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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1994

The search for brown dwarfs with infrared surveys

Infrared Astronomy Satellite (IRAS), ISO, Space Infrared Telescope Facility (SIRTF), WIRE, Deep Near-Infrared Survey (DENIS), and Two Micron All-Sky Survey (2MASS) observations were used to compute the maximum number of observable brown dwarfs for various infrared surveys by combining the maximum possible Oort limit (0.1 'missing' solar mass p/cu c) with all possible brown dwarf mass and age distributions. This approach shows what limits will be placed on the contribution of brown dwarfs to any possible 'missing mass' if no brown dwarfs are observed. I consider brown dwarfs with masses of 0.01-0.08 solar mass and ages of 10(exp 9)-10(exp 10) years. The full range of predicted numbers of brown dwarfs above approx. 6 times the noise of each of the below surveys is: IRAS Point Source Catalog, 0.02-6; IRAS Faint Source Catalog absolute value of b greater than 10 deg, 0.05-16; ISO (2 week 12 micrometer survey), 0.15-80; SIRTF (2 week 12 micrometer survey), 2.50-1600; WIRE (4 month 12 micrometer survey), 21.80-6000; DENIS(half sky) absolute value of b greater than 10 deg, 0.00-2000; and 2MASS(full sky) absolute value of b greater than 10 deg, 0.00-8800. A failure to find brown dwarfs in the IRAS FSC would just barely rule out about half of the mass-age range for Oort limit total masses. A failure to find brown dwarfs in 2MASS/DENIS would rule out roughly the same mass-age range, but would set a limit of 0.1-0.01 times the Oort mass in that mass-age region. No limits would be set for the other half of the mass-age range since both IRAS and 2MASS/DENIS have insufficient sensitivity for brown dwarfs with T less than 750 K. A failure to find brown dwarfs with ISO would rule out almost all of the mass-age range for Oort limit total masses, but would not set a significantly lower limit to the brown dwarf mass limit. A failure to find brown dwarfs with SIRTF or WIRE would rule out the entire mass-age range for Oort limit total masses and set an upper limit of 0.1-0.001 times the Oort mass. To date, about 18% of the IRAS FSC has been searched down to 6 sigma, and no brown dwarfs have been found. This sets a 95% upper limit of 3 in 18% of the sky, or 13 in the entire FSC for absolute value b greater than 10 deg. To begin to set useful limits from 2MASS or DENIS, approximately 400 square degrees needs to be analyzed. To date, only a few square degrees of results from the 2MASS prototype camera have been examined, with no brown dwarfs found so far.

Chester, T. J.↗
DOE OSTI2021

Deep Learning Experiments for Tropical Cyclone Intensity Forecasts

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

58 GEOSCIENCES↗
DOE OSTI2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗
NASA NTRS2016

Electron Flux Models for Different Energies at Geostationary Orbit

Forecast models were derived for energetic electrons at all energy ranges sampled by the third-generation Geostationary Operational Environmental Satellites (GOES). These models were based on Multi-Input Single-Output Nonlinear Autoregressive Moving Average with Exogenous inputs methodologies. The model inputs include the solar wind velocity, density and pressure, the fraction of time that the interplanetary magnetic field (IMF) was southward, the IMF contribution of a solar wind-magnetosphere coupling function proposed by Boynton et al. (2011b), and the Dst index. As such, this study has deduced five new 1 h resolution models for the low-energy electrons measured by GOES (30-50 keV, 50-100 keV, 100-200 keV, 200-350 keV, and 350-600 keV) and extended the existing >800 keV and >2 MeV Geostationary Earth Orbit electron fluxes models to forecast at a 1 h resolution. All of these models were shown to provide accurate forecasts, with prediction efficiencies ranging between 66.9% and 82.3%.

Boynton, R. J.↗
NASA NTRS2023

On the Origin of Fluorine-Poor Apatite in Chondrite Parent Bodies

We conducted a petrologic study of apatite within one LL chondrite, six R chondrites, and six CK chondrites. These data were combined with previously published apatite data from a broader range of chondrite meteorites to determine that chondrites host either chlorapatite or hydroxylapatite with ≤33 mol% F in the apatite X-site (unless affected by partial melting by impacts, which can cause F-enrichment of residual apatite). These data indicate that either fluorapatite was not a primary condensate from the solar nebula or that it did not survive lower temperature nebular processes and/or parent body processes. Bulk-rock Cl and F data from chondrites were used to determine that the solar system has a Cl/F ratio of 10.5 ± 1.0 (3σ). The Cl/F ratios of apatite from chondrites are broadly reflective of the solar system Cl/F value, indicating that apatite in chondrites is fluorine poor because the solar system has about an order of magnitude more Cl than F. The Cl/F ratio of the solar system was combined with known apatite-melt partitioning relationships for F and Cl to predict the range of apatite compositions that would form from a melt with a chondritic Cl/F ratio. This range of apatite compositions allowed for the development of a crude model to use apatite X-site compositions from achondrites (and chondrite melt rocks) to determine whether they derive from a volatile-depleted and/or differentiated source, albeit with important caveats that are detailed in the manuscript. This study further highlights the utility of apatite as a mineralogical tool to understand the origin of volatiles (including H 2 O) and the diversity of their associated geological processes throughout the history of our solar system, including at its nascent stage.

Francis M. McCubbin↗
DOE OSTI2025

Thermal and photoinduced chemistry of the aromatic Criegee intermediate, benzaldehyde oxide: Implications for indoor air quality

Essential oils contain a complex mixture of volatile organic compounds, ranging from terpenes to aromatics. When released into the indoor air environment or into the atmosphere, they may undergo oxidation to generate complex reactive intermediates that affect indoor air quality. Cinnamaldehyde is one such aromatic molecule that is abundant in essential oils. When released into the indoor air environment, it may undergo oxidation to form a carbonyl oxide (Criegee intermediate) with an aromatic substituent: benzaldehyde oxide. In this manuscript, we present a high-level quantum chemical study that shows that, unlike smaller atmospherically relevant Criegee intermediates, benzaldehyde oxide is expected to undergo solar photolysis on timescales that are competitive with its ground state unimolecular and bimolecular chemistry. We show that aromatic substitution leads to a drastic bathochromic shift in the spectroscopically relevant excited states, revealing that photolysis in the indoor or outdoor environment should not be neglected when modeling the climate and air quality implications of Criegee intermediates with extended conjugation. Here, we predict a range of products that may be important for forming lower volatility compounds via tropospherically relevant photochemistry. To motivate future experimental validation of our results, we propose a viable synthetic procedure of the relevant precursor for generating and stabilizing benzaldehyde oxide.

atmospheric photochemistry↗
NASA NTRS1985

Numerical weather prediction in low latitudes

Based on the results of a number of numerical prediction experiments, the differential heating between land and ocean is an important and critical factor for investigation of phenomenon such as the onset of monsoons over the Indian subcontinent. The pre-onset period during the month of May shows a rather persistent flow field in the monsoon region. At low levels the circulation exhibits anticyclonic excursions over the Arabian Sea, flowing essentially parallel to the west coast of India from the north. Over the Indian subcontinent the major feature is a shallow heat low over northern India. As the heat sources commence a rapid northwestward movement toward the southern edge of the Tibetan Plateau, an interesting configuration of the large-scale divergent circulation occurs. A favorable configuration for a rapid exchange of energy from the divergent to the rotational kinetic energy develops. Strong low level monsoonal circulations evolve, attendant with that the onset of monsoon rains occurs. In order to test this observational sequence, a series of short-range numerical prediction experiments were initiated to define the initial heat sources.

Krishnamurti, T. N.↗
DOE OSTI2025

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗
NASA NTRS1977

Atmospheric model development in support of SEASAT. Volume 4: Forecast model sensitivity study

Atmospheric analysis and prediction models of varying (grid) resolution were developed. The models were tested using real observational data for the purpose of assessing the impact of grid resolution on short range numerical weather prediction. The work statement was amended to include the performance of sensitivity tests using a coarse mesh (63 x 63 x 5 level) prediction model in order to identify and order factors which might mask or impair the utility of SEASAT data on short range weather prediction. Such factors included: initial conditions; topography; surface friction; latent heating; diffusion of momentum and temperature; and computational devices such as tendency truncators, pressure smoothers, and temporal filters.

Lewit, H. L.↗
NASA NTRS2008

A Probabilistic Wake Vortex Lateral Transport Model Using Data from SFO and DEN

In a previous report, we considered the behavior of the lateral position of vortices as a function of time after vortex formation for Out of Ground Effects (OGE) data for aircraft landing at San Francisco International Airport (SFO). We quantified the spread in lateral position as a function of time and examined how predictable lateral position is under a variety of assumptions. The combination of spread and predictability allowed us to derive probability distribution functions (PDFs) for lateral position given observed crosswind (CW) velocities. In this study, we examine the portability of these PDFs with respect to other landing sites. To this end, we consider OGE data obtained by the Federal Aviation Administration for landings at Denver International Airport (DEN) between 04/05/2006 and 06/03/2006. We consider vortices from both B733 (Boeing 737 models 200-500) and B757 (Boeing 757) aircraft. The data set contains 635 B733 landings and 506 B757 landings. The glide slope altitude for these measurements was 280 m, determined by the average initial vortex observation adjusted for a 3-second delay in the initial observation. The comparable SFO altitude was 158 m. We note that the principal mechanism for lateral transport in the OGE regime is advection by the ambient wind. This implies that a simple crosswind correction may be effective in explaining much of the variation in the lateral transport data. In this study, we again consider the use of ASOS data and average Lidar crosswind data over the vortex altitude range to predict vortex location as a function of time.

Mellman, George R.↗
NASA NTRS2001

NASA/University JOint VEnture (JOVE) Program: Transverse Shear Moduli Using the Torsional Responses of Rectangular Laminates

The first year included a study of the non-visible damage of composite overwrapped pressure vessels with B. Poe of the Materials Branch of Nasa-Langley. Early determinations showed a clear reduction in non-visible damage for thin COPVs when partially pressurized rather than unpressurized. Literature searches on Thicker-wall COPVs revealed surface damage but clearly visible. Analysis of current Analytic modeling indicated that that current COPV models lacked sufficient thickness corrections to predict impact damage. After a comprehensive study of available published data and numerous numerical studies based on observed data from Langley, the analytic framework for modeling the behavior was determined lacking and both Poe and Bogan suggested any short term (3yr) result for Jove would be overly ambitious and emphasis should be placed on transverse shear moduli studies. Transverse shear moduli determination is relevant to the study of fatigue, fracture and aging effects in composite structures. Based on the techniques developed by Daniel & Tsai, Bogan and Gates determined to verify the results for K3B and 8320. A detailed analytic and experimental plan was established and carried out that included variations in layup, width, thickness, and length. As well as loading rate variations to determine effects and relaxation moduli. The additional axial loads during the torsion testing were studied as was the placement of gages along the composite specimen. Of the proposed tasks, all of tasks I and 2 were completed with presentations given at Langley, SEM conferences and ASME/AIAA conferences. Sensitivity issues with the technique associated with the use of servohydraulic test systems for applying the torsional load to the composite specimen limited the torsion range for predictable and repeatable transverse shear properties. Bogan and Gates determined to diverge on research efforts with Gates continuing the experimental testing at Langley and Bogan modeling the apparent non-linear behavior at low torque & angles apparent from the tests.

Bogan, Sam↗
NASA NTRS2019

Constraining the Earth System with EOS-Aura Observations

NASA's Goddard Earth Observing System (GEOS) model and data assimilation system is a flexible, modular global system that is used for applications that range from weather prediction to climate analysis. Resolving scales ranging from a few kilometers to several tens of kilometers, with scale-aware parametrization settings, the GEOS system offers NASA scientists and their partners a flexible system that is attuned to bringing in observations from all components of the Earth System. The GEOS system thus serves as a tool that enhances the value to NASA of observations from individual instruments, by bringing them into context with the full suite of "operational" observations and other research datasets. This presentation will emphasize how the GEOS system has been used to extend the value of observations from EOS-Aura, in conjunction with other NASA and non-NASA observations. One example is atmospheric ozone from the OMI and MLS instruments, that has been used extensively in GEOS systems for both weather (GEOS-FP) and the MERRA-2 reanalysis. The presentation will emphasize the value of these ozone datasets for studying long-term changes of ozone since 2004 and will discuss prospects of continuing such analyses in the post-Aura era. A new configuration of GEOS, the Composition Forecasting (CF) system has recently gone in to production: this uses a full troposphere-stratosphere chemistry mechanism (GEOS-Chem) to analyze and predict global constituent distributions, including surface air quality. While constituent observations are not yet assimilated into GEOS-CF, EOS-Aura data are used substantially to evaluate the system and plans are in place to introduce assimilation at a later stage. Examples from GEOS-CF will be shown to illustrate the value of EOS-Aura observations. Discussions will focus on the likely value of long-term analyses of EOS-Aura observations in context of understanding potential impacts on the health of humans and the biosphere, including the importance of sustaining long-term, global observing systems such as that pioneered by EOS-Aura.

Pawson, Steven↗
DOE OSTI2026

Implementing the finite-volume three-pion scattering formalism across all non-maximal isospins

We present a numerical exploration of the relativistic-field-theory (RFT) formalism for three pions with all possible values of non-maximal isospin, I πππ = 2, 1 and 0. Using the generic-isospin extension of the RFT formalism [1] and applying our open-source Python library to implement the framework, we predict a range of three-pion energies for illustrative values of the two-to-two scattering amplitudes for various finite-volume irreps also with non-zero total momentum P in the finite-volume frame. The results restrict attention to the case of a vanishing intrinsic three-body interaction so that the spectra can be understood as a baseline. In future lattice QCD calculations, deviations from these values will be translated into evidence for intrinsic three-body effects in the various scattering channels.

hadronic spectroscopy↗
DOE OSTI2023

Mechanisms of dissolution from gibbsite step edges elucidated by ab initio molecular dynamics with enhanced sampling

Surface reactions underpin our collective understanding of mineral dissolution. This impacts a range of predictive geochemical models (for weathering, the fate and transport of metals) as well as industrial utilization of minerals. Yet atomistic details are rarely known due to the complex mineral/fluid interfacial environment. There is significant need to understand the mechanistic details of dissolution reactions and how they depend on surface morphology and solution conditions. This work utilizes surface pit models in conjunction with changes to solution composition that mimic pH to explore surface detachment of aluminate from gibbsite, which is a primary source of Al in soils and within the industrial processing of aluminum. Ab initio molecular dynamics simulations with enhanced sampling has been used to explore the detailed process of the detachment, the results of which indicate two potential pathways that are differentiated based upon the extent of water hydration. Here, the heights of the energy barriers depend upon the local morphology which influence the number of bridges (quasi-)simultaneously broken (1 or 2) or the Al-O coordination of the neighboring aluminum atoms (5 or 6) at the armchair edge. pH effects are significant, with a nearly 50% reduction in barrier height under alkaline conditions that are relevant to geothermal fluids and Al extraction from minerals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

The present study reports chemometric modeling of power conversion efficiency (PCE) of dye sensitized solar cells (DSSCs) using the biggest available data set till date which comprises around 1200 dyes covering 7 chemical classes. To extract the best structural features required for higher PCE, we have developed multiple partial least squares (PLS) quantitative structure-property relationship (QSPR) models for the Triphenylamine, Phenothiazine, Indoline, Porphyrin, Coumarin, Carbazole and Diphenylamine chemical classes using descriptors derived from the best subset selection method followed by selection of best five models in each dataset based on the Mean Absolute Error (MAE) values. The models were validated both internally and externally followed by the consensus predictions employing “Intelligent Consensus Predictor” tool to examine whether the quality of predictions can be improved with the “intelligent” selection of multiple PLS models. The quality of predictions for the respective external sets showed that the consensus models (CM) are better than the individual models (IM) in most of the cases. From the insights of the developed models, we concluded that attributes like a packed structure toward higher conductivity of electrons, auxiliary donor fragment of aromatic tertiary amines, number of thiophenes inducing the bathochromic shift and augmenting the absorption, presence of additional electron donors, enhancement of electron-donating abilities, number of non-aromatic conjugated C(sp 2 ) which helps as conjugation extension units to broaden the absorption and highly conjugated $π$-systems exert positive contributions to the PCE. On the contrary, features negatively contributing to PCE are the followings: fragments which lower the tendency of localized $π–π*$ transition, fragments related to larger volume and surface area of dyes along with hydrophobicity resulting in poor adhesion, fragment RC = N causing dye hydrolysis, steric hindrance for π electronic mobility, fragments enhancing polarity, etc. Finally, the identified features from the best QSPR model of the coumarin dataset was employed in designing of ten more efficient coumarin dyes (predicted %PCE ranging from 8.93 to 10.62) than the existing ones.

14 SOLAR ENERGY↗
DOE OSTI2023

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13 C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Ion Size Effects on the Thermodynamic, Kinetic, and Mechanical Properties during Ion Exchange in Solid-State Electrolytes

Ion exchange offers a pathway to impose residual compressive stresses to mitigate the electro-chemo-mechanical cracking of solid-state electrolytes such as lithium lanthanum zirconium oxide. This study uses a coupled multiscale framework (integrating density functional theory (DFT), molecular dynamics (MD), and continuum modeling) to examine how exchange ion size influences stress, diffusion, fracture toughness, and electronic properties. Larger isovalent ions (Na + , Ag + , K + ) were exchanged with Li + , with DFT confirming their preference for octahedral 96h sites and a linear relationship between ion size and chemical free expansion coefficient. MD simulations reveal stress and concentration effects on exchange ion diffusivity at elevated temperatures, with Na + and Ag + maintaining favorable mobility while K + showing concentration-dependent clustering. Continuum modeling predicts the range of fracture strength improvements and the required ion exchange concentration profile. It was shown that a 5% surface exchange concentration can induce ∼0.6 GPa of surface compressive stress using Na + and ∼1.0 GPa of surface compressive stress using Ag + . On the other hand, larger ion exchange species may penalize Li + diffusivity by increasing the activation volume and activation energy. Interestingly, Na + has a negligible penalty on Li-ion diffusivity. The room temperature Li + ion diffusivity is reduced by ∼40% with Ag + ion exchange. Electronic band structure analysis shows no size-dependent change in the bandgap, though Ag + introduces localized defect states near the valence band maximum. This study highlights ion size as a key factor in optimizing LLZO properties, offering a framework to improve the solid-state battery performance.

Jagad, Harsh D. [Brown Univ., Providence, RI (Unit↗
DOE OSTI2021

Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities

Abstract Viruses are abundant yet understudied members of soil environments that influence terrestrial biogeochemical cycles. Here, we characterized the dsDNA viral diversity in biochar-amended agricultural soils at the preplanting and harvesting stages of a tomato growing season via paired total metagenomes and viral size fraction metagenomes (viromes). Size fractionation prior to DNA extraction reduced sources of nonviral DNA in viromes, enabling the recovery of a vaster richness of viral populations (vOTUs), greater viral taxonomic diversity, broader range of predicted hosts, and better access to the rare virosphere, relative to total metagenomes, which tended to recover only the most persistent and abundant vOTUs. Of 2961 detected vOTUs, 2684 were recovered exclusively from viromes, while only three were recovered from total metagenomes alone. Both viral and microbial communities differed significantly over time, suggesting a coupled response to rhizosphere recruitment processes and/or nitrogen amendments. Viral communities alone were also structured along an 18 m spatial gradient. Overall, our results highlight the utility of soil viromics and reveal similarities between viral and microbial community dynamics throughout the tomato growing season yet suggest a partial decoupling of the processes driving their spatial distributions, potentially due to differences in dispersal, decay rates, and/or sensitivities to soil heterogeneity.

59 BASIC BIOLOGICAL SCIENCES↗