灵敏度(控制系统)
计算机科学
纳米传感器
压力传感器
信号(编程语言)
软件部署
材料科学
分类
系统集成
无线传感器网络
人工智能
智能传感器
热电效应
响应时间
人工神经网络
信号处理
电子工程
实时计算
深度学习
嵌入式系统
触觉传感器
钥匙(锁)
匹配(统计)
主动感知
作者
Fangyuan Yu,Ping Sun,Y. J. Liu,Xiaodong Wang,Shuaihang Hou,Zuoxu Wu,Liming Xiao,Jian Wang,Zhihua Miao,Jinhua Mao,Qian Zhang,Feng Cao
标识
DOI:10.1002/aenm.202506640
摘要
ABSTRACT Embodied artificial intelligence (Embodied AI) depends on the integration of multimodal sensing and physical interaction to achieve autonomous perception and adaptive control in complex environments. However, conventional multimodal sensing systems often rely on separate sensors for each physical stimulus, leading to integration challenges and signal interference. Here, we report a monolithic bimodal sensor based on a 3D Ag 2 Se thermoelectric network that enables simultaneous and decoupled detection of temperature and pressure within a single device. The sensor demonstrates a high temperature sensitivity of −122.7 µV K −1 with a fast response time of ∼0.14 s, and a high pressure sensitivity of −2.94% kPa −1 with a fast response time of about 0.08 s, indicating excellent signal isolation between the two sensing channels. When combined with deep learning, the sensor enables a real‐time intelligent sorting system that achieves 96% recognition accuracy across nine materials, outperforming single‐mode sensing approaches. This work provides an integrated multimodal sensing solution that advances the deployment of embodied AI in complex environments.
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