2D transition metal dichalcogenides for neuromorphic vision system

Abstract

It has been a long-sought dream for human beings to realize a powerful and reliable artificial vision system that can liberate human beings from tedious brain work. In the past few years, computer vision based on brain-inspired algorithm has made great achievements in several commercial applications such as the face recognition, medical image diagnosis and driverless vehicles. Nonetheless, the mainstream computer hardware is based on the von Neumann architecture which cannot meet the growing needs for powerful and energyefficient artificial intelligence. Fortunately, two dimensional (2D) transition metal dichalcogenides (TMDCs) device that can mimic neural architectures may allow us to overcome these challenges. To recreate flexibility, sensitivity and adaptability in biological visual system, the exploration of emerging materials with high photoresponsivity and synaptic plasticity has become the most critical requirement for the neuromorphic devices[1−4]. The 2D TMDCs (Fig. 1(a)) not only possess an excellent optoelectronic performance but also offer an external electrical tenability for the synaptic setting. By stacking different 2D materials together, the optical response of van der Waals (vdW) heterostructures can be modulated by using the piezophototronic effect[5]. Compared with conventional semiconductor materials, the TMDCs-based vdW heterostructures take advantages like lightweight, semitransparency and flexibility. In addition, the fabrication technology of 2D materials has the potential to offer efficient large-scale integration due to their thermodynamic stability and interlayer coupling capability[5]. Therefore, 2D TMDCs are the ideal candidate for realizing hierarchical organizations and synaptic functions. In 2020, Wang et al. proposed a neuromorphic vision system by networking a retinomorphic sensor and a memristive crossbar[4]. The sensor (Fig. 1(b)) was fabricated by using WSe2/h-BN/Al2O3 van der Waals heterostructures with gatetunable photoresponses. This device could mimic human retinal capabilities for sensing and processing images. The bulk WSe2 and h-BN were processed into thin flakes by mechanical exfoliation and then transferred onto Al2O3 layer to realize vdW heterostructure. Under light illumination, the photoresponse changed with the back-gate voltage, resembling a light-stimulated biological response of the bipolar cell in retina[6]. By networking such retinomorphic sensors (Fig. 1(c)), the square array with nine nodes could perform a real-time multiplication of the projected image. The image information could be detected and pre-processed before coming into the memristive neural network for complex visual perception. Therefore, the limitation of transmission bandwidth in the conventional computer vision could be broken and the resulting high latency is minimized. This neuromorphic vision system also holds promising capabilities in carrying out objecttracking tasks. Recently, Mennel et al. also demonstrated that the early processing occurring in retinomorphic sensor could drastically increase the efficiency of signal processing[1]. Similar to previous retinomorphic sensor, they presented a WSe2 photodiode array that could simultaneously sense and process images projected onto the chip. The light intensity of each image pixel was multiplied with the tunable photoresponsivity of each photodiode, generating the processed output currents. Such bio-inspired pre-processing ability could greatly accelerate the image recognition and take great advantage in processing large-scale data. In this way, the photodiode array finally achieved ultrafast image recognition with a throughput of 20 million bins per second. To realize a superior intelligence similar to human brain, the neuromorphic photoelectronics usually requires not only high photoresponsivity but also fundamental synaptic characteristics. In a recent work from Cheng et al.[7], the TMDCsbased heterojunction exhibited a wide variety of classical neuromorphic behaviors such as excitatory postsynaptic current (EPSC), inhibitory postsynaptic potential (IPSP), and pairedpulse facilitation (PPF). When light irradiation was applied, large numbers of electron–hole pairs were first generated in the photosensitive material CsPbBr3 and then separated under the built-in electric field (Fig. 1(d)). Therefore, the light intensity could flexibly control the photoelectric performance of TMDCs devices by changing the carrier-transport characteristics at the heterojunction interfaces. In particular, the mixed-dimensional vertical van der Waals heterojunction phototransistor (MVVHT) could well mimic complex neuromorphic behaviors such as efficiency-adjustable photoelectronic Pavlovian conditioning. Fig. 1(e) schematically presented the mathematical modes of the corresponding neural algorithms. The neuronal additive operations are induced by the ratevaried electric or optic stimulus. Therefore, the neuronal in-