Synaptic Characteristics and Neuromorphic Computing Enabled by Oxygen Vacancy Migration Based on Porous In₂O₃ Electrolyte-Gated Transistors

The migration of oxygen vacancies is decisively affectingthe modulationof channel conductance. However, for electrolyte-gated transistors(EGTs), the modulation of channel conductance driven by the migrationof oxygen vacancies can be easily concealed by the existence of anelectrical double layer (EDL). Here, we first observed the modulationof channel conductance caused by the migration of oxygen vacancies,marked by a clockwise transfer hysteresis, by keeping the top gateelectrode at a far distance from the source/drain electrodes. Thecontribution degree of the migration of oxygen vacancies and the EDLon the modulation of channel conductance can be adjusted by changingthe distance between the top gate and source/drain electrodes. Theresults were supported by X-ray photoelectron spectroscopy measurementsand first-principles calculations. Due to the migration of oxygenvacancies, the proposed porous In2O3 EGT couldemulate biological synaptic functions, such as long-term potentiation/depression,paired-pulse facilitation/depression, image learning, and memorizing.A convolutional neural network based on EGTs is constructed to identifythe traffic sign data sets with a recognition accuracy of 91.3%. Theporous nature of the developed EGT improved both the long-term memoryand the neuromorphic computing properties. From the provided results,a deep understanding of the underlying mechanism of the modulationof channel conductance composed of EGTs is provided. Moreover, ourwork paves the way for the fabrication of next-generation high-performanceartificial synapses.