Y3 contamination, SPT-SZ incompleteness or outlier fraction. Finally, we discuss the prospects of the techniques presented here to limit systematic selection effects in future cluster cosmological studies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Allometric Scaling of Hyporheic Respiration Across Basins in the Pacific Northwest United States

Abstract Hyporheic zones regulate biogeochemical processes in streams and rivers, but high spatiotemporal heterogeneity makes it difficult to predict how these processes scale from individual reaches to river basins. Recent work applying allometric scaling (i.e., power‐law relationships between size and function) to river networks provides a new paradigm for understanding cumulative hyporheic biogeochemical processes. We used previously published model predictions of reach‐scale hyporheic aerobic respiration to explore patterns in allometric scaling across two climatically divergent basins with differing characteristics in the Pacific Northwest, United States. In the model, hydrologic exchange fluxes (HEFs) regulate hyporheic respiration, so we examined how HEFs might influence allometric scaling of respiration. We found consistent scaling behaviors where HEFs were either very low or very high, but differences between basins when HEFs were moderate. Our findings provide initial model‐generated hypotheses for factors influencing allometric scaling of hyporheic respiration. These hypotheses can be used to optimize new data generation efforts aimed at developing predictive understanding of allometries that can, in turn, be used to scale biogeochemical dynamics across watersheds.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Spatial Microbial Respiration Variations in the Hyporheic Zones Within the Columbia River Basin

Abstract While the hyporheic zone (HZ) accounts for a significant portion of whole stream CO 2 concentrations, HZ respiration modeling studies are lacking in quantifying their contributions to the total CO 2 at large watershed/basin scales. Quantifying the contribution of anaerobic respiration is also underappreciated. This study used a carbon‐nitrogen‐coupled river corridor model to quantify HZ aerobic and anaerobic respiration and determined the key factors controlling their spatial variability within the Columbia River Basin (CRB). The modeled respiration patterns showed high spatial variability. Among the nine sub‐basins composing the CRB, the Lower Columbia and the Willamette, which receive higher precipitation, had higher respiration. Medium‐sized rivers (fourth to sixth orders) produced the highest aerobic and anaerobic respiration among reaches of different sizes. At the basin scale, aerobic respiration is dominant, representing approximately 98.7% of the total respiration across the CRB. While most of the reaches were dominant with aerobic respiration, reaches in agricultural land showed a relatively higher anaerobic respiration (18%) ratio. A variable importance analysis showed that hyporheic exchange flux controlled most of the spatial variability of HZ respiration, dominating over other physical variables such as residence time, stream dissolved organic carbon (DOC), nitrate, and dissolved oxygen (DO). The influence of substrate concentration (DOC and DO) is larger in modeling anaerobic respiration than aerobic respiration. Future efforts will focus on improving the estimation of the HZ exchange flux and the implementation of spatially explicit parameterizations for the reactions of interest to reduce model uncertainty.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Landscape composition and configuration have scale-dependent effects on agricultural pest suppression

Increasing landscape heterogeneity (composition and configuration) can enhance natural enemy populations and support pest suppression in agricultural landscapes. Using a network-based data mining approach, we examined independent gradients of landscape composition and configuration at six spatial scales that were associated with pest suppression services measured at 32 sites in Michigan and Wisconsin, USA. We compared the relative effects of landscape composition and configuration across scales with those of local crop type (corn or grassland). We found that multiple gradients of configurational heterogeneity were independent of composition and strongly associated with pest suppression, with different configuration metrics being predictive of pest suppression depending on the spatial scales and regions considered. Landscapes that were more configurationally heterogeneous at smaller spatial scales consistently supported higher pest suppression. In Michigan, pest suppression increased in landscapes with high edge contrast between annual crops and surrounding habitats and high edge density of grassland within 250-500 m radii. In Wisconsin, pest suppression increased with large core area of grassland and high field density within a 250 m radius. The main compositional effect we found was a positive relationship between grassland cover and pest suppression occurring at larger spatial scales (1000-1500 m) and occurring in Wisconsin but not in Michigan. Our findings demonstrate that effects of landscape composition and configuration on pest suppression differ across spatial scales and vary regionally. The network-based data mining techniques used here could be useful for disentangling intercorrelated landscape metrics in a variety of other contexts in landscape ecology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A scale-wise analysis of intermittent momentum transport in dense canopy flows

We investigate the intermittent dynamics of momentum transport and its underlying time scales in the near-wall region of the neutrally stratified atmospheric boundary layer in the presence of a vegetation canopy. This is achieved through an empirical analysis of the persistence time scales (periods between successive zero-crossings) of momentum flux events, and their connection to the ejection–sweep cycle. Using high-frequency measurements from the GoAmazon campaign, spanning multiple heights within and above a dense canopy, the analysis suggests that, when the persistence time scales ( $t_p$ ) of momentum flux events from four different quadrants are separately normalized by $\varGamma _{w}$ (integral time scale of the vertical velocity), their distributions $P(t_p/\varGamma _{w})$ remain height-invariant. This result points to a persistent memory imposed by canopy-induced coherent structures, and to their role as an efficient momentum-transporting mechanism between the canopy airspace and the region immediately above. Moreover, $P(t_p/\varGamma _{w})$ exhibits a power-law scaling at times $t_{p}<\varGamma _{w}$ , with an exponential tail appearing for $t_{p} \geq \varGamma _{w}$ . By separating the flux events based on $t_p$ , we discover that around 80 % of the momentum is transported through the long-lived events ( $t_{p} \geq \varGamma _{w}$ ) at heights immediately above the canopy, while the short-lived ones ( $t_{p} < \varGamma _{w}$ ) only contribute marginally ( $\approx 20\,\%$ ). To explain the role of instantaneous flux amplitudes in momentum transport, we compare the measurements with newly developed surrogate data and establish that the range of time scales involved with amplitude variations in the fluxes tends to increase as one transitions from within to above the canopy.

Mechanics↗

DOE OSTI2024

FORSE+: Simulating non-Gaussian CMB foregrounds at 3 arcmin in a stochastic way based on a generative adversarial network

We present FORSE+, a Python package that produces non-Gaussian diffuse Galactic thermal dust emission maps at arcminute angular scales and that has the capacity to generate random realizations of small scales. This represents an extension of the FORSE (Foreground Scale Extender) package, which was recently proposed to simulate non-Gaussian small scales of thermal dust emission using generative adversarial networks (GANs). With the input of the large-scale polarization maps from observations, FORSE+ has been trained to produce realistic polarized small scales at 3′ following the statistical properties, mainly the non-Gaussianity, of observed intensity small scales, which are evaluated through Minkowski functionals. Furthermore, by adding different realizations of random components to the large-scale foregrounds, we show that FORSE+ is able to generate small scales in a stochastic way. In both cases, the output small scales have a similar level of non-Gaussianity compared with real observations and correct amplitude scaling as a power law. These realistic new maps will be useful, in the future, to understand the impact of non-Gaussian foregrounds on the measurements of the cosmic microwave background (CMB) signal, particularly on the lensing reconstruction, de-lensing, and the detection of cosmological gravitational waves in CMB polarizationB-modes.

Astronomy & Astrophysics↗

DOE OSTI2025

Spin-on deposition of amorphous zeolitic imidazolate framework films for lithography applications

Amorphous zeolitic imidazolate framework (aZIF) films have been recently introduced as resists for electron beam and extreme ultraviolet lithography. aZIFs are also being considered for separation applications, including thin film membranes. However, the reported methods for aZIF deposition are currently based on highly empirical trial-and-error approaches that hinder control of film composition, thickness and uniformity as well as scale-up and transferability to different coating geometries. This work presents a method for depositing aZIF films with controllable thickness using dilute precursors mixed immediately before encountering the substrate. Importantly, the method is amenable to quantitative analysis by computational fluid dynamics to extract intrinsic deposition rates and limiting reactant transport diffusivities, enabling predictive physics-based modeling of the deposition process. This allows the deposition method to be adapted for spin coating on silicon wafers to prepare high-quality aZIF films with consistently controlled thickness. Using this approach, high-resolution resist performance and wafer-scale use for beyond extreme-ultraviolet lithography of aZIF films is demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

On the relationship between precipitation extreme and local temperature over eastern China based on convection permitting simulations: roles of different moisture processes and precipitation types

The Clausius–Clapeyron (CC) scaling, which indicates a roughly 7% increase in saturated water vapor per 1 °C increase in temperature, can serve as a strong constraint linking the intensity of precipitation extremes and local temperature. However, the relationship between precipitation extreme and local temperature (referred to as the PE-T relationship) does not always follow the CC scaling and is highly dependent on climate regimes. In this study, we investigated the impacts of different moisture processes and precipitation types on the PE-T relationship over eastern China during the summertime based on convection-permitting model simulations. Consistent with observations, the simulated intensity of precipitation extremes increases with temperature at a rate close to CC (double-CC) scaling below (above) 20 °C. When the temperature exceeds 25 °C, precipitation intensity starts to drop. Precipitation extremes are mainly contributed by the stratiform, MCS (i.e., mesoscale convective system) convective, and non-MCS convective precipitation at low (< 20 °C), medium (20–25 °C), and high (> 25 °C) temperatures, respectively, suggesting that the double-CC scaling occurs when convective types become dominant, while the negative scaling at high temperatures is attributed to the reduced horizontal scale of convection. Corresponding to the reduced intensity of precipitation at high temperatures, there are stronger divergence and subsidence in the low-level atmosphere, which is probably caused by the net cooling associated with the enhanced melting and evaporation of falling hydrometeors due to the lower relative humidity in the low-level atmosphere. Overall, our findings contribute to a deeper understanding of the temperature dependence of precipitation extremes in eastern China.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

High-Fidelity Simulation Study of the Unsteady Flow Effects on High-Pressure Turbine Blade Performance

Abstract Unsteadiness, in the form of both broadband background disturbances and discrete coherent wakes, can have a strong effect on the performance of turbomachinery blades. The influence of the incoming flow has received much interest as it inevitably affects the blade boundary layers and develops as it passes through the machine. In the present work, we investigate the effect of unsteady flow on high-pressure turbines (HPTs), using high-fidelity datasets produced by wall resolved large-eddy simulation of an HPT stage. The effects of incident wakes from an upstream stator, compounded by the presence of freestream turbulence, on the downstream rotor are investigated. Based on analyzing cases with different turbulence intensities and length scales prescribed at the inlet, we show that changing the freestream turbulence characteristics has a direct effect on the unsteady behavior of the stator wakes. As a result, the performance of the rotor is also significantly affected. By detailing the influence of the wake–turbulence interaction, we aim to distinguish driving forces on rotor performance, be it changes in the incident wakes or direct influence from the freestream turbulence. Furthermore, the aerothermal behaviors of the rotor blades have been extensively investigated, showing that the blade boundary layers on the suction and pressure sides respond differently to external disturbances. The insights gained can provide designers with guidelines in understanding the unsteady flow effects of a given flow state, and how the unsteadiness present, either broadband or deterministic, will affect the performance of downstream blades.

Engineering↗

DOE OSTI2022

Technoeconomic Analysis of High-Value, Crystalline Silicon Photovoltaic Module Recycling Processes

Recycling is an important circular economy strategy, and for photovoltaics (PV), the one that has received the greatest research attention. Recycling of PV modules is required in Europe; everywhere else it competes in the market of end-of-life options, where cost is a primary decision factor. The vast majority of PV modules sold globally are crystalline-silicon (c-Si); most of the rest of the market are cadmium telluride thin film modules whose primary manufacturer runs its own commercial-scale recycling program. While many different c-Si recycling approaches and technologies have been proposed, they generally lack accompanying cost estimates or enough process information to model costs. Herein we develop detailed estimates of seven categories of capital and operating costs along with estimates of revenue from recovered materials for each step in two proposed recycling processes for c-Si PV modules. Using these results, we develop a hypothetical third recycling process merging process steps from the original two, estimate surcharges required to achieve minimum sustainable prices for each recycling process, as well as consider how economies of scale could reduce costs. Increasing the purity of and identifying higher-value markets for recovered materials are approaches to reducing costs and increasing recycling rates in voluntary markets.

crystalline silicon↗

DOE OSTI2022

Progress Towards a Predictive Eagle Behavior and Risk Modeling Framework: Overview and Recent Validation Efforts

This presentation summarizes progress to date of the U.S. Department of Energy project, "Development of a computational framework for modeling golden eagles (Aquila chrysaetos) near wind farms," which focuses on stochastic behavioral modeling of soaring raptors across landscape, facility, and turbine spatiotemporal scales. This publicly available, open-source modeling framework includes behavioral models based on three different underlying principles: energy minimization at landscape scale, behavioral heuristics at landscape-facility scale, and data-driven behaviors at the facility-micro-scale. We will briefly overview the key advancements in the behavioral modeling state of the art, which leverages multiple high-resolution telemetry data sources combined with high-fidelity atmospheric flow modeling insights. We then present preliminary results from a validation study in Altamont, California. This new study involves a novel application of the Stochastic Soaring Raptor Simulator (SSRS), in a new geographic locale, to understand facility scale eagle movement patterns over time scales representative of a wind project's lifetime. For this desktop analysis (that does not depend on any high-performance computing resources), SSRS simultaneously considers a variety of wind conditions and eagle approach vectors toward a project site of interest. This work demonstrates the integration of publicly available landscape-scale atmospheric datasets, our recently improved engineering updraft models (see presentation from Thedin et al.), and our energy minimization behavioral models within the SSRS framework. While we only present results from a single behavioral model, the integration of these three modeling components forms the foundation for our more sophisticated behavioral models (see presentations from Brandes et al., Sandhu et al.) that are under active development. Results are presented in the form of presence maps, which may be applied to estimate risk to wildlife, augment ground survey data, inform wind-plant operations, or incorporated into wind-plant designs.

agent-based modeling↗

DOE OSTI2022

Estimating dermal contact soil exposure for amphibians

Abstract Chemical exposure estimation through the dermal route is an underemphasized area of ecological risk assessment for terrestrial animals. Currently, there are efforts to create exposure models to estimate doses from this pathway for use in ecological risk assessment. One significant limitation has been insufficient published data to characterize exposure and to support the selection and parameterization of appropriate models, particularly for amphibians in terrestrial habitats. Recent publications measuring pesticide doses to terrestrial‐phase amphibians have begun to rectify this situation. We collated and summarized available measurements of terrestrial amphibian dermal exposure to pesticides from 11 studies in which researchers measured tissue concentrations associated with known pesticide experimental application rates. This data set included tissue concentrations in 11 amphibian species and 14 different pesticides. We then compared the results of two screening exposure models that differed based on surface area scaling approaches as a function of body weight (one based on birds as surrogates for amphibians and another amphibian‐specific) to the measured tissue residue concentrations. We define a false‐negative rate for each screening model as the proportion of amphibians for which the predicted concentration is less than the observed concentration (i.e., underestimate), contrary to the intent of screening models, which are intended to have a bias for higher exposure concentrations. The screening model that uses birds as surrogates did not have any instances where estimated expected avian doses were less than measured amphibian body burdens. When using the amphibian‐specific exposure model that corrected for differences between avian and amphibian surface area, measured concentrations were greater than model estimates for 11.3% of the 1158 comparisons. The database of measured pesticide concentrations in terrestrial amphibians is provided for use in calculating bioconcentration factors and for future amphibian dermal exposure model development. Integr Environ Assess Manag 2023;19:9–16. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Environmental Sciences & Ecology↗

DOE OSTI2020

Deformation-enhanced hierarchical multiscale structure heterogeneity in a Pd-Si bulk metallic glass

Here, the multiscale structures in a Pd 82 Si 18 binary bulk metallic glass before and after deformation were studied using electron microscopies, high-energy synchrotron X-ray diffraction, and small-angle scattering techniques. The experimental results revealed an enhancement of hierarchical structure heterogeneities on multiple length scales after deformation. Hierarchical multiple shear bands of high number density were observed after bending, introducing complex but periodically distributed residual strain. Pair distribution function analysis revealed that the connectivity of the short-range clusters on the medium-range scale determines the packing density difference between the tension side and the compression side in the sample after bending. In-situ synchrotron X-ray diffraction study also revealed a transformation of connection modes among short-range clusters under uniaxial tension and compression, which is consistent with those of triaxial tension/compression parts upon bending in Pd 82 Si 18 glassy alloys. The nanoscale heterogeneities for metallic glasses after deformation observed by small-angle scattering and transmission electron microscopy may be attributed to the nanoscale amorphous phase separation and interacting multiple shear bands enhanced by plastic deformation. Our findings suggested that the enhancement of hierarchical heterogeneous structure on multiple length scales may explain the excellent plasticity of Pd-Si glassy alloys, deepening the understanding of structure-property relation during plastic deformation in metallic glasses.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Investigating the effect of different shielding gas mixtures on microstructure and mechanical properties of 410 stainless steel fabricated via large scale additive manufacturing

Metal Big Area Additive Manufacturing (mBAAM) offers the potential to fabricate large scale tools at high deposition rates (15 lb/h+). 410 martensitic steel is a potential tooling material, owing to its low cost, good machinability and reasonable printability. During the mBAAM process, the shielding gas can have a significant impact on the material properties as well as the process cost. Therefore, the current study aims to understand the effect of different shielding gas mixtures on large-scale additive manufacturing of 410 martensitic stainless steel. We show that an argon mixture with 3% nitrogen gas produced the best performance in terms of maximum hardness and tensile strength, with much less scatter in tensile strength. He-Ar-CO 2 or tri-mix shielded samples showed a low tensile strength with wide scatter, due to stabilized delta ferrite in microstructure during printing. Both tri-mix and Ar-CO 2 shielded samples showed slightly higher porosity. Thus, we recommend the use of argon-3% nitrogen as a shielding gas mixture for processing 410 steel for tool applications, based on the relatively low cost of this gas mixture and the resulting higher hardness, higher dimensional stability, and lower porosity.

36 MATERIALS SCIENCE↗

DOE OSTI2021

WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)

The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.

Miara, Ariel↗

DOE OSTI2021

Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3)

Miara, Ariel↗

DOE OSTI2020

Organismic materials for beyond von Neumann machines

The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.

42 ENGINEERING↗

DOE OSTI2023

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

Abstract This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗