• 中文核心期刊要目总览
  • 中国科技核心期刊
  • 中国科学引文数据库(CSCD)
  • 中国科技论文与引文数据库(CSTPCD)
  • 中国学术期刊文摘数据库(CSAD)
  • 中国学术期刊(网络版)(CNKI)
  • 中文科技期刊数据库
  • 万方数据知识服务平台
  • 中国超星期刊域出版平台
  • 国家科技学术期刊开放平台
  • 荷兰文摘与引文数据库(SCOPUS)
  • 日本科学技术振兴机构数据库(JST)

Ultrathin SrTiO3-based oxide memristor with both drift and diffusive dynamics as versatile synaptic emulators for neuromorphic computing

  • Abstract: Artificial synapses are electronic devices that simulate important functions of biological synapses, and therefore are the basic components of artificial neural morphological networks for brain-like computing. One of the most important objectives for developing artificial synapses is to simulate the characteristics of biological synapses as much as possible, especially their self-adaptive ability to external stimuli. Here, we have successfully developed an artificial synapse with multiple synaptic functions and highly adaptive characteristics based on a simple SrTiO3/Nb: SrTiO3 heterojunction type memristor. Diverse functions of synaptic learning, such as short-term/long-term plasticity (STP/LTP), transition from STP to LTP, learning-forgetting-relearning behaviors, associative learning and dynamic filtering, are all bio-realistically implemented in a single device. The remarkable synaptic performance is attributed to the fascinating inherent dynamics of oxygen vacancy drift and diffusion, which give rise to the coexistence of volatile- and nonvolatile-type resistive switching. This work reports a multi-functional synaptic emulator with advanced computing capability based on a simple heterostructure, showing great application potential for a compact and low-power neuromorphic computing system.

     

/

返回文章
返回