Photonic Memristor for Future Computing: A Perspective

Abstract

Photonic computing and neuromorphic computing could address the inherent limitations of traditional von Neumann architecture and gradually invalidate Moore's law. As photonics applications are capable of storing and processing data in an optical manner with unprecedented bandwidth and high speed, two-terminal photonic memristors with a remote optical control of resistive switching behaviors at defined wavelengths ensure the benefit of on-chip integration, low power consumption, multilevel data storage, and a large variation margin, suggesting promising advantages for both photonic and neuromorphic computing. Herein, the development of photonic memristors is reviewed, as well as their application in photonic computing and emulation on optogenetics-modulated artificial synapses. Different photoactive materials acting as both photosensing and storage media are discussed in terms of their optical-tunable memory behaviors and underlying resistive switching mechanism with consideration of photogating and photovoltaic effects. Moreover, light-involved logic operations, system-level integration and light-controlled artificial synaptic memristors along with improved learning tasks performance are presented. Furthermore, the challenges in the field are discussed, such as the lack of a comprehensive understanding of microscopic mechanisms under light illumination and a general constraint of inferior near-infrared (NIR) sensitivity.

Stimuli‐Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

“…[58][59][60] In perovskite-based memristors, dynamic ion migration related to the device current-voltage hysteresis has been considered as a basic form for data storage. [42,61,62] Xu et al [63] investigated the ionic migration mechanism in an organometeal halide perovskite (OHP) artificial synapse. The OHP was sandwiched between a bottom buffer-capped conducting polymer electrode and a top Al electrode to emulate the working principles of biological synapses.…”

“…The materials used for the channel layer include 2D transition-metal oxides (TMOs) [22] and dichalcogenides (TMDs), [23,33] conducting polymers, [14] and organic nanowire. [16] The use of 2D van der Waals (vdW) structures in synaptic devices for neuromorphic computing has provoked considerable interest because of the intriguing physical and chemical properties of these structures associated with their strictly defined low dimensionalities, [42,65] including their large surface-to-volume ratios, [33,66] dangling-bond-free surfaces, [65,67,68] and highly gatetunable bandgaps. [69][70][71][72] A variety of layered crystals, including MoO 3 , MoS 2 , WS 2 , and WSe 2 , can emulate both STP and LTP effectively.…”

Halide Perovskite Quantum Dots Photosensitized‐Amorphous Oxide Transistors for Multimodal Synapses

“…Optimized pulsing schemes with synergistic electro‐optical modes aids in modulating short‐ and long‐term memory, which is the basis for learning and computing. [ 26,27 ] To satisfy the programming/erasing requirements of ANNs, we utilized synergistic optical and electrical signals in our artificial synaptic TFT for inducing long‐term conductance change. Here, optical pulsing schemes aid in achieving nonvolatile writing, while electrical pulsing schemes aid in erasing weight states via electrical gating.…”

Recent advances in synthesis and application of perovskite quantum dot based composites for photonics, electronics and sensors

“…Possessing excellent photoelectronic properties, HP-QDs were also considered as promising candidates for memristor via light-stimulated resistive switching; however, instability to environmental factors, low electrontransport efficiency and easy interfacial reaction with electrode layer limit their application [175,176]. Stable devices with high photoresponsivity and efficiency are required for light-stimulated memristor.…”