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NASA NTRS1986

The force on the flex: Global parallelism and portability

A parallel programming methodology, called the force, supports the construction of programs to be executed in parallel by an unspecified, but potentially large, number of processes. The methodology was originally developed on a pipelined, shared memory multiprocessor, the Denelcor HEP, and embodies the primitive operations of the force in a set of macros which expand into multiprocessor Fortran code. A small set of primitives is sufficient to write large parallel programs, and the system has been used to produce 10,000 line programs in computational fluid dynamics. The level of complexity of the force primitives is intermediate. It is high enough to mask detailed architectural differences between multiprocessors but low enough to give the user control over performance. The system is being ported to a medium scale multiprocessor, the Flex/32, which is a 20 processor system with a mixture of shared and local memory. Memory organization and the type of processor synchronization supported by the hardware on the two machines lead to some differences in efficient implementations of the force primitives, but the user interface remains the same. An initial implementation was done by retargeting the macros to Flexible Computer Corporation's ConCurrent C language. Subsequently, the macros were caused to directly produce the system calls which form the basis for ConCurrent C. The implementation of the Fortran based system is in step with Flexible Computer Corporations's implementation of a Fortran system in the parallel environment.

Jordan, H. F.↗

DOE OSTI2014

Intrinsic SiO{sub x}-based unipolar resistive switching memory. II. Thermal effects on charge transport and characterization of multilevel programing

Multilevel programing and charge transport characteristics of intrinsic SiO{sub x}-based resistive switching memory are investigated using TaN/SiO{sub x}/n{sup ++}Si (MIS) and TiW/SiO{sub x}/TiW (MIM) device structures. Current transport characteristics of high- and low-resistance states (HRS and LRS) are studied in both device structures during multilevel operation. Analysis of device thermal response demonstrates that the effective electron energy barrier is strongly dependent on the resistance of the programed state, with estimates of 0.1 eV in the LRS and 0.6 eV in the HRS. Linear data fitting and conductance analyses indicate Poole-Frenkel emission or hopping conductance in the low-voltage region, whereas Fowler-Nordheim (F-N) or trap-assisted tunneling (TAT) is indicated at moderate voltage. Characterizations using hopping transport lead to hopping distance estimates of ∼1 nm in the LRS for both device structures. Relative permittivity values (ε{sub r}) were extracted using the Poole-Frenkel formulism and estimates of local filament temperature, where ε{sub r} values were ∼80 in the LRS and ∼4 in the HRS, suggesting a strongly polarized medium in the LRS. The onset of F-N tunneling or TAT corresponds to an observed “overshoot” in the I-V response with an estimated threshold of 1.6 ± 0.2 V, in good agreement with reported electro-luminescence results for LRS devices. Resistive switching is discussed in terms of electrochemical reactions between common SiO{sub 2} defects, and specific defect energy levels are assigned to the dominant transitions in the I-V response. The overshoot response in the LRS is consistent with TAT through either the Eγ' oxygen vacancy or the hydrogen bridge defect, both of which are reported to have an effective bandgap of 1.7 eV. The SET threshold at ∼2.5 V is modeled as hydrogen release from the (Si-H){sub 2} defect to generate the hydrogen bridge, and the RESET transition is modeled as an electrochemical reaction that re-forms (SiH){sub 2}. The results provide further insights into charge transport and help identify potential switching mechanisms in SiO{sub x}-based unipolar resistive switching memory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

A rank-exploiting infinite Arnoldi algorithm for nonlinear eigenvalue problems

We consider the nonlinear eigenvalue problem M ( λ ) x = 0, where M ( λ ) is a large parameter-dependent matrix. In several applications, M ( λ ) has a structure where the higher-order terms of its Taylor expansion have a particular low-rank structure. We propose a new Arnoldi-based algorithm that can exploit this structure. More precisely, the proposed algorithm is equivalent to Arnoldi's method applied to an operator whose reciprocal eigenvalues are solutions to the nonlinear eigenvalue problem. The iterates in the algorithm are functions represented in a particular structured vector-valued polynomial basis similar to the construction in the infinite Arnoldi method [Jarlebring, Michiels, and Meerbergen, Numer. Math., 122 (2012), pp. 169–195]. In this paper, the low-rank structure is exploited by applying an additional operator and by using a more compact representation of the functions. This reduces the computational cost associated with orthogonalization, as well as the required memory resources. The structure exploitation also provides a natural way in carrying out implicit restarting and locking without the need to impose structure in every restart. In conclusion, the efficiency and properties of the algorithm are illustrated with two large-scale problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

High-Speed Ionic Synaptic Memory Based on 2D Titanium Carbide MXene

Synaptic devices with linear high-speed switching can accelerate learning in artificial neural networks (ANNs) embodied in hardware. Conventional resistive memories however suffer from high write noise and asymmetric conductance tuning, preventing parallel programming of ANN arrays. Electrochemical random-access memories (ECRAMs), where resistive switching occurs by ion insertion into a redox-active channel, aim to address these challenges due to their linear switching and low noise. ECRAMs using 2D materials and metal oxides however suffer from slow ion kinetics, whereas organic ECRAMs enable high-speed operation but face challenges toward on-chip integration due to poor temperature stability of polymers. Here, ECRAMs using 2D titanium carbide (Ti 3 C 2 T x ) MXene that combine the high speed of organics and the integration compatibility of inorganic materials in a single high-performance device are demonstrated. These ECRAMs combine the speed, linearity, write noise, switching energy, and endurance metrics essential for parallel acceleration of ANNs, and importantly, they are stable after heat treatment needed for back-end-of-line integration with Si electronics. The high speed and performance of these ECRAMs introduces MXenes, a large family of 2D carbides and nitrides with more than 30 stoichiometric compositions synthesized to date, as promising candidates for devices operating at the nexus of electrochemistry and electronics.

2D materials↗

DOE OSTI2016

On the origin of resistive switching volatility in Ni/TiO{sub 2}/Ni stacks

Resistive switching and resistive random access memories have attracted huge interest for next generation nonvolatile memory applications, also thought to be able to overcome flash memories limitations when arranged in crossbar arrays. A cornerstone of their potential success is that the toggling between two distinct resistance states, usually a High Resistive State (HRS) and a Low Resistive State (LRS), is an intrinsic non-volatile phenomenon with the two states being thermodynamically stable. TiO{sub 2} is one of the most common materials known to support non-volatile RS. In this paper, we report a volatile resistive switching in a titanium dioxide thin film sandwiched by two nickel electrodes. The aim of this work is to understand the underlying physical mechanism that triggers the volatile effect, which is ascribed to the presence of a NiO layer at the bottom interface. The NiO layer alters the equilibrium between electric field driven filament formation and thermal enhanced ion diffusion, resulting in the volatile behaviour. Although the volatility is not ideal for non-volatile memory applications, it shows merit for access devices in crossbar arrays due to its high LRS/HRS ratio, which are also briefly discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

A eutectic dual-phase design towards superior mechanical properties of heusler-type ferromagnetic shape memory alloys

Heusler-type ferromagnetic shape memory alloys possess attractive multifunctional properties, including magnetic field induced shape memory effect, magnetoresistance and magnetocaloric effect, owing to the unique concurrent magnetic and martensitic transformations. However, these intermetallics generally exhibit intrinsic high brittleness and low strength, which severely impede their workability for processing and applicability in real use. In this study, we demonstrate a new grain refining strategy by means of eutectic solidification to improve the mechanical properties in Ni-Mn-Sn-Fe alloys. In a fully eutectic microstructure, the average γ lamellae thickness was refined to ~170 nm and the composite showed a compressive strength of 1950 MPa, ductility of 19.5%, Young’s Modulus of 38 GPa, pseudoelasticity of 3.2% and high mechanical cyclic stability. The high mechanical performance is attributed to the effect of departmentalization of the brittle Heusler alloy by the densely distributed γ phase fine lamellae in resisting crack propagation. The eutectic Heusler composite exhibited a metamagnetic phase transformation, with a magnetic entropy change of 10.2 J/kg·K and a refrigeration capacity of 168 J/kg in a field change of 5 T.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Implementation of Triply Periodic Minimal Surfaces (TPMS) as surface objects in OpenMC

Triply Periodic Minimal Surfaces (TPMS) represent a promising geometry for future fuel designs due to their significant surface-to-volume ratio, which facilitates efficient cooling of nuclear fuel, a crucial factor for safety and efficiency. Demonstrating the remarkable capabilities of TPMS fuel requires initial modeling and simulation. This paper presents an implementation of TPMS in the Monte Carlo code OpenMC, enabling reactor physics modeling of TPMS. Here, the primary advantages over traditional methods using CAD files include reduced memory requirements for computations and high-fidelity implementation. This implementation has been tested against CAD files loaded in Serpent2, yielding promising results with low biases in the $k_{\textrm{eff}}$, comparable to biases in the material balance sheet. The implementation presented in this work will be used in future reactor physics computations related to new reactor designs involving TPMS-based fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Size dependent polaronic conduction in hematite

Lithium Ion Batteries have been attracted as the major renewable energy source for all portable electronic devices because of its advantages like superior energy density, high theoretical capacity, high specific energy, stable cycling and less memory effects. Recently, α-Fe{sub 2}O{sub 3} has been considered as a potential anode material due to high specific capacity, low cost, high abundance and environmental benignity. We have synthesized α-Fe{sub 2}O{sub 3} with various sizes by using the ball milling and sol-gel procedure. Here, we report the dc conductivity measurement for the crystallite size ranging from 15 nm to 50 nm. It has been observed that the enhancement in the polaronic conductivity nearly two orders in magnitude while reducing the crystallite size from bulk into nano scale level. The enhancement in the conductivity is due to the augmented to compressive strain developed in the material which leads to pronounced decrease in the hopping length of polarons. Thus, nanocrystaline α-Fe{sub 2}O{sub 3} may be a better alternative anode material for lithium ion batteries than earlier reported systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Electrical-current-induced magnetic hysteresis in self-assembled vertically aligned L a 2 / 3 S r 1 / 3 Mn O 3 : ZnO nanopillar composites

Magnetoresistive random-access memory (MRAM) is poised to become a next-generation information storage device. Yet, many materials challenges remain unsolved before it can become a widely used memory storage solution. Among them, an urgent need is to identify a material system that is suitable for downscaling and is compatible with low-power logic applications. Self-assembled, vertically aligned La 2/3 Sr 1/3 MnO 3 : ZnO nanocomposites, in which La 2/3 Sr 1/3 MnO 3 (LSMO) matrix and ZnO nanopillars form an intertwined structure with coincident-site-matched growth occurring between the LSMO and ZnO vertical interfaces, may offer new MRAM applications by combining their superior electric, magnetic ( B ), and optical properties. Here, in this Rapid Communication, we show the results of electrical current induced magnetic hysteresis in magnetoresistance measurements in these nanopillar composites. We observe that when the current level is low, for example, 1 µA, the magnetoresistance displays a linear, negative, nonhysteretic B field dependence. Surprisingly, when a large current is used, I > 10 µA, a hysteretic behavior is observed when the B field is swept in the up and down directions. This hysteresis weakens as the sample temperature is increased. Finally, a possible spin-valve mechanism related to this electrical current induced magnetic hysteresis is proposed and discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Trends in data locality abstractions for HPC systems

The cost of data movement has always been an important concern in high performance computing (HPC) systems. It has now become the dominant factor in terms of both energy consumption and performance. Support for expression of data locality has been explored in the past, but those efforts have had only modest success in being adopted in HPC applications for various reasons. However, with the increasing complexity of the memory hierarchy and higher parallelism in emerging HPC systems, locality management has acquired a new urgency. Developers can no longer limit themselves to low-level solutions and ignore the potential for productivity and performance portability obtained by using locality abstractions. Fortunately, the trend emerging in recent literature on the topic alleviates many of the concerns that got in the way of their adoption by application developers. Data locality abstractions are available in the forms of libraries, data structures, languages and runtime systems; a common theme is increasing productivity without sacrificing performance. Furthermore, this paper examines these trends and identifies commonalities that can combine various locality concepts to develop a comprehensive approach to expressing and managing data locality on future large-scale high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Chiral symmetry breaking, entanglement, and the nucleon spin decomposition

The nucleon is naturally viewed as a bipartite system of valence spin — defined by its non-vanishing chiral charge — and non-valence or sea spin. The sea spin can be traced over to give a reduced density matrix, and it is shown that the resulting entanglement entropy acts as an order parameter of chiral symmetry breaking in the nucleon. In the large-[Formula: see text] limit, the entanglement entropy vanishes and the valence spin accounts for all of the nucleon spin, while in the limit of maximal entanglement entropy, the nucleon loses memory of the valence spin and consequently has spin dominated by the sea. The nucleon state vector in the chiral basis, fit to low-energy data, gives a valence spin content consistent with experiment and lattice QCD determinations, and has large entanglement entropy.

Astronomy & Astrophysics↗

DOE OSTI2014

Field Test of Boiler Primary Loop Temperature Controller

Beyond these initial system efficiency upgrades are an emerging class of Advanced Load Monitoring (ALM) aftermarket controllers that dynamically respond to the boiler load, with claims of 10% to 30% of fuel savings over a heating season. For hydronic boilers specifically, these devices perform load monitoring, with continuous measurement of supply and in some cases return water temperatures. Energy savings from these ALM controllers are derived from dynamic management of the boiler differential, where a microprocessor with memory of past boiler cycles prevents the boiler from firing for a period of time, to limit cycling losses and inefficient operation during perceived low load conditions. These differ from OTR controllers, which vary boiler setpoint temperatures with ambient conditions while maintaining a fixed differential. PARR installed and monitored the performance of one type of ALM controller, the M2G from Greffen Systems, at multifamily sites in the city of Chicago and its suburb Cary, IL, both with existing OTR control. Results show that energy savings depend on the degree to which boilers are over-sized for their load, represented by cycling rates. Also savings vary over the heating season with cycling rates, with greater savings observed in shoulder months. Over the monitoring period, over-sized boilers at one site showed reductions in cycling and energy consumption in line with prior laboratory studies, while less over-sized boilers at another site showed muted savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Field Test of Boiler Primary Loop Temperature Controller

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1992

Error control techniques for satellite and space communications

Worked performed during the reporting period is summarized. Construction of robustly good trellis codes for use with sequential decoding was developed. The robustly good trellis codes provide a much better trade off between free distance and distance profile. The unequal error protection capabilities of convolutional codes was studied. The problem of finding good large constraint length, low rate convolutional codes for deep space applications is investigated. A formula for computing the free distance of 1/n convolutional codes was discovered. Double memory (DM) codes, codes with two memory units per unit bit position, were studied; a search for optimal DM codes is being conducted. An algorithm for constructing convolutional codes from a given quasi-cyclic code was developed. Papers based on the above work are included in the appendix.

Costello, Daniel J., Jr.↗

NASA NTRS2002

The Fractional Step Method Applied to Simulations of Natural Convective Flows

This paper describes research done to apply the Fractional Step Method to finite-element simulations of natural convective flows in pure liquids, permeable media, and in a directionally solidified metal alloy casting. The Fractional Step Method has been applied commonly to high Reynold's number flow simulations, but is less common for low Reynold's number flows, such as natural convection in liquids and in permeable media. The Fractional Step Method offers increased speed and reduced memory requirements by allowing non-coupled solution of the pressure and the velocity components. The Fractional Step Method has particular benefits for predicting flows in a directionally solidified alloy, since other methods presently employed are not very efficient. Previously, the most suitable method for predicting flows in a directionally solidified binary alloy was the penalty method. The penalty method requires direct matrix solvers, due to the penalty term. The Fractional Step Method allows iterative solution of the finite element stiffness matrices, thereby allowing more efficient solution of the matrices. The Fractional Step Method also lends itself to parallel processing, since the velocity component stiffness matrices can be built and solved independently of each other. The finite-element simulations of a directionally solidified casting are used to predict macrosegregation in directionally solidified castings. In particular, the finite-element simulations predict the existence of 'channels' within the processing mushy zone and subsequently 'freckles' within the fully processed solid, which are known to result from macrosegregation, or what is often referred to as thermo-solutal convection. These freckles cause material property non-uniformities in directionally solidified castings; therefore many of these castings are scrapped. The phenomenon of natural convection in an alloy under-going directional solidification, or thermo-solutal convection, will be explained. The development of the momentum and continuity equations for natural convection in a fluid, a permeable medium, and in a binary alloy undergoing directional solidification will be presented. Finally, results for natural convection in a pure liquid, natural convection in a medium with a constant permeability, and for directional solidification will be presented.

Westra, Douglas G.↗

DOE OSTI2014

Building America Case Study: Advanced Boiler Load Monitoring Controllers, Chicago, Illinois (Fact Sheet)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Machine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US

Incomplete representations of physical processes often lead to structural errors in process-based (PB) hydrologic models. Machine learning (ML) algorithms can reduce streamflow modeling errors but do not enforce physical consistency. As a result, ML algorithms may be unreliable if used to provide future hydroclimate projections where climates and land use patterns are outside the range of training data. Here we test hybrid models built by integrating PB model outputs with a ML algorithm known as Long Short-Term Memory (LSTM) network on their ability to simulate streamflow in 531 catchments representing diverse conditions across the Conterminous United States. Model performance of hybrid models as measured by Nash-Sutcliffe efficiency (NSE) improved relative to standalone PB and LSTM models. More importantly, hybrid models provide highest improvement in catchments where PB models fail completely (i.e., NSE < 0). However, all models performed poorly in catchments with extended low flow periods, suggesting need for additional research.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Unique properties of SBN and their use in a layered optical memory

Holographic storage experiments using crystal Sr(0.75)Ba(0.25)Nb2O6 (SBN 75/25) as a volume-phase holographic medium show that this material is the most sensitive crystalline storage medium yet discovered. An exposure level of 0.003 J/sq cm at 0.488 micron produces a 1% diffraction efficiency in a 5-mm length of crystal. In addition to high recording sensitivity, SBN 75/25 exhibits interesting electric-field induced effects that include electric-field enhanced recording sensitivity and voltage-switchable latent-to-active holographic reconstruction efficiency. These effects are explained in terms of drift and diffusion of photoionized carriers coupled with the nonlinear electrooptic behavior characteristic of this low Curie temperature ferroelectric crystal. A mechanism is proposed that correlates the observed electrically controlled holographic response with the dielectric behavior of the crystal. These interesting effects are used to implement a novel, layered optical memory having no moving parts and having electrical access for writing or reading selected layers.

Thaxter, J. B.↗