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At least 1,279 records · Page 71

Emergent ferroelectricity in subnanometer binary oxide films on silicon

The critical size limit of voltage-switchable electric dipoles has extensive implications for energy-efficient electronics, underlying the importance of ferroelectric order stabilized at reduced dimensionality. Here, we report on the thickness-dependent antiferroelectric-to-ferroelectric phase transition in zirconium dioxide (ZrO 2 ) thin films on silicon. The emergent ferroelectricity and hysteretic polarization switching in ultrathin ZrO 2 , conventionally a paraelectric material, notably persists down to a film thickness of 5 angstroms, the fluorite-structure unit-cell size. This approach to exploit three-dimensional centrosymmetric materials deposited down to the two-dimensional thickness limit, particularly within this model fluorite-structure system that possesses unconventional ferroelectric size effects, offers substantial promise for electronics, demonstrated by proof-of-principle atomic-scale nonvolatile ferroelectric memory on silicon. Additionally, it is also indicative of hidden electronic phenomena that are achievable across a wide class of simple binary materials.

42 ENGINEERING↗

Potential of minicomputer/array-processor system for nonlinear finite-element analysis

The potential of using a minicomputer/array-processor system for the efficient solution of large-scale, nonlinear, finite-element problems is studied. A Prime 750 is used as the host computer, and a software simulator residing on the Prime is employed to assess the performance of the Floating Point Systems AP-120B array processor. Major hardware characteristics of the system such as virtual memory and parallel and pipeline processing are reviewed, and the interplay between various hardware components is examined. Effective use of the minicomputer/array-processor system for nonlinear analysis requires the following: (1) proper selection of the computational procedure and the capability to vectorize the numerical algorithms; (2) reduction of input-output operations; and (3) overlapping host and array-processor operations. A detailed discussion is given of techniques to accomplish each of these tasks. Two benchmark problems with 1715 and 3230 degrees of freedom, respectively, are selected to measure the anticipated gain in speed obtained by using the proposed algorithms on the array processor.

Strohkorb, G. A.↗

Implementation of a fast digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. A Hughes liquid crystal light valve, the residue arithmetic representation, and a holographic optical memory are used to construct position coded optical look-up tables. All operations are performed in effectively one light valve response time with a potential for a high information density.

Habiby, Sarry F.↗

Support of Multidimensional Parallelism in the OpenMP Programming Model

OpenMP is the current standard for shared-memory programming. While providing ease of parallel programming, the OpenMP programming model also has limitations which often effect the scalability of applications. Examples for these limitations are work distribution and point-to-point synchronization among threads. We propose extensions to the OpenMP programming model which allow the user to easily distribute the work in multiple dimensions and synchronize the workflow among the threads. The proposed extensions include four new constructs and the associated runtime library. They do not require changes to the source code and can be implemented based on the existing OpenMP standard. We illustrate the concept in a prototype translator and test with benchmark codes and a cloud modeling code.

Jin, Hao-Qiang↗

Performance Bounds on Two Concatenated, Interleaved Codes

A method has been developed of computing bounds on the performance of a code comprised of two linear binary codes generated by two encoders serially concatenated through an interleaver. Originally intended for use in evaluating the performances of some codes proposed for deep-space communication links, the method can also be used in evaluating the performances of short-block-length codes in other applications. The method applies, more specifically, to a communication system in which following processes take place: At the transmitter, the original binary information that one seeks to transmit is first processed by an encoder into an outer code (Co) characterized by, among other things, a pair of numbers (n,k), where n (n > k)is the total number of code bits associated with k information bits and n k bits are used for correcting or at least detecting errors. Next, the outer code is processed through either a block or a convolutional interleaver. In the block interleaver, the words of the outer code are processed in blocks of I words. In the convolutional interleaver, the interleaving operation is performed bit-wise in N rows with delays that are multiples of B bits. The output of the interleaver is processed through a second encoder to obtain an inner code (Ci) characterized by (ni,ki). The output of the inner code is transmitted over an additive-white-Gaussian- noise channel characterized by a symbol signal-to-noise ratio (SNR) Es/No and a bit SNR Eb/No. At the receiver, an inner decoder generates estimates of bits. Depending on whether a block or a convolutional interleaver is used at the transmitter, the sequence of estimated bits is processed through a block or a convolutional de-interleaver, respectively, to obtain estimates of code words. Then the estimates of the code words are processed through an outer decoder, which generates estimates of the original information along with flags indicating which estimates are presumed to be correct and which are found to be erroneous. From the perspective of the present method, the topic of major interest is the performance of the communication system as quantified in the word-error rate and the undetected-error rate as functions of the SNRs and the total latency of the interleaver and inner code. The method is embodied in equations that describe bounds on these functions. Throughout the derivation of the equations that embody the method, it is assumed that the decoder for the outer code corrects any error pattern of t or fewer errors, detects any error pattern of s or fewer errors, may detect some error patterns of more than s errors, and does not correct any patterns of more than t errors. Because a mathematically complete description of the equations that embody the method and of the derivation of the equations would greatly exceed the space available for this article, it must suffice to summarize by reporting that the derivation includes consideration of several complex issues, including relationships between latency and memory requirements for block and convolutional codes, burst error statistics, enumeration of error-event intersections, and effects of different interleaving depths. In a demonstration, the method was used to calculate bounds on the performances of several communication systems, each based on serial concatenation of a (63,56) expurgated Hamming code with a convolutional inner code through a convolutional interleaver. The bounds calculated by use of the method were compared with results of numerical simulations of performances of the systems to show the regions where the bounds are tight (see figure).

Moision, Bruce↗

Dynamic Simulation with on the fly Doppler Broadening treatment in RMC

In conventional transient analysis, thermal hydraulics calculations are generally coupled to deterministic neutronics solvers. Due to the limited accuracy of deterministic methods and the rapid development of computer power, Monte Carlo neutronics calculations have received increasing attention nowadays. One of challenges for Monte Carlo methods coupled to thermal hydraulics calculations is the temperature dependent cross sections. Taking the detailed temperature distribution feedback into account, each nuclide may be in a large range of temperatures, pre-generated libraries at every temperature point are no longer applicable owing to unaffordable memory footprint. Different solutions have been proposed to deal with this problem. TMS, accounting for Doppler broadening effect by the explicit treatment of thermal motion, was used to model fast transients in Serpent 2. Stochastic mixing, using two sets of libraries for each nuclide and mixing them to get the correct temperature, was used in transient analysis by Sjenitzer and Hoogenboom. Besides, there are other on the fly Doppler broadening methods being developed, including series expansion of cross sections, multipole representation, different integration algorithms based on Doppler broadening equation. In this paper, on the fly Doppler broadening treatment based on integration algorithms was applied to transient calculation in Reactor Monte Carlo code RMC . In the following section, the integration algorithms implemented and dynamic simulation method in RMC is briefly introduced. Finally, a pure physical transient fuel assembly model was chosen for numerical validation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Progression-regression effects in tracking repeated patterns

Subjects used a position control system to perform compensatory tracking of a repeated input pattern. The input pattern was 20 seconds in duration and was either an arctangent function or the sum of two sine waves. Tracking error decreased with practice and increased with the addition of a concurrent memory task. The shape of the ensemble-average tracking error resembled the shape of the input velocity signal throughout these changes in performance. Regression analyses were used to parameterize these effects and compare these results with the predictions of several conceptualizations of perceptual-motor learning.

Jagacinski, R. J.↗

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

The formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗

Analysis of memory use for improved design and compile-time allocation of local memory

Trace analysis techniques are used to study memory referencing behavior for the purpose of designing local memories and determining how to allocate them for data and instructions. In an attempt to assess the inherent behavior of the source code, the trace analysis system described here reduced the effects of the compiler and host architecture on the trace by using a technical called flattening. The variables in the trace, their associated single-assignment values, and references are histogrammed on the basis of various parameters describing memory referencing behavior. Bounds are developed specifying the amount of memory space required to store all live values in a particular histogram class. The reduction achieved in main memory traffic by allocating local memory is specified for each class.

Mcniven, Geoffrey D.↗

Oxygen plasma immersion ion implantation treatment to enhance data retention of tungsten nanocrystal nonvolatile memory

Data retention characteristics of tungsten nanocrystal (W-NC) memory devices using an oxygen plasma immersion ion implantation (PIII) treatment are investigated. With an increase of oxygen PIII bias voltage and treatment time, the capacitance–voltage hysteresis memory window is increased but the data retention characteristics become degraded. High-resolution transmission electron microscopy images show that this poor data retention is a result of plasma damage on the tunneling oxide layer, which can be prevented by lowering the bias voltage to 7 kV. In addition, by using the elevated temperature retention measurement technique, the effective charge trapping level of the WO{sub 3} film surrounding the W-NCs can be extracted. This measurement reveals that a higher oxygen PIII bias voltage and treatment time induces more shallow traps within the WO{sub 3} film, degrading the retention behavior of the W-NC memory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dynamical Evolution of Meteoroid Streams, Developments Over the Last 30 Years

As soon as reliable methods for observationally determining the heliocentric orbits of meteoroids and hence the mean orbit of a meteoroid stream in the 1950s and 60s, astronomers strived to investigate the evolution of the orbit under the effects of gravitational perturbations from the planets. At first, the limitations in the capabilities of computers, both in terms of speed and memory, placed severe restrictions on what was possible to do. As a consequence, secular perturbation methods, where the perturbations are averaged over one orbit became the norm. The most popular of these is the Halphen- Goryachev method which was used extensively until the early 1980s. The main disadvantage of these methods lies in the fact that close encounter can be missed, however they remain useful for performing very long-term integrations. Direct integration methods determine the effects of the perturbing forces at many points on an orbit. This give a better picture of the orbital evolution of an individual meteoroid, but many meteoroids have to be integrated in order to obtain a realistic picture of the evolution of a meteoroid stream. The notion of generating a family of hypothetical meteoroids to represent a stream and directly integrate the motion of each was probably first used by Williams Murray & Hughes (1979), to investigate the Quadrantids. Because of computing limitations, only 10 test meteoroids were used. Only two years later, Hughes et. al. (1981) had increased the number of particles 20-fold to 200 while after a further year, Fox Williams and Hughes used 500 000 test meteoroids to model the Geminid stream. With such a number of meteoroids it was possible for the first time to produce a realistic cross-section of the stream on the ecliptic. From that point on there has been a continued increase in the number of meteoroids, the length of time over which integration is carried out and the frequency with which results can be plotted so that it is now possible to produce moving images of the stream. As a consequence, over recent years, emphasis has moved to considering stream formation and the role fragmentation plays in this.

Williams, I. P.↗

Complexin2 modulates working memory-related neural activity in patients with schizophrenia

The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 ( CPLX2 ) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms by investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. In this paper, we examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Finally, since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as ‘neural inefficiency,’ these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.

60 APPLIED LIFE SCIENCES↗

Joule Heating Effect on Field-Free Magnetization Switching by Spin-Orbit Torque in Exchange-Biased Systems

Switching of magnetization via spin-orbit torque provides an efficient alternative for nonvolatile memory and logic devices. However, to achieve deterministic switching of perpendicular magnetization, an external magnetic field collinear with the current is usually required, which makes these devices inappropriate for practical applications. As such, in this work, we examine the current-induced magnetization switching in a perpendicularly magnetized exchange-biased Pt/CoFe/IrMn system. A magnetic field annealing technique is used to introduce in-plane exchange biases, which are quantitatively characterized. Under proper conditions, field-free current-driven switching is achieved.We study the Joule heating effect, and we show how it can decrease the in-plane exchange bias and degrade the field-free switching. Furthermore, we discuss that the exchange-bias training effect can have similar effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A memory-distributed quasi-Newton solver for nonlinear programming problems with a small number of general constraints

We approach the problem of parallelizing state-of-the-art nonlinear programming optimization algorithms.Specifically, we focus on parallelizing quasi-Newton interior-point methods that use limited-memory secant Hessian approximations. Such interior-point methods are known to have better convergence properties and to be more effective on large-scale problems than gradient-based and derivative-free optimization algorithms. We target nonlinear and potentially nonconvex optimization problems with an arbitrary number of bound constraints and a small number of general equality and inequality constraints on the optimization variables. These problems occur for example in the form of optimal control, optimal design, and inverse problems governed by ordinary or partial differential equations, whenever they are expressed in a “reduced-space” optimization approach. We introduce and analyze the time and space complexity of a decomposition method for solving the quasi-Newton linear systems that leverages the fact that the quasi-Newton Hessian matrix has a small number of dense blocks that border a low-rank update of a diagonal matrix. This enables an efficient parallelization on memory-distributed computers of the iterations of the optimization algorithm, a state-of-the-art filter line-search interior-point algorithm by Wächter et. al. We illustrate the efficiency of the proposed method by solving structural topology optimization problems on up to 4608 cores on a parallel machine.

97 MATHEMATICS AND COMPUTING↗

High-energy synchrotron radiation X-ray diffraction measurements during in situ aging of a NiTi-15 at. % Hf high temperature shape memory alloy

NiTiHf high temperature shape memory alloys (HTSMAs) have begun to show considerable progress in their ability to be manufactured and are now on the cusp of becoming viable alloys for use in the aerospace industry, mainly as actuation devices. By aging the alloys at intermediate temperatures between 450 and up to 700 °C, Ni-rich NiTiHf HTSMAs form the H-phase, a Ni-rich nanoscale precipitate which can be used to strengthen the alloy and improve the shape memory response; however, precipitate phase evolution and growth has not yet been studied in-situ nor have the effects of previous thermo-mechanical processing on their formation. In this study, H-phase precipitate formation is observed experimentally in situ during aging of a Ni-rich NiTiHf alloy using high energy synchrotron radiation X-ray diffraction (SR-XRD) measurements. The effects of prior thermo-mechanical treatments, i.e. hot and cold rolling, on its formation rate and coarsening rate are compared. It is shown that growth of the H-phase can be observed in situ using SR-XRD and the H-phase formation rate seems to exhibit linear growth when aging at 550 °C, while increasing the temperature to 650 °C shows a logarithmic trend that plateaus after approximately 1 h of aging. Other properties such as incubation time, austenite lattice strains, texture evolution, and overall comparison between hot and cold rolling are discussed. New potential peak age conditions are suggested based on the diffraction data and evaluated using three-point bending and TEM imaging.

36 MATERIALS SCIENCE↗

InversionNet3D: Efficient and Scalable Learning for 3-D Full-Waveform Inversion

Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has shown some encouraging results in obtaining 2-D velocity maps. However, due to high computational complexity and large memory consumption, the reconstruction of 3-D high-resolution velocity maps via deep networks is still a great challenge. Here, in this article, we present InversionNet3D (InvNet3D), an efficient and scalable encoder–decoder network for 3-D FWI. The proposed method employs group convolution in the encoder to establish an effective hierarchy for learning information from multiple sources while cutting down unnecessary parameters and operations at the same time. The introduction of invertible layers further reduces the memory consumption of intermediate features during training and, thus, enables the development of deeper networks with more layers and higher capacity as required by different application scenarios. Experiments on the 3-D Kimberlina dataset demonstrate that InvNet3D achieves state-of-the-art reconstruction performance with lower computational cost and lower memory footprint compared to the baseline.

58 GEOSCIENCES↗

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗

Scaled CMOS Technology Reliability Users Guide

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. A methodology on how to accomplish this and techniques for deriving the expected product-level reliability on commercial memory products are provided.Competing mechanism theory and the multiple failure mechanism model are applied to the experimental results of scaled SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope (beta)=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and their key parameters.

Microelectronics Reliability↗