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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31

Effects of Transcranial Direct Current Stimulation (tDCS) on Human Memory.

Training a person in a new knowledge base or skill set is extremely time consuming and costly, particularly in highly specialized domains such as the military and the intelligence community. Recent research in cognitive neuroscience has suggested that a technique called transcranial direct current stimulation (tDCS) has the potential to revolutionize training by enabling learners to acquire new skills faster, more efficiently, and more robustly (Bullard et al., 2011). In this project, we tested the effects of tDCS on two types of memory performance that are critical for learning new skills: associative memory and working memory. Associative memory is memory for the relationship between two items or events. It forms the foundation of all episodic memories, so enhancing associative memory could provide substantial benefits to the speed and robustness of learning new information. We tested the effects of tDCS on associative memory, using a real-world associative memory task: remembering the links between faces and names. Working memory refers to the amount of information that can be held in mind and processed at one time, and it forms the basis for all higher-level cognitive processing. We investigated the degree of transfer between various working memory tasks (the N-back task as a measure of verbal working memory, the rotation-span task as a measure of visuospatial working memory, and Raven's progressive matrices as a measure of fluid intelligence) in order to determine if tDCS-induced facilitation of performance is task-specific or general.

Matzen, Laura E.↗

Mind racing: The influence of exercise on long-term memory consolidation

Over time, regular exercise can lower the risk for age-related decline in cognition. However, the immediate effects of exercise on memory consolidation in younger adults have not been fully investigated. As such, in two experiments, the effects of exercise were assessed on three different memory tasks. These included paired-associate learning, procedural learning and text memory. Results indicate that performance on procedural learning and situation model memory was increased with exercise, regardless of if participants exercised before or after encoding. No benefit of exercise was found for paired-associate learning. These findings suggest that intense exercise may benefit certain types of memory consolidation.

60 APPLIED LIFE SCIENCES↗

Multi-Level Memory Algorithmics for Large, Sparse Problems

In this report, we abstract eleven papers published during the project and describe preliminary unpublished results that warrant follow-up work. The topic is multi-level memory algorithmics, or how to effectively use multiple layers of main memory. Modern compute nodes all have this feature in some form.

97 MATHEMATICS AND COMPUTING↗

Viscel: A general purpose computer program for analysis of linear viscoelastic structures, volume 2

The VISCEL program is a general purpose computer program developed for equilibrium analysis of linear viscoelastic structures. The program is written in FORTRAN 5 language to operate on the Univac 1108 computer under the EXEC 8 operating system. The program, an extension of the linear equilibrium problem solver ELAS, is an updated and extended version of its earlier form written for the IBM 7094 computer. Finite element matrix displacement approach coupled with the synchronized material property concept, utilizing incremental time steps, was adopted for the solution presented. The step-by-step procedure involves solution of recursive equations in the time domain, which takes into account the memory of material properties. Incremental and accumulative displacements and stresses are obtained at the end of each time step. In order to minimize the extent of computations resulting from accumulative effects of material memory, the program provides an option which enables the employment of constant time steps in the logarithmic scale. Program documentation is presented.

Gupta, K. K.↗

Effects of composition and crystallographic ordering on the ferromagnetic transition in Ni–Co–Mn–In magnetic shape memory alloys

In the present study, the effects of composition and the level of crystallographic ordering were studied in Ni 45 Co 5 Mn 50-X In X magnetic shape memory alloys with X = 13.55, 13.71 and 13.92, in order to reveal the relationship between the Curie temperature (T C ) of the austenite phase and the degree of L2 1 ordering. Various samples were prepared using secondary heat treatments at different temperatures below the order-disorder transition temperature and for different durations, after solution heat treatment, in order to control the degree of ordering. T C s were determined using calorimetric and magnetometry measurements. The relationship between the T C and the degree of order was used to predict the evolution of the order during selected heat treatments. It was shown that the T C of austenite exhibits a monotonous non-linear dependence on the fraction of the L2 1 phase. This relationship was corroborated via ab initio numerical calculations within a mean field approximation. Dependence of the crystallographic order parameter on temperature and duration of secondary heat treatments showed that ordering kinetics is fast, the total degree of order depends only on the annealing temperature and cooling rate for long enough treatments, and maximum achievable degree of order is limited by the low thermal energy available for atomic diffusion at low temperatures. Lastly, small changes in composition were observed to have a significant impact on martensitic transformation temperatures, and a significant but smaller effect on the ferromagnetic transition in these systems.

36 MATERIALS SCIENCE↗

Heavy Ion and Proton-Induced Single Event Upset Characteristics of a 3D NAND Flash Memory

We evaluated the effects of heavy ion and proton irradiation for a 3D NAND flash. The 3D NAND showed similar single-event upset (SEU) sensitivity to a planar NAND of identical density in the multiple-cell level (MLC) storage mode. The 3D NAND showed significantly reduced SEU susceptibility in single-level-cell (SLC) storage mode. Additionally, the 3D NAND showed less multiple-bit upset susceptibility than the planar NAND, with fewer number of upset bits per byte and smaller cross sections overall. However, the 3D architecture exhibited angular sensitivities for both base and face angles, reflecting the anisotropic nature of the SEU vulnerability in space. Furthermore, the SEU cross section decreased with increasing fluence for both the 3D NAND and the Micron 16 nm planar NAND, which suggests that typical heavy ion test fluences will underestimate the upset rate during a space mission. These unique characteristics introduce complexity to traditional ground irradiation test procedures.

3D NAND Flash memory; radiation susceptibility; si↗

Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning

Terrestrial ecosystems play a central role in the global carbon cycle and affect climate change. However, our predictive understanding of these systems is still limited due to their complexity and uncertainty about how key drivers and their legacy effects influence carbon fluxes. Here, we propose an interpretable Long Short-Term Memory (iLSTM) network for predicting net ecosystem CO 2 exchange (NEE) and interpreting the influence on the NEE prediction from environmental drivers and their memory effects. We consider five drivers and apply the method to three forest sites in the United States. Besides performing the prediction in each site, we also conduct transfer learning by using the iLSTM model trained in one site to predict at other sites. Results show that the iLSTM model produces good NEE predictions for all three sites and, more importantly, it provides reasonable interpretations on the input driver's importance as well as their temporal importance on the NEE prediction. Additionally, the iLSTM model demonstrates good across-site transferability in terms of both prediction accuracy and interpretability. The transferability can improve the NEE prediction in unobserved forest sites, and the interpretability advances our predictive understanding and guides process-based model development.

Liu, Siyan↗

On the Feasibility of 1T Ferroelectric FET Memory Array

To fully exploit the ferroelectric field effect transistor (FeFET) as compact embedded nonvolatile memory for various computing and storage applications, it is desirable to use a single FeFET (1T) as a unit cell and arrange the cells into an array. However, many write mechanisms for an 1T FeFET array reported in the literature are yet to be validated experimentally. In this work, we performed a comprehensive experimental characterization on the write operations in an 1T- NOR and 1T- AND array using n-channel bulk FeFETs. We discovered that: 1) the source/drain contact can only supply minority carriers (i.e., electrons) to the channel for polarization screening during the low- V TH state programming; 2) the body contact can not only supply majority carriers (i.e., holes) for efficient high- V TH state write, but also depletion charge for low- V TH state programming, though with lower efficiency; and 3) during the low/high- V TH programming, only the path that can supply negative/positive screening charges, respectively, need to respond, which necessitates the application of proper write biases on the corresponding terminal. Based on the understanding of these write mechanisms, we show the importance of localized body contact or column-wise body contact for the successful high- V TH state programming. We also show that the previously proposed C- AND write scheme fails to program the FeFET to the low- V TH state for our devices. Finally, we propose several write schemes for both 1T- AND and 1T- NOR arrays for various scenarios providing insights for choosing the appropriate write scheme, which will facilitate the adoption of 1T FeFET memory arrays for emerging applications.

FeFET↗

SRAM Based Re-programmable FPGA for Space Applications

An SRAM (static random access memory)-based reprogrammable FPGA (field programmable gate array) is investigated for space applications. A new commercial prototype, named the RS family, was used as an example for the investigation. The device is fabricated in a 0.25 micrometers CMOS technology. Its architecture is reviewed to provide a better understanding of the impact of single event upset (SEU) on the device during operation. The SEU effect of different memories available on the device is evaluated. Heavy ion test data and SPICE simulations are used integrally to extract the threshold LET (linear energy transfer). Together with the saturation cross-section measurement from the layout, a rate prediction is done on each memory type. The SEU in the configuration SRAM is identified as the dominant failure mode and is discussed in detail. The single event transient error in combinational logic is also investigated and simulated by SPICE. SEU mitigation by hardening the memories and employing EDAC (error detection and correction) at the device level are presented. For the configuration SRAM (CSRAM) cell, the trade-off between resistor de-coupling and redundancy hardening techniques are investigated with interesting results. Preliminary heavy ion test data show no sign of SEL (single event latch-up). With regard to ionizing radiation effects, the increase in static leakage current (static I(sub CC)) measured indicates a device tolerance of approximately 50krad(Si).

Wang, J. J.↗

Spin-transfer-torque efficiency enhanced by edge-damage of perpendicular magnetic random access memories

We numerically investigate the effect of magnetic and electrical damages at the edge of a perpendicular magnetic random access memory (MRAM) cell on the spin-transfer-torque (STT) efficiency that is defined by the ratio of thermal stability factor to switching current. We find that the switching mode of an edge-damaged cell is different from that of an undamaged cell, which results in a sizable reduction in the switching current. Together with a marginal reduction of the thermal stability factor of an edge-damaged cell, this feature makes the STT efficiency large. Our results suggest that a precise edge control is viable for the optimization of STT-MRAM.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Retention modeling for ultra-thin density of Cu-based conductive bridge random access memory (CBRAM)

We investigate the effect of Cu concentration On-state resistance retention characteristics of W/Cu/Ti/HfO{sub 2}/Pt memory cell. The development of RRAM device for application depends on the understanding of the failure mechanism and the key parameters for device optimization. In this study, we develop analytical expression for cations (Cu{sup +}) diffusion model using Gaussian distribution for detailed analysis of data retention time at high temperature. It is found that the improvement of data retention time depends not only on the conductive filament (CF) size but also on Cu atoms concentration density in the CF. Based on the simulation result, better data retention time is observed for electron wave function associated with Cu{sup +} overlap and an extended state formation. This can be verified by analytical calculation of Cu atom defects inside the filament, based on Cu{sup +} diffusion model. The importance of Cu diffusion for the device reliability and the corresponding local temperature of the filament were analyzed by COMSOL Multiphysics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Topological insulator-based high efficiency switching of magnetic unit, method and applications

A magneto-electronic device may include: a spin-orbit torque (SOT) generator layer; a magnetic memory layer; and/or sensing electrodes configured to measure a Hall effect of the magnetic memory layer. The SOT generator layer may include topological insulator material, and the magnetic memory layer may include ferromagnetic material with perpendicular magnetic anisotropy. A magneto-electronic device may include: a spin-orbit torque (SOT) generator layer; a first magnetic memory layer on the SOT generator layer; an insulating layer on the first magnetic memory layer; and/or a second magnetic memory layer on the insulating layer. The SOT generator layer may include topological insulator material. The first magnetic memory layer and the second magnetic memory layer may include ferromagnetic material with either perpendicular magnetic anisotropy or in-plane magnetic anisotropy.

36 MATERIALS SCIENCE↗