School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
Small. 2017 Aug;13(32). doi: 10.1002/smll.201701193. Epub 2017 Jun 28.
Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm V s with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits.
为了超越标准的冯·诺依曼架构，未来的类脑神经形态计算系统需要模拟生物突触。在这里，我们在刚性和柔性衬底上基于离子-电子混合氧化物的晶体管展示了人工突触。这里报道的柔性晶体管具有约 9 cm2V s-1的高场效应迁移率和良好的机械性能。成功建立了综合学习能力/突触规则，如成对脉冲易化、兴奋性和抑制性突触后电流、尖峰时间依赖性可塑性、巩固、超线性放大和动态逻辑，这些规则描述了具有时空相关性的并发处理和存储功能。该结果提出了一种完全可溶液处理的方法来制造用于下一代透明神经电路的人工突触。
