Modulating the percolation network of polymer nanocomposites for flexible sensors
Jie Cao, Xinxing Zhang
Abstract
Flexible sensors have been the focus of intense research efforts in academic and industrial fields for Internet-of-Things applications. In this revolution, different strategies are explored to fabricate flexible tactile sensors by leveraging the pros and cons. In this Perspective, we focus on the current achievements of conductive polymer composites with three bottle-up micro/nano-conductive network structures based on the fundamental tunneling percolation theory and their potentialities and drawbacks for tactile sensor applications. Then, we highlight how model simulations can be used to elucidate the structure and property relationship clearly and guide the modulation of the network structure of conductive composites. Finally, benefiting from the precise definition of the parameters of the composites by model simulation, we discuss the perspectives of the emerging machine learning paradigm on inverse design and development of newly conductive polymer composites in the future.