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At least 667 records · Page 37

Detailed investigation of defect states in Erbium doped In2O3 thin films

Highlights: • SIMS analysis confirmed the doping of Er into the In{sub 2}O{sub 3} TF. • I–V loop analysis gives reduced current memory window for In{sub 2}O{sub 3}:Er TF based device. • High ideality factor was determined at low temperature and explained. • Defect related photoconductivity was confirmed from low temperature measurement. • 10 K temporal response of the Au/In{sub 2}O{sub 3}:Er/Si confirmed removal of oxygen defects. - Abstract: Erbium doped Indium Oxide (In{sub 2}O{sub 3}:Er) thin films (TFs) were synthesised by spin-on technique. Secondary Ion Mass Spectrometry confirmed that Er is incorporated into the In{sub 2}O{sub 3} lattice and formed an In-O-Er layer. The current–voltage loop produced a lower loop current window of ∼3.6 × 10{sup −4} A for In{sub 2}O{sub 3}:Er TF based devices. The Au/In{sub 2}O{sub 3}:Er/Si Schottky devices have lower ideality factor (∼6) and higher barrier height (∼0.63 eV) at 300 K than Au/In{sub 2}O{sub 3}/Si control samples. A blue shift in the main band-gap (∼50 nm) was calculated for In{sub 2}O{sub 3}:Er TFs from 10 K photoresponse. The Au/In{sub 2}O{sub 3}:Er/Si samples show higher photosensitivity in the temperature range 10 K–300 K and maximum (∼15 times) in the UV region at 10 K as compared to the Au/In{sub 2}O{sub 3}/Si devices. In addition, the Au/In{sub 2}O{sub 3}:Er/Si devices have better UV to visible cut-off ratio (∼3 times). Excellent temporal responses were recorded for Au/In{sub 2}O{sub 3}:Er/Si in the UV region as compared to Au/In{sub 2}O{sub 3}/Si.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Charge Condensation and Lattice Coupling Drives Stripe Formation in Nickelates

Revealing the predominant driving force behind symmetry breaking in correlated materials is sometimes a formidable task due to the intertwined nature of different degrees of freedom. This is the case for La 2–x Sr x NiO 4+δ , in which coupled incommensurate charge and spin stripes form at low temperatures. Here, we use resonant x-ray photon correlation spectroscopy to study the temporal stability and domain memory of the charge and spin stripes in La 2–x Sr x NiO 4+δ . Although spin stripes are more spatially correlated, charge stripes maintain a better temporal stability against temperature change. More intriguingly, charge order shows robust domain memory with thermal cycling up to 250 K, far above the ordering temperature. Furthermore, these results demonstrate the pinning of charge stripes to the lattice and that charge condensation is the predominant factor in the formation of stripe orders in nickelates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Approximate l-Fold Cross-Validation with Least Squares SVM and Kernel Ridge Regression

Kernel methods have difficulties scaling to large modern data sets. The scalability issues are based on computational and memory requirements for working with a large matrix. These requirements have been addressed over the years by using low-rank kernel approximations or by improving the solvers' scalability. However, Least Squares Support Vector Machines (LS-SVM), a popular SVM variant, and Kernel Ridge Regression still have several scalability issues. In particular, the O(n^3) computational complexity for solving a single model, and the overall computational complexity associated with tuning hyper parameters are still major problems. We address these problems by introducing an O(nlog n) approximate l-fold cross-validation method that uses a multi-level circulant matrix to approximate the kernel. In addition, we prove our algorithm's computational complexity and present empirical runtimes on data sets with approximately one million data points. We also validate our approximate method's effectiveness at selecting hyper parameters on real world and standard benchmark data sets. Lastly, we provide experimental results on using a multi level circulant kernel approximation to solve LS-SVM problems with hyper parameters selected using our method.

Computer Science↗

Performance Analysis and Optimal Node-aware Communication for Enlarged Conjugate Gradient Methods

Krylov methods are a key way of solving large sparse linear systems of equations but suffer from poor strong scalability on distributed memory machines. Furthermore, this is due to high synchronization costs from large numbers of collective communication calls alongside a low computational workload. Enlarged Krylov methods address this issue by decreasing the total iterations to convergence, an artifact of splitting the initial residual and resulting in operations on block vectors. In this article, we present a performance study of an enlarged Krylov method, Enlarged Conjugate Gradients (ECG), noting the impact of block vectors on parallel performance at scale. Most notably, we observe the increased overhead of point-to-point communication as a result of denser messages in the sparse matrix-block vector multiplication kernel. Additionally, we present models to analyze expected performance of ECG, as well as motivate design decisions. Most importantly, we introduce a new point-to-point communication approach based on node-aware communication techniques that increases efficiency of the method at scale.

97 MATHEMATICS AND COMPUTING↗

Disorder, interactions, and their interplay in novel narrow-gap Dirac materials and Weyl semimetals

Progress of the modern day condensed matter physics is to a large extent driven by the synthesis of new materials, advances in their experimental characterization and theoretical description. Recent discoveries of novel gapless Weyl semimetals, such as NaBi,CdAs, and BiTe-based films, in which magnetic dopants essentially suppress the gap, have added to the family of graphene and topological insulators actively investigated over the past decade. With the field of novel semimetals rapidly maturing, its focus necessarily shifts from demonstrations of the feasibility of such materials to their quantitative characterization. While the transport and optical properties of graphene and topological insulators are well captured within the picture of free non-interacting electrons, gapless 3D Weyl semimetals and narrow-gap 2D semiconductors with Dirac spectrum are known to be extremely susceptible to disorder and electron-electron interactions. This susceptibility obscures the manifestations of nontrivial band structure -- like quantum anomalous Hall effect -- of the new topological materials. Among particular projects to be addressed are: 1) optical conductivity of 3D gapless Dirac fermions in the presence of smooth disorder, 2) interplay of disorder and Coulomb interactions in the spectral properties of such fermions, 3) formation and structure of the impurity band with Coulomb supercritical clusters, 4) Coulomb interaction-driven renormalization of the electron spectrum and of the transport response in the presence of strong magnetic field, 5) instanton approach to the disorder-induced fluctuation states in zero-gap 3D materials, and 6) the role of disorder in quantum anomalous Hall effect. The proposal relies upon the investigators' previous broad expertise in interacting and disordered electron systems. The methods to be employed include perturbative diagrammatic technique, non-perturbative instanton and self-consistent approximations, hydrodynamics of electron liquid. Both analytical as well as numerical approaches are to be employed. The anticipated broader outcome of the proposal includes gaining an in-depth understanding of the interplay of the disorder and interactions under the conditions when this interplay has the most dramatic impact on observables. Traditionally, interaction effects are among the most challenging and interesting problems of condensed matter physics. Similarly, disordered systems typically present very difficult but extremely rich problems in the description of various materials. Importantly, understanding the spectral and transport properties of such materials not only presents the fundamental objective, but is also of particular interest for many applications, such as computation, memory, optics, plasmonics. In particular realization of the quantum anomalous Hall effect may lead to the development of low-power-consumption electronics. Indeed, a major constraint for practical use of the quantum Hall effect is limited by the requirement of the quantizing magnetic field. At the same time, the quantum anomalous Hall effect samples exhibit non-dissipative edge quantum transport in a zero magnetic field.

36 MATERIALS SCIENCE↗

Computing the Properties of Matter with Leadership Computing Resources (Closeout Report for DE-SC0018121)

In order to add more capabilities to Halide, we have designed a new framework called Tiramisu and integrated this framework into Halide. Since Tiramisu enables Halide to target heterogeneous architectures, our development efforts have been refocused on Tiramisu. Most high-performance computer systems today are complex and increasingly heterogeneous; they may have CPUs, GPUs and FPGAs. Achieving best performance requires taking full advantage of all these different architectures. To address this issue, we have designed Tiramisu, an optimization framework that enables Halide (and other DSLs) to target heterogeneous architectures. Tiramisu is an optimization framework that takes as input a high level, architecture-independent representation of code and a set of scheduling and data mapping commands that guide code transformation. The input can either be generated by a domain-specific language (DSL) compiler such as Halide or directly written by a programmer. Tiramisu then applies the user-specified code and data-layout transformations and generates an architecture-specific, low-level intermediate representation (IR) that takes advantage of modern architectural features such as multicore parallelism, non-uniform memory (NUMA) hierarchies, clusters, and accelerators like GPUs and FPGAs. We integrated Tiramisu within Halide and implemented a representative set of benchmarks to evaluate this integration. Tiramisu is now open source and is available for public use (http://tiramisu-compiler.org/). A paper about Tiramisu was published, it shows that Tiramisu extends Halide with many new capabilities and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide. In addition to making Tiramisu more robust, we have used Tiramisu to implement a set of representative tensor operation for constructing baryon building blocks required for multi baryon contractions in LQCD. In order to implement this code, we needed to generalize Tiramisu in two ways: first we needed to support indirect array accesses, and second, we needed to add support for complex numbers to Tiramisu. The code generated by Tiramisu is 6x faster than the reference code. Our efforts towards an MPI based multi-node version of tiramisu have matured and the resulting code scales well on multiple nodes (tests up to 512 KNL nodes have been undertaken).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensor Fish: an autonomous sensor package for characterizing complex flow fields and fish passage

Fish passing through dams or other hydraulic structures may be injured or killed despite advances in turbine design, project operations, and other fish bypass systems. The Sensor Fish (SF) device is an autonomous sensor package that characterizes the physical conditions and stressors to which fish are exposed during passage through hydro facilities. It was designed to move passively as a neutrally buoyant object through severe hydraulic environments, while collecting high-resolution sensor data. Since its first generation1, the SF device has been successfully deployed in many fish passage studies and has evolved to be a major tool for characterizing fish passage conditions during fish passage in the Columbia River Basin. To better accelerate hydropower development, the U.S. Department of Energy Water Power Program provided funding to develop a new generation (Gen 2 SF) to incorporate more capabilities and accommodate a wider range of users over a broader range of turbine designs and operating environments. The Gen 2 SF (Figure 1) is approximately the size and density of a yearling salmon smolt and is nearly neutrally buoyant. It contains three-dimensional (3D) rotation sensors, 3D linear acceleration sensors, a pressure sensor, a temperature sensor, a 3D orientation sensor, a radiofrequency (RF) transmitter, and a recovery module2. A low-power microcontroller collects data from the sensors and stores up to 5 min of data on internal flash memory at a sampling frequency of 2048 Hz. The recovery module makes the SF positively buoyant after a pre-programmed period of time, causing it to float to the surface for recovery.

Sensor Fish↗

The organic redox transistor for neuromorphic computing

Inspired by the in-memory computing architectures of biological systems, neuromorphic computing using crossbar arrays of artificial synapses based on non-volatile memory (NVM) devices with variable conductances has emerged as a new paradigm to enable massively parallel and ultra-low power computing hardware for data centric applications. Although inference has been demonstrated successfully using crossbars based on a variety of NMV technologies, efficient learning and scaling to large arrays (>10 6 elements) remains a challenge due to the synaptic elements' non-ideal electrical characteristics which degrades ANN accuracy. A further challenge is that in the conductive state memristors draw large currents >μA resulting in significant voltage drops in the interconnect wires and increased probability of failure in scaled arrays. We suggest the organic polymer redox transistor (RT) is an alternate approach that could solve many of these challenges, enabling both inference and parallel outer product updates, as recently demonstrated by Fuller et al. An RT consists of redox-active channel and gate electrodes in contact with a liquid or solid electrolyte. lon insertion through the electrolyte controls the channel electronic conductivity, while electron transfer through an external circuit maintains overall charge neutrality. Unlike a rechargeable battery, in the RT the voltage built-up across the electrolyte is kept to a minimum (typically <100 mV) by using the same material for the gate and channel. Elimination of the voltage offset simplifies integration of the RT into programmable arrays by enabling the use of various selectors. RTs based on inorganic and organic materials have been recently demonstrated with conductance tuning occurring at potentials of just a few mV and hundreds to thousands of linearly and symmetrically programmable conductance states, enabling near ideal accuracy in neural network simulations. Introduced in the 1980's, redox transistors with metallic gate electrodes and organic channel materials, also known as organic electrochemical transistors (OECTs), have been explored for a variety of applications such as chem- and bio-sensing, neural interfaces, and low cost printed circuits. A typical channel material for OECTs is the conducting polymer poly(3,4-ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS). PEDOT is a p-type semiconducting polymer with mobile positively charged polarons that hop chain-to-chain.

Talin, Albert Alec↗

Manganese oxide microswitch for electronic memory based on neural networks

A solid-state, resistance tailorable, programmable-once, binary, nonvolatile memory switch based on manganese oxide thin films is reported. MnO(x) exhibits irreversible memory switching from conducting (on) to insulating (off) state, with the off and on resistance ratio of greater than 10,000. The switching mechanism is current-triggered chemical transformation of a conductive MnO(2-Delta) to an insulating Mn2O3 state. The energy required for switching is of the order of 4-20 nJ/sq micron. The low switching energy, stability of the on and off states, and tailorability of the on state resistance make these microswitches well suited as programmable binary synapses in electronic associative memories based on neural network models.

Ramesham, R.↗

Inadvertently programmed bits in Samsung 128 Mbit flash devices: a flaky investigation

JPL's X2000 avionics design pioneers new territory by specifying a non-volatile memory (NVM) board based on flash memories. The Samsung 128Mb device chosen was found to demonstrate bit errors (mostly program disturbs) and block-erase failures that increase with cycling. Low temperature, certain pseudo- random patterns, and, probably, higher bias increase the observable bit errors. An experiment was conducted to determine the wearout dependence of the bit errors to 100k cycles at cold temperature using flight-lot devices (some pre-irradiated). The results show an exponential growth rate, a wide part-to-part variation, and some annealing behavior.

flash memory program disturb wearout erase fail re↗

SpaceCube Mini

This version of the SpaceCube will be a full-fledged, onboard space processing system capable of 2500+ MIPS, and featuring a number of plug-andplay gigabit and standard interfaces, all in a condensed 3x3x3 form factor [less than 10 watts and less than 3 lb (approximately equal to 1.4 kg)]. The main processing engine is the Xilinx SIRF radiation- hardened-by-design Virtex-5 FX-130T field-programmable gate array (FPGA). Even as the SpaceCube 2.0 version (currently under test) is being targeted as the platform of choice for a number of the upcoming Earth Science Decadal Survey missions, GSFC has been contacted by customers who wish to see a system that incorporates key features of the version 2.0 architecture in an even smaller form factor. In order to fulfill that need, the SpaceCube Mini is being designed, and will be a very compact and low-power system. A similar flight system with this combination of small size, low power, low cost, adaptability, and extremely high processing power does not otherwise exist, and the SpaceCube Mini will be of tremendous benefit to GSFC and its partners. The SpaceCube Mini will utilize space-grade components. The primary processing engine of the Mini is the Xilinx Virtex-5 SIRF FX-130T radiation-hardened-by-design FPGA for critical flight applications in high-radiation environments. The Mini can also be equipped with a commercial Xilinx Virtex-5 FPGA with integrated PowerPCs for a low-cost, high-power computing platform for use in the relatively radiation- benign LEOs (low-Earth orbits). In either case, this version of the Space-Cube will weigh less than 3 pounds (.1.4 kg), conform to the CubeSat form-factor (10x10x10 cm), and will be low power (less than 10 watts for typical applications). The SpaceCube Mini will have a radiation-hardened Aeroflex FPGA for configuring and scrubbing the Xilinx FPGA by utilizing the onboard FLASH memory to store the configuration files. The FLASH memory will also be used for storing algorithm and application code for the PowerPCs and the Xilinx FPGA. In addition, it will feature highspeed DDR SDRAM (double data rate synchronous dynamic random-access memory) to store the instructions and data of active applications. This version will also feature SATA-II and Gigabit Ethernet interfaces. Furthermore, there will also be general-purpose, multi-gigabit interfaces. In addition, the system will have dozens of transceivers that can support LVDS (low-voltage differential signaling), RS-422, or SpaceWire. The SpaceCube Mini includes an I/O card that can be customized to meet the needs of each mission. This version of the SpaceCube will be designed so that multiple Minis can be networked together using SpaceWire, Ethernet, or even a custom protocol. Scalability can be provided by networking multiple SpaceCube Minis together. Rigid-Flex technology is being targeted for the construction of the SpaceCube Mini, which will make the extremely compact and low-weight design feasible. The SpaceCube Mini is designed to fit in the compact CubeSat form factor, thus allowing deployment in a new class of missions that the previous SpaceCube versions were not suited for. At the time of this reporting, engineering units should be available in the summer 2012.

Michael Lin↗

Multiferroic and Related Hysteretic Behavior in Ferromagnetic Shape Memory Alloys

In this work, we combine a Ginzburg–Landau model for a ferroelastic transition with the theory of micromagnetism to study the magnetostructural behavior leading to multicaloric effects in ferromagnetic shape memory alloys. We analyze the ferroelastic transition under different conditions of temperature, stress and magnetic field and establish the corresponding phase diagram. On the one hand, our results show that the proper combination of both fields may be used to reduce the transition hysteresis and thus improve the reversibility of the related elastocaloric effects, superelasticity and stress-mediated magnetocaloric effects. On the other hand, the stress-free magnetic field-driven and thermally driven magnetostructural evolution provides physical insight into the low-temperature field-induced domain reorientation, from which we derive strategies to modify the operational temperature ranges and thus the corresponding (magnetic) shape-memory effect.

36 MATERIALS SCIENCE↗

NEPP non-volatile memory : FY09 summary report

This report documents the activities and results of the fiscal year 2009 (FY09) funding for the NASA Electronic Parts and Packaging (NEPP) program for non-volatile memory (NVM) devices. The FY09 task was divided into two main efforts: 1. Development of in-house measurement capability for flash devices 2. Reliability characterization of multi-level vs. single-level flash devices The FY09 NEPP Non Volatile Memory study was organized into these two sections in recognition of the continued and increasing importance of NVM to NASA. All NASA missions use NVM for boot code storage and some limited data archiving. Space-grade NVM has lagged commercial NVM development by many orders of magnitude, however. This gap in density only continues to increase as space-grade memories remain constant in the 1–16 Mbit levels, while commercial flash-based devices shrink in size and double in capacity every 18 months. Commercial flash devices are now at the 32 Gbit level, 10,000 times denser than current NASA NVM. This FY marks the beginning of a significant technological transition in NVM for NASA. The aggressive scaling of commercial NVMs has, as a by-product, made some of the flash devices radiation-tolerant enough to be at least considered for low-level radiation environment missions [Irom 2008]. This NEPP task is focused on understanding the reliability and potential future applications of such highly scaled flash memories.

Heidecker, Jason↗

Scalable Quantum Monte Carlo Method for Polariton Chemistry via Mixed Block Sparsity and Tensor Hypercontraction Method

We present a reduced-scaling auxiliary-field quantum Monte Carlo (AFQMC) framework designed for large molecular systems and ensembles, with or without coupling to optical cavities. Our approach leverages the natural block sparsity of the Cholesky decomposition (CD) of electron repulsion integrals in molecular ensembles and employs tensor hypercontraction (THC) to efficiently compress low-rank Cholesky blocks. By representing the Cholesky vectors in a mixed format, keeping high-rank blocks in block-sparse form and compressing low-rank blocks with THC, we reduce the scaling of exchange-energy evaluation from quartic to robust cubic in the number of molecular orbitals N, while lowering memory from cubic toward quadratic. Benchmark analyses on one-, two-, and three-dimensional molecular ensembles (up to ∼1,200 orbitals) show that (a) the number of nonzeros in Cholesky tensors grows linearly with system size across dimensions; (b) the average numerical rank increases sublinearly and does not saturate at these sizes; and (c) rank heterogeneity─some blocks nearly full rank and many low rank, naturally motivates the proposed mixed block sparsity and THC scheme for efficient calculation of exchange energy. In conclusion, we demonstrate that the mixed scheme yields cubic wall-time scaling with favorable prefactors and preserves AFQMC accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shape-Memory-Alloy-Based Deicing System Developed

Ice buildup on aircraft leading edge surfaces has historically been a problem. Most conventional deicing systems rely either on surface heating to melt the accreted ice or pneumatic surface inflation to mechanically debond the ice. Deicers that rely solely on surface heating require large amounts of power. Pneumatic deicers usually cannot remove thin layers of ice and lack durability. Thus, there is a need for an advanced, low-power ice protection system. As part of the NASA Small Business and Innovation Research (SBIR) program, Innovative Dynamics, Inc., developed an aircraft deicing system that utilizes the properties of Shape Memory Alloys (SMA). The SMA-based system has achieved promising improvements in energy efficiency and durability over more conventional deicers. When they are thermally activated, SMA materials change shape; this is analogous to a conventional thermal expansion. The thermal input is currently applied via conventional technology, but there are plans to implement a passive thermal input that is supplied from the energy transfer due to the formation of the ice itself. The actively powered deicer was tested in the NASA Lewis Icing Research Tunnel on a powered rotating rig in early 1995. The system showed promise, deicing both rime and glaze ice shapes as thin as 1/8 in. The first prototype SMA deicer reduced power usage by 45 percent over existing electrothermal systems. This prototype system was targeted for rotorcraft system development. However, there are current plans underway to develop a fixed-wing version of the deicer.

Source record↗

Ice as a Construction Material

This presentation shows how water and ice can enable exceptionally simple ways to construct structures in deep space. Practicality is underscored by applying advanced tank methods being developed for Mars missions. Water or ice is now known to be present or abundant on most objects in the solar system, starting with the planet Mercury. Thermal processes alone can be used to melt ice . The cold of space can refreeze water back into ice. The anomalous low vapor pressure of water, about 7 mm Hg, permits bladder containers. Tanks or bladders made with modern polymer fiber and film can exhibit very small (<0.1 %) equivalent tankage and ullage fractions and thus hold thousands of tons of water per ton bladder. Injecting water into a bladder whose shape when inflated is the desired final shape, such as a space vehicle, provides a convenient way to construct large structures. In space, structures of 1O,OOO-T mass become feasible because the bladder mass is low enough to be launched. The bladder can weigh 1OOO times less than its contents, or 10 T. The bladder would be packed like a parachute. Shaped memory materials and/or gas inflation could reestablish the desired structure shape after unpacking. The water comes from space resources. An example examines construction of torus space vehicle with 100-m nominal dimension. People would live inside the torus. A torus, like a tire on an automobile, would spin and provide synthetic gravity at its inner surface. A torus of order 100 m across would provide a gravity with gradients low enough to mitigate against vertigo.

Zuppero, Anthony↗

MetaStrider: Architectures for Scalable Memory-centric Reduction of Sparse Data Streams

Reduction is an operation performed on the values of two or more key-value pairs that share the same key. Reduction of sparse data streams finds application in a wide variety of domains such as data and graph analytics, cybersecurity, machine learning, and HPC applications. However, these applications exhibit low locality of reference, rendering traditional architectures and data representations inefficient. This article presents MetaStrider, a significant algorithmic and architectural enhancement to the state-of-the-art, SuperStrider. Furthermore, these enhancements enable a variety of parallel, memory-centric architectures that we propose, resulting in demonstrated performance that scales near-linearly with available memory-level parallelism.

97 MATHEMATICS AND COMPUTING↗

Quantifying data retention of perpendicular spin-transfer-torque magnetic random access memory chips using an effective thermal stability factor method

The thermal stability of perpendicular Spin-Transfer-Torque Magnetic Random Access Memory (STT-MRAM) devices is investigated at chip level. Experimental data are analyzed in the framework of the Néel-Brown model including distributions of the thermal stability factor Δ. We show that in the low error rate regime important for applications, the effect of distributions of Δ can be described by a single quantity, the effective thermal stability factor Δ{sub eff}, which encompasses both the median and the standard deviation of the distributions. Data retention of memory chips can be assessed accurately by measuring Δ{sub eff} as a function of device diameter and temperature. We apply this method to show that 54 nm devices based on our perpendicular STT-MRAM design meet our 10 year data retention target up to 120 °C.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗