Extremely Low Operating Current Resistive Memory Based on Exfoliated 2D Perovskite Single Crystals for Neuromorphic Computing

He Tian, Lianfeng Zhao, Xuefeng Wang, Yao Wen Yeh, Nan Yao, Barry P. Rand, Tian Ling Ren

Research output: Contribution to journalArticlepeer-review

274 Scopus citations


Extremely low energy consumption neuromorphic computing is required to achieve massively parallel information processing on par with the human brain. To achieve this goal, resistive memories based on materials with ionic transport and extremely low operating current are required. Extremely low operating current allows for low power operation by minimizing the program, erase, and read currents. However, materials currently used in resistive memories, such as defective HfOx, AlOx, TaOx, etc., cannot suppress electronic transport (i.e., leakage current) while allowing good ionic transport. Here, we show that 2D Ruddlesden-Popper phase hybrid lead bromide perovskite single crystals are promising materials for low operating current nanodevice applications because of their mixed electronic and ionic transport and ease of fabrication. Ionic transport in the exfoliated 2D perovskite layer is evident via the migration of bromide ions. Filaments with a diameter of approximately 20 nm are visualized, and resistive memories with extremely low program current down to 10 pA are achieved, a value at least 1 order of magnitude lower than conventional materials. The ionic migration and diffusion as an artificial synapse is realized in the 2D layered perovskites at the pA level, which can enable extremely low energy neuromorphic computing.

Original languageEnglish (US)
Pages (from-to)12247-12256
Number of pages10
JournalACS Nano
Issue number12
StatePublished - Dec 26 2017

All Science Journal Classification (ASJC) codes

  • General Engineering
  • General Materials Science
  • General Physics and Astronomy


  • 2D perovskites
  • neuromorphic computing
  • organic-inorganic hybrid perovskites
  • perovskite single crystal
  • resistive memory


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