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Register a new userA non-volatile memory based on nonlinear magnetoelectric effects
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The magnetoelectric effects in multiferroics have a great potential in creating next-generation memory devices. We conceive a new concept of non-volatile memories based on a type of nonlinear magnetoelectric effects showing a butterfly-shaped hysteresis loop. The principle is to utilize the states of the magnetoelectric coefficient, instead of magnetization, electric polarization or resistance, to store binary information. Our experiments in a device made of the PMN-PT/Terfenol-D multiferroic heterostructure clearly demonstrate that the sign of the magnetoelectric coefficient can be repeatedly switched between positive and negative by applying electric fields, confirming the feasibility of this principle. This kind of non-volatile memory has outstanding practical virtues such as simple structure, easy operations in writing and reading, low power, fast speed, and diverse materials available.
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The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric memories have been proposed and explored in the past decade. Here we propose a new principle to realize a multilevel nonvolatile memory based on the multiple states of the magnetoelectric coefficient ({alpha}) of multiferroics. Because the states of {alpha} depends on the relative orientation between magnetization and polarization, one can reach different levels of {alpha} by controlling the ratio of up and down ferroelectric domains with external electric fields. Our experiments in a device made of the PMN-PT/Terfenol-D multiferroic heterostructure confirm that the states of {alpha} can be well controlled between positive and negative by applying selective electric fields. Consequently, two-level, four-level, and eight-level nonvolatile memory devices are demonstrated at room temperature. This kind of multilevel magnetoelectric memory retains all the advantages of ferroelectric random access memory but overcomes the drawback of destructive reading of polarization. In contrast, the reading of {alpha} is nondestructive and highly efficient in a parallel way, with an independent reading coil shared by all the memory cells.
This paper presents a novel resistive-only Binary and Ternary Content Addressable Memory (B/TCAM) cell that consists of two Complementary Resistive Switches (CRSs). The operation of such a cell relies on a logic$rightarrow$ON state transition that enables this novel CRS application.
Information technologies require entangling data stability with encryption for a next generation of secure data storage. Current magnetic memories, ranging from low-density stripes up to high-density hard drives, can ultimately be detected using routinely available probes or manipulated by external magnetic perturbations. Antiferromagnetic resistors feature unrivalled robustness but the stable resistive states reported scarcely differ by more than a fraction of a percent at room temperature. Here we show that the metamagnetic (ferromagnetic to antiferromagnetic) transition in intermetallic Fe0.50Rh0.50 can be electrically controlled in a magnetoelectric heterostructure to reveal or cloak a given ferromagnetic state. From an aligned ferromagnetic phase, magnetic states are frozen into the antiferromagnetic phase by the application of an electric field, thus eliminating the stray field and likewise making it insensitive to external magnetic field. Application of a reverse electric field reverts the antiferromagnetic state to the original ferromagnetic state. Our work demonstrates the building blocks of a feasible, extremely stable, non-volatile, electrically addressable, low-energy dissipation, magnetoelectric multiferroic memory.
Recent experiments on layered {alpha}-In2Se3 have confirmed its room-temperature ferroelectricity under ambient condition. This observation renders {alpha}-In2Se3 an excellent platform for developing two-dimensional (2D) layered-material based electronics with nonvolatile functionality. In this letter, we demonstrate non-volatile memory effect in a hybrid 2D ferroelectric field effect transistor (FeFET) made of ultrathin {alpha}-In2Se3 and graphene. The resistance of graphene channel in the FeFET is tunable and retentive due to the electrostatic doping, which stems from the electric polarization of the ferroelectric {alpha}-In2Se3. The electronic logic bit can be represented and stored with different orientations of electric dipoles in the top-gate ferroelectric. The 2D FeFET can be randomly re-written over more than $10^5$ cycles without losing the non-volatility. Our approach demonstrates a protype of re-writable non-volatile memory with ferroelectricity in van de Waals 2D materials.
Flat combining (FC) is a synchronization paradigm in which a single thread, holding a global lock, collects requests by multiple threads for accessing a concurrent data structure and applies their combined requests to it. Although FC is sequential, it significantly reduces synchronization overheads and cache invalidations and thus often provides better performance than that of lock-free implementations. The recent emergence of non-volatile memory (NVM) technologies increases the interest in the development of persistent (a.k.a. durable or recoverable) objects. These are objects that are able to recover from system failures and ensure consistency by retaining their state in NVM and fixing it, if required, upon recovery. Of particular interest are detectable objects that, in addition to ensuring consistency, allow recovery code to infer if a failed operation took effect before the crash and, if it did, obtain its response. In this work, we present the first FC-based persistent object. Specifically, we introduce a detectable FC-based implementation of a concurrent LIFO stack object. Our empirical evaluation establishes that thanks to the usage of flat combining, the novel stack algorithm requires a much smaller number of costly persistence instructions than competing algorithms and is therefore able to significantly outperform them.
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