Electronegative, Transparent, and Flexible Triboelectric Electrodes via Three-Dimensionally Stacked Interconnect...

Flexible and transparent triboelectric nanogenerators (TENGs) have exhibited tremendous application potential in the fields of human-machine interfaces (HMIs), invisible anticounterfeiting, and environmental monitoring. However, developing electrode materials that simultaneously achieve high stability, excellent electrical conductivity, and good optical transparency remains a key challenge. Existing electrodes such as aluminum, indium tin oxide (ITO), and silver nanowires (Ag NWs) are electropositive, which greatly limits their applications in flexible wearable electronics and human-machine interfaces because human skin, clothing, and gloves are usually electropositive. Here, in this work, we propose flexible and transparent triboelectric electrodes through rationally designing a MXene-Ag NWs-MXene (MAM) 3D stacked interconnect structure. The electrodes exhibit high transparency, flexibility, stability, and electronegativity. The top layer MXene acts as both an electronegative layer and protective layer, which can help generate electrical output after contact and separation with electropositive materials (clothes, gloves, and human skins) and protect the Ag NWs from being oxidated even under circumstance of high temperature (85 °C) and humidity (99% RH). The Ag NW layer performs as a conductive layer to provide a cross-interface electron transport channel even though the top MXene layer is oxidated. The bottom MXene layer serves as both an adhesive and a conductive component. The MAM electrodes demonstrate a high optical transmittance of ∼84% at 550 nm and maintain stable conductivity and output performance after 1,000 bending and twisting cycles with different angles. To further demonstrate the practical potential, the MAM electrode-based TENG array is designed as invisible HMIs to control the LED and as a security overlay for keyboards to realize the function of identity recognition through machine learning. This work provides a strategy for developing advanced flexible and transparent electrodes in HMI systems.