Reconfigurable perovskite nickelate electronics for artificial intelligence.
Hai-Tian ZhangTae Joon ParkA N M Nafiul IslamDat S J TranSukriti MannaQi WangSandip MondalHaoming YuSuvo BanikShaobo ChengHua ZhouSampath GamageSayantan MahapatraYimei ZhuYohannes AbateNan JiangSubramanian K R S SankaranarayananAbhronil SenguptaChristof TeuscherShriram RamanathanPublished in: Science (New York, N.Y.) (2022)
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 NdNiO 3 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.
Keyphrases
- artificial intelligence
- machine learning
- big data
- deep learning
- working memory
- room temperature
- high efficiency
- solar cells
- spinal cord
- climate change
- resting state
- white matter
- quality improvement
- electronic health record
- multiple sclerosis
- functional connectivity
- data analysis
- blood brain barrier
- cerebral ischemia
- water quality
- visible light