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At least 73 records · Page 4

Shifts in belowground processes along a temperate forest edge

Abstract Context Forests are increasingly fragmented, and as a result most forests in the United States are within one km of an edge. Edges change environmental conditions of the forest—especially radiation, roughness, temperature, and moisture—that can have consequences for plant productivity and ecosystem functions. However, edge effects on aboveground characteristics of plants and the environment are better understood relative to plant roots and soil in the belowground environment. Objectives Our main objectives were to determine if soil C pools and fluxes are higher at the edge relative to other landscape positions, and to understand how specific belowground processes contribute to bulk differences in pools and fluxes. Methods We measured environmental conditions, live and dead fine root traits, soil chemistry, and soil respiration along a 75 m transect from interior forest to meadow in Gaithersburg, MD. Results We observed differences in the soil chemical, biological and hydrological environment between the forest interior, edge and adjacent meadow. In some cases, the forest edge represented a mid-point in environmental or belowground characteristics between the forest interior and meadow ( e.g. , pH, C-to-N ratio [C:N], live fine root biomass, heterotrophic respiration), likely reflecting the change in litter type and quality associated with the transition from grass to woody species. In other cases, neighboring landscape positions were different from the forest edge, which was drier and had higher dead fine root biomass. Although soil C contents were not significantly different across landscape positions, there was a tendency towards higher average soil C content at the edge relative to other landscape positions, suggesting that increased C loss related to root decay and greater soil respiration at the edge relative to the forest interior may have been offset by increased C gain from high plant productivity and subsequent inputs to soil. Conclusions This research provides insight into how forest edge environments may differ from the interior and how concurrent processes above- and belowground may contribute to those differences.

54 ENVIRONMENTAL SCIENCES↗

Mapping 1D Confined Electromagnetic Edge States in 2D Monolayer Semiconducting MoS 2 Using 4D-STEM

Here, four-dimensional (4D) scanning transmission electron microscopy is used to study the electric fields at the edges of 2D semiconducting monolayer MoS2. Sub-nanometer 1D features in the 2D electric field maps are observed at the outermost region along zigzag edges and also along nanowire MoS-terminated MoS 2 edges. Atomic-scale oscillations are detected in the magnitude of the 1D electromagnetic edge state, with spatial variations that depend on the specific periodic edge reconstructions. Electric field reconstructions, along with integrated differential phase contrast reconstructions, reveal the presence of low Z number atoms terminating many of the uniform edges, which are difficult to detect by annular dark field scanning transmission electron microscopy due to its limited dynamic range. Density functional theory calculations support the formation of periodic 1D edge states and also show that enhancement of the electric field magnitude can occur for some edge terminations. The experimentally observed electric fields at the edges are attributed to the absence of an opposing electric field from a nearest neighbor atom when the electron beam propagates through the 2D monolayer and interacts. These results show the potential of 4D-STEM to map the atomic scale structure and fluctuations of electric fields around edge atoms with different bonding states than bulk atoms in 2D materials, beyond conventional imaging.

2D materials↗

Origin and Suppression of Beam Damage-Induced Oxygen-K Edge Artifact from γ-Al 2 O 3 using Cryo-EELS

Gamma-alumina (γ-Al 2 O 3 ), like other low-Z oxides, is readily damaged when exposed to an electron beam. This typically results in the formation of a characteristic pre-edge peak in the oxygen-K edge of electron energy-loss spectra (EELS) acquired during or after the damage process. This artifact can mask the presence of intrinsic O-K edge fine structure that would reveal chemical properties of the material; therefore, its suppression is key. In this work, we systematically investigate the conditions that give rise to the damage-induced O-K pre-edge peak and show that it can be effectively suppressed by performing EELS experiments at cryogenic (cryo) temperatures. Prolonged exposure of γ-Al 2 O 3 to a focused electron beam results in a hole bored through the sample; this was used as a reproducible beam damage condition. O-K edge EELS spectra were collected from a single-crystal γ-Al 2 O 3 sample both during and after focused 2 electron beam hole drilling, and at room and cryo temperatures, using a monochromated scanning transmission electron microscope (STEM). Furthermore, the characteristic 531 eV pre-edge peak visible in the room temperature EELS spectra was completely suppressed in the cryo-EELS spectra, even in the presence of a visible drilled hole. We then correlated these experimental observations with multiple-scattering EELS simulations to determine the likely atomistic origin of the damage-induced O-K pre-edge peak. The findings indicate that the pre-edge peak is caused primarily by the presence of surface O dimer (O-O) bonds formed during beam damage, and that operating at cryo temperature suppresses the formation of surface O-O bonds, thus preventing formation of the O-K pre-edge peak. Additionally, Al-L 2,3 edge EELS spectra revealed Al loss primarily from tetrahedral sites during hole drilling.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Effect of energetic ions on edge-localized modes in tokamak plasmas

The most efficient and promising operational regime for the International Thermonuclear Experimental Reactor tokamak is the high-confinement mode. In this regime, however, periodic relaxations of the plasma edge can occur. These edge-localized modes pose a threat to the integrity of the fusion device. Here we reveal the strong impact of energetic ions on the spatio-temporal structure of edge-localized modes in tokamaks using nonlinear hybrid kinetic–magnetohydrodynamic simulations. A resonant interaction between the fast ions at the plasma edge and the electromagnetic perturbations from the edge-localized mode leads to an energy and momentum exchange. Energetic ions modify, for example, the amplitude, frequency spectrum and crash timing of edge-localized modes. The simulations reproduce some observations that feature abrupt and large edge-localized mode crashes. The results indicate that, in the International Thermonuclear Experimental Reactor, a strong interaction between the fusion-born alpha particles and ions from neutral beam injection, a main heating and fast particle source, is expected with predicted edge-localized mode perturbations. This work advances the understanding of the physics underlying edge-localized mode crashes in the presence of energetic particles and highlights the importance of including energetic ion kinetic effects in the optimization of edge-localized mode control techniques and regimes that are free of such modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Visualizing interaction-driven restructuring of quantum Hall edge states

Many topological phases host gapless boundary modes that can be dramatically modified by electronic interactions. Even for the long-studied edge modes of quantum Hall phases, forming at the boundaries of two-dimensional (2D) electron systems, the nature of such interaction-induced changes has been elusive. Despite advances made using local probes, key experimental challenges persist: the lack of direct information about the internal structure of edge states on microscopic scales, and complications from edge disorder. Here, we use scanning tunneling microscopy (STM) to image pristine electrostatically defined quantum Hall edge states in graphene with high spatial resolution and demonstrate how correlations dictate the structures of edge channels on both magnetic and atomic length scales. For integer quantum Hall states in the zeroth Landau level, we show that interactions renormalize the edge velocity, dictate the spatial profile for copropagating modes, and induce unexpected edge valley polarization that differ from those of the bulk. While some of our findings can be understood by mean-field theory, others show breakdown of this picture, highlighting the roles of edge fluctuations and inter-channel couplings. We also extend our measurements to spatially resolve the edge state of fractional quantum Hall phases and detect spectroscopic signatures of interactions in this chiral Luttinger liquid. Furthermore, our study establishes STM as a promising tool for exploring edge physics of the rapidly expanding 2D topological phases, including newly realized fractional Chern insulators.

Electronic properties and materials↗

Real-time Implementation of Grid Code Compliant Grid Edge Energy Management System

Integrated distributed energy resources (DER) in a distribution system need to follow grid codes to avoid violations that result in DER/circuit segment disconnection. To comply with grid code requirements at the grid edge level, network constrained grid edge energy management system (EMS) can be deployed. The objective of grid edge EMS is to provide economic solution for active and reactive power DER setpoints at each dispatch interval and ensure voltage regulation to support secure interconnection of the grid edge segment to the distribution system with multiple inverter based DER units. In this work, real-time simulation of grid code compliant grid edge EMS is deployed in a realistic feeder circuit segment. For real-time simulation, communication between the grid edge EMS and DERs is done exploiting IEC 61850-7-420. It enables interoperability among different DERs and grid edge EMS. No prior art has deployed IEC 61850-7-420 GOOSE communication protocol for grid edge EMS. Conversion of IEC 61850 GOOSE messages to Modbus communication protocol is also performed to communicate with grid edge EMS in commodity-off the shelf embedded boards in this work. The real-time simulation in OPAL-RT real-time digital simulator shows the out-performance of grid edge EMS by reducing the voltage violation in the distribution circuit.

Energy management system↗

Evaluating Dynamic Stall-Onset Criteria for Mixed and Trailing-Edge Stall

We evaluate two leading-edge-based dynamic stall-onset criteria (namely, the maximum magnitudes of the leading-edge suction parameter and the boundary enstrophy flux) for mixed and trailing-edge stall. These criteria have been shown to successfully predict the onset of leading-edge stall at Reynolds numbers of [Formula: see text], where the leading-edge suction drops abruptly. However, for mixed/trailing-edge stall, leading-edge suction tends to persist even when there is significant trailing-edge reversed flow and stall is underway, necessitating further investigation into the effectiveness of these criteria. Using wall-resolved large-eddy simulations and the unsteady Reynolds-averaged Navier–Stokes method, we simulate one leading-edge stall and three mixed/trailing-edge stall cases at Reynolds numbers of [Formula: see text] and [Formula: see text]. We contrast the progression of flow features such as trailing-edge separation and vortex formation across different stall types and evaluate the stall-onset criteria relative to critical points in the flow. We find that the criteria nearly coincide with the instance of leading-edge suction collapse and are reached in advance of dynamic stall vortex formation and lift stall for all four cases. We conclude that the two criteria effectively signal dynamic stall onset in cases where the dynamic stall vortex plays a prominent role.

Engineering↗

Optimization of edge bead removal (EBR) process to enhance defect reduction in optical lithography

Defect reduction remains a critical objective in the integrated circuit manufacturing process, particularly within the highly re-entrant lithography modules where minimizing defects is crucial. Defects at the wafer edge can contaminate lithography modules and downstream processing equipment, leading to redistribution onto the wafer surface and adversely affecting overall device yield. A persistent challenge in the resist coating process is the formation of resist edge beads, driven by the strong Van der Waals attraction of excess photoresist (PR) to itself and the underlying substrate. The edge bead removal (EBR) process is a standard cleaning step designed to eliminate these edge beads and prevent potential contamination. Here, in this study, we identify the sources of EBR induced defects and additional EBR process encroachment toward edge patterning during the EBR cleaning process. This study provides a comprehensive study aimed at optimizing the EBR cleaning process to effectively eliminate EBR-induced defects, thereby enhancing overall device yield. Specifically, we identify three primary defects induced by the EBR cleaning process: rainbow-type, finger-shaped, and teardrop-type defects. Our experimental study reveals that in addition to EBR rinse time, PR cast time is crucial parameters contributing to the formation of these defects. By properly optimizing the PR cast time and EBR rinse time, we were able to remove nearly 100 % of dense clusters of defects that were easily visible even at low magnification optical microscopy throughout the wafer edge. We observed that shorter PR casting times shows edge defects caused by inefficient EBR process because of insufficient time for PR to fully settle causing superfluous PR to continue flowing toward wafer edge during EBR clearing step, leading to partial removal of PR at the wafer edge and the formation of rainbow defects. Proper optimization of both PR casting time and EBR chemistries dispense time is essential to resolve these defects, ensuring efficient EBR cleaning process and improved overall device yield.

42 ENGINEERING↗

Atomic Edge-Guided Polyethylene Crystallization on Monolayer Two-Dimensional Materials

In this report we combine an advanced synthesis of two-dimensional (2D) materials (MoSe 2 ) having well-defined atomic edge configurations with ab initio and atomistic molecular dynamics (MD) simulations to study how atomic edges interact with polyethylene (HDPE) chains in a dilute solution assembly process. Our results reveal that Mo-terminated zigzag (Mo-ZZ) edges act as preferred nucleation sites and strongly interact with HDPE chains. The HDPE chains align in parallel with the Mo-ZZ edges and form arrays of lamellae that are perpendicular to the edges. Interestingly, atomic edge configurations are observed to dramatically change such interactions. The crystallization discrepancy at different edges was demonstrated on the same piece of MoSe 2 with different types of edges. The ab initio and MD simulations between n-alkane (n = 5 and 25), a segment of HDPE, and MoSe 2 suggest that the atomic structures of MoSe 2 can affect their interactions with n-alkane chains. Following the Mo-ZZ edge preferred nucleation principle, controlled long-range alignment of HDPE lamellae can be realized by creating multilayer MoSe 2 with parallel atomic steps. This research opens a pathway toward an atomic level understanding of polymer–2D nanomaterial interactions. It also bridges the gap between atomic-level and long-range mesoscopic structures and introduces a novel strategy for long-range structural control.

36 MATERIALS SCIENCE↗

Electrode biasing maintains the edge shear layer at high density in the J-TEXT tokamak

Collapse of the edge flow shear as the line-averaged density approaches the Greenwald density limit has been observed as a precursor to the enhanced edge particle flux characteristic of proximity to the density limit regime. Here, we report the use of a biased electrode to sustain the edge shear layer in high density discharges, in which the shear layer would otherwise collapse. A stable increase in line-averaged density is observed along with a strong increase in edge density. These experiments were carried out on the J-TEXT tokamak. The Reynolds stress at the edge is enhanced, and the zonal flow sustained, while density perturbation levels, the flux of turbulence internal energy (i.e., turbulence spreading), and particle and heat flux all decrease significantly. Electron adiabaticity increases, and bias voltage modulation experiments show that an increase in the edge shear leads the increase in adiabaticity. Furthermore, these results suggest that external edge E × B flow shear drive may be of interest for sustaining edge plasma states at high density, and support the hypothesis that collapse of the edge shear layer triggers the onset of the strong transport and turbulence characteristic of the density limit regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnetic multilayer edges in Bernal-stacked hexagonal boron nitride

Single-layer h-BN is known to have edges with unique magnetism; however, in the commonly fabricated multilayer AA'-h-BN, edge relaxations occur that create interlayer bonds and eliminate the unpaired electrons at the edge. Recently, a robust method of growing the unconventional Bernal-stacked h-BN (AB-h-BN) has been reported. Here, we use theoretical approaches to investigate the nitrogen-terminated zigzag edges in AB-h-BN that can be formed in a controlled fashion using a high-energy electron beam. We find that these "open"edges remain intact in bilayer and multilayer AB-h-BN, enabling researchers potentially to investigate these edge states experimentally. We also investigate the thermodynamics of the spin configurations at the edge by constructing a lattice model that is based on parameters extracted from a set of first-principles calculations. We find that the edge spins in neighboring layers interact very weakly, resulting in a sequence of independent spin chains in multilayer samples. By solving this model using Monte Carlo simulations, we can determine nm-scale correlation lengths at liquid-N 2 temperatures and lower. At low temperatures, these edges may be utilized in magnetoresistance and spintronics applications.

1-dimensional spin chains↗

Habitat specialization and edge effects of soil microbial communities in a fragmented landscape

Abstract Soil microorganisms play outsized roles in nutrient cycling, plant health, and climate regulation. Despite their importance, we have a limited understanding of how soil microbes are affected by habitat fragmentation, including their responses to conditions at fragment edges, or “edge effects.” To understand the responses of soil communities to edge effects, we analyzed the distributions of soil bacteria, archaea, and fungi in an experimentally fragmented system of open patches embedded within a forest matrix. In addition, we identified taxa that consistently differed among patch, edge, or matrix habitats (“specialists”) and taxa that showed no habitat preference (“nonspecialists”). We hypothesized that microbial community turnover would be most pronounced at the edge between habitats. We also hypothesized that specialist fungi would be more likely to be mycorrhizal than nonspecialist fungi because mycorrhizae should be affected more by different plant hosts among habitats, whereas specialist prokaryotes would have smaller genomes (indicating reduced metabolic versatility) and be less likely to be able to sporulate than nonspecialist prokaryotes. Across all replicate sites, the matrix and patch soils harbored distinct microbial communities. However, sites where the contrasts in vegetation and pH between the patch and matrix were most pronounced exhibited larger differences between patch and matrix communities and tended to have edge communities that differed from those in the patch and forest. There were similar numbers of patch and matrix specialists, but very few edge specialist taxa. Acidobacteria and ectomycorrhizae were more likely to be forest specialists, while Chloroflexi, Ascomycota, and Glomeromycota (i.e., arbuscular mycorrhizae) were more likely to be patch specialists. Contrary to our hypotheses, nonspecialist bacteria were not more likely than specialist bacteria to have larger genomes or to be spore‐formers. We found partial support for our mycorrhizal hypothesis: arbuscular mycorrhizae, but not ectomycorrhizae, were more likely to be specialists. Overall, our results indicate that soil microbial communities are sensitive to edges, but not all taxa are equally affected, with arbuscular mycorrhizae in particular showing a strong response to habitat edges. In the context of increasing habitat fragmentation worldwide, our results can help inform efforts to maintain the structure and functioning of the soil microbiome.

Winfrey, Claire C. [Department of Ecology and Evol↗

Tuning Electronic Properties of 2D Materials Using Metal Adsorbates: Cu at WTe 2 Edges

Two-dimensional materials exhibit properties promising for novel applications. Topologically protected states at their edges can be harnessed for use in quantum devices. We use ab initio simulations to examine properties of edges in 1T'-WTe 2 monolayers, known to exhibit topological order, and their interactions with Cu atoms. Comparison of (010)-oriented edges that have the same composition but different terminations shows that, as the number of Cu atoms increases, their thermodynamically-preferred arrangement depends on the details of the edge structure. Cu atoms aggregate into a cluster at the most stable edge; while the cluster is non-magnetic, it spin-polarizes the W atoms along the edge, which removes the topological protection. At the metastable edge, Cu atoms form a chain incorporated into the WTe 2 lattice; the topological state is preserved in spite of the dramatic edge restructuring. This suggests that exploiting interactions of metal species with metastable edge terminations can provide a path towards non-invasive interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗

Edge counts for the auxiliary pair graph within the graphical unitary group approach

Closed-form expressions are presented for the numbers of edges in the auxiliary pair graphs (APGs) associated with non spin-orbit and spin-orbit Shavitt graphs for full configuration interaction expansions. A Shavitt graph is a visual representation of a configuration state function expansion space constructed via the graphical unitary group approach (GUGA). An APG is an organisational aid and a programmatic tool generated from a Shavitt graph. The number of edges in an APG determines bounds on the computational scaling as a function of the total numbers of electrons, orbitals, and spin multiplicities. The edge counts extend a suite of Shavitt graph statistics based on these functional parameters. The derivation and the presentation of the formulas for the edge counts has been assisted by the bra-ket interchange symmetry and the particle-hole interchange symmetry in the GUGA formalism. Furthermore, these symmetry operators produce one-to-one correspondences between various sets of edges, and this yields identities among some edge count formulas. There are 208 possible edge types. Of these, some do not contribute to two-electron operators, some are related by bra-ket interchange symmetry, and some are related by particle-hole interchange symmetry. For the remaining unique edge types, explicit expressions are derived for the numbers of edges.

74 ATOMIC AND MOLECULAR PHYSICS↗

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗

Edge-driven transition between extended quantum anomalous Hall crystal and fractional Chern insulator in rhombohedral graphene multilayers

Fractional Chern insulators (FCI) with fractionally quantized Hall conductance at fractional fillings and an extended quantum anomalous Hall (EQAH) crystal with an integer quantized Hall conductance over an extended region of doping were recently observed in pentalayer graphene. One particularly puzzling observation is the transition between the EQAH and FCI regimes, driven either by temperature or electrical current. Here, in this study, we propose a scenario to understand these transitions based on the topologically protected gapless edge modes that are present in both the FCI and EQAH phases and should be most relevant at temperature scales below the energy gap. Our consideration is based on the simple assumption that the edge velocity in FCI is smaller than that in EQAHE and thus contributes to a higher entropy. We further argue that domains with opposite fractionally quantized Hall conductance are ubiquitous in the devices due to disorder, which gives rise to a network of edge modes. The velocity of the edge modes between domains is further reduced due to edge reconstruction. The edge velocity can also be reduced by current when the occupation of the edge mode approaches the gap edge. The edge entropy therefore drives the transition from EQAH to FCI either by temperature or current at a nonzero temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

ECAR-5067 Computational Evaluation on Effect of Edge-rounding in Circular to Annular Flow Transitions within a Hexagonal Duct

In this ECAR, the computational fluid dynamics (CFD) simulation of the duct with a cross-section varying from circle to annulus was performed to evaluate the effect of edge-rounding of the internal edges. The edge of circular channel and the edge of inner annular channel were rounded with the radius of curvature ranged from 0 mm to 20 mm. The CFD results show that the pressure loss of the duct can be reduced by increasing the radius of the rounded edge. Case-A results showed that the pressure drop can be significantly reduced by the edge-rounding, e.g., the pressure drop was reduced approximately 56% by the radius of curvature of 5.0mm, and reduced 70% by the radius of curvature of 20.0 mm although its effectiveness would be attenuated as the radius of curvature of edge increases. Results from Case-B showed the impact of rounding the inlet edge was practically negligible compared to the outlet edge. This ECAR could provide a guideline to determine the optimum inlet module design of the VTR fuel rod bundle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗