Han Joon-Kyu, Park Sang-Chan, Yu Ji-Man, Ahn Jae-Hyuk, Choi Yang-Kyu
School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Department of Electronics Engineering, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of Korea.
Nano Lett. 2022 Jul 13;22(13):5244-5251. doi: 10.1021/acs.nanolett.2c01107. Epub 2022 Jun 23.
A novel biomimicked neuromorphic sensor for an energy efficient and highly scalable electronic tongue (E-tongue) is demonstrated with a metal-oxide-semiconductor field-effect transistor (MOSFET). By mimicking a biological gustatory neuron, the proposed E-tongue can simultaneously detect ion concentrations of chemicals on an extended gate and encode spike signals on the MOSFET, which acts as an input neuron in a spiking neural network (SNN). Such in-sensor neuromorphic functioning can reduce the energy and area consumption of the conventional E-tongue hardware. pH-sensitive and sodium-sensitive artificial gustatory neurons are implemented by using two different sensing materials: AlO for pH sensing and sodium ionophore X for sodium ion sensing. In addition, a sensitivity control function inspired by the biological sensory neuron is demonstrated. After the unit device characterization of the artificial gustatory neuron, a fully hardware-based E-tongue that can classify two distinct liquids is demonstrated to show a practical application of the artificial gustatory neurons.
一种用于高效节能且高度可扩展的电子舌（E-tongue）的新型仿生神经形态传感器通过金属氧化物半导体场效应晶体管（MOSFET）得以展示。通过模仿生物味觉神经元，所提出的电子舌能够同时检测扩展栅极上化学物质的离子浓度，并在充当脉冲神经网络（SNN）中输入神经元的MOSFET上编码脉冲信号。这种传感器内的神经形态功能可降低传统电子舌硬件的能量和面积消耗。通过使用两种不同的传感材料实现了对pH敏感和对钠敏感的人工味觉神经元：用于pH传感的AlO和用于钠离子传感的钠离子载体X。此外，展示了受生物感觉神经元启发的灵敏度控制功能。在对人工味觉神经元进行单元器件表征之后，展示了一种能够对两种不同液体进行分类的完全基于硬件的电子舌，以展示人工味觉神经元的实际应用。
