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

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


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.

Original languageEnglish (US)
Article numberA29
Issue number6580
StatePublished - Feb 4 2022

All Science Journal Classification (ASJC) codes

  • General


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