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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Isolation of potential plant growth-promoting bacteria from nodules of legumes grown in arid Botswana soil

As the world population increases, improvements in crop growth and yield will be needed to meet rising food demands, especially in countries that have not developed agricultural practices optimized for their own soils and crops. In many African countries, farmers improve agricultural productivity by applying synthetic fertilizers and pesticides to crops, but their continued use over the years has had serious environmental consequences including air and water pollution as well as loss of soil fertility. To reduce the overuse of synthetic amendments, we are developing inocula for crops that are based on indigenous soil microbes, especially those that enhance plant growth and improve agricultural productivity in a sustainable manner. We first isolated environmental DNA from soil samples collected from an agricultural region to study the composition of the soil microbiomes and then used Vigna unguiculata (cowpea), an important legume crop in Botswana and other legumes as “trap” plants using the collected soil to induce nitrogen-fixing nodule formation. We have identified drought-tolerant bacteria from Botswana soils that stimulate plant growth; many are species of Bacillus and Paenibacillus . In contrast, the cowpea nodule microbiomes from plants grown in these soils house mainly rhizobia particularly Bradyrhizobium , but also Methylobacterium spp. Hence, the nodule microbiome is much more limited in non-rhizobial diversity compared to the soil microbiome, but also contains a number of potential pathogenic bacteria.

Kosty, Melissa↗
DOE OSTI2022

ADAPTIVE GROUP TESTING WITH MISMATCHED MODELS

Accurate detection of infected individuals is one of the critical steps in stopping any pandemic. When the underlying infection rate of the disease is low, testing people in groups, instead of testing each individual in the population, can be more efficient. In this work, we consider noisy adaptive group testing design with specific test sensitivity and specificity that select the optimal group given previous test results based on pre-selected utility function. As in prior studies on group testing, we model this problem as a sequential Bayesian Optimal Experimental Design (BOED) to adaptively design the groups for each test. We analyze the required number of group tests when using the updated posterior on the infection status and the corresponding Mutual Information (MI) as our utility function for selecting new groups. More importantly, we study how the potential bias on the ground-truth noise of group tests may affect the group testing sample complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I–VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers’ views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Divide and conquer: using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. Sometimes, the amount of roots in a sample is too much to fit into a single scanned image, so the sample is divided among several scans, and there is no standard method to aggregate the data. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image. These concatenated images and the original images were processed with RhizoVision Explorer, a free and open-source software. An R script was developed, which identifies rows of data belonging to the same sample and applies correct statistical methods to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Most root measurements were nearly identical between the two methods except median diameter, which cannot be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Parallel Computing Infrastructure for Building Energy Simulation

In order to study grid-interactive efficient buildings, Pacific Northwest National Laboratories (PNNL) needs an infrastructure for urban-scale building energy modeling. Such an infrastructure should be fast, scalable, and easy-to-use. Given a set of data from the Energy Information Administration’s Commercial Building Energy Consumption Survey (CBECS) and tool to translate survey data into simulation inputs, this project aimed to conduct the simulation of the entire dataset in parallel. Before running the simulations, the necessary software was bundled into a container for use on the PNNL supercomputing network. Then, the parallel simulation workflow was designed using GNU Make, a file creation software, and submitted to a supercomputing partition which could run hundreds of simulations simultaneously. The EnergyPlus simulations output hourly electric meter data for each CBECS sample, which represents the electricity consumption of similar commercial buildings across the United States. Analyzing and visualizing the meter data is important to the future of the work, and this project wrote code to make common analysis methods simple, fast, and accessible. Moving forwards, the model will need to be expanded to include data from other sources and its accuracy will need to be improved and eventually validated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Quantifying Subsurface Biogeochemical Variability in a High Altitude Watershed During Winter Isolation

Shallow subsurface microbial and geochemical processes in watersheds are dynamic and responsive to seasonal and long-term environmental change. At high elevation or latitude, such changes may occur during winter months when normal sampling is impossible, impractical, unsafe, or may actually alter the processes being studied. Yet accurate modeling of biogeochemical parameters in these environments requires sampling that can capture events and persistent cold climate trends. Gaps in current models exist where data have not been collected during extended snow- or ice-covered periods. The goals of our exploratory study were to examine the biogeochemical processes occurring in a well-studied high altitude watershed during winter when the system is largely inaccessible. We tested the hypothesis that during snow cover in the East River (ER) watershed, episodic excursions of microbial community structure and biogeochemical processes and concentrations fluctuated from values extrapolated from pre- and post-snow time periods. Through our research we identified previously unresolved subsurface-surface transport phenomena and a heretofore under-appreciated methane cycle occurring during wintertime months, thus providing valuable insight into watershed processes. Our research showed that autonomous sampling techniques, first used in marine systems, is extremely versatile and can be adapted for use in harsh continental settings to examine temporal changes in freshwater chemistry and microbial community assemblage. Further, we found that by sampling during periods when systems are hard to access, will lend insight and better accountability for global budgets for methane, an important greenhouse gas. By strengthening our knowledge of wintertime biogeochemical relationships in high altitude watersheds our research leads to more complete descriptions of cryptic processes and ultimately will inform and improve the reactive transport models that simulate processes in these systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Moisture Sorption and Swelling of Sylgard-184

The report summarizes the quantitative assessment of moisture sorption by Sylgard-184. It is an important ingredient in many of our materials. Moisture sorption for this material has been extensively studied with data from 9 different samples available for analysis. These samples varied in size and geometry. Seven of the 9 samples were thin slabs. The remaining 2 were cylinders, one of which had comparable height and diameter and is therefore considered a 3-D sample. All the samples, except 2 (1D_slab4.06mm and 1D_Sylgard_2016_Sharma) belonged to lot number A1606324. They were all prepared by Tony Rodrigues in the plastics shop in the Summer of 2016 and tested by Hom Sharma between October 2016 and June 2017. 1D_slab4.06mm was also prepared by Tony Rodrigues in the plastics shop in Summer of 2016, however, the sample did not have a lot number. 1D_Sylgard_2016_Sharma was prepared by Hom Sharma in February 2016 and tested potentially around May - June 2016.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Double-differential Measurements of Mesonless Charged-current Muon Neutrino Interactions on Argon with Final-State Protons using the MicroBooNE Detector

This note reports the first double-differential measurements of charged-current $ν_µ$ scattering on argon leading to final states containing zero mesons and one or more protons. This event topology (hereafter abbreviated as CC0$πNp$) is the most common at the neutrino energies typically produced by the Fermilab Booster Neutrino Beam. A detailed understanding of neutrino-argon scattering in the CC0$πNp$ channel is therefore crucial for the success of the precision neutrino oscillation analyses planned for the Short-Baseline Neutrino (SBN) program. This remains true for the upcoming Deep Underground Neutrino Experiment (DUNE), but the higher mean neutrino energy used there will ensure that more inelastic reaction modes, such as single pion production, will also play a major role. The analysis described in this note builds on a previous MicroBooNE study of the CC0$πNp$ channel which obtained the first single-differential cross-section measurements on an argon target. Since that foundational work, significant improvements have been made to MicroBooNE’s simulation software, event reconstruction algorithms, and procedure for calculating systematic uncertainties. When combined with a larger dataset (corresponding to a beam exposure of 6.79 × 10 20 protons-on-target versus 1.60 × 10 20 in Ref. [3]), these enhancements allow the important CC0$πNp$ channel to be studied in more detail. This note begins with a description of the data and simulation samples used as input to the analysis. Section 3 then defines the CC0$πNp$ signal event topology, and Section 4 describes a set of selection criteria designed to identify these events in MicroBooNE data. Binning schemes are then defined in Section 5 for two double-differential measurements of event rates. The first of these considers the momentum and scattering cosine of the outgoing muon, while the second reports the same observables for the leading proton, i.e., the final-state proton with the largest momentum. After a discussion of systematic uncertainties in Section 6, the note concludes by comparing the predictions of MicroBooNE Monte Carlo (MC) simulations to the measured double-differential distributions. These results will form the basis for a future extraction of flux-averaged double-differential CC0$πNp$ cross sections that will be immediately comparable to the theoretical predictions of multiple neutrino event generators. The selection described herein may also be used to study various other observables in CC0$πNp$ events, including those which are sensitive to correlations between leptonic and hadronic kinematics in the final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Bldg. 7930 Cell G Neutron Detector New Electronics Testing

The Cell G neutron assay system within 7930 provides an important function in the production of Californium-252 in the quantitative determination of the amount of Cf-252 present in a sample. The assay system consists of a Uranium-238 fission chamber coupled to the necessary counting electronics including preamplifier, amplifier, discriminator and counter/timer. The original electronics date back to the 1970s but were replaced back in 2011 with little documentation detailing the testing and replacement efforts. This work focused on procuring a new spare set of electronics, their subsequent testing as a backup in case any of the currently in use electronics were to fail and documentation of the existing and new setups.

Taylor, Neil [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2022

MINERvA results and prospects

MINERvA is a dedicated neutrino cross section experiment that ran in the NuMI beamline at Fermilab from 2009 through 2019. MINERvA has made a broad suite of measurements that are informing the neutrino interaction models in use by not only today's oscillation experiments but also by future generations of oscillation experiments. Of particular interest are MINERvA's measurements of the quasielastic-like and pion production processes, since those channels dominate the oscillation landscape. MINERvA has also ushered in the era of using neutrino electron scattering to make precise flux predictions, another important input for oscillation experiments. This paper briefly describes a few recently published results from MINERvA's neutrino and antineutrino scattering sample on the hydrocarbon target including its new flux constraints, and points to some upcoming quasielastic and pion production results that will showcase simultaneous measurements of exclusive final states across different nuclei, ranging from carbon and water to iron and lead.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Riverine organic matter functional diversity increases with catchment size

A large amount of dissolved organic matter (DOM) is transported to the ocean from terrestrial inputs each year (~0.95 Pg C per year) and undergoes a series of abiotic and biotic reactions, causing a significant release of CO 2 . Combined, these reactions result in variable DOM characteristics (e.g., nominal oxidation state of carbon, double-bond equivalents, chemodiversity) which have demonstrated impacts on biogeochemistry and ecosystem function. Despite this importance, however, comparatively few studies focus on the drivers for DOM chemodiversity along a riverine continuum. Here, we characterized DOM within samples collected from a stream network in the Yakima River Basin using ultrahigh-resolution mass spectrometry (i.e., FTICR-MS). To link DOM chemistry to potential function, we identified putative biochemical transformations within each sample. We also used various molecular characteristics (e.g., thermodynamic favorability, degradability) to calculate a series of functional diversity metrics. We observed that the diversity of biochemical transformations increased with increasing upstream catchment area and landcover. This increase was also connected to expanding functional diversity of the molecular formula. This pattern suggests that as molecular formulas become more diverse in thermodynamics or degradability, there is increased opportunity for biochemical transformations, potentially creating a self-reinforcing cycle where transformations in turn increase diversity and diversity increase transformations. We also observed that these patterns are, in part, connected to landcover whereby the occurrence of many landcover types (e.g., agriculture, urban, forest, shrub) could expand DOM functional diversity. For example, we observed that a novel functional diversity metric measuring similarity to common freshwater molecular formulas (i.e., carboxyl-rich alicyclic molecules) was significantly related to urban coverage. These results show that DOM diversity does not decrease along stream networks, as predicted by a common conceptual model known as the River Continuum Concept, but rather are influenced by the thermodynamic and degradation potential of molecular formula within the DOM, as well as landcover patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Distant Relatives: The Chemical Homogeneity of Comoving Pairs Identified in Gaia

Comoving pairs, even at the separations of $\mathcal{O}$(10 6 ) are a predicted reservoir of conatal stars. Here we present detailed chemical abundances of 62 stars in 31 comoving pairs with separations of 10 2 –10 7 au and 3D velocity differences <2 km s -1 . This sample includes both bound comoving pairs/wide binaries and unbound comoving pairs. Observations were taken using the Magellan Inamori Kyocera Echelle (MIKE) spectrograph on board the Magellan/Clay Telescope at high resolution (R~ 45,000) with a typical signal-to-noise ratio of 150 pixel -1 . With these spectra, we measure surface abundances for 24 elements, including Li, C, Na, Mg, Al, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Sr, Y, Zr, Ba, La, Nd, and Eu. Taking iron as the representative element, our sample of wide binaries is chemically homogeneous at the level of 0.05 dex, which agrees with prior studies on wide binaries. Importantly, even systems at separations 2 × 10 5 –10 7 au are homogeneous to 0.09 dex, as opposed to the random pairs, which have a dispersion of 0.23 dex. Assuming a mixture model of the wide binaries and random pairs, we find that 73 ± 22% of the comoving pairs at separations 2 × 10 5 –10 7 au are conatal. Our results imply that a much larger parameter space of phase space may be used to find conatal stars, to study M-dwarfs, star cluster evolution, exoplanets, chemical tagging, and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Evidence for Black Holes in Green Peas from WISE Colors and Variability

We explore the presence of active galactic nuclei (AGNs)/black holes in Green Pea galaxies (GPs), motivated by the presence of high-ionization emission lines such as He ii and [Ne iii] in their optical spectra. In order to identify AGN candidates, we used mid-infrared (MIR) photometric observations from the all-sky Wide-field Infrared Survey Explorer (WISE) mission for a sample of 1004 GPs. Considering only >5σ detections with no contamination from neighboring sources in AllWISE, we select 31 GPs out of 134 as candidate AGNs based on a stringent three-band WISE color diagnostic. Using multi-epoch photometry in W1 and W2 bands based on time-resolved unWISE coadd images, we find two sources exhibiting variability in both the WISE bands among 112 GPs with W1 ≤16 mag and no contamination from neighboring sources in unWISE. These two variable sources were selected as AGNs by the WISE three-band color diagnostic as well. Compared to variable AGN fractions observed among low-mass galaxy samples in previous studies, we find a higher fraction (~1.8%) of MIR variable sources among GPs, which demonstrates the uniqueness and importance of studying these extreme objects. Through this work, we demonstrate that MIR diagnostics are promising tools to select AGNs that may be missed by other selection techniques (including optical emission-line ratios and X-ray emission) in star formation-dominated, low-mass, low-metallicity galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Huge ensembles – Part 1: Design of ensemble weather forecasts using spherical Fourier neural operators

Abstract. Simulating low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems presently use up to 100 members, larger ensembles could enrich the sampling of internal variability. They may capture the long tails associated with climate hazards better than traditional ensemble sizes. Due to computational constraints, it is infeasible to generate huge ensembles (comprised of 1000–10 000 members) with traditional, physics-based numerical models. In this two-part paper, we replace traditional numerical simulations with machine learning (ML) to generate hindcasts of huge ensembles. In Part 1, we construct an ensemble weather forecasting system based on spherical Fourier neural operators (SFNOs), and we discuss important design decisions for constructing such an ensemble. The ensemble represents model uncertainty through perturbed-parameter techniques, and it represents initial condition uncertainty through bred vectors, which sample the fastest-growing modes of the forecast. Using the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) as a baseline, we develop an evaluation pipeline composed of mean, spectral, and extreme diagnostics. With large-scale, distributed SFNOs with 1.1 billion learned parameters, we achieve calibrated probabilistic forecasts. As the trajectories of the individual members diverge, the ML ensemble mean spectra degrade with lead time, consistent with physical expectations. However, the individual ensemble members' spectra stay constant with lead time. Therefore, these members simulate realistic weather states during the rollout, and the ML ensemble passes a crucial spectral test in the literature. The IFS and ML ensembles have similar extreme forecast indices, and we show that the ML extreme weather forecasts are reliable and discriminating. These diagnostics ensure that the ensemble can reliably simulate the time evolution of the atmosphere, including low-likelihood high-impact extremes. In Part 2, we generate a huge ensemble initialized each day in summer 2023, and we characterize the simulations of extremes.

Mahesh, Ankur↗
NASA NTRS1972

Site preferences of Ni/2+/ and Co/2+/ in clinopyroxene and olivine - Limitations of the statistical approach.

Criticism of a statistical approach used by Dasgupta (1972) in analyzing Snyder's (1959) chemical data for minerals from the Duluth Complex in Minnesota. Apart from obvious mathematical objections to citing correlation coefficients to four significant figures from Snyder's relatively inaccurate analytical data, several more fundamental criticisms are leveled at the statistical approach of Dasgupta. These relate to compositional zoning and disequilibrium in the minerals, inhomogeneities of the samples caused by inclusions and exsolved phases, measured site population data for the major cations in olivines and pyroxenes, and the importance of coupled substitutions in the crystal structures. It is concluded that the crystal field predictions of relative enrichments of Ni(2+) and Co(2+) ions in olivine and pyroxene structures have not been disproved by Dasgupta's statistical approach.

Burns, R. G.↗
NASA NTRS1983

Lunar sample analysis

The evolution of the lunar regolith under solar wind and micrometeorite bombardment is discussed as well as the size distribution of ultrafine iron in lunar soil. The most important characteristics of complex graphite, sulfide, arsenide, palladium, and platinum mineralization in a pegmatoid pyroxenite of the Stillwater Complex in Montana are examined. Oblique reflected light micrographs and backscattered electron SEM images of the graphite associations are included.

Housley, R. M.↗
NASA NTRS1989

Cordierite-spinel troctolite, a new magnesium-rich lithology from the lunar highlands

A clast of spineltroctolite containing 8 percent cordierite (Mg2,Al4Si5O18) has been identified among the constituents of Apollo 15 regolith breccia 15295. The cordierite and associated anorthite, forsteritic olivine, and pleonaste spinel represent a new, Mg-rich lunar highlands lithology that formed by metamorphism of an igneous spinel cumulate. The cordierite-forsterite pair in the assemblage is stable at a maximum pressure of 2.5 kilobars, equivalent to a depth of 50 kilometers, or 10 kilometers above the lunar crust-mantle boundary. The occurrence of the clast indicates that spinel cumulates are a more important constituent of the lower lunar crust than has been recognized. The rarity of cordierite-spinel troctolite among lunar rock samples suggests that it is excavated only by large impact events, such as the one that formed the adjacent Imbrium Basin.

Marvin, Ursula B.↗
NASA NTRS1989

Physical processing of cometary nuclei

Cometary nuclei were formed far from the Sun in the colder regions of the solar nebula, and have been stored in distant orbits in the Oort cloud over most of the history of the solar system. It had been thought that this benign environment would preserve comets in close to their original pristine state. However, recent studies have identified a number of physical processes that have likely acted to modify cometary nuclei in a variety of significant ways. It is important to consider all of these possible processes, both in deciding on a site on the nucleus for collection of cometary samples, and in interpreting the results of analyses of returned cometary samples. Although it can no longer be said that comets are pristine samples of original solar nebula material, they are still the best obtainable samples of that unique period in the formation of the planetary system.

Weissman, Paul R.↗