Humidity Stable Thermoelectric Hybrid Materials Toward a Self‐Powered Triple Sensing System

Author:

Tu Suo1,Tian Ting1,Xiao Tianxiao1,Yao Xiangtong2,Shen Sicong2,Wu Yansong2,Liu Yinlong3,Bing Zhenshan2,Huang Kai4,Knoll Alois2,Yin Shanshan1,Liang Suzhe1,Heger Julian E.1,Pan Guangjiu1,Schwartzkopf Matthias5,Roth Stephan V.56,Müller‐Buschbaum Peter17ORCID

Affiliation:

1. TUM School of Natural Sciences Department of Physics Chair for Functional Materials Technical University of Munich James‐Franck‐Str. 1 85748 Garching Germany

2. TUM School of Computation Information and Technology Chair for Robotics AI and Embedded Systems Technical University of Munich Boltzmannstr. 3 85748 Garching Germany

3. State Key Laboratory of Internet of Things for Smart City (SKL‐IOTSC) University of Macau Avenida Da Universidade Taipa Macao SAR 999078 China

4. School of Computer Science Sun Yat‐sen University 132 Outer Ring East Road Guangzhou 510006 China

5. Deutsches Elektronen‐Synchrotron DESY Notkestr. 85 22603 Hamburg Germany

6. Department of Fibre and Polymer Technology KTH Royal Institute of Technology Teknikringen 56–58 Stockholm SE‐100 44 Sweden

7. Heinz Maier‐Leibnitz Zentrum (MLZ) Technical University of Munich Lichtenbergstr. 1 85748 Garching Germany

Abstract

AbstractHighly sensitive and humidity‐resistive detection of the most common physical stimuli is of primary importance for practical application in real‐time monitoring. Here, a simple yet effective strategy is reported to achieve a highly humidity‐stable hybrid composite that enables simultaneous and accurate pressure and temperature sensing in a single sensor. The improved electronic performance is due to the enhanced planarity of poly (3,‐4ethylenedioxythiophene) (PEDOT) and charge transfer between PEDOT:polystyrene sulfonate (PEDOT:PSS) and multi‐walled carbon nanotubes (CNTs) by strong π–π interaction. The preferred electronic pathway induced by a robust morphology in the hybrid composite is responsible for the high humidity stability. This study also demonstrates that the sensor has tremendous potential for intelligent object identification with a high level of 97.78% accuracy. Together with the position‐detection capability of a triboelectric nanogenerator (TENG), advantages for potential industrial applications of the triple sensing system in terms of intelligent classification without seeing are foreseen.

Funder

China Scholarship Council

Center for NanoScience, Ludwig-Maximilians-Universität München

Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst

Deutsche Forschungsgemeinschaft

Publisher

Wiley

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