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At least 721 records · Page 40

Morphology and property tuning in ZnO–Ni hybrid metamaterials in vertically aligned nanocomposite (VAN) form

ZnO thin films have attracted significant interest in the past decades owing to their unique wide band gap properties, piezoelectric properties, non-linearity and plasmonic properties. Recent efforts have been made in coupling ZnO with secondary phases to enhance its functionalities, such as Au–ZnO nanocomposite thin films with tunable optical and plasmonic properties. In this work, magnetic nanostructures of Ni are incorporated in ZnO thin films in a vertically aligned nanocomposite (VAN) form to couple magnetic and plasmonic response in a complex hybrid metamaterial system. Nickel (Ni) is of interest due to its ferromagnetic and plasmonic properties along with gold (Au) which is also plasmonic. Therefore, two approaches, namely, tuning of the deposition pressure and use of a ZnO–Au seeding layer have been attempted to achieve unique Ni nanostructures in addition to tuning of the microstructure. Together, both approaches demonstrate a range of microstructures such as core–shell, nanodisk, nanocup, and nanocube-like morphologies not previously attempted. Additionally, there is effective tuning of properties. Specifically, the seeding layer thickness causes hyperbolic behavior as well as redshift in the surface plasmon resonance (SPR) wavelength. The addition of the ZnO–Au seeding layer directly influences the optical properties. Plus, regardless of the different approaches, the films demonstrate magnetic anisotropy based on the composition and microstructure of the film which impacted the saturation magnetization and coercivity. This study demonstrates the potential of ZnO-based complex hybrid metamaterials with coupled electro-magneto-optical properties for integrated photonic devices.

Bhatt, Nirali A. [Purdue Univ., West Lafayette, IN↗

Reconfigurable Pinwheel Artificial-Spin-Ice and Superconductor Hybrid Device

The ability to control the potential landscape in a medium of interacting particles could lead to intriguing collective behavior and innovative functionalities. In this work, we utilize spatially reconfigurable magnetic potentials of a pinwheel artificial-spin-ice (ASI) structure to tailor the motion of superconducting vortices. The reconstituted chain structures of the magnetic charges in the pinwheel ASI and the strong interaction between magnetic charges and superconducting vortices allow significant modification of the transport properties of the underlying superconducting thin film, resulting in a reprogrammable resistance state that enables a reversible and switchable vortex Hall effect. Our results highlight an effective and simple method of using ASI as an in situ reconfigurable nanoscale energy landscape to design reprogrammable superconducting electronics, which could also be applied to the in situ control of properties and functionalities in other magnetic particle systems, such as magnetic skyrmions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Runtime power allocation approach for GAMESS hybrid CPU‐GPU implementation

Summary To improve power consumption of applications at the runtime, modern processors provide frequency scaling capabilities, which along with workload optimization, are also available on GPU accelerators. In this work, a runtime strategy is proposed to distribute a given power allocation among the host components and the GPU according to the current application performance and power usage, such that GPU execution is prioritized over CPU for power allocation to maximize application performance. Next, the strategy is tailored to an application, a quantum‐chemistry package GAMESS for ab initio electronic structure calculations. Specifically, GAMESS hybrid CPU–GPU implementation as provided in the Libcchem library is considered. Experiments, performed on a 28‐core node with a Kepler GPU, resulted in performance gains of up to 50% under the proposed strategy and the largest power allocation considered here as compared with the scenario when this allocation was equally distributed among the computing‐platform components.

Sundriyal, Vaibhav↗

2D kinetic-ion simulations of inverted corona fusion targets

Laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. The scheme consists of a hollow or gas-filled spherical shell made of deuterated plastic. The shell has one or more laser entrance holes (LEH), resembling a spherical hohlraum. The laser passes through the LEH’s and illuminates the interior surface of the shell, ablating a plasma that travels inward towards the target center. Long ion mean free paths in the converging plasma can lead to significant interpenetration, atomic mix, and other kinetic effects. Here, in this work we report on numerical simulations of inverted corona targets using the kinetic-ion, fluid–electron hybrid particle-in-cell (PIC) approach in 2D RZ geometry. 2D simulations suggest that shape effects do not have a significant impact on plasma evolution and observed yield trends are primarily the result of 1D kinetic mix mechanisms. Simulations are also compared against available experimental data recorded at the OMEGA laser facility. In particular, synthetic x-ray emission images show good qualitative agreement with experimental results, albeit with an apparent timing discrepancy for the two-sided vacuum target. More generally, we demonstrate the potential of hybrid-PIC simulations for full-system modeling and experimental design, including collisional absorption of laser energy, plasma evolution, mix, and fusion burn.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Identifying the nature of the QCD transition in heavy-ion collisions with deep learning

In this proceeding, we review our recent work using deep convolutional neural network (CNN) to identify the nature of the QCD transition in a hybrid modeling of heavy-ion collisions. Within this hybrid model, a viscous hydrodynamic model is coupled with a hadronic cascade “after-burner”. As a binary classification setup, we employ two different types of equations of state (EoS) of the hot medium in the hydrodynamic evolution. The resulting final-state pion spectra in the transverse momentum and azimuthal angle plane are fed to the neural network as the input data in order to distinguish different EoS. To probe the effects of the fluctuations in the event-by-event spectra, we explore different scenarios for the input data and make a comparison in a systematic way. We observe a clear hierarchy in the predictive power when the network is fed with the event-by-event, cascade-coarse-grained and event-fine-averaged spectra. The carefully-trained neural network can extract high-level features from pion spectra to identify the nature of the QCD transition in a realistic simulation scenario.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Single Entity Electrochemistry in Nanopore Electrode Arrays: Ion Transport Meets Electron Transfer in Confined Geometries

Electrochemical measurements conducted in confined volumes provide a powerful and direct means to address scientific questions at the nexus of nanoscience, biotechnology, and chemical analysis. How are electron transfer and ion transport coupled in confined volumes and how does understanding them require moving beyond macroscopic theories? Also, how do these coupled processes impact electrochemical detection and processing? We address these questions by studying a special type of confined-volume architecture, the nanopore electrode array, or NEA, which is designed to be commensurate in size with physical scaling lengths, such as the Debye length, a concordance that offers performance characteristics not available in larger scale structures. The experiments described here depend critically on carefully constructed nanoscale architectures that can usefully control molecular transport and electrochemical reactivity. We begin by considering the experimental constraints that guide the design and fabrication of zero-dimensional nanopore arrays with multiple embedded electrodes. These zero-dimensional structures are nearly ideal for exploring how permselectivity and unscreened ion migration can be combined to amplify signals and improve selectivity by enabling highly efficient redox cycling. Our studies also highlight the benefits of arrays, in that molecules escaping from a single nanopore are efficiently captured by neighboring pores and returned to the population of active redox species being measured, benefits that arise from coupling ion accumulation and migration. These tools for manipulating redox species are well-positioned to explore single molecule and single particle electron transfer events through spectroelectrochemistry, studies which are enabled by the electrochemical zero-mode waveguide (ZMW), a special hybrid nanophotonic/nanoelectronic architecture in which the lower ring electrode of an NEA nanopore functions both as a working electrode to initiate electron transfer reactions and as the optical cladding layer of a ZMW. Furthermore, while the work described here is largely exploratory and fundamental, we believe that the development of NEAs will enable important applications that emerge directly from the unique coupled transport and electron-transfer capabilities of NEAs, including in situ molecular separation and detection with external stimuli, redox-based electrochemical rectification in individually encapsulated nanopores, and coupled sorters and analyzers for nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tensor decompositions for count data that leverage stochastic and deterministic optimization

There is growing interest to extend low-rank matrix decompositions to multi-way arrays, or tensors. One fundamental low-rank tensor decomposition is the canonical polyadic decomposition (CPD). The challenge of fitting a low-rank, nonnegative CPD model to Poisson-distributed count data is of particular interest. Several popular algorithms use local search methods to approximate the maximum likelihood estimator (MLE) of the Poisson CPD model. Here, this work presents two new algorithms that extend state-of-the-art local methods for Poisson CPD. Hybrid GCP-CPAPR combines Generalized Canonical Decomposition (GCP) with stochastic optimization and CP Alternating Poisson Regression (CPAPR), a deterministic algorithm, to increase the probability of converging to the MLE over either method used alone. Restarted CPAPR with SVDrop uses a heuristic based on the singular values of the CPD model unfoldings to identify convergence toward optimizers that are not the MLE and restarts within the feasible domain of the optimization problem, thus reducing overall computational cost when using a multi-start strategy. We provide empirical evidence that indicates our approaches outperform existing methods with respect to converging to the Poisson CPD MLE.

CPAPR↗

Prediction of topological phases in metastable ferromagnetic $MPX_3$ monolayers

Density functional theory calculations are carried out to study the electronic and topological properties of MPX 3 (M = Mn, Fe, Co,Ni; X = S, Se) monolayers in the ferromagnetic (FM) metastable magnetic state. Here we find that FM MnPSe 3 monolayers host topological semimetal signatures that are gapped out when spin-orbit coupling is included. These findings are supported by explicit calculations of the Berry curvature and the Chern number. The choice of the Hubbard-U parameter to describe the d-electrons is thoroughly discussed, as well as the influence of using a hybrid-functional approach. The presence of band inversions and the associated topological features are found to be formalism-dependent. Nevertheless, routes to achieve the topological phase via the application of external biaxial strain are demonstrated. Within the hybrid-functional picture, topological band structures are recovered under a pressure of 15% (17 GPa). The present work provides a potential avenue for uncovering new topological phases in metastable ferromagnetic phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Intrinsic and complex defect engineering of quasi-one-dimensional ribbons Sb 2 S 3 for photovoltaics performance

Sb 2 S 3 has attracted great attention recently as a prospective solar cell absorber material. In this work, intrinsic defects, dopants, and their complexes in Sb 2 S 3 are systematically investigated by using hybrid functional theory. V Sb and V S are dominant native defects and pin the Fermi level near the midgap, which is consistent with the high resistivity observed experimentally. Both V Sb and V S introduce deep levels inside the band gap, which can trap free carriers. Our calculated deep transition levels of V Sb and Sb S are consistent well with the results of the deep-level transient spectroscopy measurement. We further study dopants (including Cu, Ti, Zn, Br, and Cl) in Sb 2 S 3 and find that Zn and Br/Cl are shallow acceptors and donors, respectively, which may be used to control the carrier and trap densities in Sb 2 S 3 . In addition, the defect complexes, i.e., Cu(Zn) Sb +V S and Cl(Br) S +V Sb are also investigated. The interaction between the donor and acceptor defects makes the defect levels of complexes shallower and less detrimental to carrier transport.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kauhale 'O Kipapa: Kahikinui Community Cultural, Educational, and Resilience Center Preliminary Design Technical Assistance Summary Report

The Kahikinui Homestead Community in Maui faces energy resilience challenges due to its remote, off-grid location. This report summarizes preliminary technical assistance to design a microgrid for six modular homes using solar PV, wind, and battery storage. Findings show hybrid PV and battery systems, supplemented by small wind turbines, offer cost-effective, resilient solutions. This work supports enhanced energy independence and disaster preparedness for the community.

Quiroz, Jimmy Edward [Sandia National Laboratories↗

A unified N-body and statistical treatment of stellar dynamics. III - Early postcollapse evolution of globular clusters

The period immediately following the core collapse phase in the evolution of a globular cluster is studied using a hybrid N-body/Fokker-Planck stellar dynamical code. Several core oscillations of the type predicted in earlier work are seen. The oscillations are driven by the formation, hardening, and ejection of binaries by three-body processes, and appear to decay on a timescale of about 10 to the 7th yr, for the choice of 'typical' cluster parameters made here. There is no evidence that they are gravothermal in nature. The mechanisms responsible for the decay are discussed in some detail. The distribution of hard binaries produced by the oscillations is compared with theoretical expectations and the longer term evolution of the system is considered.

Mcmillan, S. L. W.↗

Testing of SMA-enabled Active Chevron Prototypes under Representative Flow Conditions

Control of jet noise continues to be an important research topic. Exhaust-nozzle chevrons have been shown to reduce jet noise, but parametric effects are not well understood. Additionally, thrust loss due to chevrons at cruise suggests significant benefit from active chevrons. The focus of this study is development of an active chevron concept for the primary purpose of parametric studies for jet noise reduction in the laboratory and secondarily for technology development to leverage for full scale systems. The active chevron concept employed in this work consists of a laminated composite structure with embedded shape memory alloy (SMA) actuators, termed a SMA hybrid composite (SMAHC). SMA actuators are embedded on one side of the neutral axis of the structure such that thermal excitation, via joule heating, generates a moment and deflects the structure. The performance of two active chevron concepts is demonstrated in the presence of representative flow conditions. One of the concepts is shown to possess significant advantages for the proposed application and is selected for further development. Fabrication and design changes are described and shown to produce a chevron prototype that meets the performance objectives.

Turner, Travis L.↗

Toward a NASA Deep Space Optical Communications System

As discussed at SpaceOps in 2016, we expect the data rates from deep space missions to increase approximately one order of magnitude per decade for the next 50 years. The first order of magnitude improvement will come from existing plans for radio frequency (RF) communications including enhancements to both spacecraft and Deep Space Network (DSN) facilities. The next two orders of magnitude are predicted to come from the introduction of deep space optical communications. Studies indicate that optical receive apertures of between 8m12m are desired. The large cost of dedicated receive telescopes makes this method unrealistic – at least in the near-term. The cost of large optical ground terminals is driven primarily by the cost of the optics and by the cost of a stable structure for the telescope. We propose a novel hybrid design in which existing DSN 34m beam waveguide (BWG) radio antennas can be modified to include an 8m equivalent optical primary. By utilizing a low-cost segmented spherical mirror optical design, pioneered by the optical astronomical community, and by exploiting the already existing extremely stable large radio aperture structures in the DSN, we can minimize both of these cost drivers for implementing large optical communications ground terminals. Two collocated hybrid RF/optical antennas could be arrayed to synthesize the performance of an 11.3m receive aperture to support more capable or more distant space missions or used separately to communicate with two optical spacecraft simultaneously. NASA is in the midst of building six new 34m BWG antennas in the DSN. The final two are planned to be built at the DSN Goldstone, California and Canberra complexes. We are now investigating building these last two antennas as RF/optical hybrids. By delaying their operational dates by two years, we would be able to add the 8m optical receive capability for these two antennas while fitting within existing budgetary constraints. This paper describes the hybrid antenna design, the technical challenges being addressed, and plan for using this concept, together with ongoing work on optical flight terminals, to infuse operation optical communications into deep space missions.

Cornwell, Donald M.↗

Modeling FLEX Human Actions Using the EMRALD Dynamic Risk Assessment Tool

Most current efforts have modified and applied existing human reliability analysis (HRA) methods to treat human actions related to beyond-design-basis external events in which diverse and flexible coping strategies (FLEX) equipment would be deployed. However, many questions remain regarding the suitability of legacy HRA methods to address FLEX human actions, sparking the need for a new method of reasonably evaluating them. In this context, Idaho National Laboratory (INL) researched a relatively new approach to treating FLEX human actions via Event Modeling Risk Assessment Using Linked Diagrams (EMRALD) software. EMRALD was developed to support the increasing need for dynamic probabilistic risk assessment (PRA) models that can respond to evolving plant conditions during simulations. A couple benefits were identified when analyzing FLEX human actions through this software. In general, it is especially useful for evaluating a strategy’s feasibility, including FLEX human actions that require a relatively long time to perform. In this paper, we suggest how FLEX human actions can be modeled using the EMRALD software. Two different HRA modeling approaches using EMRALD are introduced: (1) procedure-based modeling and (2) PRA/HRA-based modeling. The former approach was introduced in the authors’ previous paper, whereas this paper mainly discusses how the latter approach works for an extended loss of AC power (ELAP) scenario with relevant procedures and PRA models. A hybrid method combining the two modeling approaches is introduced at the paper’s conclusion.

99 GENERAL AND MISCELLANEOUS↗

Desalination Multi-Effect Evaporator Models in Support of Integrated Energy Systems

The purpose of this work is to contribute to the Integrated Energy Systems (IES) modeling efforts from the Department of Energy with Idaho National Laboratory. The DOE is working on a plug-and-play set of models in an open-source repository called HYBRID that can be used to improve IES modeling capabilities.

99 GENERAL AND MISCELLANEOUS↗

Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning

Here, we develop a computational database, website applications (web-apps), and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D) heterostructures. Using density functional theory (DFT) based lattice parameters and electronic band energies for 674 nonmetallic exfoliable 2D materials, we generate 226 779 possible bilayer heterostructures. We classify these heterostructures into type-I, -II, and -III systems according to Anderson’s rule, which is based on the relative band alignments of the noninteracting monolayers. We find that type II is the most common and type III the least common heterostructure type. We subsequently analyze the chemical trends for each heterostructure type in terms of the Periodic Table of constituent elements. The band alignment data can also be used for identifying photocatalysts and high-work-function 2D metals for contacts. We validate our results by comparing them to experimental data as well as hybrid-functional predictions. Additionally, we carry out DFT calculations of a few selected systems (MoS 2 /WSe 2 , MoS 2 /h-BN, and MoSe 2 /CrI 3 ), to compare the band-alignment description with the predictions from Anderson’s rule. We develop web-apps to enable users to virtually create combinations of 2D materials and predict their properties. Additionally, we use ML tools to predict band-alignment information for 2D materials. The web-apps, tools, and associated data will be distributed through the JARVIS-HETEROSTRUCTURE website. Our analysis, results, and the developed web-apps can be applied to the screening and design applications, such as finding alternative photocatalysts, photodetectors, and high-work-function (WF) 2D-metal contacts.

2-dimensional systems↗

A reduced order sulfuric acid decomposition model for a nuclear-powered hybrid sulfur cycle

A reduced order model of sulfuric acid decomposition within a bayonet chemical reactor was developed to support the U. S. Department of Energy Integrated Energy System program, and address the lack of knowledge in scaling and integration for joint chemical and nuclear processes. Sulfuric acid decomposition within a bayonet reactor was modeled to provide chemical and thermodynamic data relevant to advanced nuclear reactor-driven integrated energy systems based on desired operational scale and operational conditions. The temperature range required for high-temperature advanced nuclear reactor integrated energy systems, 750-850 °C, was shown to produce reasonable agreement (within a few percent relative error) with past models and experimental data, and yielded good efficiency results for bayonet reactor operations. The results of the reduced order model agreed with previous work from Savannah River National Labs within a maximum of 3.4% error on the decomposition of sulfur trioxide, and on previous Hybrid Sulfur flowsheets from Gorensek and Summers that showed operational temperature, pressure, and composition ranges for efficiency which made the Hybrid Sulfur cycle competitive with water electrolysis. Here, the agreement with previous high-fidelity models provided a framework for future Integrated Energy System grid evaluations with an advanced nuclear reactor and large-scale hydrogen production using a mathematical model to represent chemical operations.

08 HYDROGEN↗

Intelligence for Human-Assistant Planetary Surface Robots

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

Hirsh, Robert↗