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At least 757 records · Page 42

Impact of Resonant Magnetic Perturbations on the Toroidal Location of the Runaway Electron Final Loss Strike Point

It is demonstrated that the peak toroidal impact phase of the post-disruption runaway electrons (REs) can be varied shot-to-shot by means of applied static non-axisymmetric (3D) magnetic fields, or resonant magnetic perturbations (RMPs). In the experiments, high-current (500 kA), purged RE plateaus (i.e. low impurity post-disruption plasmas with current carried completely by REs) were terminated on the DIII-D tokamak center post (CP). The global toroidal impact peak of the REs appears to be dominantly set by the toroidal phase of a wall-locked tearing mode, typically (m/n) = (2/1), but sometimes (m/n) = (3/2). In the absence of external RMP, the locked mode reliably locks close to a preferred toroidal phase Φ ≃ 75◦ probably set by intrinsic error fields. With applied RMP, the locked mode and RE impact phase is pushed to a new location. When the tearing mode is (m/n) = (2/1), the phase is well controlled and tracks the applied RMP phase, but in the case of an (m/n) = (3/2) tearing mode, the new phase location is not well controlled. These results could have application in ITER and other fusion power plant (FPP) - sized tokamaks as a method for spreading disruption first wall damage from REs

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The restricted three-body problem including radiation pressure

The force of radiation pressure is included in the restricted three-body problem by considering the major radial components of the pressure force for the case of a particle in the vicinity of two luminous massive bodies, as well as by introducing the Poynting-Robertson effect for the case of one luminous body. The positions of the Lagrangian points L4 and L5 are found as functions of the ratio of radiation to gravitational forces. The Poynting-Robertson effect renders the L4 and L5 points unstable on a time scale that is long compared to the period of rotation of the two massive bodies. Implications for space colonization and a mechanism for producing azimuthal asymmetries in the interplanetary dust complex are discussed.

Schuerman, D. W.↗

All-Electric Nonassociative Learning in Nickel Oxide

Habituation and sensitization represent nonassociative learning mechanisms in both non-neural and neural organisms. They are essential for a range of functions from survival to adaptation in dynamic environments. Design of hardware for neuroinspired computing strives to emulate such features driven by electric bias and can also be incorporated into neural network algorithms. Herein, cellular-like learning in oxygen-deficient NiO x devices is demonstrated. Both habituation learning and sensitization response can be achieved in a single device by simply controlling the magnitude of the electric field. Spontaneous memory relaxations and dynamic redistribution of oxygen vacancies under electric bias enable such learning behavior of NiO x under sequential training. These characteristics in simple device arrays are implemented to learn alphabets as well as demonstrate simulated algorithmic use cases in digit recognition. Transition metal oxides with carefully prepared defect concentrations can be highly sensitive to electronic structure perturbations under moderate electrical stimulus and serve as building blocks for next-generation neuroinspired computing hardware.

36 MATERIALS SCIENCE↗

A scalable compressible volume of fluid solver using a stratified flow model

Here, in this paper, a Volume of Fluid method which uses a Stratified Flow model for flux calculation is proposed to solve a compressible multiphase flow in a way that has high parallel efficiency. The solver is part of an open-source computing tool to study fuel entrainment and combustion in the application of paraffin-based hybrid rocket motors. This paper focuses on the compressible Volume of Fluid solver for the liquid and gaseous phases in this environment. This solver uses perfect gas and stiffened gas models for equation of state, with the ability to easily add other models as desired. Additionally a comparison of a Riemann solver versus an AUSM+up scheme is conducted, showing improvement with the later in the solution of multiphase flows. This solver successfully reproduces shock tube cases with the expected accuracy, as well as simulating two-dimensional shear and gravity-driven flows. Results also show that the code is able to utilize a Stratified Flow model to evaluate shear flow without the need for interface reconstruction or gradient calculations. Finally, it is shown that the solver has near-ideal scaling under strong scaling tests as well as good performance in static scaling, giving improved performance over current options and implying future advancement of high-performance computing efficiency for multiphase flow solvers.

97 MATHEMATICS AND COMPUTING↗

Tau-jet signatures of vectorlike quark decays to heavy charged and neutral Higgs bosons

We study 4 b + 2 τ and 4 b + 1 τ signatures of heavy neutral and charged Higgs bosons originating from cascade decays of pair-produced new quarks. Decays of vectorlike quarks through heavy Higgses can easily dominate in the two Higgs doublet model of type-II, and the studied signatures are common to many possible decay chains. We design search strategies for these final states and discuss the mass ranges of heavy Higgs bosons and new quarks that can be explored at the Large Hadron Collider as functions of branching ratios in a model independent way. We further combine the results with a similar study focusing on decays which lead to a 6 b final state and interpret the sensitivity to charged and neutral Higgs bosons and vectorlike quarks in the type-II two Higgs doublet model. We find that the LHC reach for their masses extends to well above 2 TeV in the case of an SU(2) doublet quark and to at least 1.8 TeV for a bottom-like SU(2) singlet quark in the whole range of tan β between 1 and 50.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

GraphTango: A Hybrid Representation Format for Efficient Streaming Graph Updates and Analysis

Abstract Streaming graph processing performs batched updates and analytics on a time-evolving graph. The underlying representation format of the graph largely determines the throughputs of these updates and analytics phases. Existing representation formats usually employ variations of hash tables or adjacency lists. However, a recent study showed that the adjacency-list-based approaches perform poorly on heavy-tailed graphs, and the hash table-based approaches suffer on short-tailed graphs. We propose GraphTango, a hybrid representation format that provides excellent update and analytics throughput regardless of the graph’s degree distribution. GraphTango dynamically switches among three different formats based on a vertex’s degree: (i) Low-degree vertices store the edges directly with the neighborhood metadata, confining accesses to a single cache line, (2) Medium-degree vertices use adjacency lists, and (3) High-degree vertices use hash tables as well as adjacency lists. In this case, the adjacency list provides fast traversal during the analytics phase, while the hash table provides constant-time lookups during the update phase. We further optimized the performance by designing an open-addressing-based hash table that fully utilizes every fetched cache line. In addition, we developed a thread-local lock-free memory pool that allows fast growing/shrinking of the adjacency lists and hash tables in a multi-threaded environment. We evaluated GraphTango with the help of the SAGA-Bench framework and compared it with four other representation formats: Stinger, Degree-aware Robin Hood Hashing, and two adjacency list-based formats with different workload balancing scheme. On average, GraphTango provides 4.5x higher insertion throughput, 3.2x higher deletion throughput, and 1.1x higher analytics throughput over the next best format. Furthermore, we integrated GraphTango with the state-of-the-art graph processing frameworks DZiG and RisGraph. Compared to the vanilla DZiG and vanilla RisGraph , [ GraphTango + DZiG ] and [ GraphTango + RisGraph ] reduces the average batch processing time by 2.3x and 1.5x, respectively.

Ahmed, Alif↗

Decarbonization scenarios of the U.S. Electricity system and their costs

Decarbonizing the electricity system to zero-carbon emission is crucial for climate change mitigation. Previous studies have shown that such a transition in the United States (U.S.) may lead to higher system cost compared to a business-as-usual case, but it is not well-known how the cost of electricity generation varies at sub-regional level under the transition, and studies have rarely evaluated the trade-off between the cost and avoided climate damages, as well as the potential roles of negative emission technologies (NETs) in the electricity decarbonization. In this work, we present a regionally resolved national model to quantify the cost of decarbonizing the U.S. electricity system under a set of possible scenarios. The results show that, compared to the reference scenario without a decarbonization policy, reaching zero CO 2 emission by 2050 would incur, depending on the scenarios, 335-494 billion USD additional cost to the U.S. electric power sector during 2020-2050. The regional costs of electricity generation ranges from 2.4 to 4.7 cent/kWh, largely due to the generation profiles and renewable resources availability of those regions. The additional costs can be translated to an average CO 2 abatement cost of 29-59 USD/metric ton CO 2 (with 2%-7% discount rates), which are comparable to the social cost of carbon in the literature at around 4% discount rate. The results also show that the cost of mitigating the last few percent CO 2 emission from the U.S. electricity system may exceed the costs of NETs, indicating an opportunity for NETs to contribute to electricity decarbonization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

In situ probing of structure and deagglomeration of SnO 2 colloids via small-angle X-ray scattering

Transforming dry nanopowders into stable colloidal dispersions remains challenging due to the cohesive forces between the nanoparticles (NPs) which promote agglomeration. Effective dispersion and deagglomeration of these agglomerates is a critical process in the formulation and preparation of nanoparticle-based functional materials via the colloidal route. Understanding the deagglomeration dynamics provides information to improve microstructural quality in various applications by enabling engineering of agglomerate size, structure and morphology. However, the deagglomeration process dynamics with respect to the evolution of the fractal agglomerate structures, particularly for very small NPs, is still poorly understood and requires further investigation. This study employs in situ small-angle X-ray scattering (SAXS) to investigate the sonication-induced deagglomeration of SnO 2 NPs. Electrostatically stabilized SnO 2 colloids with varying primary particle size (6–21 nm) are investigated in a specifically designed in situ cell using synchrotron-based SAXS to study the influence of sonication time and intensity on the nanoscaled agglomerates. Complete structural analysis via SAXS reveals a direct correlation between changes in agglomerate size and structure, size-dependent deagglomeration behavior and a dependence on the overall energy introduced during sonication into the dispersion regardless of the actual power as well as ultrasonic process parameters in case of SnO 2 NPs. The results suggest that control of the dispersion process during ultrasonic deagglomeration results in tailoring agglomerates with respect to size and structure.

Deagglomeration↗

Magnetic well and Mercier stability of stellarators near the magnetic axis

We have recently demonstrated that by expanding in small distance from the magnetic axis compared with the major radius, stellarator shapes with low neoclassical transport can be generated efficiently. To extend the utility of this new design approach, here we evaluate measures of magnetohydrodynamic interchange stability within the same expansion. In particular, we evaluate the magnetic well, Mercier's criterion, and resistive interchange stability near a magnetic axis of arbitrary shape. In contrast to previous work on interchange stability near the magnetic axis, which used an expansion of the flux coordinates, here we use the ‘inverse expansion’ in which the flux coordinates are the independent variables. Reduced expressions are presented for the magnetic well and stability criterion in the case of quasisymmetry. The analytic results are shown to agree with calculations from the VMEC equilibrium code. Finally, we show that near the axis, Glasser, Greene and Johnson's stability criterion for resistive modes approximately coincides with Mercier's ideal condition.

Physics↗

Recent Advances in Plasma Catalysis

Plasma catalysis is the integration of plasmas and catalysts to achieve reactant conversions and product selectivities that are inaccessible with plasmas or catalysts alone. While chemical transformations via plasma and catalysis are individually well-developed and optimized in many cases, efficient and effective plasma catalysis coupling remains primitive. Molecular understanding of plasma catalysis is further challenged by the complicated natures of plasma and catalysis separately. In this Virtual Issue, we collect 35 examples highlighting recent advances in plasma catalysis that were published in ACS journals from 2019 to 2021. Here, we categorized these 35 into six classes, ranging from fundamental plasma/surface characterizations to applied research on chemical transformations and catalyst synthesis, as presented in Figure 1. We hope this collection is helpful especially to those new to this emerging area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Liquid Phase Exfoliation of Chemically Prelithiated Bilayered Vanadium Oxide in Aqueous Media for Li-Ion Batteries

Bilayered vanadium oxides are attractive for energy storage due to their high initial specific capacities, which could be stabilized by integrating the bilayers with conductive nanoflakes often produced in a form of aqueous dispersions. Therefore, exfoliation of the bilayered vanadium oxides in water with high yield is desirable. Here, this work introduces the first aqueous exfoliation of chemically prelithiated bilayered vanadium oxide (i.e., δ-Li x V 2 O 5 ·nH 2 O or LVO) followed by vacuum filtration to produce a free-standing film, exhibiting a lamellar stacking of the bilayered vanadium oxide nanoflakes as evidenced by scanning electron microscopy. Due to the hydrated nature of bilayered vanadium oxides, the relationship between interlayer water content and the vacuum drying temperature (105 °C vs 200 °C) was studied using X-ray diffraction, thermogravimetric analysis, and Raman spectroscopy. It was found that vacuum drying the LVO nanoflakes at 200 °C enabled more efficient removal of crystallographic water than drying at 105 °C, and did not induce a phase transformation. Scanning transmission electron microscopy confirmed the layered structure of the samples, which was more well-ordered in the 200 °C case and had no clear boundaries between flakes at the atomic scale. Furthermore, electrochemical testing in nonaqueous Li-ion cells revealed that vacuum drying at 200 °C led to improvements in ion storage capacity and electrochemical stability. Improvements in electrochemical charge storage properties of the electrodes obtained via LVO exfoliation and free-standing film assembly in water dried at 200 °C reveal that conventional battery electrode drying protocols need to be revised as new electrochemically active materials are synthesized, such as hydrated layered oxides with expanded interlayer regions. The remaining capacity fading can be attributed to the structural LVO degradation, dissolution of vanadium oxide in electrolyte, and parasitic effects of the remaining interlayer water molecules. Our results establish an environmentally friendly and safe approach to obtain two-dimensional (2D) bilayered vanadium oxide nanoflakes and create a pathway to constructing novel 2D heterostructures for improved performance in energy storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data compression and covariance matrix inspection: Cosmic shear

Covariance matrices are among the most difficult pieces of end-to-end cosmological analyses. In principle, for two-point functions, each component involves a four-point function, and the resulting covariance often has hundreds of thousands of elements. We investigate various compression mechanisms capable of vastly reducing the size of the covariance matrix in the context of cosmic shear statistics. This helps identify which of its parts are most crucial to parameter estimation. We start with simple compression methods, by isolating and “removing” 200 modes associated with the lowest eigenvalues, then those with the lowest signal-to-noise ratio, before moving on to more sophisticated schemes like compression at the tomographic level and, finally, with the massively optimized parameter estimation and data compression (MOPED). We find that, while most of these approaches prove useful for a few parameters of interest, like Ω m , the simplest yield a loss of constraining power on the intrinsic alignment (IA) parameters as well as S 8 . For the case considered—cosmic shear from the first year of data from the Dark Energy Survey—only MOPED was able to replicate the original constraints in the 16-parameter space. Finally, we apply a tolerance test to the elements of the compressed covariance matrix obtained with MOPED and confirm that the IA parameter A IA is the most susceptible to inaccuracies in the covariance matrix.

79 ASTRONOMY AND ASTROPHYSICS↗

Nanocrystalline protein domains via salting-out

Protein salting-out is a well established phenomenon that in many cases leads to amorphous structures and protein gels, which are usually not considered to be useful for protein structure determination. Here, microstructural measurements of several different salted-out protein dense phases are reported, including of lysozyme, ribonuclease A and an IgG1, showing that salted-out protein gels unexpectedly contain highly ordered protein nanostructures that assemble hierarchically to create the gel. The nanocrystalline domains are approximately 10–100 nm in size, are shown to have structures commensurate with those of bulk crystals and grow on time scales in the order of an hour to a day. Beyond revealing the rich, hierarchical nanoscale to mesoscale structure of protein gels, the nanocrystals that these phases contain are candidates for structural biology on next-generation X-ray free-electron lasers, which may enable the study of biological macromolecules that are difficult or impossible to crystallize in bulk.

Biochemistry & Molecular Biology↗

BTE-Sim: Fast Simulation Environment For Public Transportation

The public commute is essential to all urban centers and is an efficient and environment-friendly way to travel. Transit systems must become more accessible and user-friendly. Since public transit is majorly designed statically, with very few improvements coming over time, it can get stagnated, unable to update itself with changing population trends. To better understand transportation demands and make them more usable, efficient, and demographic-focused, we propose a fast, multi-layered transit simulation that primarily focuses on public transit simulation (BTE-Sim). BTE-Sim is designed based on the population demand, existing traffic conditions, and the road networks that exist in a region. The system is versatile, with the ability to run different configurations of the existing transit routes, or inculcate any new changes that may seem necessary, or even in extreme cases, new transit network design as well. In all situations, it can compare multiple transit networks and provide evaluation metrics for them. It provides detailed data on each transit vehicle, the trips it performs, its on-time performance and other necessary factors. Its highlighting feature is the considerably low computation time it requires to perform all these tasks and provide consistently reliable results.

Sen, Rishav↗

A Method to Represent a Well in a Three‐Dimensional Discrete Fracture Network Model

Abstract In discrete fracture network (DFN) modeling, fractures are randomly generated and placed in the model domain. The rock matrix is considered impermeable. Small fractures and isolated fractures are often ignored to reduce computational expense. As a result, the rock matrix between fractures could be large and intersections may not be found between a well introduced in the model and the hydraulically connected fracture networks (fracture backbones). To overcome this issue, this study developed a method to conceptualize a well in a three‐dimensional (3D) DFN using two orthogonal rectangular fractures oriented along the well's axis. Six parameters were introduced to parameterize the well screen and skin zone, and to control the connectivity between the well and the fracture backbones. The two orthogonal fractures were discretized using a high‐resolution mesh to improve the quality of flow and transport simulations around and along the well. The method was successfully implemented within dfnWorks 2.0 (Hyman et al. 2015) to incorporate a well in a 3D DFN and to track particles leaving an injection well and migrating to a pumping well. Verification of the method against MODFLOW/MODPATH found a perfect match in simulated hydraulic head and particle tracking. Using three examples, the study showed that the method ensured the connectivity between wells and fracture backbones, and honored the physical processes of flow and transport along and around wells in DFNs. Recommendations are given for estimating the values of the six introduced well parameters in a real‐world case study.

Pham, Hai (ORCID:0000000310164394)↗

Multiscale Airborne Infectious Disease Transmission

Airborne disease transmission is central to many scientific disciplines, including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated; e.g., the U.S. National Library of Medicine’s Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences, as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation. To inform future work, this paper highlights selected, well-established airborne transmission events, largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations, and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the ability to cause disease in plants, animals, and humans over multiple distances, from near range (<5 m) to continental (>500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burdens for several airborne-transmitted diseases.

59 BASIC BIOLOGICAL SCIENCES↗

Linking resource availability to pantropical forest canopy resistance and resilience to cyclone disturbance

Statement of purpose: Tropical cyclones are intensifying and occurring at higher latitudes in recent decades, but the mechanisms underpinning the resistance (ability to withstand disturbance-induced change) and resilience (pace of return to pre-disturbance reference values) of tropical forests to cyclones remains largely unexplored at the pantropical scale. We conducted a meta-analysis to investigate the role of soil resource availability (i.e., total soil phosphorus concentration) in mediating site-level forest canopy resistance and resilience to cyclones pan-tropically. We evaluated cyclone-induced and post-cyclone litterfall mass (g/m2/day), phosphorus (P) and nitrogen (N) fluxes (mg/m2/day), as well as concentrations (mg/g) across 73 case studies in Australia, Guadeloupe, Hawaii, Mexico, Puerto Rico, and Taiwan. The dataset zip file includes three data and two metadata files: - The compiled Litterfall Mass Flux data from tropical forests across the globe prior to and after varying tropical cyclone disturbances are provided in Litterfall_Mass.csv. This data file also includes site location, geographical characteristics, elevation, soil phosphorus concentration, geology, and several variables related to each tropical cyclone disturbance. - The compiled Litterfall Nitrogen and Phosphorus Flux data from tropical forests across the globe prior to and after varying tropical cyclone disturbances are provided in Litterfall_Nutrients.csv. This data file also includes site location, geographical characteristics, elevation, soil phosphorus concentration, geology, and several variables related to each tropical cyclone disturbance. - Tropical cyclone track data compiled from HURDAT2 and IBTrACS databases and used as input in the HURRECON model (https://github.com/hurrecon-model/HurreconR) to generate wind data is provided in hurdat2-1851-2019-052520.txt. - The metadata file (Metadata_Meta-analysis_Litterfall-Mass.pdf) has the complete information on each variable included in the Litterfall_Mass.csv dataset, the data sources, and data processing information. - The metadata file (Metadata_Meta-analysis_Litterfall-Nutrients.pdf) has the complete information on each variable included in the Litterfall_Nutrients.csv dataset, the data sources, and data processing information.

54 ENVIRONMENTAL SCIENCES↗