Search NASA⌕ Search

SEARCH · Search NASA

Results for “memory effects”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Tuning martensitic transitions in (MnNiSi) 0.65 (Fe 2 Ge) 0.35 through heat treatment and hydrostatic pressure

A first-order magneto-structural transition from a ferromagnetic orthorhombic TiNiSi-type martensite phase to a paramagnetic hexagonal Ni2In-type austenite phase was observed in (MnNiSi) 0.65 (Fe2Ge) 0.35 . In this work, we demonstrate that the first-order magneto-structural transition temperature for a given composition is tunable over a wide temperature range through heat treatment and hydrostatic pressure. The first-order transition temperature was reduced by over 100 K as the annealing temperature went from 600 to 900 °C, and this first-order transition was converted to second order when the sample was annealed at 1000 °C. The maximum magnetic-induced isothermal entropy change with μ0ΔH=7 T reaches -58 J/kg K for the sample annealed at 600 °C, and the relative cooling power reaches 558 J/kg for the sample annealed at 700 °C. Similar to the influence of annealing temperatures, the first-order martensitic transition temperatures were reduced as the application of hydrostatic pressure increased until they were converted to second order. Our results suggest that the (MnNiSi) 0.65 (Fe2Ge) 0.35 system is a promising platform for tuning magneto-structural transitions and the associated magnetocaloric effects. Furthermore, a similar heat treatment methodology or application of hydrostatic pressure can be applied to MnNiSi-based shape memory alloys to tailor their working transition temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quantum optical memory for entanglement distribution

Optical photons are powerful carriers of quantum information, which can be delivered in free space by satellites or in fibers on the ground over long distances. Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Quantum optical memories are devices designed to store quantum information in the form of stationary excitations, such as atomic coherence, and are capable of coherently mapping these excitations to flying qubits. Quantum memories can effectively store and manipulate quantum states, making them indispensable elements in future long-distance quantum networks. Over the past two decades, quantum optical memories with high fidelities, high efficiencies, long storage times, and promising multiplexing capabilities have been developed, especially at the single-photon level. In this review, we introduce the working principles of commonly used quantum memory protocols and summarize the recent advances in quantum memory demonstrations. We also offer a vision for future quantum optical memory devices that may enable entanglement distribution over long distances.

Lei, Yisheng↗

Effect of wheel speed and annealing temperature on microstructure and texture evolution of Ni{sub 45}Mn{sub 36.6}In{sub 13.4}Co{sub 5} ribbon

Ni{sub 45}Mn{sub 36.6}In{sub 13.4}Co{sub 5} magnetic shape memory alloy was successfully produced as preferentially textured ribbon by melting spinning with different wheel speed. X-ray diffraction (XRD) and electron back scatter diffraction (EBSD) were used to study structure and texture evolution of these melt-spun ribbons. The thickness of melt-spun ribbon is 42 μm, 65 μm and 30 μm depending on wheel speed of 1 0 m/s, 15 m/s and 20 m/s, respectively. Density of α fiber texture (〈100〉//ND) vary with wheel speed changes, and is most intensive in the ribbon with wheel speed of 15 m/s. Grains of the ribbons grow after being annealed at 873 K, 973 K, 1073 K and 1173 K, recrystallization was not observed in ribbons after being annealed at 873 K but occurred in ribbons after being annealed at higher temperatures. The α fiber texture becomes weaker to some extent after annealing at different temperatures, due to new recrystallization texture formed at the process of annealing. - Highlights: •Sectional part of shape memory ribbon is firstly investigated by EBSD method. •Thickness and texture of ribbons vary with wheel speed. •Annealing temperature affect texture and microstructure evolution greatly. •Recrystallization textures were observed in ribbons after being annealed.

36 MATERIALS SCIENCE↗

High-Performance, Radiation-Hardened Electronics for Space Environments

The Radiation Hardened Electronics for Space Environments (RHESE) project endeavors to advance the current state-of-the-art in high-performance, radiation-hardened electronics and processors, ensuring successful performance of space systems required to operate within extreme radiation and temperature environments. Because RHESE is a project within the Exploration Technology Development Program (ETDP), RHESE's primary customers will be the human and robotic missions being developed by NASA's Exploration Systems Mission Directorate (ESMD) in partial fulfillment of the Vision for Space Exploration. Benefits are also anticipated for NASA's science missions to planetary and deep-space destinations. As a technology development effort, RHESE provides a broad-scoped, full spectrum of approaches to environmentally harden space electronics, including new materials, advanced design processes, reconfigurable hardware techniques, and software modeling of the radiation environment. The RHESE sub-project tasks are: SelfReconfigurable Electronics for Extreme Environments, Radiation Effects Predictive Modeling, Radiation Hardened Memory, Single Event Effects (SEE) Immune Reconfigurable Field Programmable Gate Array (FPGA) (SIRF), Radiation Hardening by Software, Radiation Hardened High Performance Processors (HPP), Reconfigurable Computing, Low Temperature Tolerant MEMS by Design, and Silicon-Germanium (SiGe) Integrated Electronics for Extreme Environments. These nine sub-project tasks are managed by technical leads as located across five different NASA field centers, including Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, Langley Research Center, and Marshall Space Flight Center. The overall RHESE integrated project management responsibility resides with NASA's Marshall Space Flight Center (MSFC). Initial technology development emphasis within RHESE focuses on the hardening of Field Programmable Gate Arrays (FPGA)s and Field Programmable Analog Arrays (FPAA)s for use in reconfigurable architectures. As these component/chip level technologies mature, the RHESE project emphasis shifts to focus on efforts encompassing total processor hardening techniques and board-level electronic reconfiguration techniques featuring spare and interface modularity. This phased approach to distributing emphasis between technology developments provides hardened FPGA/FPAAs for early mission infusion, then migrates to hardened, board-level, high speed processors with associated memory elements and high density storage for the longer duration missions encountered for Lunar Outpost and Mars Exploration occurring later in the Constellation schedule.

Keys, Andrew S.↗

Simulated performance of coded PCM/FM modem on Rician fading channel

This paper describes a simulation approach to characterizing the performance of a coded PCM/FM modem operating on the classical Rician fading channel. In particular, we consider the performance of short constraint length convolutional codes in conjunction with Viterbi maximum likelihood decoding. The receiver consists of a narrowband filter followed by an ideal limiter/discriminator. Primary interest is in the bit error probability performance parameterized by both the fading channel and receiver parameters. Particular attention is given to simulating the impulse noise appearing at the discriminator output. This is the 'click' noise caused by encirclements of the origin by the instantaneous signal-plus-noise phasor. Results include the effects of channel memory and narrowband receiver filtering effects on overall bit error probability.

Modestino, J. W.↗

Functional Properties of Porous Ti-48.0 at.% Ni Shape Memory Alloy Produced by Self-Propagating High-Temperature Synthesis

The functional behavior of the porous shape memory alloy produced by self-propagating high-temperature synthesis from the Ti-48.0 at.% Ni powder mixture was studied. It was found that a large unelastic strain recovered on unloading and it was not attributed to the pseudoelasticity effect. A decrease in deformation temperatures did not influence the value of strain that recovered on unloading, while the effective modulus decreased from 1.9 to 1.44 GPa. It was found that the porous Ti-48.0 at.% Ni alloy revealed the one-way shape memory effect, where the maximum recoverable strain was 5%. The porous Ti-48.0 at.% Ni alloy demonstrated the transformation plasticity and the shape memory effects on cooling and heating under a stress. An increase in stress did not influence the shape memory effect value, which was equal to 1%. It was shown that the functional properties of the porous alloy were determined by the TiNi phase consisted of the two volumes Ti{sub 49.3}Ni{sub 50.7} and Ti{sub 50}Ni{sub 50} where the martensitic transformation occurred at different temperatures. The results of the study showed that the existence of the Ti{sub 49.3}Ni{sub 50.7} volumes in the porous Ti-48.0 at.% Ni alloy improved the functional properties of the alloy.

36 MATERIALS SCIENCE↗

Summer Proceedings 2016: The Center for Computing Research at Sandia National Laboratories

Solving sparse linear systems from the discretization of elliptic partial differential equations (PDEs) is an important building block in many engineering applications. Sparse direct solvers can solve general linear systems, but are usually slower and use much more memory than effective iterative solvers. To overcome these two disadvantages, a hierarchical solver (LoRaSp) based on H2-matrices was introduced in [22]. Here, we have developed a parallel version of the algorithm in LoRaSp to solve large sparse matrices on distributed memory machines. On a single processor, the factorization time of our parallel solver scales almost linearly with the problem size for three-dimensional problems, as opposed to the quadratic scalability of many existing sparse direct solvers. Moreover, our solver leads to almost constant numbers of iterations, when used as a preconditioner for Poisson problems. On more than one processor, our algorithm has significant speedups compared to sequential runs. With this parallel algorithm, we are able to solve large problems much faster than many existing packages as demonstrated by the numerical experiments.

97 MATHEMATICS AND COMPUTING↗

ZFP Hardware Implementation

As core counts increase in new HPC systems with comparatively little increase in memory bandwidth, the trend is an effective decrease in memory bandwidth per core. Other bandwidth limitations in HPC systems exist between CPU and GPU memory, between system nodes, and between node memory and storage. Compression of floating-point data has the potential to reduce data movement and pressure across these communication channels. Furthermore, it has the potential to reduce the footprint of floating-point arrays stored in memory. ZFP, implemented in software, is gaining traction as an effective method in floating-point compression; however, performance gains are limited to the spare compute cycles available before reaching the bandwidth limitations of the communication channel. A hardware implementation of ZFP has the potential to raise the bar on performance. From the inception of ZFP, it was designed to accommodate a hardware implementation.

42 ENGINEERING↗

Curvature Memory in Electrically Stimulated Lipid Membranes

Here, we demonstrate, using non-equilibrium molecular dynamics simulations, that lipid membrane capacitance varies with surface charge accumulation linked to membrane shape and curvature changes. Specifically, we show that lipid membranes exhibit a hysteretic response when exposed to oscillatory electric fields. The electromechanical coupling in these membranes leads to hysteretic buckling, in which the membrane can spontaneously buckle in one of two distinct directions along the electric field, even for the same ionic charge accumulation at the water–membrane interface. In this regard, these binary buckled membrane states suggest potential applications in neuromorphic computing. Their bistable nature, characterized by two distinct and stable configurations, could serve as a foundation for implementing memory storage systems and logic operations. Furthermore, we introduce a circuit model that captures these dynamic effects, offering insights into emergent memory effects in electrically stimulated lipid membranes. Finally, this work presents lipid bilayers as dynamic, adaptable elements and suggests a new platform for exploring energy storage, information processing, and memory encoding at the lipid membrane level.

59 BASIC BIOLOGICAL SCIENCES↗

Compact and efficient elastocaloric heat pumps—Is there a path forward?

Elastocaloric cooling holds promise for energy-efficient heat pumping near room temperature with low environmental impact. Its adoption is, however, impeded by disproportionally large sizes of actuators compared with the active material volume. Taking magnetocaloric cooling as the baseline, the value of no more than 10:1 actuator volume to active material volume should lead to both size- and cost-effective solutions that may potentially be competitive with vapor-compression devices. With the goal to establish performance metrics that can lead to informed actuator selection for specific regenerator requirements, we analyze a wide range of elastocaloric materials and actuator technologies to find the best matches. We find that actuation with magnetic shape memory alloys meets all requirements; however, this technology is currently in early developmental stages and such actuators are not widely commercially available. Another promising and easily accessible option is standard rotary electric motors in combination with rotary-to-linear transduction mechanisms. A theoretical analysis of two case studies of elastocaloric systems using rotary electric motors with a Scotch yoke mechanism demonstrates the usefulness of our approach. Actuator requirements are based on two different regenerator configurations: one starting from zero strain without any mechanical energy recovery and another with 2% pre-strain and mechanical energy recovery to reduce the power and torque required from the motor. Our results indicate that the 10:1 target actuator to active material volume ratio can be met and feasibly lowered further, demonstrating that the proposed method for selecting actuators makes compact and efficient elastocaloric systems possible.

42 ENGINEERING↗

Analysis and mitigation of parasitic resistance effects for analog in-memory neural network acceleration

To support the increasing demands for efficient deep neural network processing, accelerators based on analog in-memory computation of matrix multiplication have recently gained significant attention for reducing the energy of neural network inference. However, analog processing within memory arrays must contend with the issue of parasitic voltage drops across the metal interconnects, which distort the results of the computation and limit the array size. This work analyzes how parasitic resistance affects the end-to-end inference accuracy of state-of-the-art convolutional neural networks, and comprehensively studies how various design decisions at the device, circuit, architecture, and algorithm levels affect the system's sensitivity to parasitic resistance effects. Here, a set of guidelines are provided for how to design analog accelerator hardware that is intrinsically robust to parasitic resistance, without any explicit compensation or re-training of the network parameters.

97 MATHEMATICS AND COMPUTING↗

Selective growth of Ni4Ti3 precipitate variants induced by complicated cyclic stress during laser additive manufacturing of NiTi-based composites

Highlights: • The NiTi-based composites were in-situ synthesized by SLM. • Ni{sub 4}Ti{sub 3} could tailor the phase transformation temperature of TiC/NiTi composites. • A three-dimensional stress field modeling of TiC/NiTi composites was established. • The relationship between growth of Ni{sub 4}Ti{sub 3} variants and cyclic stress was disclosed. - Abstract: NiTi-based composites were in-situ synthesized by selective laser melting (SLM) additive manufacturing technology with formation of a great many Ni{sub 4}Ti{sub 3} precipitates. The differential scanning calorimetry (DSC) were carried out to exhibit the similar phase transformation temperature (A{sub s} = 51.82 °C, A{sub f} = 94.02 °C, M{sub s} = 55.87 °C and M{sub f} = 18.93 °C) by comparing with that of SLM-fabricated equi-atomic NiTi alloy, which could be attributed to the compensation of Ni{sub 4}Ti{sub 3} precipitates for the effect of an addition of TiC particles. Three different Ni{sub 4}Ti{sub 3} precipitate variants ((111){sub R}//(1 1-bar 1-bar ){sub B2}, (111){sub R}//( 1-bar 1-bar 1){sub B2}, and (111){sub R}//( 1-bar 1 1-bar ){sub B2}) with various precipitate diameters were observed within SLM fabricated part, showing apparently selective growth behavior. By high-resolution transmission electron microscopy, severe lattice defects formed surrounding the smaller variant, while relatively intact lattice structure was found around the larger one, which indicated that high strain energy was produced in the interface between the matrix and the smaller variant. Furthermore, finite element simulation method was applied to disclose the evolution features of complicated cyclic stress during SLM processing of TiC/NiTi composites. By predicting, the main constraint mode within as-fabricated track was tensile stress effect. Based on the redistribution behavior of thermal stress and the coupling effect between the thermal stress and strain field induced by Ni{sub 4}Ti{sub 3} precipitate, the selective growth mechanism of Ni{sub 4}Ti{sub 3} variant was revealed.

36 MATERIALS SCIENCE↗

Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion

In system prognostics and health management, multivariable degradation models have been widely developed to predict the life of complex systems using degradation data of multiple Performance Characteristics (PCs). Recent studies have detected a Long-Term Memory (LTM) effect among the degradation process of various PCs, implying a strong coupling phenomenon between the future degradation behavior and historical degradation trajectory. Although the LTM has been widely integrated into single-PC-based degradation modeling, it has not been considered in multi-PC-based scenarios. To capture LTM among multiple PCs, this article proposes a novel LTM-integrated Multivariate Degradation Model (MDM) for system life prediction based on multivariate fractional Brownian motion, which simultaneously incorporates the cross-correlation among different PCs. To estimate parameters of the LTM-integrated MDM, a maximum likelihood method is developed. Here, two likelihood-ratio hypothesis tests are developed to test the existence of the overall and individual LTM effect among multiple PCs. Both simulation studies and physical experiments on the performance degradation of solar energy conversion and storage devices are conducted to validate the proposed model. Results reveal that the proposed LTM-integrated MDM significantly outperforms existing MDMs in life prediction, while the lifetime uncertainty is heavily underestimated by those traditional approaches that neglect the LTM.

42 ENGINEERING↗

Volatile organic compound emissions from 4D printing: Effects of material composition and external stimulus

4D printing of stimuli-responsive materials extends 3D printing by enabling the fabricated structures to transform their shapes and properties over time in response to external stimuli. Numerous research efforts have been dedicated to developing new smart materials, enhancing material printability, and ensuring time-evolving properties. Meanwhile, the use of smart materials and external stimuli in 4D printing has introduced the possibility of air emissions that can potentially deteriorate the indoor air quality at the workplace and pose continuous health hazards to users during the production and use phases. These potential air emissions caused by 4D printing have not yet been assessed in current literature, leading to unknown occupational hazards and human health effects. This study focuses on stereolithography-based 4D printing with constrained thermo-mechanics and builds an emission model to quantify the volatile organic compound emissions from printing, shape programming, and shape recovery stages. The established model mathematically links the emission characteristics with material compositional design and stimuli-response mechanisms. Additionally, shape fixity and recovery abilities are considered to analyze the trade-off between the air emissions and stimuli-response performance of 4D printed parts. Case study results suggest that the methacrylate-based thermo-responsive material with higher glass transition temperature leads to higher air emissions, surpassing the permissible exposure level in the indoor environment. By altering the thermo-temporal conditions, a 61.29% reduction in emission yield can be achieved while ensuring a satisfactory shape memory performance.

36 MATERIALS SCIENCE↗

Deep learning–based digital twins for heat pumps

Heat pumps are effective cooling and heating appliances to save energy in buildings. However, traditional heat pump models are challenging to integrate with building demands in a co-simulation environment because of the nonlinear thermodynamics of refrigerants. Developing digital twin representatives for heat pumps capable of faster calculations with good accuracy is desirable. This study aimed to establish a generic deep learning–based digital twin for heat pumps with a large amount of high-fidelity data. Two refrigerants for two different heat pumps were considered: an air source heat pump with refrigerant R-410A, an air source heat pump with refrigerant CO 2 , a water source heat pump with refrigerant R-410A, and a water source heat pump with refrigerant CO 2 . Furthermore, results showed that the deep learning (long short-term memory) models effectively represented these four heat pumps as a digital twin: (a) accuracy for training and testing showed smaller than 0.02 for heating electricity and heating demands, and (b) the digital twins showed good consistency with original data for heating electricity and heating demands (root mean square errors of less than 0.12 W and 0.19 W, respectively). Therefore, deep learning–based heat pump models can be used in the co-simulation of building mechanical systems.

Air source heat pump↗

Modification to the Hawking temperature of a dynamical black hole by a flow-induced supertranslation

One interesting proposal to solve the black hole information loss paradox without modifying either general relativity or quantum field theory, is the soft hair, a diffeomorphism charge that records the anisotropic radiation in the asymptotic region. This proposal, however, has been challenged, given that away from the source the soft hair behaves as a coordinate transformation that forms an Abelian group, thus unable to store any information. To maintain the spirit of the soft hair but circumvent these obstacles, we consider Hawking radiation as a probe sensitive to the entire history of the black hole evaporation, where the soft hairs on the horizon are induced by the absorption of a null anisotropic flow, generalizing the shock wave considered in [1, 2]. To do so we introduce two different time-dependent extensions of the diffeomorphism associated with the soft hair, where one is the backreaction of the anisotropic null flow, and the other is a coordinate transformation that produces the Unruh effect and a Doppler shift to the Hawking spectrum. Together, they form an exact BMS charge generator on the entire manifold that allows the nonperturbative analysis of the black hole horizon, whose surface gravity, i.e. the Hawking temperature, is found to be modified. The modification depends on an exponential average of the anisotropy of the null flow with a decay rate of 4M, suggesting the emergence of a new 2-D degree of freedom on the horizon, which could be a way out of the information loss paradox.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effects of deposition and annealing conditions on the crystallisation of NiTi thin films by e-beam evaporation

This Letter demonstrates the effects of deposition and annealing conditions on the crystallisation of nickel–titanium (NiTi) thin films deposited by the e-beam evaporation. NiTi thin films of 0.5 μm thick are fabricated on P-type (110) silicon substrates using the e-beam evaporation technique. We find that with the characterisations using the X-ray diffraction method, the results indicate that low e-beam deposition rate and argon employed annealing procedures can be beneficial to the formation of NiTi crystalline structure. Additionally, the as-deposited NiTi thin films without annealing procedures are amorphous, when deposited on the substrates at low temperatures. The differential scanning calorimetry studies show NiTi thin films formed by the e-beam evaporation are Ni-rich. Furthermore, SEM images illustrate that high-precision patterned NiTi thin film microstructures can be fabricated by combining with the e-beam evaporation and lift-off resist methods, without any wet or dry etching procedures. The proposed fabrication process for NiTi thin film microstructures shows great potential for application in shape memory alloy medical devices, as well as the micro-robotics.

36 MATERIALS SCIENCE↗

NMR study of Ni 50+x ⁢Ti 50-x strain glasses

Here, we studied Ni 50+x ⁢Ti 50-x with compositions up to x = 2, performing 47 Ti and 49 Ti nuclear magnetic resonance (NMR) measurements from 4 to 400 K. For large x in this system, a strain glass appears in which frozen ferroelastic nanodomains replace the displacive martensite structural transition. Here, we demonstrate that NMR can provide an extremely effective probe of the strain-glass freezing process, with large changes in NMR line shape due to the effects of random strains which become motionally narrowed at high temperatures. At the same time with high-resolution x-ray diffraction we confirm the lack of structural changes in x ≥ 1.2 samples, while we show that there is little change in the electronic behavior across the strain-glass freezing temperature. NMR spin-lattice relaxation time (T 1 ) measurements provide a further measure of the dynamics of the freezing process, and indicate a predominantly thermally activated behavior both above and below the strain-glass freezing temperature. We show that the strain-glass results are consistent with a very small density of critically divergent domains undergoing a Vogel-Fulcher-type freezing process, coexisting with domains exhibiting faster dynamics and stronger pinning.

36 MATERIALS SCIENCE↗