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At least 415 records · Page 23

Meta-aerogels: Auxetic Shape-memory Polyurethane Aerogels

Shape-memory poly(isocyanurate-urethane) (PIR-PUR) aerogels are low-density monolithic nanoporous solids that remember and return to their permanent shape through a heating actuation step. Herein, through structural design at the macro scale, the shape-memory response is augmented with an auxetic effect manifested by a negative Poisson’s ratio of approximately -0.8 at 15% compressive strain. Thus, auxetic shape-memory PIR-PUR monoliths experience volume contraction upon compression at a temperature above the glass transition temperature of the base polymer (Tg ~ 30 °C), and they can be stowed indefinitely in that temporary shape by cooling below Tg. By heating back above Tg, the compressed/shrunk form expands back to their original shape/size. This technology is relevant to a broad range of industries spanning the commercial, aeronautical, and aerospace sectors. The materials are referred to as meta-aerogels and their potential applications include minimally invasive medical devices, soft robotics, and in situations where volume is at a premium, as for example for storage of deployable space structures and planetary habitats during transport to the point of service.

Sadeq Malakooti↗

Radiation tests of highly scaled high density commercial nonvolatile NAND flash memories update 2009

Heavy ion single-event measurements on a variety of high density commercial NAND flash memories are reported. Three single event effect (SEE) phenomena are examined: single effect upsets (SEUs), single event functional interrupts (SEFIs), and catastrophic loss of ability to erase and program the device. Also, radiation results of multilevel flash technology are compared with results from single-level flash technology. These commercial high density memories appear to be much less susceptible to SEE and have better TID response compared to older generations of flash memories. The single-level devices are less sensitive to SEUs than multi-level devices. The charge pump in this study survived up to 600 krads. A new high current phenomenon in high density NAND flash memories is also discussed.

Nguyen, Duc N.↗

Hutchinson Trace Estimation for high-dimensional and high-order Physics-Informed Neural Networks

Physics-Informed Neural Networks (PINNs) have proven effective in solving partial differential equations (PDEs), especially when some data are available by seamlessly blending data and physics. However, extending PINNs to high-dimensional and even high-order PDEs encounters significant challenges due to the computational cost associated with automatic differentiation in the residual loss function calculation. Herein, we address the limitations of PINNs in handling high-dimensional and high-order PDEs by introducing the Hutchinson Trace Estimation (HTE) method. Starting with the second-order high-dimensional PDEs, which are ubiquitous in scientific computing, HTE is applied to transform the calculation of the entire Hessian matrix into a Hessian vector product (HVP). This approach not only alleviates the computational bottleneck via Taylor-mode automatic differentiation but also significantly reduces memory consumption from the Hessian matrix to an HVP’s scalar output. We further showcase HTE’s convergence to the original PINN loss and its unbiased behavior under specific conditions. Comparisons with the Stochastic Dimension Gradient Descent (SDGD) highlight the distinct advantages of HTE, particularly in scenarios with significant variability and variance among dimensions. We further extend the application of HTE to higher-order and higher-dimensional PDEs, specifically addressing the biharmonic equation. By employing tensor-vector products (TVP), HTE efficiently computes the colossal tensor associated with the fourth-order high-dimensional biharmonic equation, saving memory and enabling rapid computation. The effectiveness of HTE is illustrated through experimental setups, demonstrating comparable convergence rates with SDGD under memory and speed constraints. Additionally, HTE proves valuable in accelerating the Gradient-Enhanced PINN (gPINN) version as well as the Biharmonic equation. Overall, HTE opens up a new capability in scientific machine learning for tackling high-order and high-dimensional PDEs.

Curse of dimensionality↗

Analytical Bit-Error Model of NAND Flash Memories for Dosimetry Application

In this work, we provide an analytical model for the total ionizing dose (TID) effects on the bit error statistics of commercial flash memory chips. We have validated the model with experimental data collected by irradiating several commercial NAND flash memory chips from different technology nodes. We find that our analytical model can project bit errors at higher TID values (~ 20 krad(Si)) from measured data at lower TID values (<1 krad(Si)). Based on our model and the measured data, we have formulated basic design rules for using a commercial flash memory chip as a dosimeter. We discuss the impact of NAND chip-to-chip variability, noise margin and the intrinsic errors on the dosimeter design using detailed experimentation.

3-D NAND↗

Effects of Palladium Content, Quaternary Alloying, and Thermomechanical Processing on the Behavior of Ni-Ti-Pd Shape Memory Alloys for Actuator Applications

The need for compact, solid-state actuation systems for use in the aerospace, automotive, and other transportation industries is currently driving research in high-temperature shape memory alloys (HTSMA) having transformation temperatures above 100 C. One of the basic high temperature systems under investigation to fill this need is NiTiPd. Prior work on this alloy system has focused on phase transformations and respective temperatures, no-load shape memory behavior (strain recovery), and tensile behavior for selected alloys. In addition, a few tests have been done to determine the effect of boron additions and thermomechanical treatment on the aforementioned properties. The main properties that affect the performance of a solid state actuator, namely work output, transformation strain, and permanent deformation during thermal cycling under load have mainly been neglected. There is also no consistent data representing the mechanical behavior of this alloy system over a broad range of compositions. For this thesis, ternary NiTiPd alloys containing 15 to 46 at.% palladium were processed and the transformation temperatures, basic tensile properties, and work characteristics determined. However, testing reveals that at higher levels of alloying addition, the benefit of increased transformation temperature begins to be offset by lowered work output and permanent deformation or "walking" of the alloy during thermal cycling under load. In response to this dilemma, NiTiPd alloys have been further alloyed with gold, platinum, and hafnium additions to solid solution strengthen the martensite and parent austenite phases in order to improve the thermomechanical behavior of these materials. The tensile properties, work behavior, and dimensional stability during repeated thermal cycling under load for the ternary and quaternary alloys were compared and discussed. In addition, the benefits of more advanced thermomechanical processing or training on the dimensional stability of these alloys during repeated actuation were investigated. Finally, the effect of quaternary alloying on the thermal stability of NiTiPdX alloys is determined via thermal cycling of the materials to increasing temperatures under load. It was found that solid solution additions of platinum and gold resulted in about a 30 C increase in upper use temperature compared to the baseline NiTiPd alloy, providing an added measure of over-temperature protection.

Bigelow, Glen↗

On nonlinear finite element analysis in single-, multi- and parallel-processors

Numerical solution of nonlinear equilibrium problems of structures by means of Newton-Raphson type iterations is reviewed. Each step of the iteration is shown to correspond to the solution of a linear problem, therefore the feasibility of the finite element method for nonlinear analysis is established. Organization and flow of data for various types of digital computers, such as single-processor/single-level memory, single-processor/two-level-memory, vector-processor/two-level-memory, and parallel-processors, with and without sub-structuring (i.e. partitioning) are given. The effect of the relative costs of computation, memory and data transfer on substructuring is shown. The idea of assigning comparable size substructures to parallel processors is exploited. Under Cholesky type factorization schemes, the efficiency of parallel processing is shown to decrease due to the occasional shared data, just as that due to the shared facilities.

Utku, S.↗

Tuning the temperature range of superelastic Ni-Ti alloys for elastocaloric cooling via thermal processing

Abstract Caloric cooling enlisting solid-state refrigerants is potentially a promising eco-friendly alternative to conventional cooling based on vapor compression. The most common refrigerant materials for elastocaloric cooling to date are Ni-Ti based superelastic shape memory alloys. Here, we have explored tuning the operation temperature range of Ni 50.8 Ti 49.2 for elastocaloric cooling. In particular, we have studied the effect of thermal treatments (a.k.a. aging) on the transformation temperature, superelasticity, and elastocaloric effects of Ni 50.8 Ti 49.2 shape memory alloy tubes. The isothermal compressive test revealed that the residual strain of thermally-treated Ni-Ti tubes at room temperature approaches zero as aging time is increased. Short-time aging treatment at 400 °C resulted in good superelasticity and elastocaloric cooling performance with a large tunable austenite finish ( A f ) temperature range of 24.7 °C, as determined from the A f temperature of the samples that were aged 5–120 min. The main reason of the property change is the formation of a different amount of Ni 4 Ti 3 precipitates in the NiTi matrix. Our findings show that it is possible to tailor the A f temperature range for development of cascade elastocaloric cooling systems by thermally treating a starting single composition Ni-Ti alloy.

36 MATERIALS SCIENCE↗

Intrinsic quantized anomalous Hall effect in a moiré heterostructure

The quantum anomalous Hall (QAH) effect combines topology and magnetism to produce precisely quantized Hall resistance at zero magnetic field. We report the observation of a QAH effect in twisted bilayer graphene aligned to hexagonal boron nitride. The effect is driven by intrinsic strong interactions, which polarize the electrons into a single spin- and valley-resolved moiré miniband with Chern number C = 1. In contrast to magnetically doped systems, the measured transport energy gap is larger than the Curie temperature for magnetic ordering, and quantization to within 0.1% of the von Klitzing constant persists to temperatures of several kelvin at zero magnetic field. Electrical currents as small as 1 nanoampere controllably switch the magnetic order between states of opposite polarization, forming an electrically rewritable magnetic memory.

Science & Technology - Other Topics↗

Performance of FORTRAN floating-point operations on the Flex/32 multicomputer

A series of experiments has been run to examine the floating-point performance of FORTRAN programs on the Flex/32 (Trademark) computer. The experiments are described, and the timing results are presented. The time required to execute a floating-point operation is found to vary considerbaly depending on a number of factors. One factor of particular interest from an algorithm design standpoint is the difference in speed between common memory accesses and local memory accesses. Common memory accesses were found to be slower, and guidelines are given for determinig when it may be cost effective to copy data from common to local memory.

Crockett, Thomas W.↗

Analysis of space radiation data of semiconductor memories

This article presents an analysis of radiation effects for several select device types and technologies aboard the Combined Release and Radiation Effects Satellite (CRRES) satellite. These space-flight measurements covered a period of about 14 months of mission lifetime. Single Event Upset (SEU) data of the investigated devices from the Microelectronics Package (MEP) were processed and analyzed. Valid upset measurements were determined by correcting for invalid readings, hard failures, missing data tapes (thus voids in data), and periods over which devices were disabled from interrogation. The basic resolution time of the measurement system was confirmed to be 2 s. Lessons learned, important findings, and recommendations are presented.

Flight Experiment↗

Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗

Are Current SEE Test Procedures Adequate for Modern Devices and Electronics Technologies?

Believe it or not, this has been a simplistic look at starting a checklist for SEE testing. Given a memory that has 68 operating modes, when a SEU occurs that changes the mode, just how do you determine what's going on? Laser and microbeam tests can help, but not easily for modern packaged devices. Expanding this approach to other more complex devices such as ADCs or processors as well as analog devices should be considered. The recommendation is to use the existing text standards as the starting point. Just make your own checklist for the device/technology/issues being considered. At HEART 2007, we presented some of the burgeoning challenges associated with single event effect(SEE) testing of modern commercial memories: a) Package, device complexity, test fixture, and data analysis issues were discussed; b) "Complete" SEE Characterization would take 15 years; c) Qualification test costs have a greater than 4 times increase over the last decade. In this talk, we continue to explore the roles of technology with an emphasis on the existing SEE Test Procedures and some of the concerns related to modern devices. The primary objective of the briefing is to provide some overarching guidance concerning the many considerations involved in the formulation of a SEE test plan provided in a " Checklist" format.we note that there is no such thing as a complete check list and that the best approach is to develop a flexible test plan that takes into account the device type and functions, the device technology, circuit and package design, and, of course, test facility and beam characteristics.

LaBel, Kenneth A.↗

Characterization of a New Phase and Its Effect on the Work Characteristics of a Near-Stoichiometric Ni30Pt20Ti50 High-Temperature Shape Memory Alloy (HTSMA)

A new phase observed in a nominal Ni30Pt20Ti50 (at.%) high temperature shape memory alloy has been characterized using transmission electron microscopy and 3-D atom probe tomography. This phase forms homogeneously in the B2 austenite matrix by a nucleation and growth mechanism and results in a concomitant increase in the martensitic transformation temperature of the base alloy. Although the structure of this phase typically contains a high density of faults making characterization difficult, it appears to be trigonal (-3m point group) with a(sub o) approx. 1.28 nm and c(sub o) approx. 1.4 nm. Precipitation of this phase increases the microhardness of the alloy substantially over that of the solution treated and quenched single-phase material. The effect of precipitation strengthening on the work characteristics of the alloy has been explored through load-biased strain-temperature testing in the solution-treated condition and after aging at 500 C for times ranging from 1 to 256 hours. Work output was found to increase in the aged alloy as a result of an increase in transformation strain, but was not very sensitive to aging time. The amount of permanent deformation that occurred during thermal cycling under load was small but increased with increasing aging time and stress. Nevertheless, the dimensional stability of the alloy at short aging times (1-4 hours) was still very good making it a potentially useful material for high-temperature actuator applications.

Garg, A.↗

In-Flight Observations of Long-Term Single Event Effect(SEE)Performance on Orbview-2 and Xray Timing Explorer(XTE)Solid State Recorders (SSR)

This paper presents Single Event Effect (SEE) in-flight data on Solid State Recorders (SSR) that have been collected over a long period of time for two NASA spacecraft: Orbview-2 and XTE. SEE flight data on solid-state memories give an opportunity to study the behavior in space of SEE sensitive commercial devices. The actual Single Event Upset (SEU) rates can be compared with the calculated rates based on environment models and ground test data. The SEE mitigation schemes can also be evaluated in actual implementation. A significant amount of data has already been published concerning observed SEE effects on memories in space. However, most of the data presented cover either a short period of time or a small number of devices. The data presented here has been collected on a large number of devices during several years. This allows statistically significant information about the effect of space weather fluctuations on SEU rates, and the effectiveness of SEE countermeasures used to be analyzed. Only Orbview-2 data is presented in this summary. XTE data will be included in the final paper.

Poivey, Christian↗

Effects of Stoichiometry on Transformation Temperatures and Actuator-Type Performance of NiTiPd and NiTiPdX High-Temperature Shape Memory Alloys

High-temperature shape memory NiTiPd and NiTiPdX (X=Au, Pt, Hf) alloys were produced with titanium equivalent (Ti+Hf) compositions of 50.5, 50.0, 49.5, and 49.0 at.%. Thermo-mechanical testing in compression was used to evaluate the transformation temperatures, transformation strain, work output, and permanent deformation behavior of each alloy to study the effects of quaternary alloying and stoichiometry on high-temperature shape memory alloy behavior. Microstructural evaluation showed the presence of second phases for all alloy compositions. No load transformation temperatures in the stoichiometric alloys were relatively unchanged by Au and Pt substitutions, while the substitution of Hf for Ti causes a drop in transformation temperatures. The NiTiPd, NiTiPdAu and NiTiPdHf alloys exhibited transformation temperatures that were highest in the Ti-rich compositions, slightly lower at stoichiometry, and significantly reduced when the Ti equivalent composition was less than 50 at.%. For the NiTiPdPt alloy, transformation temperatures were highest for the Ti-rich compositions, lowest at stoichiometry, and slightly higher in the Ni-rich composition. When thermally cycled under constant stresses of up to 300 MPa, all of the alloys had transformation strains, and therefore work outputs, which increased with increasing stress. In each series of alloys, the transformation strain and thus work output was highest for stoichiometric or Ti-rich compositions while permanent strain associated with the constant-load thermal cycling was lowest for alloys with Ni-equivalent-rich compositions. Based on these results, basic rules for optimizing the composition of NiTiPd alloys for actuator performance will be discussed.

Bigelow, Glen S.↗

Radiation Test Challenges for Scaled Commerical Memories

As sub-100nm CMOS technologies gather interest, the radiation effects performance of these technologies provide a significant challenge. In this talk, we shall discuss the radiation testing challenges as related to commercial memory devices. The focus will be on complex test and failure modes emerging in state-of-the-art Flash non-volatile memories (NVMs) and synchronous dynamic random access memories (SDRAMs), which are volatile. Due to their very high bit density, these device types are highly desirable for use in the natural space environment. In this presentation, we shall discuss these devices with emphasis on considerations for test and qualification methods required.

LaBel, Kenneth A.↗

Persistent optical phenomena in oxide semiconductors

The interaction of transparent oxide semiconductors with light is critically important for a range of applications. Persistent effects could be exploited for holographic memory or optically defined circuits. Conversely, they may also be detrimental to device operation. Large, room-temperature persistent photoconductivity (PPC) was discovered in strontium titanate (SrTiO 3 , STO) after annealing in a hydrogen-containing atmosphere. Barium titanate (BaTiO 3 , BTO), a ferroelectric material, was recently found to also exhibit PPC. Room-temperature photodarkening was observed in Cu-doped gallium oxide (β-Ga 2 O 3 ) after exposure to sub-bandgap light. Hydrogen is believed to play a central role in these persistent phenomena. In the proposed model, a photon excites substitutional hydrogen (a proton inside an oxygen vacancy), making the defect unstable. The proton leaves and binds to a host oxygen atom, forming an O-H bond that is observed with infrared spectroscopy. Here, an oxygen vacancy is left behind. Because oxygen vacancies in STO and BTO are shallow donors, this process results in PPC. In β-Ga 2 O 3 :Cu, however, the oxygen vacancy neighbors a Cu acceptor. In that case, photoexcitation results in the rare Cu 3+ state, which absorbs visible light. The effect can be “erased” by annealing at 300-400°C.

Annealing↗

Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis

Traditional filter data structures, such as Bloom filters, do not offer necessary features that modern high-performance data analytics applications need in order to efficiently perform complex data analysis tasks. For example, MetaHipMer, a de novo metagenome assembler, can use filters to weed out singleton k-mers and reduce memory usage by 30%-70%. However, the filter needs the ability to associate values with k-mers in order to perform the analysis in a single communication pass. Bloom filters do not support value associations and cause the application to perform an extra communication pass, thereby increasing the run time. Therefore, MetaHipMer faces a trade off between memory and speed due to the limited capabilities of traditional filters. In this paper, we overcome the memory and speed trade off in MetaHipMer by integrating a GPU-based feature-rich filter, the Two-Choice filter (TCF), in the MetaHipMer pipeline. The TCF uses key-value association to approximately store k-mers with extensions. This allows MetaHipMer to perform k-mer analysis on the GPUs in a single communication pass. Our empirical analysis shows a 50% reduction in memory usage in k-mer analysis on each node in MetaHipMer without any effect on the overall run time or assembly quality. The memory reduction in turn results in a 43% reduction in the number of nodes required to assemble datasets and enables MetaHipMer to scale to much larger datasets.

McCoy, Hunter↗