Artificial Synapse Based on Vertically Aligned Nanocomposite Ferroelectric Thin Films

Enhanced Memristive Performance via a Vertically Heterointerface in Nanocomposite Thin Films for Artificial Synapses

“…24 Ferroelectric nanocomposite thin films have also been developed to reduce the leakage current and hence improve the performance of the ferroelectric memristor. 7,25 However, there is limited work on utilizing the vertical heterointerface in vertically aligned nanocomposites (VANs) as the conductive channels in resistive random access memory for artificial neuromorphic computing, except the very recent work on the SrTiO 3 −MgO-based memristor. 26 While certain prior investigations have examined VANs and their enhanced resistive switching properties, they predominantly focused on ionic conductive materials, with limited exploration into their applicability in artificial neuromorphic computing.…”

“…In the conventional computer architecture rooted in the von Neumann paradigm, the computational and storage modules are physically distinct entities, leading to inherent challenges such as heightened energy consumption and limited efficiency. − Such issues find more elegant resolutions within the domain of neuromorphic computing, which is inspired by the biological nervous system, emulating key functions such as memory and learning by constructing computing architectures analogous to the human brain. This approach facilitates the integration of computing and storage elements, co-locating them within artificial synapses for efficient information processing and storage. − In memristors, the top electrode, bottom electrode, and functional layer correspond, respectively, to the presynaptic neuron, postsynaptic neuron, and the synaptic gap, and their inherent electrical characteristics closely mimic those of natural synapses, − which makes them emerging as highly promising candidates for simulating synaptic functions in neuromorphic computing systems.…”

“…Moreover, it mitigates the inherent randomness associated with filament formation and rupture, thereby substantially enhancing the uniformity of resistance distribution across these devices . Ferroelectric nanocomposite thin films have also been developed to reduce the leakage current and hence improve the performance of the ferroelectric memristor. , …”

“…In addition, BTO stands as a well-established and enduring ferroelectric material, garnering substantial attention for its application as a functional layer in memristor devices . A comprehensive body of research has been dedicated to optimizing the performance of both ZnO and BTO-based memristor devices. ,, However, ZnO–BTO nanocomposite thin film has not yet been well studied as a functional layer for memristor, where both filament and ferroelectricity might contribute to the overall performance of the device. Regarding the other reported VAN-based memristors, , where the VAN design aims to reduce leakage current in the ferroelectric phase to enhance the device performance.…”

Diode Characteristics in Magnetic Domain Wall Devices via Geometrical Pinning for Neuromorphic Computing

“…Different material classes have been investigated to realize artificial neurons and synapses. Among these, resistive random-access memory, , ferroelectric materials, − phase-change materials, and spintronics materials have gotten significant attention from the research community. Recent research trend indicates that spintronic domain wall (DW) devices are potentially useful for NC owing to their low energy consumption, high endurance, and nonvolatile nature. , In 2012, Sharad et al simulated the DW-based synapse in their spin-based synapse-neuron model intended for character recognition tasks .…”