High-performance Synaptic Phototransistor Using a Photoactive Self-assembled Layer toward Ultralow Energy Consumption
Ya-Shuan Wu, Ai-Chun Chang, Wei-Cheng Chen, Ender Ercan, Yi-Hsun Weng, Bi-Hsuan Lin, Cheng-Liang Liu, Yan-Cheng Lin*, and Wen-Chang Chen*
2024/04/24
Artificial synapses have gained great interest in the past few years because of their importance in deep learning and image recognition. To fulfill device miniaturization and reduce the energy consumption of device operation, a series of silane-based photoactive/conjugated self-assembled molecules (CSAMs), including isoindigo (IID), diketopyrrolopyrrole, and benzodithiophene, are used as the charge-trapping layers in synaptic phototransistors. The devices comprising CSAM demonstrate excellent short-term/long-term memory behaviors and can emulate the paired-pulse facilitation (PPF) function. Notably, the IID-based device shows the highest photoresponse, and this performance is highly related to the charge transfer efficiency and the photophysics lifetimes derived from the time-resolved photoluminescence and the transient absorption characterizations. Therefore, IID produces the highest PPF ratios of 139% to blue light and 144% to green light. In addition, the energy consumption of 0.029 fJ at an operating voltage of −0.1 mV is achieved, which is the lowest value in synaptic phototransistors so far. Notably, neural networks of supervised and unsupervised learning algorithms are demonstrated in the device studied to process a pattern recognition system. Collectively, using conjugated self-assembled materials as a charge-trapping layer is a promising way for synaptic phototransistor applications to reduce energy consumption and fulfill the device miniaturization.
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