LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
Not Available
74 ATOMIC AND MOLECULAR PHYSICS↗
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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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SIDIS-RC EvGen: A Monte-Carlo event generator of semi-inclusive deep inelastic scattering with the lowest-order QED radiative corrections
SIDIS-RC EvGen is a C++ standalone Monte-Carlo event generator for studies of semi-inclusive deep inelastic scattering (SIDIS) processes at medium to high lepton beam energies. In particular, the generator contains binary and library components for generating SIDIS events and calculating cross sections for unpolarized or longitudinally polarized beam and unpolarized, longitudinally or transversely polarized target. The structure of the generator incorporates transverse momentum-dependent parton distribution and fragmentation functions, whereby we obtain multi-dimensional binned simulation results, which will facilitate the extraction of important information about the three-dimensional nucleon structure from SIDIS measurements. In order to build this software, we have used recent elaborate QED calculations of the lowest-order radiative effects, applied to the leading order Born cross section in SIDIS. Here, in this paper, we provide details on the theoretical formalism as well as the construction and operation of SIDIS-RC EvGen, e.g., how we handle the event generation process and perform multi-dimensional integration. We also provide example programs, flowcharts, and numerical results on azimuthal transverse single-spin asymmetries.
97 MATHEMATICS AND COMPUTING↗
Efficient and robust optimal design for quantile regression based on linear programming
Not Available
Peng, Cheng↗
A reporting format for leaf-level gas exchange data and metadata
Not Available
54 ENVIRONMENTAL SCIENCES↗
Unravelling biogeochemical drivers of methylmercury production in an Arctic fen soil and a bog soil
Arctic tundra soils store a globally significant amount of mercury (Hg), which could be transformed to the neurotoxic methylmercury (MeHg) upon warming and thus poses serious threats to the Arctic ecosystem. However, our knowledge of the biogeochemical drivers of MeHg production is limited in these soils. Using substrate addition (acetate and sulfate) and selective microbial inhibition approaches, we investigated the geochemical drivers and dominant microbial methylators in 60-day microcosm incubations with two tundra soils: a circumneutral fen soil and an acidic bog soil, collected near Nome, Alaska, United States. Results showed that increasing acetate concentration had negligible influences on MeHg production in both soils. However, inhibition of sulfate-reducing bacteria (SRB) completely stalled MeHg production in the fen soil in the first 15 days, whereas addition of sulfate in the low-sulfate bog soil increased MeHg production by 5-fold, suggesting prominent roles of SRB in Hg(II) methylation. Without the addition of sulfate in the bog soil or when sulfate was depleted in the fen soil (after 15 days), both SRB and methanogens contributed to MeHg production. Analysis of microbial community composition confirmed the presence of several phyla known to harbor microorganisms associated with Hg(II) methylation in the soils. Lastly, the observations suggest that SRB and methanogens were mainly responsible for Hg(II) methylation in these tundra soils, although their relative contributions depended on the availability of sulfate and possibly syntrophic metabolisms between SRB and methanogens.
54 ENVIRONMENTAL SCIENCES↗
Quantifying pH buffering capacity in acidic, organic-rich Arctic soils: Measurable proxies and implications for soil carbon degradation
Dynamic pH change promoted by biogeochemical reactions in Arctic tundra soils can be a major control on the production and release of CO 2 and CH 4 , which contribute to rising global temperatures. Large quantities of soil organic matter (SOM) in these soils are susceptible to microbial decomposition, leading to pH changes during permafrost thaw. Soil pH buffering capacity (β) modulates the extent of pH change but has not been thoroughly studied and represented in predictive ecosystem scale biogeochemical models in Arctic tundra soils. In this study, we generated titration curves for 21 acidic tundra soils from three Arctic sites across northern Alaska, United States of America. Geochemical and hydrological soil properties were evaluated, and correlations with β were developed. Strong correlations between β and both gravimetric water content (Θ g ) (R 2 = 0.847, p < 0.001) and soil water retention (SWR) (R 2 = 0.849, p = 0.001) indicate that the ability of soil to retain water could be associated with its buffering properties. Correlations between β and soil organic carbon (SOC) and cation exchange capacity (CEC) were also explored, and relationships to SWR are discussed. These correlations were then used with existing soil databases reporting SOC, CEC, and SWR to estimate β across Alaska soils. We further demonstrated the quantitative relationships between β and the simulated rates of biogeochemical reactions and show that lower β leads to higher soil pH and more CH 4 production. Overall, our study provides simple proxies for β in Arctic soils and highlights the importance and implications of representing soil buffering in predictive models, thereby enabling quantitative coupling between pH dynamics associated with biogeochemical reactions. Integrating β into predictive models of Arctic biogeochemical cycling may reduce model uncertainty and further our understanding of permafrost SOM degradation accelerated by warming.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials
Reliable models of the thermodynamic properties of materials are critical for industrially relevant applications that require a good understanding of equilibrium phase diagrams, thermal and chemical transport, and microstructure evolution. The goal of thermodynamic models is to capture data from both experimental and computational studies and then make reliable predictions when extrapolating to new regions of parameter space. These predictions will be impacted by artifacts present in real data sets such as outliers, systematic errors, and unreliable or missing uncertainty bounds. Such issues increase the probability of the thermodynamic model producing erroneous predictions. We present a Bayesian framework for the selection, calibration, and quantification of uncertainty of thermodynamic property models. The modular framework addresses numerous concerns regarding thermodynamic models including thermodynamic consistency, robustness to outliers, and systematic errors by the use of hyperparameter weightings and robust Likelihood and Prior distribution choices. Furthermore, the framework’s inherent transparency (e.g. our choice of probability functions and associated parameters) enables insights into the complex process of thermodynamic assessment. We introduce these concepts through examples where the true property model is known. Additionally, we demonstrate the utility of the framework through the creation of a property model from a large set of experimental specific heat and enthalpy measurements of Hafnium metal from 0 to 4900K.
36 MATERIALS SCIENCE↗
Mapping wall-to-wall fractional cover of Arctic tundra plant functional types in Alaska using 20-m spatial resolution satellite imagery and harmonized plot observations
Estimates of fractional cover (fCover) across given land surfaces are used to assess, and often model, vegetation composition and diversity, which are crucial for understanding the health and functioning of terrestrial ecosystems. Remote sensing provides a useful means for scaling local, plot-measured fCover estimates to regional scales. Leveraging a recently synthesized and harmonized plot database, this study generated wall-to-wall maps of fCover for six Alaskan-Arctic plant functional types (PFT), including non-vascular plants, forbs, graminoids, and deciduous and evergreen shrubs, using 20-m satellite data (Sentinel-1, Sentinel-2, ArcticDEM) using a machine learning regression approach, specifically the random forest (RF) algorithm, which is well-suited for handling nonlinear relationships and high-dimensional satellite datasets. This study additionally addressed the spatio-temporal inconsistencies e.g., sampling scale, plot size, and collection year in plot measured fCover by adopting a multivariate outlier detection approach—Cook’s distance—to identify high-quality plots for model training and validation. Our approach achieves high accuracy (R 2 = 0.59–0.93, root mean squared errors = 0.02–0.10 for all PFTs) between plot-observed and satellite-derived fCover when using high-quality plot samples. The mapped fCover characterizes the spatial patterns of different PFTs across the tundra biome at a 20-m resolution, providing key information needed for improved representation of Arctic tundra vegetation in terrestrial biosphere models to better understand climate-vegetation feedback across the Arctic tundra.
Arctic tundra↗
X-ray absorption spectroscopy characterization of embedded and extracted nano-oxides
Here, the chemistries and structures of both embedded and extracted Ysingle bondTisingle bondO nanometer-scale oxides in a nanostructured ferritic alloy (NFA) were probed by x-ray absorption spectroscopy (XAS). Y 2 Ti 2 O 7 is the primary embedded phase, while the slightly larger extracted oxides are primarily Y 2 TiO 5 . Analysis of the embedded nano-oxides is difficult partly due to the multiple Ti environments associated with different oxides and those still residing in matrix lattice sites. Thus, bulk extraction followed by selective filtration was used to isolate the larger Y 2 TiO 5 oxides for XAS, while the smaller predominant embedded phase Y 2 Ti 2 O 7 oxides passed through the filters and were analyzed using the log-ratio method.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Exceptionally high spallation strength for a high-entropy alloy demonstrated by experiments and simulations
High-entropy alloys are materials with an increasing number of technological applications. Amongst them, the Cantor alloy, FeMnCoCrNi, shows desirable mechanical properties at normal loading conditions. In this study we focus on the performance of the Cantor alloy at the ultra-high deformation rates of shock waves. We study shock-induced spallation using both experiments and atomistic simulations. Experimental loading is achieved using high power laser, with VISAR to obtain velocity profiles and spall strength, followed by transmission electron microscopy of the recovered samples. Molecular Dynamics (MD) simulations of shock-induced spallation are compared with experiments. Both experiments and simulations show a high spall strength which would be beneficial for certain applications, with experiments giving ~8 GPa at ~10 7 s -1 and MD giving almost ~30 GPa at ~10 9 s -1 . The difference between experiments and simulations can be explained by the difference in strain rate. Post-mortem analysis of the experimental samples shows nanotwins near the spall plane, while MD simulations show a highly disordered region giving rise to void nucleation and spall during loading.
36 MATERIALS SCIENCE↗
Evapotranspiration across plant types and geomorphological units in polygonal Arctic tundra
Coastal tundra ecosystems are relatively flat, and yet display large spatial variability in ecosystem traits. The microtopographical differences in polygonal geomorphology produce heterogeneity in permafrost depth, soil temperature, soil moisture, soil geochemistry, and plant distribution. Few measurements have been made, however, of how water fluxes vary across polygonal tundra plant types, limiting our ability to understand and model these ecosystems. In this study, our objective was to investigate how plant distribution and geomorphological location affect actual evapotranspiration (ET). These effects are especially critical in light of the rapid change polygonal tundra systems are experiencing with Arctic warming. At a field site near Barrow, Alaska, USA, we investigated the relationships between ET and plant cover in 2014 and 2015. ET was measured at a range of spatial and temporal scales using: (1) An eddy covariance flux tower for continuous landscape-scale monitoring; (2) An automated clear surface chamber over dry vegetation in a fixed location for continuous plot-scale monitoring; and (3) Manual measurements with a clear portable chamber in approximately 60 locations across the landscape. We found that variation in environmental conditions and plant community composition, driven by microtopographical features, has significant influence on ET. Among plant types, ET from moss-covered and inundated areas was more than twice that from other plant types. ET from troughs and low polygonal centers was significantly higher than from high polygonal centers. ET varied seasonally, with peak fluxes of 0.14 mm h -1 in July. Despite 24 hours of daylight in summer, diurnal fluctuations in incoming solar radiation and plant processes produced a diurnal cycle in ET. Finally, combining the patterns we observed with projections for the impact of permafrost degradation on polygonal structure suggests that microtopographic changes associated with permafrost thaw have the potential to alter tundra ecosystem ET.
54 ENVIRONMENTAL SCIENCES↗
Evaluation of Preoperative and Intraoperative Mobile Gamma Camera Imaging in Sentinel Lymph Node Biopsy for Melanoma Independent of Preoperative Lymphoscintigraphy
Sentinel lymph node biopsy (SLNB) is standard practice for staging cutaneous melanoma. High false negative rates have increased interest in adjunctive techniques for localizing SLNs. Mobile gamma cameras (MGCs) represent potential tools to enhance SLNB performance. Twenty eligible melanoma patients underwent 99mTc sulfur colloid injection and standard lymphoscintigraphy with a fixed gamma camera (FGC). A survey using a 20 cm square MGC, performed immediately preoperatively by the study surgeon, was used to establish an operative plan while blinded to the FGC results. Subsequently, SLNB was performed using a gamma probe and a novel 6 cm diameter handheld MGC. A total of 24 SLN basins were detected by FGC. Prior to unblinding, all 24 basins were identified with the preoperative MGC, and the operative plan established by preoperative MGC imaging was confirmed accurate by review of the FGC images. All individual SLNs were identified during intraoperative MGC imaging, and in 5/24 (21%) cases, additional clinical information was obtained from the MGC. Preoperative MGC images provide information consistent with FGC images for planning SLNB and in some cases provides additional information that aided in surgical decision-making.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Large-Eddy Simulation of a wind turbine using a Filtered Actuator Line Model
When dealing with multirotor devices such as quadcopters or wind farms, the cost of blade-resolved large-eddy simulation (LES) becomes prohibitive. Combining LES with a family of lower-fidelity models, called actuator line models (ALMs), has grown in popularity in the past decade. ALM replaces full blade resolution with an array of actuator points or lines parameterized by aerodynamic lift/drag polar plots along the blades. Body forces computed based on these actuator points are then projected onto the LES flow mesh, mimicking the effect of rotating blades on the flow. However, the optimal projection radius and the associated LES grid size is often too restrictive for multirotor simulations. Recently, a new tip-correction-based filtered ALM (F-ALM) was proposed by Martinez-Tossas and Meneveau (2019), which allows coarser-than-optimal grids by avoiding the associated overprediction of thrust. In this work, F-ALM is implemented into a high-order, in-house LES code to simulate National Renewable Energy Laboratory Phase VI wind turbine. It is then followed by a comparison between the baseline ALM and the newly implemented F-ALM in terms of instantaneous and time-averaged flow fields and blade loads, revealing the advantages of F-ALM in preventing the overprediction of power on coarse grids. Finally, this encourages accurate and affordable simulations of multirotor devices in the future.
17 WIND ENERGY↗
Flame spray pyrolysis optimization via statistics and machine learning
Not Available
36 MATERIALS SCIENCE↗
Spin waves excitation at micron-sized, anisotropy modified regions in amorphous Fe 80 B 20 stripes: Local properties and inter-regions coupling
We report on the measurement of the local magnetization dynamics occurring, at units of GHz, in large aspect ratio stripes lithographed from reduced damping amorphous Fe 80 B 20 films. The stripes were submitted to local anisotropy modifications by micrometric beam synchrotron X-ray irradiation. Our results include data on the dispersion relationships and group velocities corresponding to spin waves excited at both the non-irradiated and the irradiated regions. Whereas in the former case we observed standing spin waves with transverse-to-the stripe axis wave vector, in the latter one, for which the wave vector of the spin waves was parallel-to-the stripe axis, propagating spin waves were excited. In both regions, we measured the effective propagation distance of the spin waves, which resulted to be independent of the wave vector orientation. In the spin waves excited at the irradiated region, we also measured the decay time and effective damping coefficient, which was in good agreement with previously reported values obtained from FMR measurements in amorphous Fe 80 B 20 continuous films. We show that the interaction of the non-irradiated and irradiated zones results, at the stripe transverse saturation remanence and under an exciting field frequency of 4 GHz, in the introduction of a π phase shift between the standing spin waves excited at both sides of the irradiated region. This result opens the possibility of using the local, transverse to the stripe axis, magnetic anisotropy easy axis induced by the X-ray irradiation as a crucial constituent of a zero-applied field spin wave phase-shifter.
36 MATERIALS SCIENCE↗
Bayesian automated weighting of aggregated DFT, MD, and experimental data for candidate thermodynamic models of aluminum with uncertainty quantification
Atomic-scale modeling methods such as density functional theory (DFT) and molecular dynamics (MD) can predict the thermodynamic properties of materials at a lower cost than experimental measurements. However, their regular usage in thermodynamic model construction is hampered by the lack of quantitative agreement with experimental measurements and the lack of uncertainty estimates on the data. To make regular usage of this atomistic simulation data, it is important to assess whether the atomistic simulation datasets, by themselves or in combination with experimental measurements, result in the same physics-informed models best supported by experimental measurements alone. Here, models of aluminum thermodynamic properties are discussed using three data sources: atomistic calculations (DFT and MD), experiments, and a combination of atomistic calculations and experiments. The study shows that, after ensuring self-consistency in predicting key invariant points, both experimental measurements and atomistic calculations can significantly contribute to an optimal model.
36 MATERIALS SCIENCE↗
Electromagnetic moments of 215,217 Bi: Probing shell evolution beyond N = 126
The nuclear properties of bismuth isotopes (Z = 83) , with just one valence proton above the closed spherical shell at (Z = 82) , are expected to be governed by a single unpaired proton. However, already in semimagic 209 Bi (Z = 83, N = 126) , , the magnetic moment (μ) strongly deviates from the single-particle Schmidt value. A near linear decrease in μ with the increase of N after the N = 126 magic number was observed up to N = 130 . In order to test whether this trend is kept at N > 130 and to reveal the underlying mechanisms, an investigation of 215,217 Bi (N = 132, 134) has been undertaken. The magnetic dipole and electric quadrupole moments of the I π = 9/2 - nuclear ground states in these isotopes have been measured for the first time using the in-source resonance-ionization spectroscopy technique at ISOLDE (CERN). It has been shown that the linearly decreasing trend of μ( 209,211,213 Bi g ) is broken in 215,217 Bi with a nearly constant value of μ observed. Experimental data have been compared to calculations in the framework of the configuration-interaction shell model with the monopole-based universal V MU +LS interaction. The peculiarities in the behavior of μ(Bi, 9/2 - ) with increasing neutron number are explained as being due to the shell evolution, change of the neutron orbitals occupancies and strong configuration mixing beyond N = 130 . Also, the difference in the μ trends for bismuth (Z = 83) and astatine (Z = 85) isotopes with N > 126 are reproduced by the shell-model calculations. It is shown that monopole interaction plays noticeable role in the description of the peculiarities of the μ behaviour. Additionally, the extension of the application of the V MU interaction to the μ isotopic trends for heavy nuclei is important for further study of the capabilities of this promising version of the shell-model calculations.
Dipole magnetic moments↗
Climate-eutrophication-anoxia interactions in Late Glacial Soppensee, Switzerland: Forcings, non-linear responses and recovery
Combined effects of climate warming and anthropogenic nutrient loadings lead to lake eutrophication and anoxia globally. Because of chemical feedbacks, lakes under multiple stressors often respond in non-linear ways. However, it remains unclear whether climate change alone can lead to non-linear lake responses in the absence of anthropogenic nutrient disturbances. Here, we investigate the interactions between climate variability, nutrient cycling and trophic state changes, mixing regimes, anoxia and related chemical feedback in a small kettle-hole lake in Switzerland during Late Glacial times (15.2–12.6 cal ka BP), a period known for high-amplitude climate change in pre-anthropogenic times. After its formation during Heinrich Stadial 1 (>15 cal ka BP), Soppensee was oligotrophic and well-mixed. Soppensee became eutrophic and developed anoxia at 14.25 cal ka BP. Phosphorus (P) was released from sediments through the reductive dissolution of Fe-oxyhydroxides, fuelling eutrophication. Eutrophication lagged the Bølling warming (14.65 cal ka BP) by 400 years, suggesting that rising temperatures were not the trigger for eutrophication. Instead, eutrophication responded non-linearly to forest closure (threshold at 76 % arboreal pollen AP), which shielded Soppensee from wind mixing, enhancing lake stratification, anoxia and P release, intensifying eutrophication. These conditions ended during the 200-years cold period of the Aegelsee Oscillation (GI-1d, ca. 14.0 cal ka BP) when the landscape regionally opened (AP<76 %); the lake became well-mixed, oxygenated and P was efficiently sequestered. Throughout the Allerød (13.9–12.8 cal ka BP), enhanced Fe input prompted diagenetic vivianite formation, sequestering P in sediments, naturally remediating lake eutrophication despite closed forests, warm temperatures, lake stratification and anoxia.
Environmental sciences↗