Three‐Dimensional Ag <sub>2</sub> Se Thermoelectric Network Advances Multimodal Intelligent Perception

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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Publication Details

Journal
Advanced Energy Materials
Published
2026-02-15
DOI
https://doi.org/10.1002/aenm.202506640
Primary Topic
Advanced Thermoelectric Materials and Devices
Type
article
Field-Weighted Citation Impact
0.00

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Three‐Dimensional Ag 2 Se Thermoelectric Network Advances Multimodal Intelligent Perception

Jinhua Mao, Y. J. Liu, Fangyuan Yu, Qiang Zhang et al.
Advanced Energy Materials
Advanced Thermoelectric Materials and Devices
article

Three‐Dimensional Ag 2 Se Thermoelectric Network Advances Multimodal Intelligent Perception

Jinhua Mao, Y. J. Liu, Fangyuan Yu, Qiang Zhang, Shuaihang Hou, Zuoxu Wu, Liming Xiao, Zhihua Miao, Feng Cao, Jian Wang, Xiaodong Wang, Ping Sun
article en

Abstract

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.

Advanced Energy Materials
Harbin Institute of Technology (CN), China Guangzhou Analysis and Testing Center (CN), Shenzhen Research Institute of Big Data (CN), Harbin Welding Institute (CN), Ministry of Industry and Information Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 56%
Advanced Thermoelectric Materials and Devices
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