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Reconfigurable perovskite nickelate electronics for artificial intelligence

  • Hai Tian Zhang*
  • , Tae Joon Park*
  • , A. N.M.Nafiul Islam
  • , Dat S.J. Tran
  • , Sukriti Manna
  • , Qi Wang
  • , Sandip Mondal
  • , Haoming Yu
  • , Suvo Banik
  • , Shaobo Cheng
  • , Hua Zhou
  • , Sampath Gamage
  • , Sayantan Mahapatra
  • , Yimei Zhu
  • , Yohannes Abate
  • , Nan Jiang
  • , Subramanian K.R.S. Sankaranarayanan
  • , Abhronil Sengupta
  • , Christof Teuscher
  • , Shriram Ramanathan*
  • *此作品的通讯作者
  • Purdue University
  • Pennsylvania State University
  • Santa Clara University
  • Argonne National Laboratory
  • University of Illinois at Chicago
  • Brookhaven National Laboratory Condensed Matter Physics and Materials Science Department
  • United States Department of Energy
  • University of Georgia
  • Portland State University

科研成果: 期刊稿件文章同行评审

摘要

Reconfigurable devices offer the ability to program electronic circuits on demand. In this work, we demonstrated on-demand creation of artificial neurons, synapses, and memory capacitors in post-fabricated perovskite NdNiO3devices that can be simply reconfigured for a specific purpose by single-shot electric pulses.The sensitivity of electronic properties of perovskite nickelates to the local distribution of hydrogen ions enabled these results. With experimental data from our memory capacitors, simulation results of a reservoir computing framework showed excellent performance for tasks such as digit recognition and classification of electrocardiogram heartbeat activity. Using our reconfigurable artificial neurons and synapses, simulated dynamic networks outperformed static networks for incremental learning scenarios. The ability to fashion the building blocks of brain-inspired computers on demand opens up new directions in adaptive networks.

源语言英语
文章编号A29
期刊Science
375
6580
DOI
出版状态已出版 - 4 2月 2022
已对外发布

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