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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Perspectives on Machine Learning-assisted Plasma Medicine: Towards Automated Plasma Treatment

Cold atmospheric plasmas (CAPs) have shown great promise for medical applications through their synergistic chemical, electrical, and thermal effects, which can induce therapeutic outcomes. However, safe and reproducible plasma treatment of complex biological surfaces poses a major hurdle to the widespread adoption of CAPs for medical applications. Predictive modeling of the mutual interactions between the plasma and biological surfaces and, thus, systematic approaches to quantify and predict plasma treatment outcomes remain largely elusive due to the lack of mechanistic understanding of plasma-surface interactions that can span across vastly different length-and time-scales. In addition, real-time sensing capabilities in biomedical CAP devices are often limited, which can be detrimental to plasma treatment due to the intrinsic plasma and surface variability during the treatment, as well as sensitivity to external perturbations. All of these challenges can make reproducible and effective plasma treatment of biological surfaces difficult to realize, which is further compounded by errors due to human operation of hand-held CAP devices. Machine learning and data-driven approaches can be particularly useful in addressing these challenges in three major ways: (i) data-driven modeling of hard-to-model plasma-surface interactions and plasma treatment outcomes; (ii) learning data analytics for plasma and surface diagnostics in real-time; and (iii) developing predictive controllers that enable reliable and effective CAP treatments. Furthermore, this paper discusses the promise of machine learning to accelerate plasma medicine research in these areas, toward machine learning-assisted and automated CAP treatment of complex biological surfaces.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Modeling Plant Nutrient Acquisition Strategies Alters Projections of Carbon and Nitrogen Dynamics in Bioenergy Agroecosystems

Plant strategies to acquire nutrients from limited environments help shape ecosystem carbon (C) and nitrogen (N) cycling and response to environmental change. The effects of plant strategies on ecosystem dynamics are largely uncharacterized in bioenergy agroecosystems, where the impacts could determine bioenergy's ability to meet its sustainability goals of storing C and reducing N loss. We used FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms and Protection), a plant–microbe interaction model of coupled plant nutrient uptake and soil organic matter decomposition, to simulate the effects of nutrient acquisition strategies on soil microbial activity and ecosystem nutrient cycling in bioenergy feedstocks miscanthus (Miscanthus × giganteus) and sorghum (Sorghum bicolor (L.) Moench). We examined the model's ability to reproduce the relative effects of belowground nutrient uptake on microbial activity using a reanalysis of empirical data showing that miscanthus root exudation provoked a larger soil microbial response than sorghum. From baseline model simulations, we found that the ability of miscanthus to retranslocate N resulted in higher N uptake at a lower C cost than the sorghum/soybean rotation and that soil C and N pools increased under perennial (miscanthus) and decreased under annual (sorghum/soybean) cultivation. The model also predicted that greater root exudation increased soil C accumulation, highlighting the role of roots in forming stable soil C. Overall, the baseline model was unable to reproduce field observations of miscanthus root exudation stimulating microbial activity more than sorghum. To improve the model, we updated the soil microbial parameters in miscanthus to have faster decomposition, a higher C/N ratio, and greater carbon use efficiency. These changes improved the simulated soil microbial response to miscanthus root exudation, supporting the hypothesis that miscanthus soils foster a microbial community that is more responsive to root exudation than that of sorghum.

09 BIOMASS FUELS↗
DOE OSTI2021

Predicting nepheline precipitation in waste glasses using ternary submixture model and machine learning

Nepheline precipitation in nuclear waste glasses during vitrification can be detrimental due to its negative effect on chemical durability. Developing models to accurately predict nepheline precipitation from compositions is important to increase waste loading since existing models can be overly conservative. In this study, an expanded dataset containing 955 glasses was compiled from literature data, where 355 glasses are for high-level waste (HLW). Previously developed submixture models were refitted using the new dataset, where a misclassification rate of 7.8% was achieved. Nine machine learning (ML) algorithms (e.g., k-nearest neighbor, Gaussian process regression, artificial neural network, support vector machine, decision tree, etc.) were applied to evaluate their ability of predicting nepheline precipitation from compositions. Model accuracy, precision, recall/sensitivity, and F1 score were systemically compared between different ML algorithms and modeling protocols. Good model prediction with an accuracy ~0.9 (misclassification rate of ~10%) was observed with different algorithms under certain protocol. This study evaluated various ML models to predict nepheline precipitations in waste glasses, highlighting the importance of data preparation, modeling protocol, and their effect on model stability and reproducibility. The results provide insights into applying ML to predict glass properties and suggest areas for future research on modeling nepheline precipitations.

Lu, Xiaonan↗
DOE OSTI2023

Quasi-Steady Simulation of Glaze Ice Accretion and Heat Transfer in the Supercooled Large Droplet Regime in Atmospheric Turbulent Air Flow

Abstract To avoid the use of a computationally intensive full unsteady simulation while providing an accurate solution, a quasi-steady simulation has been performed to study glaze and mixed ice accretion in the supercooled large droplet (SLD) regime in turbulent flow of atmospheric air. We have attempted to find the minimum time-step necessary to adequately simulate the icing process on an airfoil surface. Based on node displacement, a mesh morphing scheme has been adopted in the computations to account for the moving boundaries that are caused by the continuous ice buildup. We have modeled ice accretion on an airfoil surface for a time period of 232 s using several time steps. At each time-step we solved the steady-state conservation equations for the air and droplet phases and then used the results as initial conditions for the next time position. The magnitude of the time-step ranged from a least accurate two-shot simulation (where the time-step is 116 s) to a most accurate 2320-shot simulation (where the time-step is 0.1 s). In-between these two extreme time steps, we have performed a three-shot simulation (where the time-step is 77.33 s), a four-shot simulation (where the time-step is 58 s), a six-shot simulation (where the time-step is 38.67 s), a 46-shot simulation (where the time-step is 5 s), and a 232-shot simulation (where the time-step is 1 s). We have done so to find out the degree of accuracy (or inaccuracy) of the multishot simulation approach and to find out the appropriate time-step needed for a successful and valid quasi-steady simulation. A valid quasi-steady simulation needs to use a time-step that is small enough to reproduce the full time-dependent solution within a very small error band. We have found that both the 1 s and the 0.1 s time steps produce virtually identical results. This is the primary litmus test that proves the validity of the quasi-steady-state assumption. The results adopted in this paper are thus all based on the more conservative 0.1 s time-step. In the process of performing the simulations, remeshing was required in order to maintain the grid density in zones of high curvature to be able to capture the full physics in those zones. After successfully modeling glaze ice accretion over the airfoil surface using the 0.1 s quasi-steady simulation approach, the effects of supercooled large droplets (SLDs) impacting the surface have been examined and presented in terms of the variation of the local collection efficiency, the water film thickness, and the heat transfer rate. Examination of the variation of the angle that the ice horn makes with the airfoil chord line demonstrated a 20% improvement in angle prediction when the time-step is reduced from 116 s to 0.1 s. The analysis also reveals a 12% or 8.5% increase in the maximum collection efficiency, βmax, depending on whether the value of the liquid water content (LWC) has been doubled from 0.5 g/m3 to 1 g/m3, or the value of the freestream velocity has been doubled from 75 m/s to 150 m/s, respectively. Because of the need to monitor the local collection efficiency and convective heat fluxes at each shot (regardless of the number of shots employed), the approach adopted here was found to be effective in successively and successfully reproducing the curvature of the glaze ice horn.

Engineering↗
DOE OSTI2023

Evaluation of Spray and Combustion Models for Simulating Dilute Combustion in a Direct-Injection Spark-Ignition Engine

Dilute combustion in spark-ignition engines has the potential to improve thermal efficiency by mitigating knock and by reducing throttling and wall heat losses. However, ignition and combustion processes can become unstable for dilute operation due to a lowered laminar flame speed, resulting in excessive cycle-to-cycle variability (CCV) of the combustion process. To compensate for the slower combustion in less reactive mixtures, a modified intake port geometry can be employed to generate a strong tumble flow in the cylinder and elevate turbulence levels around the spark plug, thereby promoting a faster transition to turbulent deflagration. Consequently, optimizing combustion chamber geometry and operating strategy is crucial to maximizing the benefits of using dilute combustion with enhanced in-cylinder turbulence across a wide range of operating conditions. Computational fluid dynamics (CFD) simulations can be utilized for virtual engine optimization tasks, but this would require the models to be truly predictive regarding the impact of changes to the engine design and operational parameters.In this study, multicycle large-eddy simulations (LES) are performed for a direct-injection spark-ignition engine to investigate the model performance in predicting engine combustion characteristics with respect to changes in the intake configuration. A tumble plate that blocks the lower part of the intake port inlet is used to vary the tumble. A set of CFD models that have been recently developed are employed, which takes into account the drag of nonspherical droplets, flash-boiling behavior of liquid sprays, spray-wall interaction, surrogate formulation of a research-grade E10 gasoline, and fast chemical kinetic solvers. Simulation results are compared to experimental engine data in terms of cylinder pressure, apparent heat release rate, mass fraction burned timing, and flame images. It is found that LES employing the state-of-the-art CFD models are capable of properly predicting the spray processes and reproducing the measured mean cylinder pressure for the case with the tumble plate. On the other hand, the LES over-predicts the combustion rate during the early combustion stage and under-estimates the CCV, and these discrepancies become larger when the tumble plate is removed.

computational fluid dynamics simulation↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗
DOE OSTI2018

Atomic layer deposition of 2D and 3D standards for synchrotron-based quantitative composition and structure analysis methods

Atomic layer deposition (ALD) is a scalable deposition technique known for producing uniform, conformal films of a wide range of compounds on nearly any substrate material. These traits make it an ideal deposition method for producing films to replace the National Institute of Standards and Technology (NIST) standards and create Standard Reference Materials (SRMs) on a wide range of relevant two-dimensional and three-dimensional substrates. The use of SRM from NIST for quantitative analysis of chemical composition using synchrotron based x-ray fluorescence (SR-XRF) and scanning transmission x-ray microscopy (STXM) is common. Such standards, however, can suffer from inhomogeneity in chemical composition and thickness and often require further calculations, based on sample mounting and detector geometry, to obtain quantitative results. These inhomogeneities negatively impact the reproducibility of the measurements and the quantitative measure itself. Utilizing Rutherford backscattering, x-ray reflectivity, quartz crystal microbalance, STXM, and SR-XRF, the authors show that ALD is capable of producing high quality standards that are homogenous over scales ranging from nanometers to 100s of micrometers.

Becker, Nicholas G.↗
DOE OSTI2025

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗
DOE OSTI2018

Bidisperse and polydisperse suspension rheology at large solid fraction

At the same solid volume fraction, bidisperse and polydisperse suspensions display lower viscosities, and weaker normal stress response, compared to monodisperse suspensions. The reduction of viscosity associated with size distribution can be explained by an increase of the maximum flowable, or jamming, solid fraction. In this work, concentrated or "dense" suspensions are simulated under strong shearing, where thermal motion and repulsive forces are negligible, but we allow for particle contact with a mild frictional interaction with interparticle friction coefficient of 0.2. Aspects of bidisperse suspension rheology are first revisited to establish that the approach reproduces established trends; the study of bidisperse suspensions at size ratios of large to small particle radii (2 to 4) shows that a minimum in the viscosity occurs for zeta slightly above 0.5, where zeta=phi_{large}/phi is the fraction of the total solid volume occupied by the large particles. The simple shear flows of polydisperse suspensions with truncated normal and log normal size distributions, and bidisperse suspensions which are statistically equivalent with these polydisperse cases up to third moment of the size distribution, are simulated and the rheologies are extracted. Prior work shows that such distributions with equivalent low-order moments have similar phi_{m}, and the rheological behaviors of normal, log normal and bidisperse cases are shown to be in close agreement for a wide range of standard deviation in particle size, with standard correlations which are functionally dependent on phi/phi_{m} providing excellent agreement with the rheology found in simulation. The close agreement of both viscosity and normal stress response between bi- and polydisperse suspensions demonstrates the controlling in influence of the maximum packing fraction in noncolloidal suspensions. Microstructural investigations and the stress distribution according to particle size are also presented.

Pednekar, Sidhant↗
DOE OSTI2018

The role of electron irradiation history in liquid cell transmission electron microscopy

In situ liquid cell transmission electron microscopy (LC-TEM) allows dynamic nanoscale characterization of systems in a hydrated state. Although powerful, this technique remains impaired by issues of repeatability that limit experimental fidelity and hinder the identification and control of some variables underlying observed dynamics. We detail new LC-TEM devices that improve experimental reproducibility by expanding available imaging area and providing a platform for investigating electron flux history on the sample. Irradiation history is an important factor influencing LC-TEM results that has, to this point, been largely qualitatively and not quantitatively described. We use these devices to highlight the role of cumulative electron flux history on samples from both nanoparticle growth and biological imaging experiments and demonstrate capture of time zero, low-dose images on beam-sensitive samples. In particular, the ability to capture pristine images of biological samples, where the acquired image is the first time that the cell experiences significant electron flux, allowed us to determine that nanoparticle movement compared to the cell membrane was a function of cell damage and therefore an artifact rather than visualizing cell dynamics in action. Lastly, these results highlight just a subset of the new science that is accessible with LC-TEM through the new multiwindow devices with patterned focusing aides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Thermal conductivity in Bi 0.5 Sb 1.5 Te 3+ x and the role of dense dislocation arrays at grain boundaries

Several prominent mechanisms for reduction in thermal conductivity have been shown in recent years to improve the figure of merit for thermoelectric materials. Such a mechanism is a hierarchical all-length-scale architecturing that recognizes the role of all microstructure elements, from atomic to nano to microscales, in reducing (lattice) thermal conductivity. In this context, there have been recent claims of remarkably low (lattice) thermal conductivity in Bi 0.5 Sb 1.5 Te 3 that are attributed to seemingly ordinary grain boundary dislocation networks. These high densities of dislocation networks in Bi 0.5 Sb 1.5 Te 3 were generated via unconventional materials processing with excess Te (which formed liquid phase, thereby facilitating sintering), followed by spark plasma sintering under pressure to squeeze out the liquid. We reproduced a practically identical microstructure, following practically identical processing strategies, but with noticeably different (higher) thermal conductivity than that claimed before. We show that the resultant microstructure is anisotropic, with notable difference of thermal and charge transport properties across and along two orthonormal directions, analogous to anisotropic crystals. Thus, we believe that grain boundary dislocation networks are not the primary cause of enhanced ZT through reduction in thermal conductivity. Instead, we can reproduce the purported high ZT through a favorable but impractical and incorrect combination of thermal conductivity measured along the pressing direction of anisotropy while charge transport measured in the direction perpendicular to the anisotropic direction. We believe that our work underscores the need for consistency in charge and thermal transport measurements for unified and verifiable measurements of thermoelectric (and related) properties and phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Zeolitic imidazolate framework membranes made by ligand-induced permselectivation

Zeolitic imidazolate framework (ZIF) membranes are emerging as a promising energy-efficient separation technology. However, their reliable and scalable manufacturing remains a challenge. We demonstrate the fabrication of ZIF nanocomposite membranes by means of an all-vapor-phase processing method based on atomic layer deposition (ALD) of ZnO in a porous support followed by ligand-vapor treatment. After ALD, the obtained nanocomposite exhibits low flux and is not selective, whereas after ligand-vapor (2-methylimidazole) treatment, it is partially transformed to ZIF and shows stable performance with high mixture separation factor for propylene over propane (an energy-intensive high-volume separation) and high propylene flux. Membrane synthesis through ligand-induced permselectivation of a nonselective and impermeable deposit is shown to be simple and highly reproducible and holds promise for scalability.

Science & Technology - Other Topics↗
DOE OSTI2020

Reversible structural transformations in supercooled liquid water from 135 to 245 K

Water has many anomalous properties compared to “simple” liquids, and these anomalies are typically enhanced in supercooled water.1-3 While numerous models have been proposed, including the liquid-liquid critical point,4,5 the singularity-free scenario,6 and the stability limit conjecture,1 a molecular-level understanding remains elusive. The main difficulty in determining which, if any, of these models is correct is the limited amount of data in the relevant temperature and pressure ranges. For water at ambient pressures, which is the focus of this work, data is largely missing from 160 – 232 K (“No Man’s Land”) due to rapid crystallization.2,3 Whether rapid crystallization is just an experimental obstacle, or a fundamental problem signaling the inability of water to thermally equilibrate prior to crystallization is also a major unanswered question.5,7 Here, we investigate the structural transformations of transiently-heated, supercooled water with nanosecond time resolution using infrared vibrational spectroscopy. The experiments demonstrate three key results. First, water’s structure relaxes from its initial configuration to a “steady-state” configuration prior to the onset of crystallization over a wide temperature range. Second, water’s steady-state structure can be reproduced by a linear combination of two, temperature-independent structures that correspond to a “high-temperature liquid” and a “low-temperature liquid.” Third, the observed structural changes are reversible over the full temperature range. Taken together, these results show that supercooled water can equilibrate prior to crystallization for temperatures from the homogeneous nucleation temperature, TH ~232 K,3 down to the glass transition temperature (Tg ~ 136 K). Second, the results provide support for the hypothesis that supercooled water can be described as a mixture of two, structurally-distinct, interconvertible liquids from 135 K to 245 K.5,8-18

Kringle, Loni M.↗
DOE OSTI2017

Panels of HIV-1 Subtype C Env Reference Strains for Standardized Neutralization Assessments

In the search for effective immunologic interventions to prevent and treat HIV-1 infection, standardized reference reagents are a cost-effective way to maintain robustness and reproducibility among immunological assays. To support planned and ongoing studies where clade C predominates, here we describe three virus panels, chosen from 200 well-characterized clade C envelope (Env)-pseudotyped viruses from early infection. All 200 Envs were expressed as a single round of replication pseudoviruses and were tested to quantify neutralization titers by 16 broadly neutralizing antibodies (bnAbs) and sera from 30 subjects with chronic clade C infections. We selected large panels of 50 and 100 Envs either to characterize cross-reactive breadth for sera identified as having potent neutralization activity based on initial screening or to evaluate neutralization magnitude-breadth distributions of newly isolated antibodies. We identified these panels by downselection after hierarchical clustering of bnAb neutralization titers. The resulting panels represent the diversity of neutralization profiles throughout the range of virus sensitivities identified in the original panel of 200 viruses. A small 12-Env panel was chosen to screen sera from vaccine trials or natural-infection studies for neutralization responses. We considered panels selected by previously described methods but favored a computationally informed method that enabled selection of viruses representing diverse neutralization sensitivity patterns, given that we do not a priori know what the neutralization-response profile of vaccine sera will be relative to that of sera from infected individuals. The resulting 12-Env panel complements existing panels. Use of standardized panels enables direct comparisons of data from different trials and study sites testing HIV-1 clade C-specific products. HIV-1 group M includes nine clades and many recombinants. Clade C is the most common lineage, responsible for roughly half of current HIV-1 infections, and is a focus for vaccine design and testing. Standard reference reagents, particularly virus panels to study neutralization by antibodies, are crucial for developing cost-effective and yet rigorous and reproducible assays against diverse examples of this variable virus. We developed clade C-specific panels for use as standardized reagents to monitor complex polyclonal sera for neutralization activity and to characterize the potency and breadth of cross-reactive neutralization by monoclonal antibodies, whether engineered or isolated from infected individuals. We chose from 200 southern African, clade C envelope-pseudotyped viruses with neutralization titers against 16 broadly neutralizing antibodies and 30 sera from chronic clade C infections. We selected panels to represent the diversity of bnAb neutralization profiles and Env neutralization sensitivities. Finally, use of standard virus panels can facilitate comparison of results across studies and sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules

The soil microbiome is an invaluable component of the biosphere and critical for ecosystem functions, including biogeochemical cycling, soil-atmosphere gas exchange, degradation of toxic compounds, and promotion of plant growth and stress resistance/resilience. An improved understanding of the soil microbiome will help with predicting how these processes respond to external perturbations, and with harnessing beneficial aspects of the soil microbiome for agronomic applications such as crop amendments. However, the extensive taxonomic and functional diversity inherent within the soil microbiome hinders efficient analysis of this system. Microbial biodiversity in soils is orders of magnitude greater than other commonly studied systems such as the human gut microbiome (Blum, Zechmeister-Boltenstern, and Keiblinger 2019; Berendsen, Pieterse, and Bakker 2012). Thousands of microbial taxa may be found in a single gram of soil (Roesch et al. 2007), and high rates of gene flow and mutation further promote microbial diversification (Sergaki et al. 2018). Concomitantly, functional diversity in soil is similarly extensive. Soil is a heterogeneous mixture of microenvironments with defined physical and chemical attributes (Bach et al. 2018), within which numerous microbial guilds of distinct life-strategies and metabolic capacities can be found (Perez-Garcia, Lear, and Singhal 2016; H.-S. Song et al. 2014). Furthermore, the soil microbiome harbors a significant fraction of rare and/or quiescent members (Blagodatskaya and Kuzyakov 2013) that exist below the threshold of detection of current technologies. Such rare taxa may make significant contributions to process rates (Shade and Gilbert 2015; Dawson et al. 2017), but their scarcity complicates their identification and analysis. Finally, the vast amounts of information generated through holistic analyses of soil communities represent an intense computational burden (Scholz, Lo, and Chain 2012; Prosser 2015) that precludes assessment of the complete functional and taxonomic diversity contained in this ecosystem.

Naylor, Dan T.↗
DOE OSTI2021

Wide-blocky veins explained by dependency of crystal growth rate on fracture surface type: Insights from phase-field modeling

Vein microstructures contain a wealth of information on coupled chemical and mechanical processes of fracturing, fluid transport, and crystal growth. Numerical simulations have been used for exploring the factors controlling the development of vein microstructures; however, they have not been quantitatively validated against natural veins. Here we combined phase-field modeling with microtextural analysis of previously unexplained wide-blocky calcite veins in natural limestone and of the fresh fracture surface in this limestone. Results show that the wide-blocky vein textures can only be reproduced if ~10%–20% of crystals grow faster than the rest. This fraction corresponds to the amount of transgranularly broken grains that were observed on the experimental fracture surfaces, which are dominantly intergranular. We hypothesize that transgranular fractures allow faster growth of vein minerals due to the lack of clay coatings and other nucleation discontinuities that are common along intergranular cracks. Our simulation results show remarkable similarity to the natural veins and reproduce the nonlinear relationship between vein crystal width and vein aperture. This allows accurate simulations of crystal growth processes and related permeability evolution in fractured rocks.

Geology↗
DOE OSTI2018

Dynamics of Liquid Lithium Atoms. Pseudopotential and EAM-Type Potentials

It is generally accepted that the complicated character of the interparticle interaction in liquid metals is reproduced most correctly by many-particle potentials of the EAM-type (embedded atom model) interparticle interaction. It is shown that in the case of liquid lithium near the melting temperature (T{sub m} = 453.65 K), the spherical pseudopotential provides a better agreement with experimental data on elastic and inelastic X-ray scattering as compared to the known EAM potentials. The calculations of the dynamic structural factor and spectral densities of the longitudinal and transverse atomic currents lead to the conclusion that although the pseudopotential and EAM potentials generate a certain qualitative correspondence in the features of collective dynamics, the interparticle interaction of the spherical type reproduces correctly the general form of the dynamic structure factor in a certain wavenumber range, as well as the dispersion relation for collective excitations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Electronic Structure of FeSe Monolayer Superconductors: Shallow Bands and Correlations

Electronic spectra of typical single FeSe layer superconductor—FeSe monolayer film on SrTiO{sub 3} substrate (FeSe/STO) obtained from ARPES data reveal several puzzles: what is the origin of shallow and the so called “replica” bands near the M-point and why the hole-like Fermi surfaces near the Γ-point are absent. Our extensive LDA+DMFT calculations show that correlation effects on Fe-3d states can almost quantitatively reproduce rather complicated band structure, which is observed in ARPES, in close vicinity of the Fermi level for FeSe/STO. Rather unusual shallow electron-like bands around the M-point in the Brillouin zone are well reproduced. Detailed analysis of the theoretical and experimental quasiparticle bands with respect to their origin and orbital composition is performed. It is shown that for FeSe/STO system the LDA calculated Fe-3d{sub xy} band, renormalized by electronic correlations within DMFT gives the quasiparticle band almost exactly in the energy region of the experimentally observed “replica” quasiparticle band at the Mpoint. However, correlation effects alone are apparently insufficient to eliminate the hole-like Fermi surfaces around the Γ-point, which are not observed in most ARPES experiments. The Fermi surfaces remain here even if Coulomb and/or Hund interaction strengths are increased while overall agreement with ARPES worsens. Increase of number of electrons also does not lead to vanishing of this Fermi surface and makes agreement of LDA+DMFT results with ARPES data much worse. We also present some simple estimates of “forward scattering” electron-optical phonon interaction at FeSe/STO interface, showing that it is apparently irrelevant for the formation of “replica” band in this system and significant increase of superconducting T{sub c}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗