Ideal Memory Research Articles

A Soft Shape Memory Reversible Dry Adhesive

Transfer printing is a critical procedure for manufacturing stretchable electronics. During such a procedure, stamps are utilized to transfer micro devices from silicon wafers to stretchable polymeric substrates. In addition to conventional silicone rubber stamps, epoxy resin based shape memory stamps have been developed and the transfer yield is thus significantly promoted. However, elastic modulus of the epoxy stamps is too high at both glassy and rubbery states, which may break the brittle micro devices during the adhesion process under mechanical pressure. In this work, we synthesized a copolymer of butyl acrylate (BA) and polycaprolactone diacrylate (PCLDA) as a soft reversible dry adhesive enabling a shape memory capability based on crystalline transition of polycaprolactone (PCL) segments. For the sample containing 40 wt% BA and 60 wt% PCLDA, Young’s modulus was 8.3 and 0.9 MPa respectively below and above the thermal transition temperature, which was much lower than that of the epoxy adhesive. On the other hand, the soft material still provided nearly ideal shape memory fixity and recovery ratios. Subsequently, shape memory surface with cone-shaped microstructure was prepared, which enabled a heating induced strong-to-weak adhesion transition when the microstructure recovered from a pressed temporary morphology to the permanent cone-shaped morphology. Such a soft reversible dry adhesive may contribute to large-scale and automated transfer printing processing.

Electrical switching behavior of bulk AgI-Ag2O-MoO3 glass with ON-state current and thickness

Bulk AgI-Ag2O-MoO3 (50:25:25) glasses have been prepared by melt quenching method (Microwave heating and quenched between two heavy steel plates). The electrical switching experiments have been carried out using a Keithley Source Meter (model 2410) controlled by Lab VIEW 6i, on samples of thicknesses 0.1, 0.2 and 0.3 mm at different ON state currents (3 mA, 2 mA, 1 mA, 0.6 mA, 0.4 mA and 0.25 mA). The samples are found to exhibit fast memory switching. The power dissipation increases with both thickness and ON state current. The threshold voltage, VTH increases with thickness; and for a given thickness, the VTH decreases with increasing ON state current. A sample of thickness 0.1 mm exhibits near ideal memory switching with the least power dissipation for an ON state current of 0.25 mA. The samples studied can be used for fast switching applications with minimum power dissipation.

Double network epoxies with simultaneous high mechanical property and shape memory performance

Shape memory epoxy resins(SMEPs) with both high mechanical property and ideal shape memory performances were prepared by constructing double network structure through employing two kinds of curing agents with different reactivity. Results show that when the proportion of polyetheramine (D230) and diethyltoluenediamine (DETDA) are 40% and 60%, respectively, the tensile modulus, tensile strength and toughness of SMEPs are simultaneously enhanced compared with that of the samples cured with single curing agent. Meanwhile, shape memory properties still maintain at an ideal level when the proportion of D230 is 40%, while samples cured with pure DETDA show inferior shape memory property, especially at high tensile strain. DSC results show that the formation of network of sample cured with mixed curing agents can be divided into two steps, which may lead to a unique double network structure. Different network structures were characterized by DMA, TMA, and stress relaxation tests. Results show that physical network in the double network structure endows the epoxy resin with both enhanced strength and toughness while simultaneously maintained ideal shape memory performances.

Efficient Virtual Memory Sharing via On-Accelerator Page Table Walking in Heterogeneous Embedded SoCs

Shared virtual memory is key in heterogeneous systems on chip (SoCs) that combine a general-purpose host processor with a many-core accelerator, both for programmability and performance. In contrast to the full-blown, hardware-only solutions predominant in modern high-end systems, lightweight hardware-software co-designs are better suited in the context of more power- and area-constrained embedded systems and provide additional benefits in terms of flexibility and predictability. As a downside, the latter solutions require the host to handle in software synchronization in case of page misses as well as miss handling. This may incur considerable run-time overheads. In this work, we present a novel hardware-software virtual memory management approach for many-core accelerators in heterogeneous embedded SoCs. It exploits an accelerator-side helper thread concept that enables the accelerator to manage its virtual memory hardware autonomously while operating cache-coherently on the page tables of the user-space processes of the host. This greatly reduces overhead with respect to host-side solutions while retaining flexibility. We have validated the design with a set of parameterizable benchmarks and real-world applications covering various application domains. For purely memory-bound kernels, the accelerator performance improves by a factor of 3.8 compared with host-based management and lies within 50% of a lower-bound ideal memory management unit.

A molecular dynamics study on the surface welding and shape memory behaviors of Diels-Alder network

As a notable example of the recently emerged covalent adaptable network (CAN) polymers, Diels-Alder (DA) networks could depolymerize at high temperature through the reversible DA reactions, which bestows interesting behaviors of thermosetting polymers, such as malleability, surface welding behavior, and recyclability. Recently, there are increasing research interests in combining CANs with shape memory polymers (SMPs) to enable the next generation reprogrammable and recyclable actuation materials. However, our macromolecular-level understanding of DA networks that are intended for SMP applications is still limited. In this paper, we established a molecular dynamics method to investigate the surface welding and shape memory behaviors of DA networks. The mechanical properties of fresh and fully welded networks are examined by uniaxial tension measurements. The results indicate that with sufficient welding time, the welded networks can fully recover the mechanical properties as those of fresh network. The glass transition temperature of welded network with varying weight fractions of epoxy monomers are studied, and the simulation results agree well with experiment results. In addition, the shape fixity and recovery simulations reveal ideal shape memory property of the DA networks. Parametric studies revealed that with a decreased end-to-end distance of polymer chains, the DA networks exhibit higher flexibility, which significantly influences their mechanical and shape memory properties.

Characteristics of Reduced Graphene Oxide Quantum Dots for a Flexible Memory Thin Film Transistor.

Reduced graphene oxide quantum dot (rGOQD) devices in formats of capacitor and thin film transistor (TFT) were demonstrated and examined as the first trial to achieve nonambipolar channel property. In addition, through a gold nanoparticle (Au NP) layer embedded between the rGOQD active channel and dielectric layer, memory capacitor and TFT performances were realized by capacitance-voltage (C-V) hysteresis and gate program, erase, and reprogram biases. First, capacitor structure of the rGOQD memory device was constructed to examine memory charging effect featured in hysteretic C-V behavior with a 30 nm dielectric layer of cross-linked poly(vinyl alcohol). For the intervening Au NP charging layer, self-assembled monolayer (SAM) formation of the Au NP was executed to utilize electrostatic interaction by a dip-coating process under ambient environments with a conformal fabrication uniformity. Second, the rGOQD memory TFT device was also constructed in the same format of the Au NPs SAMs on a flexible substrate. Characteristics of the rGOQD TFT output showed novel saturation curves unlike typical graphene-based TFTs. However, The rGOQD TFT device reveals relatively low on/off ratio of 101 and mobility of 5.005 cm2/V·s. For the memory capacitor, the flat-band voltage shift (ΔVFB) was measured as 3.74 V for ±10 V sweep, and for the memory TFT, the threshold voltage shift (ΔVth) by the Au NP charging was detected as 7.84 V. In summary, it was concluded that the rGOQD memory device could accomplish an ideal graphene-based memory performance, which could have provided a wide memory window and saturated output characteristics.

Analysis of electromagnetically induced transparency based on quantum memory of squeezed state of light

Quantum memory of light is not only the building block of constructing large-scale quantum computer, but also the kernel component of quantum repeater for quantum networks, which makes long distance quantum communication come true. Due to the inevitable optical losses, squeezed vacuum generated from optical parametric amplifier becomes squeezed thermal state of light, which is no longer the minimum uncertainty state. Therefore quantum memory of squeezed thermal state of optical field is the key step towards the implementation of quantum internet. Atomic ensemble is one of ideal quantum memory media, as a result of high optical depth and good atomic coherence. Electromagnetically induced transparency (EIT) is one of mature approaches to quantum state mapping between non-classical optical fields and atomic spin waves. In atomic ensembles, the EIT can on-demand map quantum state between quadratures of light and spin waves of atomic ensemble, i.e., controlled quantum memory. Here the condition of quantum memory for squeezed thermal state of light is investigated according to the fidelity benchmark of quantum memory. The fidelity benchmark of quantum memory is the maximum fidelity which can be reached by classical methods, and it is quantum memory if the memory fidelity is higher than the fidelity benchmark of quantum memory. By numerically calculating the fidelity benchmark of quantum memory for different kinds of squeezed thermal states of light and the dependence of memory fidelity on the memory efficiency, we obtain the minimum memory efficiency which can realize quantum memory for squeezed thermal state of light. The quantum memory can be easily obtained by increasing squeezing parameter r. The thermal state fluctuation is sensitive to the realization of quantum memory. The required minimum memory efficiency is lower, when smaller thermal state fluctuation is employed in experiment by reducing the optical losses in optical parametric amplifier. On the other hand, quantum memory fidelity benchmark is high for small squeezing parameter and large optical depth, which requires high memory efficiency. And atomic memory efficiency can be increased by utilizing optical cavity to enhance the interaction between light and atom or atomic ensemble with high optical depth. For example, the fidelity benchmark is 0.80, when squeezing parameter r is 0.35 and thermal state fluctuation is 2.38 dB. Thus quantum memory can be realized if the memory efficiency is larger than 4.34%. Our work can provide the direct reference for experimental design of continuous variable quantum memory, quantum repeater, and quantum computer based on atomic ensembles.

Aide memoire: What should a memory clinic or a memory assessment service look like?

With the global ageing of our societies and the predicted increase of cognitive impairment and dementia, there is increasing interest in the role and scope of memory clinics or memory assessment services in the early assessment, diagnosis and management of all subtypes of dementia. Memory clinics generally attempt to provide a multidisciplinary approach to the diagnosis and treatment of memory impairment and dementia. However, little consensus exists about the profile or complement of staff that would constitute an ideal memory clinic, and services vary widely in terms of their organisation, remit and functioning. The purpose of this article is to highlight the variation amongst the existing complement of memory clinics in Ireland. The 17 models are compared in terms of their core multidisciplinary service and services available on referral. The Irish National Dementia Strategy recommends a well-coordinated service that provides early diagnosis and treatment, and one with good links to local support agencies. However, many of the services in Ireland lack input from relevant allied health professionals. This article also focusses on one privately funded memory clinic in Ireland which aims to bridge the gap between accurate diagnosis, holistic assessment and follow-up through comprehensive multidisciplinary input. The challenges facing this service are discussed, with particular reference to the difficulties encountered when providing community follow-up by a private sector clinic.

Phenomenological theory of a renormalized simplified model based on time-convolutionless mode-coupling theory near the glass transition

Abstract The renormalized simplified model is proposed to investigate indirectly how the static structure factor plays an important role in renormalizing a quadratic nonlinear term in the ideal mode-coupling memory function near the glass transition. The renormalized simplified recursion equation is then derived based on the time-convolutionless mode-coupling theory (TMCT) proposed recently by the present author. This phenomenological approach is successfully applied to check from a unified point of view how strong liquids are different from fragile liquids. The simulation results for those two types of liquids are analyzed consistently by the numerical solutions of the recursion equation. Then, the control parameter dependence of the renormalized nonlinear exponent in both types of liquids is fully investigated. Thus, it is shown that there exists a novel difference between the universal behavior in strong liquids and that in fragile liquids not only for their transport coefficients but also for their dynamics.

Clinical importance of austenitic final point in the selection of nickel-titanium alloys for application in orthodontic-use arches

There are many nickel-titanium alloy wires available in the market.Nevertheless not all of them possess the ideal characteristicsof shape memory and super-elasticity to be used in orthodontictreatment. The aim of the present study was to find austeniticfinal temperature of these archwires so as to determine thetransformation phase in order to better use them in orthodontics.Methods: Eleven nickel-titanium orthodontic wires were selected.Transformation phase was assessed using differential scanningcalorimetry method. Conclusions: The present study illustrateshow some orthodontic Ni-Ti wires elicit results contrary to thoseadvertised.

Computational Models of Language Usage, Acquisition, and Transmission

Language LearningVolume 66, Issue S1 p. 241-278 Article Computational Models of Language Usage, Acquisition, and Transmission First published: 25 May 2016 https://doi.org/10.1111/lang.9_12177Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Supporting Information Additional Supporting Information may be found in the online version of this article at the publisher's website: Filename Description lang9_12177-sup-0001-SupMat.pdf809.3 KB Figure S9.1 Activation of the VL, VOL, and VOO pattern by different prepositions and pronouns in Simulation 1. Figure S9.2 A hierarchical category structure of 31 names which, at five different levels of generality, describe 16 referents. Figure S9.3 Three hierarchical categories of the type shown in Figure S9.2. Figure S9.4 Memory maps for Initial Adult and Initial Child representations relating the 48 referents and 93 names. In these heatmaps, lighter color relates to higher activation. Figure S9.5 Initial ideal adult memory activations at the beginning of each run and the corresponding dendrogram relating to initial conceptual structure. Figure S9.6 Generation 5 child memory activations and corresponding dendrogram conceptual structure after five generations of Principle of Least Effort discourse. Figure S9.7 Initial conceptual structure heatmap and Generation 5 child memory activations after five generations of each discourse strategy. Figure S9.8 Initial conceptual structure dendrograms and Generation 5 child memory dendrograms after five generations of each discourse strategy. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. Volume66, IssueS1Special Issue: Language Learning Monograph Series: Usage-based Approaches to Language Acquisition and Processing: Cognitive and Corpus Investigations of Construction GrammarJune 2016Pages 241-278 RelatedInformation

Effect of platinum substitution on the structural and magnetic properties ofNi2MnGaferromagnetic shape memory alloy

${\mathrm{Ni}}_{2}\mathrm{MnGa}$ exhibits ideal ferromagnetic shape memory properties, however, brittleness and a low-temperature martensite transition hinder its technological applications motivating the search for novel materials showing better mechanical properties as well as higher transition temperatures. In this work, the crystal structure, phase transitions, and the magnetic properties of quaternary ${\mathrm{Ni}}_{2\ensuremath{-}x}{\mathrm{Pt}}_{x}\mathrm{MnGa}(0\ensuremath{\le}x\ensuremath{\le}1)$ shape memory alloys were studied experimentally by x-ray diffraction, magnetization measurements, and neutron diffraction and compared to ab initio calculations. Compositions within $0\ensuremath{\le}x\ensuremath{\le}0.25$ exhibit the cubic austenite phase at room temperature. The $x\ensuremath{\approx}0.3$ composition exhibits a seven-layer modulated monoclinic martensite structure. Within $0.4\ensuremath{\le}x\ensuremath{\le}1$, the system stabilizes in the nonmodulated tetragonal structure. The martensite transition has very narrow thermal hysteresis $0\ensuremath{\le}x\ensuremath{\le}0.3$, which is a typical characteristic of a shape memory alloy. By increasing $x$, the temperature of the martensite transition increases, while that of the magnetic transition decreases. The $x=1$ composition ($\text{NiPtMnGa}$) in the martensite phase undergoes a para-to-ferrimagnetic transition. The saturation magnetization exhibits a nontrivial behavior with increasing up to $x\ensuremath{\approx}0.25$, above which, it suddenly decreases. Powder neutron diffraction reveals the presence of antisite disorder, with about 17% of the original Ga sites being occupied by Mn. Computations suggest that the antisite disorder triggers an antiferromagnetic coupling between two Mn atoms in different crystallographic positions, resulting into a sudden drop of the saturation magnetization for higher $x$.

Memory Access Scheduling for a Smart TV

A smart TV system-on-chip (SoC) has very heavy computation and memory demands that must be met with low-cost components. As a result, there is potentially an extremely high utilization of the channel between the SoC and its memory chip. This paper presents the design of a new memory access scheduler customized for the type of memory traffic typically encountered with smart TVs. This includes special accumulated hard real-time graphics requirements, user response-sensitive soft real-time requirements, and the need to provide high memory throughput and priority-handling capabilities even under extremely heavy memory traffic conditions. The simulation results show that the proposed memory access scheduler is able to achieve up to 98% of the ideal upper bound memory throughput when faced with extremely heavy memory traffic—this is a significant improvement over previous schedulers. Novel future prediction and light-handed priority handling methods are used to achieve these results while satisfying the unique real-time requirements of smart TVs.

A molecular dynamics investigation of the deformation mechanism and shape memory effect of epoxy shape memory polymers

Following deformation, thermally induced shape memory polymers (SMPs) have the ability to recover their original shape with a change in temperature. In this work, the thermomechanical properties and shape memory behaviors of three types of epoxy SMPs with varying curing agent contents were investigated using a molecular dynamics (MD) method. The mechanical properties under uniaxial tension at different temperatures were obtained, and the simulation results compared reasonably with experimental data. In addition, in a thermomechanical cycle, ideal shape memory effects for the three types of SMPs were revealed through the shape frozen and shape recovery responses at low and high temperatures, respectively, indicating that the recovery time is strongly influenced by the ratio of E-51 to 4,4’-Methylenedianiline.

Memory-built-in quantum cloning in a hybrid solid-state spin register

As a way to circumvent the quantum no-cloning theorem, approximate quantum cloning protocols have received wide attention with remarkable applications. Copying of quantum states to memory qubits provides an important strategy for eavesdropping in quantum cryptography. We report an experiment that realizes cloning of quantum states from an electron spin to a nuclear spin in a hybrid solid-state spin register with near-optimal fidelity. The nuclear spin provides an ideal memory qubit at room temperature, which stores the cloned quantum states for a millisecond under ambient conditions, exceeding the lifetime of the original quantum state carried by the electron spin by orders of magnitude. The realization of a cloning machine with built-in quantum memory provides a key step for application of quantum cloning in quantum information science.

A fractional-order memristor model and the fingerprint of the simple series circuits including a fractional-order memristor

A memristor is a nonlinear resistor with time memory. The resistance of a classical memristor at a given time is represented by the integration of all the full states before the time instant, a case of ideal memory without any loss. Recent studies show that there is a memory loss of the HP TiO2 linear model, in which the width of the doped layer of HP TiO2 model cannot be equal to zero or the whole width of the model. Based on this observation, a fractional-order HP TiO2 memristor model with the order between 0 and 1 is proposed, and the fingerprint analysis of the new fractional-order model under periodic external excitation is made, thus the formula for calculating the area of hysteresis loop is obtained. It is found that the shape and the area enclosed by the hysteresis loop depend on the order of the fractional-order derivative. Especially, for exciting frequency being bigger than 1, the memory strength of the memristor takes its maximal value when the order is a fractional number, not an integer. Then, the current-voltage characteristics of the simple series one-port circuit composed of the fractional-order memristor and the capacitor, or composed of the fractional-order memristor and the inductor are studied separately. Results demonstrate that at the periodic excitation, the memristor in the series circuits will have capacitive properties or inductive properties as the fractional order changes.

Quasi-Ideal Memory System

The definition for ideal memory system is so strict that some physical elements cannot exist in the real world. In this paper, an ideal memory system can be extended to generate 15 different kinds of quasi-ideal memory systems, which are included in memory systems as its special cases and are different from ideal memory system. For a system to be a quasi-ideal memory system, it should show three unique fingerprints: 1) the pinched hysteretic loop of a quasi-ideal memory system must be odd symmetrical in the plane; 2) the pinched hysteretic loop of a quasi-ideal memory system must be "self-crossing"; and 3) the slope of tangent line for the pinched hysteresis loop must be strictly monotone in a given period.

A Particle Swarm Optimization Approach for Reuse Guided Case Retrieval

The success of Case Based Reasoning (CBR) problem solving is mainly based on the recall process. The ideal CBR memory is one that simultaneously speeds up the retrieval step while improving the reuse of retrieved cases. In this paper, the authors present a novel associative memory model to perform the retrieval stage in a case based reasoning system. The described approach makes no prior assumption of a specific organization of the case memory, thus leading to a generic recall process. This is made possible by using Particle Swarm Optimization (PSO) to compute the neighborhood of a new problem, followed by direct access to the cases it contains. The fitness function of the PSO stage has a reuse semantic that combines similarity and adaptability as criteria for optimal case retrieval. The model was experimented on two proprietary databases and compared to the flat memory model for performance. The obtained results are very promising.

High performance organic nonvolatile flash memory transistors with high-resolution reduced graphene oxide patterns as a floating gate.

High-performance organic nonvolatile memory transistors (ONVMTs) are demonstrated, the construction of which is based on novel integration of a highly conductive polymer as a semiconductor layer, hydroxyl-free polymer as a tunneling dielectric layer, and high-resolution reduced graphene oxide (rGO) patterns as a floating gate. Finely patterned rGO, with a line width of 20-120 μm, was embedded between SiO2 and the polymer dielectric layer, which functions as a nearly isolated charge-trapping center. The resulting ONVMTs demonstrated ideal memory behavior, and the transfer characteristics promptly responded to writing and erasing the gate bias. In particular, the retention time of written/erased states tended to increase as the rGO line width was reduced, implying that the line width is a critical factor in suppressing charge release from rGO. Using a 20-μm-wide rGO pattern, a nonvolatile large memory window (>20 V) was retained for more than 5 × 10(5) s, which is 50 times longer than non-patterned rGO films.

Process Variation-Aware Nonuniform Cache Management in a 3D Die-Stacked Multicore Processor

Process variations in integrated circuits have significant impact on their performance, leakage, and stability. This is particularly evident in large, regular, and dense structures such as DRAMs. DRAMs are built using minimized transistors with presumably uniform speed in an organized array structure. Process variation can introduce latency disparity among different memory arrays. With the proliferation of 3D stacking technology, DRAMs become a favorable choice for stacking on top of a multicore processor as a last level cache for large capacity, high bandwidth, and low power. Hence, variations in bank speed create a unique problem of nonuniform cache accesses in 3D space. In this paper, we investigate cache management techniques for tolerating process variation in a 3D DRAM stacked onto a multicore processor. We modeled the process variation in a four-layer DRAM memory, including cell transistor, capacitor trench, and peripheral circuit, to characterize the latency and retention time variations among different banks. As a result, the notion of fast and slow banks from the core's standpoint is no longer associated with their physical distances with the banks. They are determined by the different bank latencies due to process variation. We develop cache migration schemes that utilize fast banks while limiting the cost due to migration. Our experiments show that there is a great performance benefit in exploiting fast memory banks through migration. On average, a variation-aware management can improve the performance of a workload over the baseline (where one of the slowest bank speed is assumed for all banks) by 16.5 percent. We are also only 0.8 percent away in performance from an ideal memory where no process variation is present.