Reconfigurable perovskite nickelate electronics for artificial intelligence

Reconfigurable perovskite nickelate electronics for artificial intelligence
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用于人工智能的可重构钙钛矿镍酸盐电子器件

DOI:
10.1126/science.abj7943
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发表时间:
2022
期刊:
影响因子:
56.9
通讯作者:
Cheng, Shaobo
Cheng, Shaobo
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Zhang, Hai-Tian;Park, Tae Joon;Islam, A. N.;Tran, Dat S.;Manna, Sukriti;Wang, Qi;Mondal, Sandip;Yu, Haoming;Banik, Suvo;Cheng, Shaobo

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可重构器件提供了按需编程电子电路的能力。在这项工作中,我们展示了在后制造的钙钛矿NdNiO3设备中按需创建人工神经元,突触和存储电容器,这些设备可以通过单次电脉冲简单地重新配置用于特定目的。钙钛矿镍酸盐的电子性质对氢离子局部分布的敏感性使这些结果成为可能。通过我们的存储电容器的实验数据,水库计算框架的模拟结果显示出出色的性能,如数字识别和心电图心跳活动的分类。使用我们的可重构人工神经元和突触,模拟的动态网络在增量学习场景中的表现优于静态网络。根据需求设计大脑启发计算机的构建模块的能力为自适应网络开辟了新的方向。
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.
受主掺杂锆酸钡中氧空位和质子的尺寸和形状
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