High‐Precision Multiplex Chemical Sensors with Pattern‐Recognition Capability via a Letter Printing‐Inspired Transfer Method

ABSTRACT Graphene‐based chemical sensors offer high sensitivity owing to exceptional charge transport and a large surface‐to‐volume ratio, yet reliable discrimination across diverse analytes remains challenging. In this study, a letterpress‐inspired, one‐step transfer‐printing strategy integrated with pattern‐recognition analysis is proposed to implement multiplexed chemical sensor arrays based on graphene field‐effect transistors (GFETs). By tuning interfacial adhesion between functional materials and a polymer stamp, accurate and area‐selective functionalization with sub‐10 µm feature sizes is achieved, thereby enabling simultaneous multifunctionalization of graphene. The resulting 3 × 3 GFET sensor arrays, comprising both functionalized and pristine channels, generate distinct sensing response patterns to representative volatile organic compounds, including chlorobenzene, toluene, and methanol, at a fixed tested concentration, driven by molecule‐specific charge‐transfer interactions at the functional layer. An artificial neural network trained on sensor‐derived patterns is further demonstrated with an increased number of sensors, delivering highly accurate classification results. This strategy highlights a versatile and scalable platform that combines lithography‐free, low‐cost transfer printing with intelligent analysis, offering a practical route toward next‐generation chemical‐sensing systems based on functionalized 2D materials.