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Register a new userTruly concomitant and independently expressed short- and long-term plasticity in Bi2O2Se-based three-terminal memristor
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Orchestration of diverse synaptic plasticity mechanisms across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable to emulate short- and long-term plasticity (STP and LTP, respectively) concomitantly are essential. However, this fundamental bionic trait has not been reported in any existing memristors where STP and LTP can only be induced selectively because of the inability to be decoupled using different loci and mechanisms. In this work, we report the first demonstration of truly concomitant STP and LTP in a three-terminal memristor that uses independent physical phenomena to represent each form of plasticity. The emerging layered material Bi2O2Se is used in memristor for the first time, opening up the prospects for ultra-thin, high-speed and low-power neuromorphic devices. The concerted action of STP and LTP in our memristor allows full-range modulation of the transient synaptic efficacy, from depression to facilitation, by stimulus frequency or intensity, providing a versatile device platform for neuromorphic function implementation. A recurrent neural circuitry model is developed to simulate the intricate sleep-wake cycle autoregulation process, in which the concomitance of STP and LTP is posited as a key factor in enabling this neural homeostasis. This work sheds new light on the highly sophisticated computational capabilities of memristors and their prospects for realization of advanced neuromorphic functions.
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Recent breakthroughs in recurrent deep neural networks with long short-term memory (LSTM) units has led to major advances in artificial intelligence. State-of-the-art LSTM models with significantly increased complexity and a large number of parameters, however, have a bottleneck in computing power resulting from limited memory capacity and data communication bandwidth. Here we demonstrate experimentally that LSTM can be implemented with a memristor crossbar, which has a small circuit footprint to store a large number of parameters and in-memory computing capability that circumvents the von Neumann bottleneck. We illustrate the capability of our system by solving real-world problems in regression and classification, which shows that memristor LSTM is a promising low-power and low-latency hardware platform for edge inference.
Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic applications, recent studies in neuroscience have revealed that biological synapses undergo meta-stable volatile strengthening followed by a long-term strengthening provided that the frequency of the input stimulus is sufficiently high. Such memory strengthening and memory decay functionalities can potentially lead to adaptive neuromorphic architectures. In this paper, we demonstrate the close resemblance of the magnetization dynamics of a Magnetic Tunnel Junction (MTJ) to short-term plasticity and long-term potentiation observed in biological synapses. We illustrate that, in addition to the magnitude and duration of the input stimulus, frequency of the stimulus plays a critical role in determining long-term potentiation of the MTJ. Such MTJ synaptic memory arrays can be utilized to create compact, ultra-fast and low power intelligent neural systems.
With a large-scale usage of portable electric appliances, a high demand for increasingly high density energy storage devices has emerged. MoO3 has, in principle, a large potential as negative electrode material in supercapacitive devices, due to high charge densities that can be obtained from its reversible redox reactions. Nevertheless, the extremely poor electrochemical stability of MoO3 in aqueous electrolytes prevents a practical use in high capacitance devices. In this work, we describe how to overcome this severe stability issue by forming amorphous molybdenum oxide/tantalum oxide nanotubes by anodic oxidation of a Mo-Ta alloy. The presence of a critical amount of Ta-oxide (> 20 at-%) prevents the electrochemical decay of the MoO3 phase and thus yields an extremely high stability. Due to the protection provided by tantalum oxide, no capacitance losses are measureable after 10000 charg-ing/discharging cycles.
2D bismuth oxyselenide (Bi2O2Se) with high electron mobility shows great potential for nanoelectronics. Although in-plane properties of Bi2O2Se have been widely studied, its out-ofplane electrical transport behavior remains elusive, despite its importance in fabricating devices with new functionality and high integration density. Here, we study the out-of-plane electrical properties of 2D Bi2O2Se at nanoscale by conductive atomic force microscope. We find that hillocks with tunable heights and sizes are formed on Bi2O2Se after applying vertical electrical field. Intriguingly, such hillocks are conductive in vertical direction, resulting in a previously unknown out-of-plane resistance switching in thick Bi2O2Se flakes while ohmic conductive characteristic in thin ones. Furthermore, we observe the transformation from bipolar to stable unipolar conduction in thick Bi2O2Se flake possessing such hillocks, suggesting its potential to function as a selector in vertical devices. Our work reveals unique out-of-plane transport behavior of 2D Bi2O2Se, providing the basis for fabricating vertical devices based on this emerging 2D material.
Practical device architectures are proposed here for the implementation of three-terminal heterojunction bipolar transistor solar cells (3T-HBTSCs). These photovoltaic devices, which have a potential efficiency similar to that of multijunction cells, exhibit reduced spectral sensitivity compared with monolithically and series-connected tandem solar cells. In addition, the simplified n-p-n (or p-n-p) structure does not require the use of tunnel junctions. In this framework, four architectures are proposed and discussed in this paper: 1) one in which the top cell is based on silicon and the bottom cell is based on a heterojunction between silicon and III-V nanomaterials; 2) one in which the top cell is made of amorphous silicon and the bottom cell is made of an amorphous silicon-silicon heterojunction; 3) one based on the use of III-V semiconductors aimed at space applications; and 4) one in which the top cell is based on a perovskite material and the bottom cell is made of a perovskite-silicon heterostructure.
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