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At least 901 records · Page 50

Abnormal grain growth of 68Cu–16Al–16Zn alloys for elastocaloric cooling via cyclical heat treatments

Abstract Cu-based superelastic shape memory alloys are promising for low-stress elastocaloric cooling. We have synthesized bulk alloys of 68Cu–16Al–16Zn under different conditions in order to promote its grain growth and enhance its elastocaloric properties. High-temperature x-ray diffraction of untreated 68Cu–16Al–16Zn alloy showed that the phase boundary between the α + β mixed phases and the high temperature phase ( β phase) was between 973 K and 1023 K. Based on this result, the 68Cu–16Al–16Zn alloy was heated and cooled in a furnace repeatedly between 773 K and 1173 K. The maximum grain size after heat treatment of the ingot rolled to 67% reached 11.1 mm. The latent heat of the martensitic transformation after grain growth was 6.3 J g −1 , which is higher than the previously reported value for the compound. The stress–strain curve of 68Cu–16Al–16Zn rolled to 67% rolling with cyclical heat treatments showed a maximum stress of 106 MPa at 4.5% strain, with adiabatic temperature change of 5.9 K in heating during stress loading and 5.6 K in cooling in stress removal. Furthermore, no fatigue in the stress–strain behavior was observed up to at least 60 000 mechanical cycles at 2% strain.

36 MATERIALS SCIENCE↗

Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

As technology advances, computer systems are subject to increasingly sophisticated cyber-attacks that compromise both their security and integrity. High performance computing platforms used in commercial and scientific applications involving sensitive, or even classified data, are frequently targeted by powerful adversaries. This situation is made worse by a lack of fundamental security solutions that both perform efficiently and are effective at preventing threats. Current security solutions fail to address the threat landscape and ensure the integrity of sensitive data. As challenges rise, both private and public sectors will require robust technologies to protect its computing infrastructure. The research outcomes from this project try to address all these challenges. For example, we present LAZARUS, a novel technique to harden kernel Address Space Layout Randomization (KASLR) against paging-based side-channel attacks. In particular, our scheme allows for fine-grained protection of the virtual memory mappings that implement the randomization. We demonstrate the effectiveness of our approach by hardening a recent Linux kernel with LAZARUS, mitigating all of the previously presented side-channel attacks on KASLR. Our extensive evaluation shows that LAZARUS incurs only 0.943% overhead for standard benchmarks, and is therefore highly practical. We also introduced HA2lloc, a hardware-assisted allocator that is capable of leveraging an extended memory management unit to detect memory errors in the heap. We also perform testing using HA2lloc in a simulation environment and find that the approach is capable of preventing common memory vulnerabilities.

97 MATHEMATICS AND COMPUTING↗

“Magnetic Memory” in Plasticity of an Aluminum Alloy with Iron Inclusions

This article is devoted to the effect of a magnetic field of 0.7 T on the state of an aluminum alloy whose creep increases after exposing to a magnetic field, exhibiting a “magnetic memory.” The alloy contains FeAl microinclusions identified by electron microscopy, magnetometry, and Mössbauer spectroscopy. Possible mechanisms of changing the states of ferromagnetic microinclusions and aluminum matrix around them under a magnetic field are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Early And Late Neurobehavioral Effects Of Male And Female Mice Exposed To Five-Ion GCRSim

With upcoming missions to the Moon and beyond to Mars, it is increasingly imperative to elucidate the detrimental effects of space travel beyond the lower Earth orbit, particularly to galactic cosmic radiation. Additionally, with the first female astronaut to soon travel to the Moon there is a strong need to understand the biological sex differences to adaptation to the deep space environment. While the effects of spaceflight on the nervous system are not fully known, studies in animal models have shown that exposure to ionizing radiation can cause neuronal damage and lead to downstream cognitive and behavioral deficits. Here, we investigated the neurobehavioral responses to space environment-like radiation exposure. Male and female 23–24-week-old mice (age-matched to average astronaut age) were exposed to 5, 15 and 50 cGy via Five-Ion Galactic Cosmic Ray Simulation at the NASA National Space Radiation Laboratory at Brookhaven National Laboratory. Both early (72hrs post exposure) and late (1-4 months post exposure) cognitive and behavioral deficits were investigated. Early analysis was performed by observing in-cage behavior including frequency/duration of digging, rearing, and grooming and nestlet building. Additionally, late effects were analyzed at NASA Ames via in-cage behavior as well as Catwalk (gait), Zero Maze (anxiety), Adhesive Removal (sensory motor), Novel Object Recognition and Barnes Maze (working memory). There were pronounced sex differences in both early and late time points. Females scored better than males in nestlet building, gait and working memory while males scored better at the sensory motor (adhesive removal) test. Dose effects were primarily observed at 50 cGy for both sexes, particularly with the Barnes Maze (working memory), where both males and females exposed to 50 cGy showed little to no improvement in test performance, though females again performed better than males. Currently, we are investigating the correlations between the observed behavior and cytokine levels in the plasma and brain. Future studies will continue to investigate cognitive consequences of galactic cosmic radiation in combination with other space-like environment stressors, including antigravity and social versus single housing.

S Puukila↗

Tuning In-Plane Magnetic Anisotropy and Interfacial Exchange Coupling in Epitaxial La 2/3 Sr 1/3 CoO 3 /La 2/3 Sr 1/3 MnO 3 Heterostructures

Controlling the in-plane magnetocrystalline anisotropy and interfacial exchange coupling between ferromagnetic (FM) layers plays a key role in next-generation spintronic and magnetic memory devices. In this work, we explored the effect of tuning the magnetocrystalline anisotropy of La 2/3 Sr 1/3 CoO 3 (LSCO) and La 2/3 Sr 1/3 MnO 3 (LSMO) layers and the corresponding effect on interfacial exchange coupling by adjusting the thickness of the LSCO layer (t LSCO ). The epitaxial LSCO/LSMO bilayers were grown on (110) o -oriented NdGaO 3 (NGO) substrates with a fixed LSMO (top layer) thickness of 6 nm and LSCO (bottom layer) thicknesses varying from 1 to 10 nm. Despite the small difference (~0.2%) in lattice mismatch between the two in-plane directions, [001] o and [11̅0] o , a pronounced in-plane magnetic anisotropy was observed. Soft X-ray magnetic circular dichroism hysteresis loops revealed that for t LSCO ≤ 4 nm, the easy axes for both LSCO and LSMO layers were along the [001] o direction, and the LSCO layer was characterized by magnetically active Co 2+ ions that strongly coupled to the LSMO layer. No exchange bias effect was observed in the hysteresis loops. In contrast, along the [11̅0] o direction, the LSCO and LSMO layers displayed a small difference in their coercivity values, and a small exchange bias shift was observed. As t LSCO increased above 4 nm, the easy axis for the LSCO layer remained along the [100] o direction, but it gradually rotated to the [11̅0] o direction for the LSMO layer, resulting in a large negative exchange bias shift. Therefore, we provide a way to control the magnetocrystalline anisotropy and exchange bias by tuning the interfacial exchange coupling between the two FM layers.

36 MATERIALS SCIENCE↗

Exact calculation of the time convolutionless master equation generator: Application to the nonequilibrium resonant level model

The generalized quantum master equation provides a powerful tool to describe the dynamics in quantum impurity models driven away from equilibrium. Two complementary approaches, one based on Nakajima–Zwanzig–Mori time-convolution (TC) and the other on the Tokuyama–Mori time-convolutionless (TCL) formulations provide a starting point to describe the time-evolution of the reduced density matrix. A key in both approaches is to obtain the so called “memory kernel” or “generator,” going beyond second or fourth order perturbation techniques. While numerically converged techniques are available for the TC memory kernel, the canonical approach to obtain the TCL generator is based on inverting a super-operator in the full Hilbert space, which is difficult to perform and thus, nearly all applications of the TCL approach rely on a perturbative scheme of some sort. Here, the TCL generator is expressed using a reduced system propagator which can be obtained from system observables alone and requires the calculation of super-operators and their inverse in the reduced Hilbert space rather than the full one. This makes the formulation amenable to quantum impurity solvers or to diagrammatic techniques, such as the nonequilibrium Green’s function. We implement the TCL approach for the resonant level model driven away from equilibrium and compare the time scales for the decay of the generator with that of the memory kernel in the TC approach. Furthermore, the effects of temperature, source-drain bias, and gate potential on the TCL/TC generators are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nanoscale magnetic phase competition throughout the Ni 50– x Co x Mn 40 Sn 10 phase diagram: Insights from small-angle neutron scattering

The Ni 2 MnSn-derived Ni 50– x Co x Mn 25+ y Sn 25– y alloys are premier examples of a class of off-stoichiometric Heusler alloys recently discovered to exhibit attractive magnetic properties in tandem with extraordinarily reversible martensitic phase transformations. Multiferroicity, magnetic phase competition and separation, field-induced martensitic transformations, magnetic shape memory behavior, and sizable magneto-, elasto-, and barocaloric effects result, generating substantial interest and application potential. In this work we expand on a prior small-angle neutron scattering (SANS) study at a single composition (Ni 44 Co 6 Mn 40 Sn 10 ) by exploring all three main regions of the recently established Ni 50–x Co x Mn 40 Sn 10 phase diagram, i.e., at the representative y = 15 composition. Wide temperature and scattering wave-vector range (20–500K, 0.004–0.2Å –1 ) SANS data on x = 2, 6, and 14 polycrystals provide a detailed picture of the evolution in magnetic order and inhomogeneity. Consistent with recent studies with a variety of techniques, phase separation into short-range coexisting ferromagnetic and antiferromagnetic regions is deduced below the martensitic transformation at x = 2 and 6, with average ferromagnetic cluster spacing of ~13 nm. Remarkably, at x = 14, where the martensitic transformation is suppressed and ferromagnetic austenite is stabilized to low temperatures, nanoscopic magnetic inhomogeneity nevertheless persists. Further, distinct ferromagnetic clusters (~36-nm average spacing) in a ferromagnetic matrix are observed at intermediate temperatures, homogenizing into a uniform long-range ordered ferromagnet only at low temperatures. This unusual ferromagnet cluster/ferromagnet matrix inhomogeneity, as well as x -dependent subtleties of the superparamagnetic freezing of ferromagnetic clusters, are discussed in light of 55 Mn nuclear magnetic resonance data, and the recent observation of annealing-induced core/shell nanoprecipitates. The origins of nanoscalemagnetic inhomogeneity are discussed in terms of statistical variations in local composition and structure, tendency to chemical phase separation, and other forms of disorder.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bridging the Gap Between LLMs and LNS with Dynamic Data Format and Architecture Codesign

Deep neural networks (DNNs) have achieved tremendous success in the past few years. However, their training and inference demand exceptional computational and memory resources. Quantization has been shown as an effective approach to mitigate the cost, with the mainstream data types reduced from FP32 to FP16/BF16 and recently FP8 in the latest NVIDIA H100 GPUs. With increasingly aggressive quantization, however, the conventional floating-point formats suffer from limited precision in representing numbers around zero. Recently, NVIDIA demonstrated the potential of using a Logarithmic Number System (LNS) for the next generation of tensor cores. While LNS mitigates the hurdles in representing small numbers, in this work we observed a mismatch between LNS and the emerging Large Language Models (LLM), where LLM exhibits significant outliers when directly adopting the LNS format. In this paper, we present a data-format/architecture codesign to bright this gap. On the format side, we propose a dynamic LNS format to flexibly represent outliers at a higher precision, by exploiting asymmetry in the LNS representation and identifying outliers through a per-vector basis. On the architecture side, for demonstration, we realize the dynamic LNS format in a systolic array, which can handle the irregularity of the outliers at runtime. We implement our approach on an Alveo U280 FPGA as a prototype. Experimental results show that our design can effectively handle the outliers and resolve the mismatch between LNS and LLM, contributing to an accuracy improvement of 15.4% and 16% over the floating-point and the original LNS baselines, using four state-of-the-art LLM models. Our observation and design lay a solid foundation for the large-scale adoption of the LNS format in the next-generation deep learning hardware.

Haghi, Pouya↗

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those it is found that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely because of differences in instrumentation, calibration, and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat-dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory), and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but they poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration, or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Finally, data from models and observations should be put on the same spatial and temporal scales before comparison.

54 ENVIRONMENTAL SCIENCES↗

Space-Time Finite Element Tensor Network Approach for the Time-Dependent Convection–Diffusion–Reaction Equation with Variable Coefficients

In this paper, we present a new space-time Galerkin-like method, where we treat the discretization of spatial and temporal domains simultaneously. This method utilizes a mixed formulation of the tensor-train (TT) and quantized tensor-train (QTT) (please see Section Tensor-Train Decomposition), designed for the finite element discretization (Q1-FEM) of the time-dependent convection–diffusion–reaction (CDR) equation. We reformulate the assembly process of the finite element discretized CDR to enhance its compatibility with tensor operations and introduce a low-rank tensor structure for the finite element operators. Recognizing the banded structure inherent in the finite element framework’s discrete operators, we further exploit the QTT format of the CDR to achieve greater speed and compression. Additionally, we present a comprehensive approach for integrating variable coefficients of CDR into the global discrete operators within the TT/QTT framework. The effectiveness of the proposed method, in terms of memory efficiency and computational complexity, is demonstrated through a series of numerical experiments, including a semi-linear example.

convection–diffusion–reaction equation↗

On the error probability of general tree and trellis codes with applications to sequential decoding

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Johannesson, R.↗

Performance of convolutional codes on fading channels typical of planetary entry missions

The performance of convolutional codes in fading channels typical of the planetary entry channel is examined in detail. The signal fading is due primarily to turbulent atmospheric scattering of the RF signal transmitted from an entry probe through a planetary atmosphere. Short constraint length convolutional codes are considered in conjunction with binary phase-shift keyed modulation and Viterbi maximum likelihood decoding, and for longer constraint length codes sequential decoding utilizing both the Fano and Zigangirov-Jelinek (ZJ) algorithms are considered. Careful consideration is given to the modeling of the channel in terms of a few meaningful parameters which can be correlated closely with theoretical propagation studies. For short constraint length codes the bit error probability performance was investigated as a function of E sub b/N sub o parameterized by the fading channel parameters. For longer constraint length codes the effect was examined of the fading channel parameters on the computational requirements of both the Fano and ZJ algorithms. The effects of simple block interleaving in combatting the memory of the channel is explored, using the analytic approach or digital computer simulation.

Modestino, J. W.↗

Convolutional code performance in fading channels

The performance of convolutional codes in fading channels typical of the planetary entry channel is examined in detail. Short constraint length codes are considered in conjunction with binary phase-shift-keyed (BPSK) modulation and Viterbi maximum likelihood decoding while for longer constraint length codes we consider sequential decoding utilizing both the Fano and Zigangirov-Jelinek (ZJ) algorithms. For short constraint length codes we are primarily interested in the bit error probability performance parameterized by the fading channel parameters. For longer constraint length codes interest will center on the effect of the fading channel parameters on the computational requirements of both the Fano and ZJ algorithms. In either case the effects of simple block interleaving in combatting the memory of the channel is thoroughly explored. The approach is analytic where possible otherwise resort is made to digital computer simulation.

Modestino, J. W.↗

Light flash phenomena induced by HzE particles

Astronauts and Apollo and Skylab missions have reported observing a variety of visual phenomena when their eyes are closed and adapted to darkness. These phenomena have been collectively labelled as light flashes. Visual phenomena which are similar in appearance to those observed in space have been demonstrated at the number of accelerator facilities by expressing the eyes of human subjects to beams of various types of radiation. In some laboratory experiments Cerenkov radiation was found to be the basis for the flashes observed while in other experiments Cerenkov radiation could apparently be ruled out. Experiments that differentiate between Cerenkov radiation and other possible mechanisms for inducing visual phenomena was then compared. The phenomena obtained in the presence and absence of Cerenkov radiation were designed and conducted. A new mechanism proposed to explain the visual phenomena observed by Skylab astronauts as they passed through the South Atlantic Anomaly, namely nuclear interactions in and near the sensitive layer of the retina, is covered. Also some studies to search for similar transient effects of space radiation on sensors and microcomputer memories are described.

Mcnulty, P. J.↗

RAY-O-VAC BR2325 Lithium Carbon Monofluoride Cell Performance

RAY-O-VAC currently markets a 160 mAH lithium cell recommended for usage in watch and calculator products. The lithium carbon monofluoride cell offers an extended shelf life with no reduction in performance effectiveness. The BR2325 cell has aerospace applications for memory devices and telemetry systems. Over one hundred thirty (130) cells were purchased and tested for evaluation purposes. The test statistics and overall cell performance of the RAY-O-VOC BR2325 lithium carbon monofluoride cell is reviewed.

Mcdermott, J. K.↗

Some aspects of the comparison of model and full-scale tests

This paper was delivered before the Royal Aeronautical Society as the 1925 Wilbur Wright Memorial lecture. It treats the subject of scale effect from the standpoint of the engineer rather than the physicist, in that it shows what compromises are necessary to secure satisfactory engineering model test data and how these test data compare with full scale or with theoretical values. The paper consists essentially of three parts: (1) a brief exposition of the theory of dynamic similarity, (2) application of the theory to airplane model tests, illustrated by test data on airfoils from the National Advisory Committee for Aeronautics variable-density wind tunnel, and (3) application of the theory to propeller testing, illustrated by comparisons of model and full-scale results.

Taylor, D W↗

Evaluation of Design Concepts for Collapsible Cryogenic Storage Vessels

Future long-duration missions to Mars using in situ resource production to obtain oxygen from the Martian atmosphere for use as a propellant or for life support will require long term oxygen storage facilities. This report describes preliminary analysis of design concepts for lightweight, collapsible liquid oxygen storage tanks to be used on the surface of Mars. With storage at relatively low pressures, an inflatable tank concept in which the cryogen is stored within a fiber-reinforced Teflon FEP bladder is an efficient approach. The technology required for such a tank is well-developed through similar previous applications in positive expulsion bladders for zero-g liquid fuel rocket tanks and inflatable space habitat technology, though the liquid oxygen environment presents unique challenges. The weight of the proposed structure is largely dominated by the support structure needed to hold the tank off the ground and permit a vacuum insulation space to be maintained around the tank. In addition to the inflatable tank concept, telescoping tank concepts are studied. For a telescoping tank, the greatest difficulty is in making effective joints and seals. The use of shape memory alloy to produce a passive clamping ring is evaluated. Although the telescoping tank concepts are a viable option, it appears that inflatable tank concepts will be more efficient and are recommended.

Fleming, David C.↗