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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamic voltage frequency scaling based on active memory barriers

A processing unit includes compute units partitioned into one or islands that are provided with operating voltages and clock signals having clock frequencies independent of providing operating voltages or clock signals to other islands of compute units. The processing unit also includes dynamic voltage and frequency scaling (DVFS) hardware configured to compute one or more numbers of active memory barriers in the one or more islands. The DVFS hardware is also configured to modify the operating voltages or clock frequencies provided to the one or more islands in response to a change in numbers of active memory barriers in the one or more islands. In some cases, the operating voltage or clock frequency provided to an island is increased in response to the number of active memory barriers in the island decreasing. The operating voltage or clock frequency provided to the island is decreased in response to the number of active memory barriers in the island increasing.

Bharadwaj, Vedula Venkata Srikant↗
DOE OSTI2022

Bias control for a memory device

Methods, systems, and devices for bias control for a memory device are described. A memory system may store indication of whether data is coherent. In some examples, the indication may be stored as metadata, where a first value indicates that the data is not coherent and a second value or a third value indicate that the data is coherent. When a processing unit or other component of the memory system processes a command to access data, the memory system may operate according to a device bias mode when the indication is the first value, and according to a host bias mode when the indication is the second value or the third value.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Method and apparatus for front end gather/scatter memory coalescing

A system for processing gather and scatter instructions can implement a front-end subsystem, a back-end subsystem, or both. The front-end subsystem includes a prediction unit configured to determine a predicted quantity of coalesced memory access operations required by an instruction. A decode unit converts the instruction into a plurality of access operations based on the predicted quantity, and transmits the plurality of access operations and an indication of the predicted quantity to an issue queue. The back-end subsystem includes a load-store unit that receives a plurality of access operations corresponding to an instruction, determines a subset of the plurality of access operations that can be coalesced, and forms a coalesced memory access operation from the subset. A queue stores multiple memory addresses for a given load-store entry to provide for execution of coalesced memory accesses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Method and apparatus for back end gather/scatter memory coalescing

A system for processing gather and scatter instructions can implement a front-end subsystem, a back-end subsystem, or both. The front-end subsystem includes a prediction unit configured to determine a predicted quantity of coalesced memory access operations required by an instruction. A decode unit converts the instruction into a plurality of access operations based on the predicted quantity, and transmits the plurality of access operations and an indication of the predicted quantity to an issue queue. The back-end subsystem includes a load-store unit that receives a plurality of access operations corresponding to an instruction, determines a subset of the plurality of access operations that can be coalesced, and forms a coalesced memory access operation from the subset. A queue stores multiple memory addresses for a given load-store entry to provide for execution of coalesced memory accesses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Bias control for a memory device

Methods, systems, and devices for bias control for a memory device are described. A memory system may store indication of whether data is coherent. In some examples, the indication may be stored as metadata, where a first value indicates that the data is not coherent and a second value or a third value indicate that the data is coherent. When a processing unit or other component of the memory system processes a command to access data, the memory system may operate according to a device bias mode when the indication is the first value, and according to a host bias mode when the indication is the second value or the third value.

Walker, Dean↗
DOE OSTI2022

Device-Centric Ransomware Detection using Machine Learning-Based Memory Forensics for Smart Inverters

Ransomware attacks are the fastest-growing form of cyberattacks worldwide. Recently, ransomware attacks have targeted industrial control systems (ICSs), including power grids. Lessons learned from recent incidents in ICSs show that ransomware groups can deliver ransomware into not only the organization’s control servers, but also the operational technology (OT) devices such as smart inverters and smart grid devices. This paper proposes a machine learning (ML)- based memory forensics method enabling the detection of ransomware binaries stored in the memory of a commercial smart inverter. Device firmware binary files are extracted from a Serial Peripheral Interface (SPI) flash memory, and samples of both benign and ransomware binaries are generated by a binary manipulation method and a real-world ransomware encryption, separately. A deep transfer learning (DTL) method is used to retrain a convolutional neural network (CNN)-based ransomware detection algorithm using the generated samples. The experimental result validates that the proposed ML-based memory forensics method can accurately detect ransomware files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Nanoporous Dielectric Resistive Memories Using Sequential Infiltration Synthesis

Resistance switching in metal–insulator–metal structures has been extensively studied in recent years for use as synaptic elements for neuromorphic computing and as nonvolatile memory elements. However, high switching power requirements, device variabilities, and considerable trade-offs between low operating voltages, high on/off ratios, and low leakage have limited their utility. Here, we have addressed these issues by demonstrating the use of ultraporous dielectrics as a pathway for high-performance resistive memory devices. Using a modified atomic layer deposition based technique known as sequential infiltration synthesis, which was developed originally for improving polymer properties such as enhanced etch resistance of electron-beam resists and for the creation of films for filtration and oleophilic applications, we are able to create ~15 nm thick ultraporous (pore size ~5 nm) oxide dielectrics with up to 73% porosity as the medium for filament formation. We show, using the Ag/Al 2 O 3 system, that the ultraporous films result in ultrahigh on/off ratio (>10 9 ) at ultralow switching voltages (~±600 mV) that are 10× smaller than those for the bulk case. In addition, the devices demonstrate fast switching, pulsed endurance up to 1 million cycles. and high temperature (125 °C) retention up to 10 4 s, making this approach highly promising for large-scale neuromorphic and memory applications. Additionally, this synthesis methodology provides a compatible, inexpensive route that is scalable and compatible with existing semiconductor nanofabrication methods and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

External-Field-Induced Phase Transformation and Associated Properties in a Ni 50 Mn 34 Fe 3 In 13 Metamagnetic Shape Memory Wire

Metamagnetic shape memory alloys exhibit a series of intriguing multifunctional properties and have great potential for applications in magnetic actuation, sensing and magnetic refrigeration. However, the poor mechanical properties of these alloys with hardly any tensile deformability seriously limit their practical application. In the present work, we developed a Ni-Fe-Mn-In microwire that exhibits both a giant, tensile superelasticity and a magnetic-field-induced first-order phase transformation. The recoverable strain of superelasticity is more than 20% in the temperature range of 233–283 K, which is the highest recoverable strain reported heretofore in Ni-Mn-based shape memory alloys (SMAs). Moreover, the present microwire exhibits a large shape memory effect with a recoverable strain of up to 13.9% under the constant tensile stress of 225 MPa. As a result of the magnetic-field-induced first-order phase transformation, a large reversible magnetocaloric effect with an isothermal entropy change ΔS m of 15.1 J kg –1 K –1 for a field change from 0.2 T to 5 T was achieved in this microwire. The realization of both magnetic-field and tensile-stress-induced transformations confers on this microwire great potential for application in miniature multi-functional devices and provides an opportunity for multi-functional property optimization under coupled multiple fields.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Medical applications of shape memory polymers

Shape memory polymers are described here and major advantages in some applications are identified over other medical materials such as shape memory alloys (SMA). A number of medical applications are anticipated for shape memory polymers. Some simple applications are already utilized in medical world, others are in examination process. Lately, several important applications are being considered for CHEM foams for self-deployable vascular and coronary devices. One of these potential applications, the endovascular treatment of aneurysm was experimentally investigated with encouraging results and is described in this paper as well.

cold hibernated elastic memory (CHEM)↗
NASA NTRS2014

Radiation Effects of Commercial Resistive Random Access Memories

We present results for the single-event effect response of commercial production-level resistive random access memories. We found that the resistive memory arrays are immune to heavy ion-induced upsets. However, the devices were susceptible to single-event functional interrupts, due to upsets from the control circuits. The intrinsic radiation tolerant nature of resistive memory makes the technology an attractive consideration for future space applications.

Random Access Memory (RAM)↗
DOE OSTI2022

Two–Photon Printing of Shape–Memory Microstructures and Metasurfaces via Radical–Mediated Thiol–Vinyl Hydrothiolation

Shape-memory resists capable of high-resolution curing into arbitrarily designed structures are increasingly demanded for soft robotics, optical sensors, microscale manufacturing, and biomedicine. Amorphous, shape-memory thiol-vinyl networks were printed using two-photon polymerization (2PP) curing of a simple resin formulated with commercially available reagents. The ability to print high-resolution feature sizes down to 200 nm is attributed to the use of radicalmediated, thiol-vinyl step-growth polymerization that quickly crosslinks the resin, limiting diffusive transport. The thermomechanical behavior of the 2PP-cured material analyzed in compression, tension and three-point bending is similar to the behavior of the UV-polymerized samples. To demonstrate the ability to design, field, and test 4D responsive microstructures, an array of nine springs with coil diameters of 330 μm was printed. Following compressive shapefixing, printed arrays can release 11 μJ of stored elastic strain energy when reheated. Further, a new concept of dichroic-memory of a metamaterial device is demonstrated by printing a twisted woodpile structure with circular dichroism as characterized by Mueller Matrix ellipsometry. Furthermore, our results demonstrate how combining high-resolution 2PP curing with stimuli-responsive molecular architectures can further the engineering of responsive microstructures and metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Functional Performances of CuZnAl Shape Memory Alloy Open-Cell Foams

Shape memory alloys (SMAs) with cellular structure offer a unique mixture of thermo-physical–mechanical properties. These characteristics can be tuned by changing the pore size and make the shape memory metallic foams very attractive for developing new devices for structural and functional applications. In this work, CuZnAl SMA foams were produced through the liquid infiltration of space holder method. In comparison, a conventional CuZn brass alloy was foamed trough the same method. Functional performances were studied on both bulk and foamed SMA specimens. Calorimetric response shows similar martensitic transformation (MT) below 0 °C. Compressive response of CuZnAl revealed that mechanical behavior is strongly affected by sample morphology and that damping capacity of metallic foam is increased above the MT temperatures. The shape memory effect was detected in the CuZnAl foams. The conventional brass shows a compressive response similar to that of the martensitic CuZnAl, in which plastic deformation accumulation occurs up to the cellular structure densification after few thermal cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Competing Interactions between Mesoscale Length-Scales, Order-Disorder, and Martensitic Transformation in Ferromagnetic Shape Memory Alloys

In the present study, the effects of composition and heat treatments and the resulting microstructural changes on the martensitic transformation and ferromagnetic transition have been investigated in NiCoMnIn metamagnetic shape memory alloys. In this shape memory alloy system, it is observed that upon heat treatments at a wide temperature range, the onset temperature of the martensitic transformation follows a non-monotonic behavior with respect to heat treatment time, and the nature of the non-monotonic behavior is also a function of composition. This behavior cannot be attributed to well-known factors such as precipitation, change in local composition due to the precipitation and/or global degree of order. In this work, a systematic investigation through synthesis, thermal processing and characterization via thermo-physical measurements, transmission electron microscopy and in-situ synchrotron x-ray diffraction experiments has been used to correlate the non-monotonic dependence of the martensitic transformation and ferromagnetic transition temperatures to the evolution of L2 1 domains arising from a order/disorder phase transition. A thermodynamic model for the magneto-structural transition is combined with classical nucleation theory to further ascertain the role of microstructural length-scales on the onset of the martensitic transformation. This work thus provides understanding of the thermodynamic and kinetic factors that can be controlled to tune the coupled magneto-structural transformations in NiCoMnIn metamagnetic shape memory alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Shape memory alloy engine for high efficiency low-temperature gradient thermal to electrical conversion

More than half of the energy generated worldwide is lost as unused thermal energy because of the lack of efficient methodology for harnessing the low-grade heat. In this paper, we demonstrate that shape-memory alloy can be an effective mechanism for recovering low-grade heat. Shape memory alloys exhibit thermally induced martensite to austenite phase transformation and super-elasticity (stress-induced martensitic transformation). Employing these two characteristics, we demonstrate a thermal engine for harnessing waste energy through all modes of heat transfer: convection, conduction, and radiation. In this work, we performed material and heat transfer analysis for achieving high frequency, sustainable and efficient operation of our engine. An optimized shape memory alloy engine generated 36 W per kilogram or 234 kW of electricity per cubic meter of active material. A continuous three-day operation of several SMA engines could generate 7.2 kWh of electricity when installed on a 500 m long hot pipe network. This generated power can potentially reduce the carbon footprint by 5.1 kg of CO 2 illustrating the promise of this technology for addressing climate change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A general non-Fourier Stefan problem formulation that accounts for memory effects

The Stefan problem is the classical model of a melting phase change. In heterogeneous systems, such phase changes can exhibit non-Fourier (anomalous) behaviors, where the advance of the melt interface does not follow the expected time scaling. These situations can be modeled by replacing the derivatives, in the governing partial differential equations, with fractional order derivatives. In particular, replacing the time derivatives leads to non-Fourier models that account for memory effects in the system. In this work, by using appropriate time convolution integrals, a general thermodynamic balance statement for melting phase problems, explicitly accounting for memory effects, is developed. From this balance, a general model formulation applicable to problems involving melting over a temperature range (i.e., a mushy region) is derived. A key component in this model is the representation of memory effects through the use of fractional derivative based constitutive models of the enthalpy and heat flux. Further, on shrinking the mushy region to a single isotherm, a general sharp interface melting model is obtained. Here, in contrast to the classic Stefan problem, the fractional derivatives induce a natural regularization, such that the constitutive models for enthalpy and heat flux are continuous at the melt interface; a result confirmed through numerical simulation. To further support the theoretical findings, a physical example of a non-Fourier Stefan problem is presented. Overall the development and results in this paper underscore the importance of explicitly relating the development of fractional calculus models to the appropriate thermodynamic balance statements.

42 ENGINEERING↗
DOE OSTI2015

Microstructure, crystallization and shape memory behavior of titania and yttria co-doped zirconia

Small volume zirconia ceramics with few or no grain boundaries have been demonstrated recently to exhibit the shape memory effect. To explore the shape memory properties of yttria doped zirconia (YDZ), it is desirable to develop large, microscale grains, instead of submicron grains that result from typical processing of YDZ. In this paper, we have successfully produced single crystal micro-pillars from microscale grains encouraged by the addition of titania during processing. Titania has been doped into YDZ ceramics and its effect on the grain growth, crystallization and microscale elemental distribution of the ceramics have been systematically studied. With 5 mol% titania doping, the grain size can be increased up to ~4 μm, while retaining a large quantity of the desired tetragonal phase of zirconia. Finally, micro-pillars machined from tetragonal grains exhibit the expected shape memory effects where pillars made from titania-free YDZ would not.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Microstructures and phase transformations of Ti-30Zr-xNb (x = 5, 7, 9, 13 at.%) shape memory alloys

The microstructures, phase transformations and shape memory properties of Ti-30Zr-xNb (x = 5, 7, 9, 13 at.%) alloys were investigated. The X-ray diffraction and transmission electron microscopy observations showed that the Ti-30Zr-5Nb, Ti-30Zr-7/9Nb and Ti-30Zr-13Nb alloys were composed of the hcp α′-martensite, orthorhombic α″-martensite and β phases, respectively. The results indicated the enhanced β-stabilizing effect of Nb in Ti-30Zr-xNb alloys than that in Ti-Nb alloys due to the high content of Zr. The differential scanning calorimetry test indicated that the Ti-30Zr-5Nb alloy displayed a reversible transformation with a high martensitic transformation start temperature of 776 K and a reverse martensitic transformation start temperature (A{sub s}) of 790 K. For the Ti-30Zr-7Nb and Ti-30Zr-9Nb alloys, the martensitic transformation temperatures decreased with the increasing Nb content. Moreover, an ω phase transformation occurred in the both alloys upon heating at a temperature lower than the corresponding A{sub s}, which is prompted by more addition of Nb. Although the critical stress in tension of the three martensitic alloys decreased with increasing Nb content, the Ti-30Zr-9Nb alloy showed a critical stress of as high as 300 MPa. Among all the alloys, the Ti-30Zr-9Nb alloy exhibited the maximum shape memory effect of 1.61%, due to the lowest critical stress for the martensite reorientation. - Highlights: •Ti-30Zr-5Nb alloy is composed of hcp α′-martensite with the M{sub s} of 776 K. •Ti-30Zr-7Nb and Ti-30Zr-9Nb alloys are predominated by orthorhombic α″-martensite. •Ti-30Zr-13Nb alloy consists of a single β phase due to the β-stabilizing effect of Nb. •The martensitic transformation temperatures decrease with increasing Nb content. •Ti-30Zr-9Nb alloy shows the maximum shape memory effect of 1.61%.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Phase transformation and microstructure evolution of the deformed Ti-30Zr-5Nb shape memory alloy

The phase transformation and microstructures of the deformed Ti-30Zr-5Nb shape memory alloy were investigated. The X-ray diffraction measurements indicated that the Ti-30Zr-5Nb alloy was composed of a single orthorhombic α″-martensite phase. The alloy exhibited one yielding behavior in the tensile test, with a critical stress of ~ 600 MPa and a tensile strain of approximately 15%. A shape memory recovery accompanied by a permanent strain was exhibited in the deformed alloys when heated at 873 K. The permanent strain increased with increasing pre-strain. The microstructure evolution of the deformed alloy was investigated by transmission electron microscopy. The results showed that the martensite reorientation occurred and the dislocations were generated during deformation. The alloy displayed a reversible martensite transformation start temperature as high as 763 K. However, no strain-induced martensite stabilization was found in the deformed alloy with different pre-strain levels, potentially because the large chemical energy of the Ti-30Zr-5Nb alloy depressed the effects of the elastic energy and the dissipative energy. - Highlights: • Ti-30Zr-5Nb alloy is composed of single orthorhombic α″-martensite phase with M{sub s} of 721 K. • No martensite stabilization has been found in Ti-30Zr-5Nb alloy with different pre-strain. • Ti-30Zr-5Nb shows the maximum shape memory effect of 2.75% with a pre-strain of 8%.

36 MATERIALS SCIENCE↗