Fully Printed Optoelectronic Synaptic Transistors Based on Quantum Dot–Metal Oxide Semiconductor Heterojunctions

Abstract

Optoelectronic synaptic transistors with hybrid heterostructure channels have been extensively developed to construct artificial visual systems, inspired by the human visual system. However, optoelectronic transistors taking full advantages of superior optoelectronic synaptic behaviors, low-cost processes, low-power consumption, and environmental benignity remained a challenge. Herein, we report a fully printed, high-performance optoelectronic synaptic transistor based on hybrid heterostructures of heavy-metal-free InP/ZnSe core/shell quantum dots (QDs) and n-type SnO 2 amorphous oxide semiconductors (AOSs). The elaborately designed heterojunction improves the separation efficiency of photoexcited charges, leading to high photoresponsivity and tunable synaptic weight changes. Under the coordinated modulation of electrical and optical modes, important biological synaptic behaviors, including excitatory postsynaptic current, short/long-term plasticity, and paired-pulse facilitation, were demonstrated with a low power consumption (∼5.6 pJ per event). The InP/ZnSe QD/SnO 2 based artificial vision system illustrated a significantly improved accuracy of 91% in image recognition, compared to that of bare SnO 2 based counterparts (58%). Combining the outstanding synaptic characteristics of both AOS materials and heterojunction structures, this work provides a printable, low-cost, and high-efficiency strategy to achieve advanced optoelectronic synapses for neuromorphic electronics and artificial intelligence.

Soft Biomaterials Based Flexible Artificial Synapse for Neuromorphic Computing

“…The average energy consumption for the potentiation/depression operation was ≈4.9 nJ µm −2 . The energy consumption of this work was relatively high compared to other synaptic technology, such as silicon CMOS chips (pJ), [ 46 ] 2D materials artificial synapses (fJ), [ 47 ] metal‐oxide artificial synapses, [ 48 ] phase‐change artificial synapses (pJ) [ 49 ] ferroelectric artificial synapses (fJ). [ 50 ] In the current work, the pulse duration was relatively long (50 ms), which induced more energy consumption.…”

A brief review on device operations and working mechanisms of organic transistor photomemories

“…[43][44][45] In the case of other photoactive charge storage material developments (such as rod-coil or rod-like liquid crystals, hybrid metal/metal-oxide nanoparticles/thin-films, metal-organic frameworks, photochromic blends/monolayers, biomass-derived electrets, and small-molecules based), and other unique morphologies/topologies of charge trapping interfaces, as well as device structures that are not covered in this section, could be found in the recently published reports and reviews. 22,23,[46][47][48][49][50][51][52][53][54][55][56][57][58] Below, the device structures and its memory characteristics to the device operations will be elaborated in detail.…”

Emerging Memristive Devices for Brain-Inspired Computing and Artificial Perception

“…Traditional sensing systems make use of electronic devices to sense and process information. Recently, because of the fast process speed and low power consumption, using new synaptic devices, particularly two terminal memristive devices, to imitate human perception has piqued the interest of researchers and has been regarded as a promising solution to build efficient artificial system Li et al, 2021;Liang et al, 2022). In this section, we will introduce some recent advances in the research of tactile, auditory, visual and olfactory artificial systems.…”