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At least 127 records · Page 7

Co-precipitation induces changes to iron and carbon chemistry and spatial distribution at the nanometer scale

Association of organic matter (OM) with mineral phases via co-precipitation is expected to be a widespread process in environments with high OM input and frequent mineral dissolution and re-precipitation. In contrast to surface area-limited adsorption processes, co-precipitation may allow for greater carbon (C) accumulation. However, the potential sub-micrometer scale structural and compositional differences that affect the bioavailability of co-precipitated C are largely unknown. In this work, we used a combination of high-resolution analytical electron microscopy and bulk spectroscopy to probe interactions between a mineral phase (ferrihydrite, nominally Fe 2 O 3 •0.5H 2 O) and organic soil-derived water-extractable OM (WEOM). In co-precipitated WEOM-Fe, nanometer-scale scanning transmission electron microscopy with electron energy loss spectroscopy (STEM-EELS) revealed increased Fe(II) and less Fe aggregation relative to adsorbed WEOM-Fe. Spatially distinct lower- and higher-energy C regions were detected in both adsorbed and co-precipitated WEOM-Fe. In co-precipitates, lower-energy aromatic and/or substituted aromatic C was spatially associated with reduced Fe(II), but higher-energy oxidized C was enriched at the oxidized Fe(III) interface. Therefore, we show that co-precipitation does not constitute a non-specific physical encapsulation of C that only affects Fe chemistry and spatial distribution, but may cause a bi-directional set of reactions that lead to spatial separation and transformation of both Fe and C forms. In particular, we propose that abiotic redox reactions between Fe and C via substituted aromatic groups (e.g., hydroquinones) play a role in creating distinct co-precipitate composition, with potential implications for its mineralization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Strange Case of Ground-Coupled Airwaves on Seismoacoustic Stations at Local to Near-Regional Scales

Here we investigate the application of ground-coupled airwaves observed by seismoacoustic stations at local to near-regional scales to detect signals of interest and determine back-azimuth information. Ground-coupled airwaves are created from incident pressure waves traveling through the atmosphere that couple to the earth and transmit as a seismic wave with retrograde elliptical motion. Previous studies at sub-local scales (<10 km from a source of interest) found the back-azimuth to the source could be accurately determined from seismoacoustic signals recorded by acoustic and 3-component seismic sensors spatially separated on the order of 10 to 150 m. The potential back-azimuth directions are estimated from the coherent signals between the acoustic and vertical seismic data, via a propagation-induced phase shift of the seismoacoustic signal. A unique solution is then informed by the particle motion of the 3-component seismic station, which was previously found to be less accurate than the seismoacoustic-sensor method. We investigate the applicability of this technique to greater source-receiver distances, from 50-100 km and up to 400 km, which contains pressure waves with tropospheric and stratospheric ray paths, respectively. Specifically, we analyze seismoacoustic sources with ground truth from rocket motor fuel elimination events at the Utah Test and Training Range (UTTR) as well as a 2020 rocket launch in Southern California. From these sources we observe evidence that while coherent signals can be seen from both sources on multiple seismoacoustic station pairs, the determined ground-coupled airwave back-azimuths are more complicated than results at more local scales. Our findings suggest more complex factors including incidence angle, coupling location, subsurface material, and atmospheric propagation effects need to be fully investigated before the ground-coupled airwave back-azimuth determination method can be applied or assessed at these further distances.

58 GEOSCIENCES↗

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Future Spatially Explicit Patterns of Land Transitions in the United States With Multiple Stressors

Climate change, income and population growth, and changing diets are major drivers of the global food system with implications for land use change. Land use in the U.S. will be affected directly by local and regional forces and indirectly through international trade. In order to investigate the effects of several potential forces on land use changes in the U.S., we advanced capabilities in representing the interactions between natural and human systems by linking a multisectoral and multiregional socio-economic model of the world economy to a model that downscales land use to a 0.5°grid scale. This enables us to translate regional projections of future land use into higher-resolution representations of time-evolving land cover (effectively spatially explicit land use transitions). We applied the framework over the U.S., with a particular interest in the Mississippi River Basin and its four sub-basins, to consider how a range of global drivers affect land use and cover in the target regions. Our results show that under scenarios of high pressure on the world food system a comparative advantage in livestock production amplifies the recent trend toward less cropland and more pastures in the U.S. Under low pressures on the world food system agricultural land is used less intensively. However, there can be key differences among the various land-use transitions at the sub- basin scale. Overall, these results highlighted the need for high resolution details to explicitly understand the implications of land use change on environmental impacts such as carbon storage, soil erosion, chemical use, hydrology, and water quality.

54 ENVIRONMENTAL SCIENCES↗

Structure optimization with stochastic density functional theory

Linear-scaling techniques for Kohn–Sham density functional theory are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the localization of the density matrix or accurate embedding approaches, limiting their applicability. In contrast, stochastic density functional theory (sDFT) achieves linear- and sub-linear scaling by statistically sampling the ground state density without relying on embedding or imposing localization. In return, ground state observables, such as the forces on the nuclei, fluctuate in sDFT, making optimizing the nuclear structure a highly non-trivial problem. In this work, we combine the most recent noise-reduction schemes for sDFT with stochastic optimization algorithms to perform structure optimization within sDFT. We compare the performance of the stochastic gradient descent approach and its variations (stochastic gradient descent with momentum) with stochastic optimization techniques that rely on the Hessian, such as the stochastic Broyden–Fletcher–Goldfarb–Shanno algorithm. In conclusion, we further provide a detailed assessment of the computational efficiency and its dependence on the optimization parameters of each method for determining the ground state structure of bulk silicon with varying supercell dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The HydroBio Dataset: a new data resource for evaluating existing and potential hydropower capacity and freshwater biodiversity in the conterminous United States

Hydropower is a critical source of affordable and reliable electricity and energy system stability services in the United States. Opportunities to expand US hydropower production include retrofitting existing non-powered dams to produce power, retrofitting existing hydropower dams to improve efficiency or increase capacity, or constructing new hydropower infrastructure on currently unregulated river reaches. We created the HydroBio Dataset, which summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin scale in the conterminous US to contextualize existing and potential grid contributions with the freshwater ecosystems in which dams are situated. We demonstrate a use-case of this dataset by rescaling and comparing potential non-powered dam nominal capacity to rarity-threat-weighted freshwater species richness for sub-basins where both types of data exist. On average, normalized freshwater biodiversity exceeded normalized potential non-powered dam nominal capacity in these sub-basins. Potential non-powered dam nominal capacity was concentrated in sub-basins in the Upper Mississippi and Ohio hydrologic regions while freshwater biodiversity was concentrated in the South Atlantic-Gulf, Ohio, and Tennessee hydrologic regions. Additionally, non-powered dams and existing hydropower dams are located in sub-basins with similar indices of freshwater biodiversity. The HydroBio Dataset adds an additional ecological dimension of context to our understanding of current and potential future US hydropower capabilities and is a valuable decision support tool for stakeholders tasked with balancing gains in services to the US power grid with the public and environmental benefits of freshwater ecosystems.

Biodiversity↗

Coupling of Spark Plasma Sintering with Advanced Modeling to Enable Process Scale-Up: Presentation to DOE-NE [Slides]

The research goal of this project is to develop at Idaho National Laboratory (INL) a first-of-its-kind Multiphysics Object-Oriented Simulation Environment (MOOSE)-based, multiscale, multiphysics spark plasma sintering (SPS) modeling and simulation code application, termed “Freya.” Freya will simulate the thermo-mechanical-electrical aspects of the SPS fabrication process and will be paired with lower length scale sub-models, such as phase-field, to predict the resulting microstructure. SPS is an advanced manufacturing process that can be used to solve a variety of material manufacturing challenges; however, this process is an extremely challenging problem for modeling and simulation. The SPS process is inherently multiphysics and multi-scale, with the macroscale electro-thermo-mechanical behavior linked intricately to the microstructure evolution of the part being sintered. Accurate modeling and simulation tools, specifically geared towards the SPS process, are needed to predict the influence of the multiple variables involved in the manufacturing process. Modeling and simulation accuracy is achieved and demonstrated through comparison to multiple validation experiments. The validation efforts for Freya include both separate effects and complete multiphysics SPS process experiments. One of the key benefits this Laboratory Directed Research & Development (LDRD) project offers stems from the emphasis placed on experimental validation of the Freya models, both on the individual length scales and of the final coupled multiscale multiphysics simulations. Experimental validation of Freya’s multiscale coupling capability provides the technical credibility necessary for potential future industry and research partners to accept the simulation predictions.

36 MATERIALS SCIENCE↗

Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)

Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

58 GEOSCIENCES↗

Accumulative Roll Bonding of Alloy 2205 Duplex Steel and the Accompanying Impacts on Microstructure, Texture, and Mechanical Properties

The mechanical and microstructural evolution of Alloy 2205 during severe plastic deformation is examined in this study. A combination of accumulative roll bonding (ARB) and cold rolling results in the successful formation of a nanograined dual-phase microstructure of austenite and ferrite with some transformed martensite. Severe deformation to cumulative reductions of 80.5, 92.5, 95, and 97 pct were performed. Microscopy indicates that grain dimensions in the sheet normal direction is less than 100 nm for reductions ≥ 92.5 pct. Shear banding is observed at reductions ≥ 95 pct while twinning is only observed at reductions < 92.5 pct. Neutron diffraction measurements indicated the presence of martensite for reductions ≥ 95 pct at ~ 8 pct volume fraction. Taken in conjunction, it appears that during initial ARB processing, both slip and twinning are active plastic mechanisms. As twinning becomes exhausted, martensitic transformation, slip, and intermittent shear banding account for the active plasticity mechanisms. Material hardness saturates at 92.5 pct reduction, with a maximum hardness of 45 HRC. Sub-sized tensile testing confirms this approximate hardness with measurements indicating a UTS of ~ 1440 MPa. Texture analysis of crystal orientation distributions in the plate normal direction suggest an approximate Kurdjumov–Sachs orientation relationship at all reductions above 80 pct indicating stability of the orientation relationship at high strains. The intragranular structure develops a fine scale sub-grain content with increasing deformation, resulting in a continual evolution of texture up to and including 97 pct reduction. The final structure presents strong components of Goss and rotated cube texture in both the austenite and ferrite. In this body of work we aim to compare ARB of an industrially relevant FCC/BCC system (Alloy 2205) to historical model FCC/BCC systems such as Cu/Nb.

36 MATERIALS SCIENCE↗

Efficient and tunable blue light generation using lithium niobate nonlinear photonics

Thin-film lithium niobate (LN) has recently emerged as a playground for chip-scale nonlinear optics and leads to efficient frequency conversions from near-infrared to near-visible bands. For many nonlinear and quantum photonics applications, it is desirable to operate deep into the visible band within LN's transparency window. However, the strong material dispersion at short wavelengths makes phase-matching difficult, necessitating sub-micrometer scale control of domain structures for efficient phase-matching. Here, we report the operation of thin film LN in the blue wavelength and high fidelity poling of the thin-film LN waveguide to this regime. As a result, quasi-phase matching is realized between IR (871 nm) and blue (435.5 nm) wavelengths in a straight waveguide and prompts strong blue light generation with a conversion efficiency (1040% ± 140%/W). This blue second harmonic generator exhibits stable temperature tunability, which is important for applications that require precise frequency alignment, such as atomic clocks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Progress on Cosmological Magnetic Fields

A variety of observations impose upper limits at the nano Gauss level on magnetic fields that are coherent on inter-galactic scales while blazar observations indicate a lower bound $\sim 10^{-16}$ Gauss. Such magnetic fields can play an important astrophysical role, for example at cosmic recombination and during structure formation, and also provide crucial information for particle physics in the early universe. Magnetic fields with significant energy density could have been produced at the electroweak phase transition. The evolution and survival of magnetic fields produced on sub-horizon scales in the early universe, however, depends on the magnetic helicity which is related to violation of symmetries in fundamental particle interactions. In conclusion, the generation of magnetic helicity requires new CP violating interactions that can be tested by accelerator experiments via decay channels of the Higgs particle.

79 ASTRONOMY AND ASTROPHYSICS↗

Effect of surface roughness on phase transition timing in megaampere pulsed-power–driven exploding conductors

An understanding of material phase transitions in megaampere pulsed-power–driven exploding conductors is important for predicting the growth of hydrodynamic instabilities in magneto-inertial fusion concepts. Here, this study analyzes phase transitions in electrical conductor explosions using 1D Lagrangian and 2D arbitrary Lagrangian–Eulerian resistive magnetohydrodynamic simulations to show that micrometer-scale surface roughness can lead to the electrothermal instability (ETI), a feedback effect that concentrates resistive heating and leads to early melting and ablation. Simulations of the Mykonos electrothermal instability II (METI-II) experiment show melting begins 19% sooner for machined rods with micrometer-scale surface roughness than for rods without these features. The surface magnetic field is 41 T around the initial region of melt, representing a lower magnitude than both the 86 T from 1D simulations and the 85 T threshold reported elsewhere. In 2D simulations with micrometer-scale surface roughness, temperature measurements indicate the critical point temperature of aluminum is reached 17% faster in comparison with 1D simulations. Values from 2D simulations with surface roughness align with predictions from ETI theory, and the observed temperature redistribution further supports the ETI as an underlying mechanism. Simulation results are validated against experimental photonic Doppler velocimetry data. This study shows 1D simulations are adequate to model conductors with sub-micrometer-scale surface roughness in this high-energy-density regime; however, 2D or 3D simulations are required to capture the full range of physics for accurately describing phase transitions in conductors with micrometer-scale or larger surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

BBN photodisintegration constraints on gravitationally produced vector bosons

Gravitational production of massive particles due to cosmic expansion can be significant during the inflationary and reheating period of the Universe. If the particle also has non-gravitational interactions that do not significantly affect its production, numerous observational probes open up, including cosmological probes. In this work, we focus on the gravitational production of light vector bosons that couple feebly to the Standard Model (SM) particles. Due to the very feeble coupling, the light vector bosons never reach thermal equilibrium, and if the Hubble scale at the end of inflation is above 10 8 GeV, the gravitational production can overwhelm the thermal production via the freeze-in mechanism by many orders of magnitude. As a result, much stronger constraints from the Big Bang Nucleosynthesis (BBN) can be placed on the lifetime and mass of the vector bosons compared to the scenario where only thermal production is considered. As an example, we study the sub-GeV scale dark photons, which couple to the SM only through kinetic mixing, and derive constraints on the mass and kinetic mixing parameter of the dark photon from the photodisintegration effects on the light element abundances relevant at the end of the BBN when the cosmic age was around 10 4 s.

79 ASTRONOMY AND ASTROPHYSICS↗

Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers

Parametric large eddy simulations (LES) of a supersonic lifted hydrogen flame are reported. The emphases are on two aspects: impacts of (1) Lewis number (Lei of the ith species) and (2) turbulent Schmidt and Prandtl numbers (⁠Sc t and Pr t ⁠) on supersonic turbulent flame and flow structures. Five cases are considered: species-specific Le i , Sc t = Sr t = 1.0 (C 0 ); unity Le i , Sc t = Pr t = 1.0 (C 1 ); species-specific Sc t = 0.5, Pr t = 1.0 (C 2 ); species-specific Le i , Sc t = 1.0, Pr t = 0.5 (C 3 ); and species-specific Le i , Sc t = Pr t = 0.5 (C 4 ). Numerical results of instantaneous and/or time-averaged species mole fractions, mixture fraction, heat release rate, flame base location, and mixed modes of premixed and diffusion combustion are compared between cases C 0 and C 1 . Differences in auto-ignition locations and strengths and flame structures and stabilization specify the impacts of Lewis number. They are triggered by different predictions of species mass and thermal diffusions at fuel-coflow and/or coflow-ambient air mixing layers. These differences are rationalized by a scale analysis of mass/thermal diffusion and convection for case C 0 , which suggests the relatively low but non-negligible former against the latter. Cases C 0 and C 2 –C 4 barely see differences in terms of instantaneous and/or time-averaged temperature, velocity, and mixed combustion modes except for further downstream areas where combustion occurs. Both Sc t and Pr t impose less significant influences than Lewis number, as sub-grid scale mass/thermal diffusion is subordinate to its resolved counterpart according to their scale analysis for case C 4 .

42 ENGINEERING↗

Effects of Focused Ion Beam Lithography on La 2– x Sr x CuO 4 Single Crystals

Focused ion beam (FIB) milling is a mask-free lithography technique that allows the precise shaping of 3D materials on the micron and sub-micron scale. The recent discovery of electronic nematicity in La 2–x Sr x CuO 4 (LSCO) thin films triggered the search for the same phenomenon in bulk LSCO crystals. With this motivation, we have systematically explored FIB patterning of bulk LSCO crystals into micro-devices suitable for longitudinal and transverse resistivity measurements. We found that several detrimental factors can affect the result, ultimately compromising the possibility of effectively using FIB milling to fabricate sub-micrometer LSCO devices, especially in the underdoped regime.

36 MATERIALS SCIENCE↗

Interplay of strain and phase evolution of laser powder bed fusion Ti–6Al–4V

While additive manufacturing (AM) provides a method of producing geometrically complex and highly detailed structures, the generation of residual strain in AM processes like laser powder bed fusion (L-PBF) can negatively impact performance-enabling properties. In applications such as orthopedic implants, specific performance windows require optimized microstructures in order to obtain desirable properties from multi-phase alloys like Ti–6Al–4V. This research aims to quantify the microscale origins of strain in L-PBF manufactured Ti–6Al–4V by understanding how strain is distributed at the grain and sub-grain scale, the interplay between phase evolution and strain, and examining post-processing strain relief strategies to control these features. Model spinal cage implants were manufactured from Ti–6Al–4V powder via L-PBF and then subjected to strain relieving heat treatment cycles above and below the Ti–6Al–4V β transus as a function of time and cooling rate. Residual strain was then studied via high resolution electron backscatter diffraction (HR-EBSD), and 2D strain maps with sub-micron resolution were generated for each post-processing state. It was found that macroscale thermal strains decreased with heat treatment time, but additional contributions from phase stabilizing residual strains retained primarily in the α' grains as lattice distortive strain remained. Additionally, the retention of β phase significantly changed the strain and dislocation distribution while reducing overall residual strain. In conclusion, these results were validated and reinforced with 3D mesoscopic micromechanical modeling of strain behavior across simulated microstructures, confirming that the local lattice dilation of α’ martensite is a primary contributor of microscale strain generation and retention in L-PBF Ti–6Al–4V.

36 MATERIALS SCIENCE↗

Restoring Historic Forest Disturbance Frequency Would Partially Mitigate Droughts in the Central Sierra Nevada Mountains

Forest thinning and prescribed fire are expected to improve the climate resilience and water security of forests in the western U.S., but few studies have directly modeled the hydrological effects of multi-decadal landscape-scale forest disturbance. By updating a distributed process-based hydrological model (DHSVM) with vegetation maps from a distributed forest ecosystem model (LANDIS-II), we simulate the water resource impacts of forest management scenarios targeting partial or full restoration of the pre-colonial disturbance return interval in the central Sierra Nevada mountains. In a fully restored disturbance regime that includes fire, thinning, and insect mortality, reservoir inflow increases by 4%–9% total and 8%–14% in dry years. At sub-watershed scales (10–100 km2), thinning dense forests can increase streamflow by >20% in dry years. In a thinner forest, increased understory transpiration compensates for decreased overstory transpiration. Consequentially, 73% of streamflow gains are attributable to decreased overstory rain and snow interception loss. Thinner forests can increase headwater peak flows, but reservoir-scale peak flows are almost exclusively influenced by climate. Uncertainty in future precipitation causes high uncertainty in future water yield, but the additional water yield attributable to forest disturbance is about five times less sensitive to annual precipitation uncertainty. This partial decoupling of the streamflow disturbance response from annual precipitation makes disturbance especially valuable for water supply during dry years. Our study can increase confidence in the water resource benefits of restoring historic forest disturbance frequencies in the central Sierra Nevada mountains, and our modeling framework is widely applicable to other forested mountain landscapes.

Boardman, Eli N. [University of Nevada, Reno, NV (↗

Atomic-scale quantum sensing based on the ultrafast coherence of an H 2 molecule in an STM cavity

A scanning tunneling microscope (STM) combined with a pump-probe femtosecond terahertz (THz) laser can enable coherence measurements of single molecules. We report THz pump-probe measurements that demonstrate quantum sensing based on a hydrogen (H 2 ) molecule in the cavity created with an STM tip near a surface. Atomic-scale spatial and femtosecond temporal resolutions were obtained from this quantum coherence. The H 2 acts as a two-level system, with its coherent superposition exhibiting extreme sensitivity to the applied electric field and the underlying atomic composition of the copper nitride (Cu 2 N) monolayer islands grown on a Cu(100) surface. We acquired time-resolved images of THz rectification of H 2 over Cu 2 N islands for variable pump-probe delay times to visualize the heterogeneity of the chemical environment at sub-angstrom scale.

Science & Technology - Other Topics↗