控制重构
计算
计算机科学
高效能源利用
量子计算机
分布式计算
极化(电化学)
能量(信号处理)
油藏计算
边缘计算
材料科学
光学计算
嵌入式系统
认知计算
高能
半导体
按需
计算科学
物联网
电子工程
半导体器件
非常规计算
图像处理
计算机体系结构
计算机工程
仿形(计算机编程)
可逆计算
作者
Linqi Guo,Haoxuan Sun,Siping Yang,Chi Zhang,Liangliang Min,Abd. Rashid bin Mohd Yusoff,Liang Li
标识
DOI:10.1002/adma.202519096
摘要
The growing demand for data-centric and intelligent applications calls for seamless integration of sensing, memory, and computation within a single device to improve efficiency, reduce energy consumption, and enable real-time processing. However, the adoption of such in-sensor computing is hindered by limited reconfigurability, which constrains its use in complex tasks beyond basic image processing. Here, we identify cascaded switching driven by interactions among differently polarized domains as a fundamental barrier to achieving high reconfiguration precision. To overcome this, we introduce a polarization energy focusing strategy, enabled by a tailored compositional distribution of ferroelectric and semiconductor materials. This approach yields the first in-sensor computing device with reconfigurable precision reaching 10 bits. Its capability in both conventional image processing and advanced reconstructed optics is demonstrated, highlighting its potential as a high-linearity, high-precision platform for next-generation intelligent systems.
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