Self-Powered Memory Systems,ACS Materials Letters

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Self-Powered Memory Systems
ACS Materials Letters ( IF 9.6 ) Pub Date : 2020-11-17 , DOI: 10.1021/acsmaterialslett.0c00364
Bai Sun _{1,

2,

3} , Guangdong Zhou ₃ , Ke Xu ₁ , Qiang Yu ₁ , Shukai Duan ₃

Affiliation

Artificial intelligence memory is expected to acquire, calculate, and analyze a large amount of logical information and data in time to dynamically respond to artificial neural networks. It is the most promising candidate for realizing a new hardware artificial intelligence architecture that mimics biological neural networks. However, the research on artificial intelligence memory is still in the initial stage, and there are some unresolved bottlenecks for the preparation of artificial intelligence memory devices. Such as it require external power supplements for the operating of memory devices, resulting in high power consumption and difficulty in real-time neuromorphic computing. Fortunately, self-powered memory devices can perfectly solve the above problems. In this Review, we have systemically summarized the current development on material, integration, and technology for the self-powered memory application, as well as provide the prospect, suggestion, and optimization method for neuromorphic computing and artificial intelligence with self-powered memory.

中文翻译：

自供电存储系统

人工智能存储器有望及时获取，计算和分析大量逻辑信息和数据，以动态响应人工神经网络。它是实现模仿生物神经网络的新型硬件人工智能架构的最有前途的候选人。但是，人工智能存储的研究还处于起步阶段，制备人工智能存储设备存在一些尚未解决的瓶颈。例如，它需要外部电源补充来操作存储设备，从而导致高功耗和实时神经形态计算的困难。幸运的是，自供电存储设备可以完美地解决上述问题。在这篇评论中，我们系统地总结了材料的最新发展，

更新日期：2020-12-07

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