A Single-Mode, Multimodal, and Self-Powered Sensor Based on Electron Relaxation Dynamics

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Abstract
The human skin possesses the capability to detect thermal and mechanical stimuli simultaneously. Ingenious flexible sensors have been explored to mimic such functionalities by integrating multiple sensing elements or adopting multimodal sensing principles. However, the widespread application of these sensors has faced obstacles such as complicated manufacturing processes, signal mismatches between different components, and high power consumption. Here, we report a single-mode self-powered flexible sensor capable of simultaneously detecting both temperature and pressure stimuli through the seamless integration of complementary and compatible thermoelectric and triboelectric sensing mechanisms. The resulting hybrid thermoelectric-triboelectric sensor exhibits unique features that are difficult to achieve with existing approaches, including single-mode output (voltage signal only), significantly simplified operation (single-measurement device), ultralow power consumption, adaptive response behavior, and excellent discriminative capability for complex stimuli. Additionally, a deep learning regression model has been implemented to dispose of the single-mode signals, achieving an impressive accuracy of 94.7% in distinguishing contact objects. This work presents an innovative design that substantially simplifies both fabrication and operation while simultaneously enhancing the functionality and energy efficiency of next-generation flexible sensing systems.
Funding Information
  • National Natural Science Foundation of China (NSFC) (62101612)
  • National Natural Science Foundation of China (NSFC) (62274190)
  • Young Teacher Promotion Program of Minzu University of China (2022QNPY74)

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