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At least 1,657 records · Page 92

A triple quantum dot based nano-electromechanical memory device

Colloidal quantum dots (CQDs) are free-standing nano-structures with chemically tunable electronic properties. This tunability offers intriguing possibilities for nano-electromechanical devices. In this work, we consider a nano-electromechanical nonvolatile memory (NVM) device incorporating a triple quantum dot (TQD) cluster. The device operation is based on a bias induced motion of a floating quantum dot (FQD) located between two bound quantum dots (BQDs). The mechanical motion is used for switching between two stable states, “ON” and “OFF” states, where ligand-mediated effective interdot forces between the BQDs and the FQD serve to hold the FQD in each stable position under zero bias. Considering realistic microscopic parameters, our quantum-classical theoretical treatment of the TQD reveals the characteristics of the NVM.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

LDRD Abbreviated report: High-Order General-Discrete-Ordinates Method Enabling Efficient Deterministic Transport in Hydrodynamic Simulations

Deterministic transport simulations for national-security and energy applications often operate in high-dimensional phase-space, where accuracy and cost both become major challenges. A common numerical artifact in such problems is the “ray-effect,” which appears as unphysical streaks. Beyond misinterpretation, these artifacts can contaminate tightly coupled physics, such as fluid dynamics, radiation-hydrodynamics, and laser-plasma interactions, eroding the predictive capability of entire multiphysics workflows. Our objective was to make high-dimension studies practical on modern hardware while mitigating the ray-effect without relying on prohibitively expensive sampling approaches such as Monte Carlo methods. We developed the Generic Discretization Library (GenDiL), a Graphics Processing Unit (GPU)-first framework that uses high-order Discontinuous Galerkin (DG) methods and matrix-free algorithms to reduce memory usage and improve computational efficiency, critical for phase-space simulations. GenDiL supports phase-space adaptivity in both mesh size and polynomial order (hp-adaptivity) to place resolution only where it is needed. A central capability is Local Dimensional Refinement (LDR), which couples lower-dimension continuum models to higher-dimension kinetic models through stable and conservative interfaces, so that high-fidelity physics is applied only in regions where it is essential. Building on the GenDiL framework, we developed the General SN (GSN) family of algorithms as a true generalization of the polar SN approach (discrete ordinates, often denoted SN). Rather than tying discrete ordinates to a specific polar change of coordinates, GSN formulates transport on an arbitrary change of coordinates chosen to reduce ray-effect. We studied two complementary variants: an analytic variant, where the coordinate map is prescribed in advance by a closed-form function; and a data-driven variant, where a quantity of interest, such as the net flux, guides the coordinate system. GenDiL provides the library infrastructure for efficient GPU execution, but the GSN concept is algorithmic and independent of any one library. Across representative high-dimension tests, including non-symmetric solutions, both variants delivered strong ray-effect mitigation at practical cost, moving four- to six-dimensional analysis toward repeatable, routine studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer–particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer–particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

36 MATERIALS SCIENCE↗

Aerodynamic Shape Optimization of Supersonic Aircraft Configurations via an Adjoint Formulation on Parallel Computers

This work describes the application of a control theory-based aerodynamic shape optimization method to the problem of supersonic aircraft design. The design process is greatly accelerated through the use of both control theory and a parallel implementation on distributed memory computers. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods (13, 12, 44, 38). The resulting problem is then implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) Standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on higher order computational fluid dynamics methods (CFD). In our earlier studies, the serial implementation of this design method (19, 20, 21, 23, 39, 25, 40, 41, 42, 43, 9) was shown to be effective for the optimization of airfoils, wings, wing-bodies, and complex aircraft configurations using both the potential equation and the Euler equations (39, 25). In our most recent paper, the Euler method was extended to treat complete aircraft configurations via a new multiblock implementation. Furthermore, during the same conference, we also presented preliminary results demonstrating that the basic methodology could be ported to distributed memory parallel computing architectures [241. In this paper, our concem will be to demonstrate that the combined power of these new technologies can be used routinely in an industrial design environment by applying it to the case study of the design of typical supersonic transport configurations. A particular difficulty of this test case is posed by the propulsion/airframe integration.

Reuther, James↗

Synthesis of monodisperse CeO 2 -ZrO 2 particles exhibiting cyclic superelasticity over hundreds of cycles

Nano- and microscale CeO 2 –ZrO 2 (CZ) shape memory ceramics are promising materials for smart micro-electro-mechanical systems (MEMS), sensing, actuation and energy damping applications, but the processing science for scalable production of such small volume ceramics has not yet been established. Herein, we report a modified sol-gel method to synthesize highly monodisperse spherical CZ particles with diameters in the range of ~0.8-3.0 μm. Synchrotron X-ray micro-diffraction (μSXRD) confirmed that most of the particles are single crystal after annealing at 1450°C. Having a monocrystalline structure and a small specimen length scale, the particles exhibit significantly enhanced shape memory and superelasticity properties with up to ~4.7% compression being completely recoverable. Highly reproducible superelasticity through over five hundred strain cycles, with dissipated energy up to ~40 MJ/m 3 per cycle, is achieved in the CZ particles containing 16 mol% ceria. This cycling capability is enhanced by ten times compared with our first demonstration using micropillars (only 50 cycles in Lai et al, Science, 2013, 341, 1505). Furthermore, the effects of cycling and testing temperature (in 25°C-400°C) on superelasticity have been investigated.

36 MATERIALS SCIENCE↗

Resummed memory kernels in generalized system-bath master equations

Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between the two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the “Landau-Zener resummation” of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multifunctional BiFeO{sub 3}/TiO{sub 2} nano-heterostructure: Photo-ferroelectricity, rectifying transport, and nonvolatile resistive switching property

Multifunctional BiFeO{sub 3} nanostructure anchored TiO{sub 2} nanotubes are fabricated by coupling wet chemical and electrochemical routes. BiFeO{sub 3}/TiO{sub 2} nano-heterostructure exhibits white-light-induced ferroelectricity at room temperature. Studies reveal that the photogenerated electrons trapped at the domain/grain boundaries tune the ferroelectric polarization in BiFeO{sub 3} nanostructures. The photon controlled saturation and remnant polarization opens up the possibility to design ferroelectric devices based on BiFeO{sub 3.} The nano-heterostructure also exhibits substantial photovoltaic effect and rectifying characteristics. Photovoltaic property is found to be correlated with the ferroelectric polarization. Furthermore, the nonvolatile resistive switching in BiFeO{sub 3}/TiO{sub 2} nano-heterostructure has been studied, which demonstrates that the observed resistive switching is most likely caused by the electric-field-induced carrier injection/migration and trapping/detrapping process at the hetero-interfaces. Therefore, BiFeO{sub 3}/TiO{sub 2} nano-heterostructure coupled with logic, photovoltaics and memory characteristics holds promises for long-term technological applications in nanoelectronics devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Isoflurane induced cognitive impairment in aged rats through hippocampal calcineurin/NFAT signaling

Calcineurin (CaN) over-activation constrains synaptic plasticity and memory formation. Upon CaN activation, NFAT imports into the nucleus and guides its downstream genes, which also affect neuronal and synaptic function. Aberrant CaN/NFAT signaling involves in neurotoxicity and cognitive impairment in neurological disorders such as Alzheimer's disease, but its role in postoperative cognitive dysfunction (POCD) remains uninvestigated. Inhaled anesthetic isoflurane facilitates the development of POCD, and the present study investigated the role of CaN/NFAT signaling in isoflurane induced cognitive impairment of aged rats, and the therapeutic effects of CaN inhibitor cyclosporine A (CsA). The results indicated that hippocampal CaN activity increased and peaked at 6 h after isoflurane exposure, and NFAT, especially NFATc4, imported into the nucleus following CaN activation. Furthermore, phamacological inhibition of CaN by CsA markedly attenuated isoflurane induced aberrant CaN/NFATc4 signaling in the hippocampus, and rescued relevant spatial learning and memory impairment of aged rats. Overall, the study suggests hippocampal CaN/NFAT signaling as the upstream mechanism of isoflurane induced cognitive impairment, and provides potential therapeutic target and possible treatment methods for POCD. - Highlights: • Isoflurane induces hippocampal calcineurin activation. • Isoflurane induces hippocampal NFAT, especially NFATc4, nuclear import. • Cyclosporine A attenuates isoflurane induced aberrant calcineurin/NFAT signaling. • Cyclosporine A rescues isoflurane induced cognitive impairment. • Calcineurin/NFAT signaling is the upstream mechanism of isoflurane induced synaptic dysfunction and cognitive impairment.

60 APPLIED LIFE SCIENCES↗

Thermally stable voltage-controlled perpendicular magnetic anisotropy in Mo|CoFeB|MgO structures

We study voltage-controlled magnetic anisotropy (VCMA) and other magnetic properties in annealed Mo|CoFeB|MgO layered structures. The interfacial perpendicular magnetic anisotropy (PMA) is observed to increase with annealing over the studied temperature range, and a VCMA coefficient of about 40 fJ/V-m is sustained after annealing at temperatures as high as 430 °C. Ab initio electronic structure calculations of interfacial PMA as a function of strain further show that strain relaxation may lead to the increase of interfacial PMA at higher annealing temperatures. Measurements also show that there is no significant VCMA and interfacial PMA dependence on the CoFeB thickness over the studied range, which illustrates the interfacial origin of the anisotropy and its voltage dependence, i.e., the VCMA effect. The high thermal annealing stability of Mo|CoFeB|MgO structures makes them compatible with advanced CMOS back-end-of-line processes, and will be important for integration of magnetoelectric random access memory into on-chip embedded applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NETRA: A parallel architecture for integrated vision systems 2: Algorithms and performance evaluation

In part 1 architecture of NETRA is presented. A performance evaluation of NETRA using several common vision algorithms is also presented. Performance of algorithms when they are mapped on one cluster is described. It is shown that SIMD, MIMD, and systolic algorithms can be easily mapped onto processor clusters, and almost linear speedups are possible. For some algorithms, analytical performance results are compared with implementation performance results. It is observed that the analysis is very accurate. Performance analysis of parallel algorithms when mapped across clusters is presented. Mappings across clusters illustrate the importance and use of shared as well as distributed memory in achieving high performance. The parameters for evaluation are derived from the characteristics of the parallel algorithms, and these parameters are used to evaluate the alternative communication strategies in NETRA. Furthermore, the effect of communication interference from other processors in the system on the execution of an algorithm is studied. Using the analysis, performance of many algorithms with different characteristics is presented. It is observed that if communication speeds are matched with the computation speeds, good speedups are possible when algorithms are mapped across clusters.

Choudhary, Alok N.↗

Basic Requirements for Systems Software Research and Development

Our success over the past ten years evaluating and developing advanced computing technologies has been due to a simple research and development (R/D) model. Our model has three phases: (a) evaluating the state-of-the-art, (b) identifying problems and creating innovations, and (c) developing solutions, improving the state- of-the-art. This cycle has four basic requirements: a large production testbed with real users, a diverse collection of state-of-the-art hardware, facilities for evalua- tion of emerging technologies and development of innovations, and control over system management on these testbeds. Future research will be irrelevant and future products will not work if any of these requirements is eliminated. In order to retain our effectiveness, the numerical aerospace simulator (NAS) must replace out-of-date production testbeds in as timely a fashion as possible, and cannot afford to ignore innovative designs such as new distributed shared memory machines, clustered commodity-based computers, and multi-threaded architectures.

Kuszmaul, Chris↗

Implementing Concurrent Non-Event Transitionsin CMS

Available on CMS information serverCMS CR -2018/277The Compact Muon Solenoid ExperimentMailing address: CMS CERN, CH-1211 GENEVA 23, SwitzerlandConference Report15 October 2018 (v2, 21 November 2018)Implementing Concurrent Non-Event Transitionsin CMSChristopher Jones for the CMS CollaborationAbstractSince the beginning of the LHC Run 2 in 2016 the CMS data processing framework, CMSSW, hasbeen running with multiple threads during production of data and simulation via the use of IntelsThread Building Blocks (TBB) library. The TBB library utilizes tasks as concurrent units of work.CMS used these tasks to allow both concurrent processing of events as well as concurrent running ofmodules processing the same event. This design has served CMS well and has allowed jobs to utilizeless memory per core as well as reduce the number of jobs that must be tracked by CMSs worflowmanagement system. As CMS has begun to utilize greater number of threads in a job, the effect ofserialization points in the framework has decreased jobs CPU efficiency. One major serialization pointoccurs when the framework processes a non-Event transition. These transitions occur when a new Runor LuminosityBlock is to be processed. In this talk we will discuss how the different transitions definethe processing model for CMSSW and how we were able to successfully allow concurrent process-ing of those transitions using TBB via task queues. We will also show CPU efficiency comparisonsbetween the same work being done with and without the additional concurrency.

Jones, Christopher↗

Nonlinear Matrix Approximation with Radial Basis Function Components

We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components. An RBF component is a generalization of the outer product between a pair of vectors, where an RBF function replaces the scalar multiplication between individual vector elements. Even though the RBF functions are positive definite, the summation across components is not restricted to convex combinations and allows us to compute the decomposition for any real matrix that is not necessarily symmetric or positive definite. We formulate the problem of seeking such a decomposition as an optimization problem with a nonlinear and non-convex loss function. Several modern versions of the gradient descent method, including their scalable stochastic counterparts, are used to solve this problem. We provide extensive empirical evidence of the effectiveness of the RBF decomposition and that of the gradient-based fitting algorithm. While being conceptually motivated by singular value decomposition (SVD), our proposed nonlinear counterpart outperforms SVD by drastically reducing the memory required to approximate a data matrix with the same L2 error for a wide range of matrix types. For example, it leads to 2 to 6 times memory save for Gaussian noise, graph adjacency matrices, and kernel matrices. Moreover, this proximity-based decomposition can offer additional interpretability in applications that involve, e.g., capturing the inner low-dimensional structure of the data, retaining graph connectivity structure, and preserving the acutance of images.

Rebrova, Elizaveta↗

Advanced Multi-phase Flow CFD Model Development for Solid Rocket Motor Flowfield Analysis

A Navier-Stokes code, finite difference Navier-Stokes (FDNS), is used to analyze the complicated internal flowfield of the SRM (solid rocket motor) to explore the impacts due to the effects of chemical reaction, particle dynamics, and slag accumulation on the solid rocket motor (SRM). The particulate multi-phase flowfield with chemical reaction, particle evaporation, combustion, breakup, and agglomeration models are included in present study to obtain a better understanding of the SRM design. Finite rate chemistry model is applied to simulate the chemical reaction effects. Hermsen correlation model is used for the combustion simulation. The evaporation model introduced by Spalding is utilized to include the heat transfer from the particulate phase to the gase phase due to the evaporation of the particles. A correlation of the minimum particle size for breakup expressed in terms of the Al/Al2O3 surface tension and shear force was employed to simulate the breakup of particles. It is assumed that the breakup occurs when the Weber number exceeds 6. A simple L agglomeration model is used to investigate the particle agglomeration. However, due to the large computer memory requirements for the agglomeration model, only 2D cases are tested with the agglomeration model. The VOF (Volume of Fluid) method is employed to simulate the slag buildup in the aft-end cavity of the redesigned solid rocket motor (RSRM). Monte Carlo method is employed to calculate the turbulent dispersion effect of the particles. The flowfield analysis obtained using the FDNS code in the present research with finite rate chemical reaction, particle evaporation, combustion, breakup, agglomeration, and VOG models will provide a design guide for the potential improvement of the SRM including the use of materials and the shape of nozzle geometry such that a better performance of the SRM can be achieved. The simulation of the slag buildup in the aft-end cavity can assist the designer to improve the design of the RSRM geometry.

Liaw, Paul↗

Effects of stress upon psychophysiological responses and performance following sleep deprivation

The usefulness of psychological and physiological variables in predicting performance under stress of 48 hours of sleep deprivation was investigated. Performance tests, with subjects of different ego strength personalities, in concept acquisition, reading comprehension, word association, word memory, and anagrams were conducted, and physiological measurements of (1) the phasic and tonic electrodermal, (2) galvanic skin response, (3) thermal skin resistance, (4) heart rate, (5) respiration, and (6) plethysmographic finger pulse volumn were recorded. It was found that the changes in the pattern of performance were the result of testing subjects at times when they would normally be sleeping, and that sleep deprivation longer than 48 hours must be maintained to produce changes in simple or well learned tasks.

Roessler, R.↗

Efficient partitioning and assignment on programs for multiprocessor execution

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

Standley, Hilda M.↗

DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance

Scientific data analytics in high-performance computing environments has been evolving along with the advancement of computing capabilities. With the onset of exascale computing, the increasing gap between compute performance and I/O bandwidth has rendered the traditional post-simulation processing a tedious process. Despite the challenges due to increased data production, there exists an opportunity to benefit from "cheap" computing power to perform query-driven exploration and visualization during simulation time. To accelerate such analyses, applications traditionally augment, post-simulation, raw data with large indexes, which are then repeatedly utilized for data exploration. However, the generation of current state-of-the-art indexes involves a compute- and memory-intensive processing, thus rendering them inapplicable in an in situ context. In this paper we propose DIRAQ, a parallel in situ, in network data encoding and reorganization technique that enables the transformation of simulation output into a query-efficient form, with negligible runtime overhead to the simulation run. DIRAQ's effective core-local, precision-based encoding approach incorporates an embedded compressed index that is 3---6 $$\times $$ ? smaller than current state-of-the-art indexing schemes. Its data-aware index adjustmentation improves performance of group-level index layout creation by up to 35 % and reduces the size of the generated index by up to 27 %. Moreover, DIRAQ's in network index merging strategy enables the creation of aggregated indexes that speed up spatial-context query responses by up to $$10\times $$ 10 ? versus alternative techniques. DIRAQ's topology-, data-, and memory-aware aggregation strategy results in efficient I/O and yields overall end-to-end encoding and I/O time that is less than that required to write the raw data with MPI collective I/O.

Computer Science↗

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys

This paper evaluates the ruggedness testing of the newly released ASTM International E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors of strain rate (ė), heating and cooling rates (Ṫ(heat) and Ṫ(cool), respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (thold), and minimum load (Fmin) imparted on the samples. The results indicate that the hold time factor had no effect on any result variable. The minimum load factor, alternatively, had the greatest effect on several result variables, with the greatest influence on the strains at martensite start and finish (strain variation ~0.1 percent), and the strains at the upper and lower cycle temperatures (strain variation of 0.14 percent). The UCT was found to have a large effect on the austenite and martensite finish tangent line and data intersect, denoted by Af* and Mf*, by ~17 and 4 °C, respectively. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test methods are presented.

shape memory alloy↗