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In-Memory Ferroelectric Differentiator

Here, authors develop an in-memory differentiator using a 40×40 array of ferroelectric capacitors. This device efficiently performs real-time differential computation and motion extraction, demonstrating low energy consumption and high operational frequency, with potential applications in edge computing.

We successfully illustrate the effectiveness of this technique in a variety of tasks, including derivative function solving, the moving object extraction and image discrepancy identification, using an in-memory differentiator constructed with a crossbar array of 1600-unit ferroelectric polymer capacitors. The non-volatile nature of ferroelectric materials, coupled with their ability to gradually change polarization states in response to external stimuli, makes them excellent candidates for simulating biomimetic synaptic devices 20, 21, 22, 23 and for constituting in-memory computing hardware 24, 25, 26, 27, 28, 29, 30, 31. Guangdi Feng, Xiaoming Zhao, Xiaoyue Huang, Xiaoxu Zhang, Yangyang Wang, Wei Li, Luqiu Chen, Shenglan Hao, Qiuxiang Zhu, Bobo Tian, Junhao Chu & Chungang Duan

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