Growing Perovskite Quantum Dots on Carbon Nanotubes for Neuromorphic Optoelectronic Computing

Abstract

Brain‐inspired (neuromorphic) computing that offers lower energy consumption and parallelism (simultaneous processing and memorizing) compared to von Neumann computing provides excellent opportunities in many computational tasks ranging from image recognition to speech processing. To accomplish neuromorphic computing, highly efficient optoelectronic synapses, which can be the building blocks of optoelectronic neuromorphic computers, are necessary. Currently, carbon nanotubes (CNTs), an attractive candidate to develop circuit‐level photonic synapses, provide weak light responses. The inferior photoresponse of CNTs increases the energy consumption of neuromorphic optoelectronic devices. Herein, a method to grow organic–inorganic halide perovskite quantum dots (PQDs) directly on multiwall CNTs (MWCNTs) to increase the photosensitivity of optoelectronic synapses is demonstrated. The new hybrid material synchronizes the high photoresponse of PQDs and the excellent electrical properties of MWCNTs to provide photonic memory under very low light intensity (125 µW cm−2). However, neat MWCNTs do not show any detectable light response at the tested light intensity, as high as 25 mW cm−2. Since the PQDs are grown directly on and in the MWCNTs, the hybrid PQD‐MWCNT provides a new direction for the future MWCNT‐based optoelectronic devices for neuromorphic computing with a potential to break the von Neumann bottleneck.

Emerging Optical In‐Memory Computing Sensor Synapses Based on Low‐Dimensional Nanomaterials for Neuromorphic Networks

“…[9,10,14] As illustrated in Figure 2d, Crawford et al fabricated a photonic synaptic device based on organic-inorganic halide perovskite QDs (PQDs) and multiwall carbon nanotube (MWCNT), which demonstrated the long-term potentiation under the 405 nm all-optical stimuli and the longterm depression with the consecutive À1 V/100 ms electrical pulses. [63] After that, they weakened the connection strength with higher efficiency by increasing the pulse width of electrical pulses, which indicated that it was feasible to adjust the learning process of neuromorphic computing by modulating various parameters of pulses. [63] For STP and LTP measurement of a single biomimetic synaptic device, the external stimuli are usually applied onto one terminal (the presynaptic terminal or the postsynaptic terminal).…”

Mixed-Halide Perovskite Film-Based Neuromorphic Phototransistors for Mimicking Experience-History-Dependent Sensory Adaptation

“…Integrating the perovskite with organic semiconductors not only improves the photosensitivity of the system but it is also suitable to the solution-processed method instead of complex multistep processes in most previous works (Table S1). ,,,− This hybrid phototransistor achieves better performance than most previous perovskite-based hybrid synaptic phototransistors including a photoresponsivity ( R ) of 4000 A/W and an excellent specific detectivity ( D *) of 2.8 × 10 16 Jones (Table S1). On basis of a type II band alignment heterojunction, it can be used to mimic the biological synaptic functions.…”

Nanostructured Materials and Architectures for Advanced Optoelectronic Synaptic Devices

“…As already discussed, 0D essentially can not only build up components of artificial optoelectronic synaptic devices but can also integrate other types of materials such as, polymers, [265] nanowires, [98] and even QDs themselves into the optoelectronic synaptic devices. [244] Thus, in order to enhance the performance of current low-dimensional optoelectronic synapses, it is necessary to develop hybrid devices that are combined with 0D and 2D materials.…”

“…[ 97 ] In addition, the inhibited recombination causes the photocurrent to decrease slowly, then originates the synaptic plasticity. [ 98 ] Photogenerated electron‐hole pairs may be separated via interfacial band alignment by using p‐n or Schottky junctions for the built‐in electrical field that can be created by doping or simply by combining hybrid materials. [ 99 ] In recent years, exploiting heterostructure to modulate the optoelectronic properties of materials has emerged as a new research area.…”

“…For device operation, however, the Δ t was ranged from 0.5 to 10 s, which was indeed far beyond a biosynapse (0.1 to 1 ms), and here the high transparency and fixability only provided an incentive to develop a neuromorphic device similar to the real biology. Besides, Agnus et al., [ 218 ] Jinxin et al., [ 98 ] and Shao et al. [ 217,219 ] reported the optically (in the visible range) programmable thin film transistor for adaptive architectures based on disordered CNTs, as shown in Figure 9g–i.…”