Modulationof Binary Neuroplasticity in a Heterojunction-BasedAmbipolar Transistor

To keep pace with the upcoming big-data era, the development of a device-level neuromorphic system with highly efficient computing paradigms is underway with numerous attempts. Synaptic transistors based on an all-solution processing method have received growing interest as building blocks for neuromorphic computing based on spikes. Here, we propose and experimentally demonstrated the dual operation mode in poly­{2,2-(2,5-bis­(2-octyldodecyl)-3,6-dioxo-2,3,5,6-tetrahydropyrrolo­[3,4-c]­pyrrole-1,4-diyl)­dithieno­[3,2-b]­thiophene-5,5-diyl-alt-thiophen-2,5-diyl}­(PDPPBTT)/ZnO junction-based synaptic transistor from ambipolar charge-trapping mechanism to analog the spiking interfere with synaptic plasticity. The heterojunction formed by PDPPBTT and ZnO layers serves as the basis for hole-enhancement and electron-enhancement modes of the synaptic transistor. Distinctive synaptic responses of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) were configured to achieve the training/recognition function for digit image patterns at the device-to-system level. The experimental results indicate the potential application of the ambipolar transistor in future neuromorphic intelligent systems.