晶体管
动态随机存取存储器
德拉姆
材料科学
电容器
计算机科学
电子线路
非易失性随机存取存储器
记忆电阻器
纳米技术
非易失性存储器
感测放大器
半导体存储器
光电子学
内存刷新
电气工程
电压
计算机硬件
计算机存储器
工程类
作者
Mingzhi Dai,Yongbin Hu,Changhe Huo,Thomas J. Webster,Liqiang Guo
摘要
Background: Artificial intelligence (AI) integrated circuits (IC) have memory devices as the key component. Due to more complex algorithms and architectures required by neuroscience and other medical applications, various memory structures have been widely proposed and investigated by involving nanomaterials, such as memristors. Methods: Due to reliability issues of mass production, the dominant memory devices in many computers are still dynamic random access memory (DRAM). A DRAM has one transistor and one capacitor, and so it contains two devices and requires a more compact design to replace. Results: A one-transistor memory device which is more compact than DRAM is proposed. As far as the authors know, this is the first/novel flexible and transparent one-transistor memory device without any additional process to make a typical transistor and which is based on polyvinyl alcohol. By using indium-titanium-oxide (ITO) as the metal gate, PVA as the dielectric layer and In-Ga-Zn-O (IGZO) as the channel, the memory is implemented mainly based on amorphous oxides and transparent flexible nanomaterials. The charge storage for the memory function was investigated here and is attributed to the mechanism of charge trapping between the ITO/IGZO junctions. It shows typical artificial synaptic transmission behaviors such as EPSC (excitatory postsynaptic currents). Conclusion: Such a first flexible and transparent one-transistor memory device based on PVA has one capacitor less than DRAM and could be a potential and promising candidate as an alternative for DRAM, especially in the highly complex AI chips needed for numerous medical applications. The flexible memory nanodevice based on flexible dielectrics such as PVA, which shows typical memory and artificial synaptic behaviors, could also be suitable for portable, flexible, transparent or skin-like medical applications.
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