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At least 883 records · Page 49

Impact of collisionality on turbulence in the edge of tokamak plasma using 3D global simulations

Collisionality is one of the key parameters in determining turbulent transport in the plasma edge, regulating phenomena such as 'shoulder formation', separation of scale lengths in the scrape-off layer (SOL), turbulence damping and zonal flow dynamics. Understanding its role is therefore of primary importance for future reactors like ITER. Getting reliable predictions and a better characterization of plasma flow properties when varying collisionality remains, however, a critical challenge for the simulations. This paper focuses on the impact of varying collisionality in a non-isothermal three-dimensional fluid model of the plasma edge. A high field side limited configuration encompassing open and closed magnetic field lines with parameters typical of a medium-sized tokamak is considered. The present model can consistently account for the variations of collisionality and its impact on both the parallel resistivity η ∥ and the ion and electron parallel thermal conductivities χ ∥e,i . Details on mean flow and turbulence properties are given. Changing collisionality leads to significant changes in the flow properties both on the mean and fluctuating quantities. In particular, lowering collisionality decreases the size of coherent structures, the fluctuation levels of turbulence, and steepens the density and temperature equilibrium profiles around the separatrix leading to a global reduction of the turbulent transport. The SOL width is observed to increase with collisionality, eventually resulting in the disappearance of the scale lengths separation between near and far SOL, consistently with previous experimental observations. At low collisionality, where the presence of narrow feature is well-established, a contribution of heat conduction increases up to compete with heat convection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The fungal collaboration gradient dominates the root economics space in plants

Plant economics run on carbon and nutrients instead of money. Leaf strategies aboveground span an economic spectrum from “live fast and die young” to “slow and steady,” but the economy defined by root strategies belowground remains unclear. Here, we take a holistic view of the belowground economy and show that root-mycorrhizal collaboration can short circuit a one-dimensional economic spectrum, providing an entire space of economic possibilities. Root trait data from 1810 species across the globe confirm a classical fast-slow “conservation” gradient but show that most variation is explained by an orthogonal “collaboration” gradient, ranging from “do-it-yourself” resource uptake to “outsourcing” of resource uptake to mycorrhizal fungi. This broadened “root economics space” provides a solid foundation for predictive understanding of belowground responses to changing environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling and simulation of gas separations with spiral–wound membranes

Models for gas separations with spiral–wound membranes are developed and found to exhibit good agreement with experiments performed on N 2 /O 2 mixtures. The two–dimensional (2D) model can be accurately approximated by a one–dimensional (1D) surrogate model when the spacer widths are chosen to make the channel pressure drops small. Subsequently, the separation of propane/propylene mixtures from the recycle purge stream of a polypropylene reactor is investigated. Assuming ideal gas is found to lead to significant overestimations in membrane stage cuts (sometimes more than 10%), an extent comparable to that associated with extrapolating constant olefin permeance from a low–pressure condition. While olefin permeance can change significantly with pressure, using a constant–permeance formulation can result in a small (< 2.5%) underprediction in stage cut if the value for the permeance is taken from the feed condition. Finally, membrane properties and costs necessary for a viable separation process are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scaling CFB risers: Maintaining microstructure dynamics

Over the years there have been numerous approaches to develop a scaleup methodology for circulating fluidized beds. Many of these past approaches have relied on macroscopic definitions of similitude to define dimensionless groups such as Reynolds number, Froude number, density ratios, and dimensional ratios involving different length scales. These approaches have demonstrated various levels of success, but often fail when used outside the bounds of experimental datasets. The issue with these methods is that they rely on macroscopic similitude with the hopes that those conditions would provide microscopic similitude as it does in single phase systems where the Buckingham Pi techniques have given reasonable success. Two of the main reasons for failure are 1) changing fluidization regimes and 2) changing material properties that result in the material falling into a different Geldart group. Both are certain to change the microstructure (local instantaneous volume solids fraction) and changes to the microstructure affect the interphase transport properties of the reactor system, namely the mass transfer and heat transfer. Here, this work presents a new approach towards scaling based upon maintaining similitude at the microscale. It reviews a novel dimensionless flow regime map developed from analysis of the deterministic chaos parameters and higher order moments to ensure microstructure similitude. The work then examines four cases from the literature to assess the scaling approach used: (1) same particle-different scale risers for Geldart Group B particles, (2) Glicksman scaling of atmospheric circulating fluidized bed combustor, (3) same particle-different scale risers for Geldart Group A particles and (4) Glicksman scaling for pressurized gasification. General findings are that none of the scaling approaches produced directly applicable microstructure similar behavior based upon the chaotic and higher moment analysis. The positive take away is that the approach can define scale conditions that will provide similar microstructure that can be us to predict transport behavior.

42 ENGINEERING↗

Thermal Stability of Quasi-1D NbS 3 Nanoribbons and Their Transformation to 2D NbS 2 : Insights from in Situ Electron Microscopy and Spectroscopy

Here in situ electron microscopy imaging and spectroscopy enabled us to study the evolution of quasi-1D NbS 3 -IV nanoribbons with respect to morphology and chemical structure at temperatures between room temperature and 1000 °C. Scanning transmission electron microscopy (STEM) experiments included imaging in the secondary electron, (transmitted) bright field, and high-angle annular dark-field modes while operating in the low kV regime. The results showed that NbS 3 -IV samples transform dramatically from smooth nanoribbons into highly textured configurations featuring polyhedral divots and steps. Similar in situ heating experiments conducted with aberration-corrected STEM revealed that bilayers of NbS 3 -IV chains convert topotactically into aligned 2H-NbS 2 sheets upon loss of sulfur. Atomic resolution imaging, fast Fourier transform analysis, and electron energy loss spectroscopy confirmed these chemical changes, from which we propose an atomistic mechanism for the NbS 3 -IV → 2H-NbS 2 conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tortuosity Engineering for Improved Charge Storage Kinetics in High-Areal-Capacity Battery Electrodes

The increasing demands of electronic devices and electric transportation necessitate lithium-ion batteries with simultaneous high energy and power capabilities. However, rate capabilities are often limited in high-loading electrodes due to the lengthy and tortuous ion transport paths with their electrochemical behaviors governed by complicated electrode architectures still elusive. Here, we report the electrode-level tortuosity engineering design enabling improved charge storage kinetics in high-energy electrodes. Both high areal capacity and high-rate capability can be achieved beyond the practical level of mass loadings in electrodes with vertically oriented architectures. The electrochemical properties in electrodes with various architectures were quantitatively investigated through correlating the characteristic time with tortuosity. The lithium-ion transport kinetics regulated by electrode architectures was further studied via combining the three-dimensional electrode architecture visualization and simulation. Finally, the tortuosity-controlled charge storage kinetics revealed in this study can be extended to general electrode systems and provide useful design consideration for next-generation high-energy/power batteries.

25 ENERGY STORAGE↗

Heteroatom-Doped Graphenes as Actively Interacting 2D Encapsulation Media for Mg-Based Hydrogen Storage

Nanoencapsulation using graphene derivatives enables the facile fabrication of two-dimensional (2D) nanocomposites with unique microstructures and has been generally applied to many fields of energy materials. Particularly, metal hydrides such as MgH 2 encapsulated by graphene derivatives have emerged as a promising hybrid material for overcoming the disadvantageous properties of Mg-based hydrogen storage. Although the behavior of the graphene–Mg nanoencapsulation interface has been studied for many composite materials, the direct modification of graphene with nonmetal foreign elements for changing the interfacial behavior has been limitedly reported. In this regard, using B-doped graphene and N-doped graphene as nanoencapsulation media for tuning the interfacial behavior of graphene derivative–Mg nanoparticles, we present altered hydrogen storage kinetics of heteroatom-doped (B and N) graphene–Mg composites. The effect of heteroatom doping is studied in terms of bonding configurations and heteroatom doping concentrations. The enhancement in hydrogen uptake was observed for all of the heteroatom-doped graphene–Mg nanocomposites. On the other hand, a few samples exhibit significantly low activation energy at the early stage of desorption, which can be related to the facilitated nucleus formation. Density functional theory calculation indicates that B-doping and N-doping accelerate hydrogen absorption kinetics in different ways, aiding charge transfer and inducing surface deformation of Mg nanoparticles, respectively. Their effects can be augmented in the presence of structural defects on graphene, such as vacancies, pores, or graphene edges. These results demonstrate that hydrogen storage kinetics of Mg-based systems can be altered by utilizing heteroatom-doped graphene oxide derivatives as 2D nanoencapsulation media, suggesting that the addition of a nonmetal doping element can also be applied to Mg-based hydrogen storage by modifying the nanoencapsulation interface without forming Mg alloy phases.

08 HYDROGEN↗

Plasma-based particle sources

High-brightness particle beams generated by advanced accelerator concepts have the potential to become an essential part of future accelerator technology. In particular, high-gradient accelerators can generate and rapidly accelerate particle beams to relativistic energies. The rapid acceleration and strong confining fields can minimize irreversible detrimental effects to the beam brightness that occur at low beam energies, such as emittance growth or pulse elongation caused by space charge forces. Due to the high accelerating gradients, these novel accelerators are also significantly more compact than conventional technology. Advanced accelerators can be extremely variable and are capable of generating particle beams with vastly different properties using the same driver and setup with only modest changes to the interaction parameters. So far, efforts have mainly been focused on the generation of electron beams, but there are concepts to extend the sources to generate spin-polarized electron beams or positron beams. The beam parameters of these particle sources are largely determined by the injection and subsequent acceleration processes. Although, over the last decade there has been significant progress, the sources are still lacking a sufficiently high 6-dimensional (D) phase-space density that includes small transverse emittance, small energy spread and high charge, and operation at high repetition rate. This is required for future particle colliders with a sufficiently high luminosity or for more near-term applications, such as enabling the operation of free-electron lasers (FELs) in the X-ray regime. Major research and development efforts are required to address these limitations in order to realize these approaches for a front-end injector for a future collider or next-generation light sources. In particular, this includes methods to control and manipulate the phase-space and spin degrees-of-freedom of ultrashort plasma-based electron bunches with high accuracy, and methods that increase efficiency and repetition rate. These efforts also include the development of high-resolution diagnostics, such as full 6D phase-space measurements, beam polarimetry and high-fidelity simulation tools. A further increase in beam luminosity can be achieve through emittance damping. Emittance cooling via the emission of synchrotron radiation using current technology requires kilometer-scale damping rings. For future colliders, the damping rings might be replaced by a substantially more compact plasma-based approach. Here, plasma wigglers with significantly stronger magnetic fields are used instead of permanent-magnet based wigglers to achieve similar damping performance but over a two orders of magnitude reduced length.

43 PARTICLE ACCELERATORS↗

Distinguishing isotropic and anisotropic signals for X-ray total scattering using machine learning

Understanding structure–property relationships is essential for advancing technologies based on thin films. X-ray pair distribution function (PDF) analysis can access relevant atomic structure details spanning local-, mid- and long-range structure. While X-ray PDF has been adapted for thin films on amorphous substrates, measurements on single-crystal substrates are necessary to accurately determine structure origins for some thin film materials, especially those for which the substrate changes the accessible structure and properties. However, when measuring films on single-crystal substrates, high-intensity anisotropic Bragg spots saturate 2D detector images, overshadowing the thin films' isotropic scattering signal. This renders previous data processing methods for films on amorphous substrates unsuitable for films on single-crystal substrates. To address this measurement need, we developed IsoDAT2D, an innovative data processing approach using unsupervised machine learning algorithms. The program combines dimensionality reduction and clustering algorithms to separate thin film and single-crystal substrate X-ray scattering signals. We use SimDAT2D , a program we developed to generate simulated thin film data, to validate IsoDAT2D . Here we also use IsoDAT2D to isolate X-ray total scattering signal from a thin film on a single-crystal substrate. The resulting PDF data are compared with similar data processed using previous methods, especially substrate subtraction for single-crystal and amorphous substrates. PDF data from IsoDAT2D -identified X-ray total scattering data are significantly better than from single-crystal substrate subtraction, but not as reliable as PDF data from amorphous substrate subtraction. With IsoDAT2D , there are new opportunities to expand PDF to a wider variety of thin films, including those on single-crystal substrates, with which new structure–property relationships can be elucidated to enable fundamental understanding and technological advances.

36 MATERIALS SCIENCE↗

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of ~4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics. Similar content being viewed by others

60 APPLIED LIFE SCIENCES↗

A new track finding algorithm based on a multi-dimensional extension of the Hough Transform

We introduce a new pattern recognition algorithm for track finding in High Energy Physics Experiments based on an extension of the Hough Transform to multiple dimensions. A remarkable property of this algorithm is that the execution time is simply proportional to the total number of the hits to be processed, making it particularly attractive for high occupancy situations. The algorithm needs to be trained using a sufficiently large set of simulated tracks. The same track finding algorithm can be used for very different detector geometries and only the set of simulated tracks used for training needs to be changed. The particular structure of the algorithm also lends itself naturally to parallel hardware implementations which, combined with its intrinsic flexibility, should provide a most powerful tool for triggering at future colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Site-specific nanoscale characterization of zirconium hydrides in the hydride rim structure of hydrogen-charged zircaloy-4 cladding

Zircaloy-4 cladding tubes were hydrogen-charged using a static pressure hydrogen charging method to experimentally produce a zirconium-hydride rim structure similar to that observed in Zircaloy-4 cladding tubes after operation in commercial light-water nuclear reactors. Detailed characterization was performed using electron energy loss spectroscopy (EELS) and four-dimensional scanning transmission electron microscopy (4D-STEM). By mapping the position of the plasmon peak in the low-loss EELS spectrum, it was determined that the zirconium hydrides formed were predominantly solid δ-phase zirconium hydrides. 4D-STEM was used to generate phase and strain maps at nanoscale. The interactions between two zirconium hydride platelets less than 200 nm apart leads to the localized lattice rotations and possible phase change, revealing a potential hydride growth mechanism.

4D-STEM↗

Probing the In Situ Pseudocapacitive Charge Storage in Ti 3 C 2 MXene Thin Films with X-ray Reflectivity

MXenes are a large family of two-dimensional materials that are attractive for energy storage due to their high-rate charging capabilities as well as for electrochemical actuators, water purification, and many other technologies. Ion intercalation during electrochemically driven charge and discharge processes is the fundamental process associated with MXene functionality, which we have characterized here using in situ and operando X-ray reflectivity (XRR). Experiments performed at the Advanced Photon Source at Argonne National Laboratory monitored the changes in the structure of a Ti 3 C 2 MXene film on a platinum current collector as a function of static applied potential between 0.3 and –0.7 V vs Ag/AgCl in an aqueous 0.1 M Li 2 SO 4 electrolyte. Negative potential sweeps lead to a contraction of 1.2 Å in the interlayer spacing and a loss of electron density between the layers, likely due to Li + ion insertion and water removal. The change in lattice spacing includes a continuous variation vs potential as well as an additional discrete contraction that occurs near –0.35 V that has the characteristics of a first-order transition. The continuous change in the MXene interlayer spacing is associated with the capacitive charge, while the discrete change in structure correlated to the weak feature in the cyclic voltammogram at –0.35 V can be interpreted as either a pseudocapacitive charging process or a potential-dependent change in capacity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Topological Data Analysis for Particulate Gels

Soft gels, formed via the self-assembly of particulate materials, exhibit intricate multiscale structures that provide them with flexibility and resilience when subjected to external stresses. Here, this work combines particle simulations and topological data analysis (TDA) to characterize the complex multiscale structure of soft gels. Our TDA analysis focuses on the use of the Euler characteristic, which is an interpretable and computationally scalable topological descriptor that is combined with filtration operations to obtain information on the geometric (local) and topological (global) structure of soft gels. We reduce the topological information obtained with TDA using principal component analysis (PCA) and show that this provides an informative low-dimensional representation of the gel structure. We use the proposed computational framework to investigate the influence of gel preparation (e.g., quench rate, volume fraction) on soft gel structure and to explore dynamic deformations that emerge under oscillatory shear in various response regimes (linear, nonlinear, and flow). Our analysis provides evidence of the existence of hierarchical structures in soft gels, which are not easily identifiable otherwise. Moreover, our analysis reveals direct correlations between topological changes of the gel structure under deformation and mechanical phenomena distinctive of gel materials, such as stiffening and yielding. In summary, we show that TDA facilitates the mathematical representation, quantification, and analysis of soft gel structures, extending traditional network analysis methods to capture both local and global organization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Superlattice reflection signatures of the insulator–metal transition in V 3 O 5 thin films

Nanoelectronic systems that are inspired by the brain are increasingly looking to insulator–metal transition (IMT) materials as they can mimic the response characteristics of neurons to temperature changes so that these can be used in robotic and computational applications. V 3 O 5 has an insulator–metal transition at ∼430 or ∼80 K higher than VO 2 and provides a unique high-temperature opportunity for these types of applications. Here, in this work, we track the structural evolution of V 3 O 5 thin films across the IMT through conventional selected-area electron diffraction (SAED) and four-dimensional scanning TEM (4D-STEM), correlated with temperature-dependent resistance measurements. SAED patterns show reversible evidence of superlattice reflections associated with the IMT—present below T IMT and absent above it—consistent with the accompanying drop in resistance. At room temperature, nanobeam electron diffraction patterns further reveal three local configurations: (i) type I regions with clean patterns lacking superlattice reflections and spot splitting; (ii) type II regions exhibiting rows of superlattice reflections and split spots indicative of crystallographic variants; and (iii) type III regions with negligible superlattice reflections but larger spot splitting suggestive of overlapping domains of insulating and conducting phases likely driven by local lattice distortions. Upon heating, the superlattice reflections disappear between 413 and 453 K, concurrent with the resistance drop at T IMT , consistent with the emergence of a conducting phase. The overall diffraction geometry remains essentially unchanged up to 573 K, implying that relative domain orientations persist through the transition. These observations reveal nanoscale structural heterogeneity in V 3 O 5 thin films across the IMT and inform operation in regimes where mixed-phase textures are expected. A plausible indexing framework rationalizing the observed geometries is presented in the Discussion section, alongside its limitations and alternative interpretations.

25 ENERGY STORAGE↗

Direct recovery of interfacial topography from coherent X-ray reflectivity: model calculations for a 1D interface

The use of coherent X-ray reflectivity to recover interfacial topography is described using model calculations for a one-dimensional interface. The results reveal that the illuminated topography can be recovered directly from the measured reflected intensities. This is achieved through an analysis of the Patterson function, the Fourier transform of the scattering intensity (as a function of lateral momentum transfer, Q // , at fixed vertical momentum transfer, Q z ). Specifically, a second-order Patterson function is defined that reveals the discrete set of separations and contrast factors (i.e., the product of changes in the effective scattering factor) associated with discontinuities in the effective interfacial topography. Finally, it is shown that the topography is significantly over-determined by the measurements, and an algorithm is described that recovers the actual topography through a deterministic sorting of this information.

36 MATERIALS SCIENCE↗

ENSO-Induced Teleconnection: Process-Oriented Diagnostics to Assess Rossby Wave Sources and Ambient Flow Properties in Climate Models

Climate model fidelity in representing ENSO-induced teleconnection is assessed with process-oriented diagnostics that examine a chain of processes, from equatorial Pacific precipitation to the midlatitude circulation pattern over the Pacific–North American regions. Such processes are rarely addressed during model development. Using an upper-tropospheric divergent level, local vorticity gradient of the ambient zonal flow (∂ 2 U¯/∂y 2 ) and a restoring force for Rossby waves (β * ) are estimated, the equivalent barotropic vorticity equation is solved, and an anomalous Rossby wave source (RWS') quantified. The analysis is applied to AMIP5 and AMIP6 simulations. For a realistic circulation response representation, the hypothesis that models accurately represent the strength and location of RWS', and spatial variations in β * is tested. Compared to AMIP5, in AMIP6 there are clear improvements in representing RWS' and β * . To validate the hypothesis, the analysis identifies two metrics: spatially coherent RWS' in the subtropical North Pacific, and longitudes of negative β * over the western-central North Pacific. By projecting these metrics in two and three-dimensional views, improvements or degradations in model versions are apparent. If a model’s fidelity in representing ∂ 2 U¯/∂y 2 and RWS' are compromised, then radiated Rossby waves are reflected more equatorward, resulting in zonally elongated circulation anomalies over the central North Pacific. Thus, during climate model development, applying this analysis frequently will keep a regular check on the fidelity of the modeled response to anomalous El Niño convection in conjunction with changing model ambient flow dependencies. As a result, this analysis is intended to form a process-oriented diagnostics package, a community contribution to the NOAA Model Diagnostics Task Force.

54 ENVIRONMENTAL SCIENCES↗

Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model

Abstract. Lakes in the Arctic are important reservoirs of heat with much lower albedo in summer and greater absorption of solar radiation than surrounding tundra vegetation. In the winter, lakes that do not freeze to their bed have a mean annual bed temperature >0 ∘C in an otherwise frozen landscape. Under climate warming scenarios, we expect Arctic lakes to accelerate thawing of underlying permafrost due to warming water temperatures in the summer and winter. Previous studies of Arctic lakes have focused on ice cover and thickness, the ice decay process, catchment hydrology, lake water balance, and eddy covariance measurements, but little work has been done in the Arctic to model lake heat balance. We applied the LAKE 2.0 model to simulate water temperatures in three Arctic lakes in northern Alaska over several years and tested the sensitivity of the model to several perturbations of input meteorological variables (precipitation, shortwave radiation, and air temperature) and several model parameters (water vertical resolution, sediment vertical resolution, depth of soil column, and temporal resolution). The LAKE 2.0 model is a one-dimensional model that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated modeled water temperatures with data of observed lake water temperatures at several depths over several years for each lake. Our validation of the LAKE 2.0 model is a necessary step toward modeling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. The sensitivity analysis shows us that lake water temperature is not highly sensitive to small changes in air temperature or precipitation, while changes in shortwave radiation and large changes in precipitation produced larger effects. Snow depth and lake ice strongly affect water temperatures during the frozen season, which dominates the annual thermal regime of Arctic lakes. These findings suggest that reductions in lake ice thickness and duration could lead to more heat storage by lakes and enhanced permafrost degradation.

Clark, Jason A. (ORCID:0000000248105261)↗