Reconfigurable perovskite nickelate electronics for artificial intelligence

被引:110
|
作者
Zhang, Hai-Tian [1 ,11 ]
Park, Tae Joon [1 ]
Islam, A. N. M. Nafiul [2 ]
Tran, Dat S. J. [3 ]
Manna, Sukriti [4 ,5 ]
Wang, Qi [1 ]
Mondal, Sandip [1 ,12 ]
Yu, Haoming [1 ]
Banik, Suvo [4 ,5 ]
Cheng, Shaobo [6 ,13 ]
Zhou, Hua [7 ]
Gamage, Sampath [8 ]
Mahapatra, Sayantan [9 ]
Zhu, Yimei [6 ]
Abate, Yohannes [8 ]
Jiang, Nan [9 ]
Sankaranarayanan, Subramanian K. R. S. [4 ,5 ]
Sengupta, Abhronil [2 ]
Teuscher, Christof [10 ]
Ramanathan, Shriram [1 ]
机构
[1] Purdue Univ, Sch Mat Engn, W Lafayette, IN 47907 USA
[2] Penn State Univ, Dept Elect Engn, University Pk, PA 16802 USA
[3] Santa Clara Univ, Dept Elect & Comp Engn, Santa Clara, CA 95053 USA
[4] Argonne Natl Lab, Ctr Nanoscale Mat, Argonne, IL 60439 USA
[5] Univ Illinois, Dept Mech & Ind Engn, Chicago, IL 60607 USA
[6] Brookhaven Natl Lab, Dept Condensed Matter Phys & Mat Sci, Upton, NY 11973 USA
[7] Argonne Natl Lab, Xray Sci Div, Adv Photon Source, Lemont, IL 60439 USA
[8] Univ Georgia, Dept Phys & Astron, Athens, GA 30602 USA
[9] Univ Illinois, Dept Chem, Chicago, IL 60607 USA
[10] Portland State Univ, Dept Elect & Comp Engn, Portland, OR 97201 USA
[11] Beihang Univ, Sch Mat Sci & Engn, Beijing 100191, Peoples R China
[12] Indian Inst Technol, Dept Elect Engn, Mumbai 400076, Maharashtra, India
[13] Zhengzhou Univ, Sch Phys & Microelect, Key Lab Mat Phys, Zhengzhou 450052, Peoples R China
基金
美国国家科学基金会;
关键词
ELASTIC BAND METHOD; NEURAL-NETWORKS; MEMRISTOR; DEVICES; SYNAPSE;
D O I
10.1126/science.abj7943
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
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 NdNiO3 devices 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.
引用
收藏
页码:533 / +
页数:91
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