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DOE OSTI2021

2D monochromatic x-ray imaging for beam monitoring of an x-ray free electron laser and a high-power femtosecond laser

Single-shot simultaneous beam monitoring of an x-ray free electron laser (XFEL) and a high-power femtosecond laser is demonstrated using 2D monochromatic Kα imaging. In a pump-probe experiment carried out at the Matter in Extreme Conditions end-station of the Linac Coherent Light Source, a thin solid titanium foil irradiated by a 25-TW relativistic intensity laser for fast electron isochoric heating was probed by a 7.0 keV XFEL beam for x-ray Thomson scattering measurements. Using a spherical crystal imager (SCI), the spatial overlap of the beams was examined by measuring 4.5 keV titanium Kα x rays produced by laseraccelerated fast electrons and the x-ray beam. Changes in XFEL-induced Kα emission patterns were observed down to a ~20×40 μm2 rectangular shape as the beam was focused. Laser-only and two-beam shots reveal that large spatial offsets of laser-induced Kα spots in a horizontal direction is attributed to imprecise target positioning rather than shot-to-shot laser pointing variations. As a consequence, successful beam overlapping was observed on ~58% of all two-beam shots for 10 μm thick samples. The Kα measurements also show a linear relationship between total Kα yields and integrated x-ray scattering signals. Monochromatic xray imaging with SCI could be used as an on-shot beam pointing diagnostic in XFEL-laser or multiple short-pulse laser experiments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Investigation of N 2 /O 2 plasma interaction with Pt-catalyst: effect of metastable adsorbates on product hysteresis

The coupling of catalysts and atmospheric-pressure plasma has the potential to improve the efficiency of certain catalytic reactions. Understanding the changes that the catalyst surface undergoes during exposure to plasma is key to improving plasma–catalytic performance. In this work, long term exposure of Pt–Al 2 O 3 powder catalyst to an Ar/N 2 /O 2 non-equilibrium atmospheric-pressure plasma-jet was investigated. Products produced by the interaction were analyzed downstream with Fourier-transform infrared spectroscopy while surface species were analyzed operandi with diffuse reflectance infrared Fourier transform spectroscopy. During exposure, the catalyst temperature was ramped cyclically between 100 °C and 350 °C to understand how substrate temperature affects the plasma–catalyst interaction. Long-lasting changes were revealed to take place on the catalyst surface during plasma exposure. At low temperatures, Pt–O and Pt–NO accumulate on the surface which react at elevated temperatures to form NO 2 . NO 2 initially appears to spill on to the Al 2 O 3 support as nitrites and nitrates instead of desorbing. Stable surface conditions are only achieved after prolonged plasma exposure, when nitrate sites on the Al 2 O 3 support are filled. By changing the catalyst temperature at various rates, the impact of total plasma species flux to the surface was analyzed. It was found that decreasing the heating rate increased the hysteresis in the pattern of NO 2 formation during thermal cycling. The variation with temperature demonstrates that plasma exposure results in a buildup of surface NO x and oxygen species which react or desorb at high temperatures. The observed changes are discussed from the generic viewpoint that a non-equilibrium plasma interacting with a catalyst at low temperature introduces metastable steady-state surface conditions. Upon heating above a threshold temperature, the introduced surface modifications can change either due to thermal effects, or, for a plasma environment, by additional interaction with the incident plasma species flux. The surface/material changes take place in a highly predictable fashion and after sufficient time above the threshold temperature reach a steady-state condition that is different from the transient behavior that is observed during initial heating. During cooling the plasma-surface interaction exhibits a different behavior than during heating, and this results in hysteresis of diverse observables. The metastability/hysteresis description appears quite generic and analogous to hysteresis behavior seen for different systems. Furthermore, it is expected to be useful for understanding the consequences of plasma–catalyst surface interactions for various systems.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The Architecture of Metabolism Maximizes Biosynthetic Diversity in the Largest Class of Fungi

Abstract Ecological diversity in fungi is largely defined by metabolic traits, including the ability to produce secondary or “specialized” metabolites (SMs) that mediate interactions with other organisms. Fungal SM pathways are frequently encoded in biosynthetic gene clusters (BGCs), which facilitate the identification and characterization of metabolic pathways. Variation in BGC composition reflects the diversity of their SM products. Recent studies have documented surprising diversity of BGC repertoires among isolates of the same fungal species, yet little is known about how this population-level variation is inherited across macroevolutionary timescales. Here, we applied a novel linkage-based algorithm to reveal previously unexplored dimensions of diversity in BGC composition, distribution, and repertoire across 101 species of Dothideomycetes, which are considered the most phylogenetically diverse class of fungi and known to produce many SMs. We predicted both complementary and overlapping sets of clustered genes compared with existing methods and identified novel gene pairs that associate with known secondary metabolite genes. We found that variation among sets of BGCs in individual genomes is due to nonoverlapping BGC combinations and that several BGCs have biased ecological distributions, consistent with niche-specific selection. We observed that total BGC diversity scales linearly with increasing repertoire size, suggesting that secondary metabolites have little structural redundancy in individual fungi. We project that there is substantial unsampled BGC diversity across specific families of Dothideomycetes, which will provide a roadmap for future sampling efforts. Our approach and findings lend new insight into how BGC diversity is generated and maintained across an entire fungal taxonomic class.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Spatial distributions of X CO 2 seasonal cycle amplitude and phase over northern high-latitude regions

Satellite-based observations of atmospheric carbon dioxide (CO 2 ) provide measurements in remote regions, such as the biologically sensitive but undersampled northern high latitudes, and are progressing toward true global data coverage. Recent improvements in satellite retrievals of total column-averaged dry air mole fractions of CO 2 (X CO 2 ) from the NASA Orbiting Carbon Observatory 2 (OCO-2) have allowed for unprecedented data coverage of northern high-latitude regions, while maintaining acceptable accuracy and consistency relative to ground-based observations, and finally providing sufficient data in spring and autumn for analysis of satellite-observed X CO 2 seasonal cycles across a majority of terrestrial northern high-latitude regions. Here, we present an analysis of X CO 2 seasonal cycles calculated from OCO-2 data for temperate, boreal, and tundra regions, subdivided into 5° latitude by 20° longitude zones. We quantify the seasonal cycle amplitudes (SCAs) and the annual half drawdown day (HDD). OCO-2 SCAs are in good agreement with ground-based observations at five high-latitude sites, and OCO-2 SCAs show very close agreement with SCAs calculated for model estimates of X CO 2 from the Copernicus Atmosphere Monitoring Services (CAMS) global inversion-optimized greenhouse gas flux model v19r1 and the CarbonTracker2019 model (CT2019B). Model estimates of X CO 2 from the GEOS-Chem CO 2 simulation version 12.7.2 with underlying biospheric fluxes from CarbonTracker2019 (GC-CT2019) yield SCAs of larger magnitude and spread over a larger range than those from CAMS, CT2019B, or OCO-2; however, GC-CT2019 SCAs still exhibit a very similar spatial distribution across northern high-latitude regions to that from CAMS, CT2019B, and OCO-2. Zones in the Asian boreal forest were found to have exceptionally large SCA and early HDD, and both OCO-2 data and model estimates yield a distinct longitudinal gradient of increasing SCA from west to east across the Eurasian continent. In northern high-latitude regions, spanning latitudes from 47 to 72° N, longitudinal gradients in both SCA and HDD are at least as pronounced as latitudinal gradients, suggesting a role for global atmospheric transport patterns in defining spatial distributions of X CO2 seasonality across these regions. GEOS-Chem surface contact tracers show that the largest X CO 2 SCAs occur in areas with the greatest contact with land surfaces, integrated over 15–30d. The correlation of X CO 2 SCA with these land surface contact tracers is stronger than the correlation of X CO 2 SCA with the SCA of CO 2 fluxes or the total annual CO 2 flux within each 5° latitude by 20° longitude zone. This indicates that accumulation of terrestrial CO 2 flux during atmospheric transport is a major driver of regional variations in X CO 2 SCA.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Simulating measurable ecosystem carbon and nitrogen dynamics with the mechanistically defined MEMS 2.0 model

Abstract. For decades, predominant soil biogeochemical models have used conceptual soil organic matter (SOM) pools and only simulated them to a shallow depth in soil. Efforts to overcome these limitations have prompted the development of the new generation SOM models, including MEMS 1.0, which represents measurable biophysical SOM fractions, over the entire root zone, and embodies recent understanding of the processes that govern SOM dynamics. Here we present the result of continued development of the MEMS model, version 2.0. MEMS 2.0 is a full ecosystem model with modules simulating plant growth with above- and belowground inputs, soil water and temperature by layer, decomposition of plant inputs and SOM, and mineralization and immobilization of nitrogen (N). The model simulates two commonly measured SOM pools – particulate and mineral-associated organic matter (POM and MAOM, respectively). We present results of calibration and validation of the model with several grassland sites in the US. MEMS 2.0 generally captured the soil carbon (C) stocks (R2 of 0.89 and 0.6 for calibration and validation, respectively) and their distributions between POM and MAOM throughout the entire soil profile. The simulated soil N matches measurements but with lower accuracy (R2 of 0.73 and 0.31 for calibration and validation of total N in SOM, respectively) than for soil C. Simulated soil water and temperature were compared with measurements, and the accuracy is comparable to the other commonly used models. The seasonal variation in gross primary production (GPP; R2 = 0.83), ecosystem respiration (ER; R2 = 0.89), net ecosystem exchange (NEE; R2 = 0.67), and evapotranspiration (ET; R2 = 0.71) was well captured by the model. We will further develop the model to represent forest and agricultural systems and improve it to incorporate new understanding of SOM decomposition.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Caught in headlights: Captive white-tailed deer responses to variations in vehicle lighting during imminent collision scenarios

Vehicle collisions with deer (Odocoileus spp.) cause billions of dollars in damages and injure thousands of drivers every year in the United States, and few mitigation methods have proven effective. However, recent research suggests that vehicle lighting might influence white-tailed deer (Odocoileus virginianus; hereafter, deer) responses to oncoming vehicles. Most new vehicles are manufactured with light emitting diode (LED) headlights which differ in total radiance and wavelength of light emitted compared to the previous industry standard of tungstenhalogen (halogen) headlights. Also, frontal vehicle illumination through rear-facing lighting has shown promise in enhancing deer responses to vehicles, but its effectiveness has not been tested under various headlight conditions (headlight type or intensity). As such, it remains unclear how these aspects of vehicle lighting affect deer responses to an approaching vehicle. We used 23 captive, wild-type deer to investigate how variations in vehicle lighting affect deer responses to an approaching vehicle at night, when most collisions occur. We released deer into a 95 m long, 3 m wide chute and approached them from the opposite end with an electric golf cart outfitted with two versions of stock 2017–2020 Ford Fusion headlights (LED and halogen) and a 51 cm rear-facing lightbar to test how vehicle lighting affected deer avoidance behaviors in an imminent, head-on collision scenario. Each deer received eight lighting treatments consisting of unique combinations of headlight type (LED vs. halogen), light intensity (low vs. high beam), and rear-facing lighting (lightbar off vs. on). We measured deer alert and flight behavior using infrared videography. We found that the halogen, high beam, lightbar off treatment had the greatest probability of evoking an alert response. Furthermore, when the lightbar was off, high beams appeared to increase alert probability for halogen headlights. Also, we found evidence that high beam, halogen headlights tend to increase alert probability over high beam, LED headlights, when the lighbar was off. We found no effect of our lighting treatments on deer alert distance, flight probability, or flight initiation distance. Across all behavioral responses, the random effect deer ID explained 0.86–9.19 × more variation than our lighting treatments, reflecting large differences in responses among deer. Overall, we found that vehicle lighting can impact deer behavior during an imminent, head-on collision scenario, although lighting was ineffective at increasing favorable flight behaviors. Future research should investigate how vehicle lighting treatments affect free-ranging, wild deer in a variety of real-world scenarios and at longer approach distances.

White-tailed deer (Odocoileus virginianus) Deer be↗

DOE OSTI2021

Adaptive variational quantum eigensolvers for highly excited states

Highly excited states of quantum many-body systems are central objects in the study of quantum dynamics and thermalization that challenge classical computational methods due to their volume-law entanglement content. In this work, we explore the potential of variational quantum algorithms to approximate such states. We propose an adaptive variational quantum eigensolver (VQE) for excited states (X) that self-generates a variational ansatz for arbitrary eigenstates of a many-body Hamiltonian H by attempting to minimize the energy variance with respect to H. We benchmark the method by applying it to an Ising spin chain with integrable and nonintegrable regimes, where we calculate various quantities of interest, including the total energy, magnetization density, and entanglement entropy. We also compare the performance of adaptive VQE-X to an adaptive variant of the folded-spectrum method. For both methods, we find a strong dependence of the algorithm's performance on the choice of operator pool used for the adaptive construction of the ansatz. In particular, an operator pool including long-range two-body gates accelerates the convergence of both algorithms in the nonintegrable regime. Here, we also study the scaling of the number of variational parameters with system size, finding that an exponentially large number of parameters may be necessary to approximate individual highly excited states. Nevertheless, we argue that these methods lay a foundation for the use of quantum algorithms to study finite-energy-density properties of many-body systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Effects of experimental and seasonal drying on soil microbial biomass and nutrient cycling in four lowland tropical forests

Changes in precipitation represent a major effect of climate change on tropical forests, which contain some of the earth’s largest terrestrial carbon (C) stocks. Such changes are expected to influence microbes, nutrients, and the fate of C in tropical forest soils. To explore this, we assessed soil microbial biomass, potential extracellular enzyme activities, and nutrient availability in a partial throughfall exclusion experiment in four seasonal lowland tropical humid forests in Panama with wide variation in precipitation and soil fertility. We hypothesized that throughfall exclusion would reduce microbial biomass and activity and accentuate dry season soil nutrient accumulation, with larger effects in wetter, less droughtresistant forests. We observed a baseline seasonal pattern of decreased microbial biomass and increased extractable dissolved organic C (DOC), total dissolved nitrogen (TDN), nitrate (NO 3 – ), and resinextractable phosphorus (P) in the dry season, with the strongest patterns for nitrogen (N). However, potential enzyme activities showed no consistent seasonality. In line with seasonal drying, throughfall exclusion decreased soil microbial biomass in the wet season and increased TDN and NO 3 – , especially in the dry season. In contrast to seasonal drying, throughfall exclusion decreased DOC and did not affect resinextractable P, but slightly decreased potential phosphatase activities. Potential enzyme activities varied among sites and sampling times, but did not explain much variation in microbial biomass or substrate availability. We conclude that reduced rainfall in tropical forests might accentuate some dry season patterns, like reductions in microbial biomass and accumulation of extractable nutrients. However, our data also suggest new patterns, like reduced inputs of DOC to soils with drying, which could have cascading effects on soil ecological function and C storage.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Dynamic deuterium retention properties of tungsten measured using laser-induced breakdown spectroscopy

Dynamic deuterium (D) retention properties of tungsten (W) are investigated under steady-state D plasma exposure in the PISCES-A linear plasma device. In contrast to static retention, dynamic retention is quickly released from the material at the termination of the incident plasma flux, and thus in-operando laser-induced breakdown spectroscopy (LIBS) measurements have been conducted during steady-state D plasma exposure. A procedure is, first, established to extract the dynamic retention component from the in-operando LIBS D I 656.1 nm line intensity, which can contain contributions from dynamic and static retention as well as background D/D 2 gas, excited by both steady-state and laser-induced plasmas. Using the developed procedure, the dynamic D retention in W is systematically examined while scanning the following plasma exposure parameters: incident ion energy, E i , sample temperature, T s , incident ion flux, Γ i . No clear E i dependence is seen in the range of E i ~ 45–175 eV, as expected from a small variation in the average implantation depth (~3-6 nm) of D in W. The dynamic retention is found to monotonously decrease with increasing T s from 348 to 573 K, while the total static retention is reported to peak at T s ~ 500–600 K. It is revealed that the dynamic retention linearly increases with increasing Γ i , and then saturates at Γ i ≥ 0.75 × 10 21 m –2 s –1 . Possible physical mechanisms for the observed dependence of the dynamic retention on T s and Γ i are discussed. Furthermore, sequential pure He, followed by pure D, plasma exposures show that the dynamic D retention is not strongly affected by He bubbles in the near-surface region.

super-saturated surface layer↗

DOE OSTI2023

Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions

Abstract As tropical forests cycle the most water and carbon, it is crucial to understand the short- and long-term effects of intensifying cyclones on these ecosystems. Soil nutrient status has been shown to moderate forest cyclone responses using field litterfall measurements, but litterfall is one of the multiple cyclone impact metrtics, which may or may not be correlated with one another or with site nutrients. We used remotely sensed vegetation indices to quantify immediate damage and two-year recovery for 42 cases across nine tropical forests in Hawaii, Puerto Rico, Mexico, Australia, and Taiwan affected by 12 cyclones between 2004 and 2017. We tested whether changes in leaf area index (LAI) and enhanced vegetation index (EVI) correlated with changes in litterfall observations and how changes varied with total soil phosphorus (P) concentrations across regions. We compared cyclone-induced changes and recovery of LAI and EVI to litterfall observations compiled in a pantropical meta-analysis. We found large variation in changes in LAI and EVI across forests, with the greatest reductions in LAI (−77%) and EVI (−77%) in Mexico (Jalisco) and Puerto Rico, respectively. LAI ( r = −0.52) and EVI ( r = −0.60) changes correlated with those in litterfall across cases. Post-cyclone data showed recovery of LAI by four months, EVI by two months, and litterfall by ten months. We detected larger changes in LAI and EVI in forests with higher soil P, but these relationships were not significant when accounting for cyclone and site as random effects. Principal component analyses indicated a regional clustering of cases related to their contrasting cyclone regimes, with the frequency and intensity of cyclone events negatively correlated. Overall, remote sensing observations complement but do not substitute for ground observations that reveal cyclone damage and post-cyclone recovery in tropical forests, and soil phosphorus moderates some but not all metrics of stability in response to cyclones.

Bloom, Dellena E. (ORCID:0000000205981747)↗

DOE OSTI2026

A nitrate transporter 1/peptide transporter family gene impacts nitrogen homeostasis and phenylpropanoid production in hybrid poplar

In plants, nitrogen and carbon metabolism are tightly interconnected, and nitrogen availability often negatively correlates with phenylpropanoids that are associated with xylem formation and stress responses. A nitrate transporter 1/peptide transporter (NRT1/PTR) family (NPF) gene (PtNPF6.1), which is expressed in the vasculature, was previously found to have a genetic association with the variation in syringyl lignin content in poplar trees (Populus trichocarpa). PtNPF6.1 belongs to an evolutionarily distinct NPF superfamily with limited taxonomic distribution. RNAi-mediated suppression of PtNPF6.1 led to increases in total foliar nitrogen and amino acids related to nitrogen transport and storage in source leaves. There was also a concomitant decrease in soluble phenolics, including attenuated stress-induced production of anthocyanins and condensed tannins. The proportions of syringyl and p-hydroxyphenyl units in lignin were slightly but significantly decreased in down-regulated lines grown under high nitrogen conditions, while there was an increase in the level of ester-linked p-hydroxybenzoate groups. Together, these results suggest that PtNPF6.1 is involved in maintaining internal nitrogen homeostasis in trees, indirectly impacting the production of nitrogen-free phenolics including lignin and soluble secondary metabolites.

amino acids↗

DOE OSTI2023

Understanding local plant extinctions before it is too late: bridging evolutionary genomics with global ecology

Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Here, two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land-use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability – and possibly the preventability – of the ongoing extinction of plant species.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗

DOE OSTI2023

Relating storm-snow avalanche instabilities to data collected from the Differential Emissivity Imaging Disdrometer (DEID)

Storm-snow avalanches are challenging to forecast due to complex alpine terrain and during rapidly changing weather conditions. They can result in loss of lives and significant economic impact. We describe how a new device that continuously measures with high-frequency snowflake mass, size, density, and type, the Differential Emissivity Imaging Disdrometer (DEID), and show how the DEID can be used to aid avalanche forecasting when coupled with a storm-snow stability model. DEID measurements of snow accumulation, snow water equivalent (SWE), and snow density obtained during seventeen storms taken at the mid-Collins Snow-Study Plot at Alta Ski Area in Utah's Central Wasatch mountain range during winter 2020–2021 show excellent agreement with infrequent manual measurements. Additionally, two new variables, the Shape Density Index (SDI) and Complexity, are proposed and used to classify snowflake habit and estimate storm-snow shear strength. We illustrate how these DEID-derived data can be used to identify layers of concern in the storm snow such as density inversions, in real-time without digging snow pits. Furthermore, the DEID-data are used to run four variations of the SNOw Slope Stability model (SNOSS) for the storms investigated. The results are evaluated with data collected from tilt-board tests, infrasound measurements, and visual observations of avalanches. For a total fourteen storms analyzed, the DEID-driven SNOSS-modeled minimum stability index predicts the general stability of the storm-snow as indicated by observed avalanches, both natural and of unknown cause. Finally, the results provide a promising approach for nowcasting instabilities within storm-snow layers with a single instrument.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Necromass responses to warming: A faster microbial turnover in favor of soil carbon stabilisation

Microbial byproducts and residues (hereafter ‘necromass’) potentially play the most critical role in soil organic carbon (SOC) sequestration. However, little is known about the influence of climate warming on necromass accumulation in the agroecosystem and the underlying mechanisms associated with microbial life strategies. Here, in order to address these knowledge gaps, we used amino sugars as biomarkers of microbial necromass, and investigated their variation through an 8-year trial in an agroecosystem with two warming levels (+1.6 and + 3.2 °C) compared to ambient temperature. The results showed that the lower warming level had no impact on total microbial necromass carbon. Conversely, warming the soil 3.2 °C above ambient increased total microbial necromass by 17 % and its contribution to SOC by 21.3 %, mainly by increasing fungal necromass (+19.8 %), whereas +3.2 °C warming had no impact on bacterial necromass. At the phylum level, compared with the ambient control, +3.2 °C warming induced an increase in the abundance of Proteobacteria and a decrease in both Acidobacteria and Actinobacteria, whereas in the fungal community, Ascomycota increased and Mortierellomycota decreased. This indicates that r-strategists outcompete K-strategists in warmer climates, which led to increased microbial necromass production and accumulation, as supported by the positive correlation between r-strategists and microbial necromass. Stronger microbial competition for resources also resulted in a higher biomass turnover rate, greater cell death, and greater production of microbial necromass. This was supported by the lower bacterial and fungal network complexity and trophic links under warming conditions. In addition, the necromass generated from accelerated microbial turnover further offsets warming-induced deceases in microbial biomass. Consequently, bulk SOC did not change, despite microbial necromass having a much greater response to warming than the soil C pool. Therefore, future climate warming may influence the composition and persistence of SOC during microbial degradation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Dynamics in a stellar convective layer and at its boundary: Comparison of five 3D hydrodynamics codes

Our ability to predict the structure and evolution of stars is in part limited by complex, 3D hydrodynamic processes such as convective boundary mixing. Hydrodynamic simulations help us understand the dynamics of stellar convection and convective boundaries. However, the codes used to compute such simulations are usually tested on extremely simple problems and the reliability and reproducibility of their predictions for turbulent flows is unclear. We define a test problem involving turbulent convection in a plane-parallel box, which leads to mass entrainment from, and internal-wave generation in, a stably stratified layer. We compare the outputs from the codes FLASH, MUSIC, PPMSTAR, PROMPI, and SLH, which have been widely employed to study hydrodynamic problems in stellar interiors. The convection is dominated by the largest scales that fit into the simulation box. All time-averaged profiles of velocity components, fluctuation amplitudes, and fluxes of enthalpy and kinetic energy are within ≲3σ of the mean of all simulations on a given grid (128 3 and 256 3 grid cells), where σ describes the statistical variation due to the flow’s time dependence. They also agree well with a 512 3 reference run. The 128 3 and 256 3 simulations agree within 9% and 4%, respectively, on the total mass entrained into the convective layer. The entrainment rate appears to be set by the amount of energy that can be converted to work in our setup and details of the small-scale flows in the boundary layer seem to be largely irrelevant. Our results lend credence to hydrodynamic simulations of flows in stellar interiors. We provide in electronic form all outputs of our simulations as well as all information needed to reproduce or extend our study.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Effect of grain size on damage and failure in two-phase materials: Homogenized CuPb

It is well known that spall failure strongly depends on the microstructure of a material. There have been numerous studies to study the effect of grain size on the overall spall strength and the total amount of damage in single element metals like copper. However, such systematic studies remain rare in two-phase materials and alloys. In this work, two incipient spall experiments were performed on a Cu–1%Pb alloy to understand the effect of grain size on the damage and failure in a two-phase material. Overall, these results showed that even though the spall strength did not change as a function of grain size, there were significant differences in the total amount of damage as a function of grain size. A clear increase in the total damage present in the material was seen as the grain size was increased from 32 to either 70 or 75 μm in either of the experiments. Furthermore, this difference was attributed to variations in the void growth rate as the grain size was increased.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Data for Application of Time-Domain 1H NMR for Investigating Dynamics of Vegetative Lipids in Bioenergy Crops at Different Developmental Stages

Sweet sorghum is typically cultivated for the food and fodder market. Recently, sweet sorghum varieties are being metabolically transitioned to enhance energy density by accumulating oil droplets in their vegetative tissues for bioenergy applications. Owing to the high biomass yield of sorghum, the transgenic lines can compete with oil-seed crops for biodiesel yield per unit area. In the initial phase of transgenic development, a high-throughput phenotyping method can bridge the gap between the production pipeline and analysis to improve the efficiency of the process. To meet the requirement, the present study extends the application of time-domain 1H-NMR spectroscopy for rapid quantification and characterization of the total in-situ lipids of sweet sorghum ‘ramada’ to lay the groundwork for analyzing the upcoming large quantity of transgenic samples. NMR technology has been successfully established for analyzing lipid contents of vegetative tissues of non-transgenic variety. The multiexponential analysis of spin-lattice (T1) relaxation spectra obtained from TD-NMR aided the investigation of the dynamics of the free and bound lipid fraction with plant development. The total lipid concentration of bagasse and leaves of non-transgenic sweet sorghum remained unchanged throughout the plant development. Leaves displayed a higher percentage of bound lipids as compared to bagasse. A significant variation in the lipid concentration of juice was observed at the different growth stages with a maximum lipid accumulation of 1.21 ± 0.04% w/w at the boot stage that decreased with further maturity of the plant.

Biomass Analytics↗