Neuromorphic computing systems that are capable of parallel information storage and processing with high area and energy efficiencies, offer important opportunities for future storage systems and in‐memory computing. Here, it is shown that a carbon dots/silk protein (CDs/silk) blend can be used as a light‐tunable charge trapping medium to fabricate an electro‐photoactive transistor synapse. The synaptic device can be optically operated in volatile or nonvolatile modes, ensuring concomitant short‐term and long‐term neuroplasticity. The synaptic‐like behaviors are attributed to the photogating effect induced by trapped photogenerated electrons in the hybrid CDs/silk film which is confirmed with atomic force microscopy based electrical techniques. In addition, system‐level pattern recognition capability of the synaptic device is evaluated by a single‐layer perceptron model. The remote optical operation of neuromorphic architecture provides promising building blocks to complete bioinspired photonic computing paradigms.

No abstract

No abstract

of stimulation will transfer the shortterm memory into long-term memory. To achieve artificial synaptic recognition for learning and memory in electronic devices, concomitant plasticity with different timescale is essential. As a result, the short-term plasticity (STP) modulates the transient dynamical efficacy during the synaptic transmission, while the longterm plasticity (LTP) shows the stabilizing effect by the given stimulation. [10][11][12][13] Therefore, the emulated synaptic plasticity of STP and LTP render themselves supportive to the sophisticated cognitive function and adaptive behavior pattern.The emphasis on neuroinspired computing so far has been predominantly in electrical stimulation-induced resistance state switching in phase change memories, [14,15] memristors, [16][17][18][19][20][21][22][23][24] as well as transistor-based memories. [25][26][27][28][29][30] In contrast with the existing electrical interconnect power loss as well as the limitation in trigger selectivity and spatially confinement inherently from the computing by electric signal, emerging optical stimulation based synaptic devices can tune the synaptic plasticity enormously by photons with low-power and high-efficiency. Therefore, the photonic synapse architecture is considered to be more favorable in handling the von Neumann bottleneck. [31][32][33][34] In addition, photonic synapse based on Parallel information storage coupled with storage density is a major focus for non-volatile memory devices to achieve neuromorphic computing that can work at low power. In this regard, a photoactive charge-trapping medium consisting of inorganic heteronanosheets for the fabrication of a synaptic transistor is demonstrated. This synaptic device senses and responds to near-infrared (NIR) light signals and mimics the memorization and dynamic forgetting process due to the reversible nature of photogenerated charge interaction. Device-level synaptic evolutions from short-term plasticity to long-term plasticity, paired pulse facilitation, and paired pulse depression are realized with light modulation on the weight update terminal. To understand the underlying mechanism of the synaptic behavior under NIR signals, systematic analysis is carried out using in situ atomic force microscopy based electrical techniques. With its photoactive architecture, this information processing analogue is validated for visual object recognition, which paves the way for implementing NIR-controlled neuromorphic computing.

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.