Bionic Olfactory Synaptic Transistors for Artificial Neuromotor Pathway Construction and Gas Recognition

Abstract The superior recognition ability and excitatory–inhibitory balance of the olfactory system has important applications in the efficient recognition, analysis, and processing of data. In this study, transistor synaptic devices are prepared utilizing poly‐diketo‐pyrrolopyrrole‐selenophene polymer (PTDPPSe‐5Si) with excellent electrical properties as the active layer, and dual‐gas pulses are applied for the first time to simulate excitatory and inhibitory behaviors in the olfactory system. Basic synaptic properties are successfully simulated, such as excitatory/inhibitory postsynaptic currents (EPSC/IPSC), and long‐term potentiation/depression (LTP/LTD). The regulation of excitatory–inhibitory balance in biomimetic olfaction is successfully simulated. This working mechanism is attributed to the capture and release of carriers in the channel induced by the gas's electron‐donating and electron‐withdrawing characteristics. The neuromotor pathway is constructed using synaptic devices as the key processing unit, which enables the integration of information from neurons and the output of information from motor neurons. A convolutional neural network is constructed to achieve recognition of eight common laboratory gas types and concentrations with a recognition accuracy of over 97%. The simulated excitatory and inhibitory behaviors exhibited by this device hold significant importance for the development of artificial neural networks, intelligent frameworks, and neural robots.