Flexible human-machine interface touch system based on double-network solid-state ionic conductive elastomers

An extremely flexible human–machine interface touch system based on double-network solid-state ionic conductive elastomer has been developed. By integrating salt-in-polymer and double-network structure strategies, we have effectively addressed the longstanding trade-off between mechanical robustness and ionic conductivity of solid-state ionic conductive elastomer. This advancement has enabled diverse applications ranging from simple “point” interactions such as flexible touch buttons in hospital communication systems, to “line” applications including stepless control sound strips and page-turning features, and finally “surface” functionalities encompassing game control and handwriting recognition on both flat and curved surfaces. [Display omitted] •We develop a flexible human–machine interface touch system based on double-network solid-state ionic conductive elastomer.•We address the conflict between mechanical robustness and ionic conductivity of solid-state ionic conductive elastomer.•The touch system encompasses various applications from “point” to “line” to “surface”.•The touch system overcomes the limitations of gel-based touchpads prone to water loss, ion/organic reagent seepage. Recent trends have seen the adoption of soft gel-based ionic conductors in the development of touch pads to enhance flexibility. Yet, these gel-based systems are hampered by intrinsic limitations like dehydration and ion/organic reagent leakage. Here, we report a flexible touch system, ingeniously combining a surface-capacitive system with solid-state ionic conductive elastomers. Combination of salt-in-polymer and double-network structure strategies effectively addresses the longstanding trade-off between mechanical robustness and ionic conductivity. This flexible touch system supports a range of applications, from singular “point” interactions (flexible touch buttons) to “line” applications (stepless sound control and page turning) and finally, “surface” functionalities (game control and handwriting recognition). This research contributes significant insights to the advancement of next-generation human interfaces and IoTs.