Peter Ballentine1,Brittany Smith1,Nicholas Williams1,Aaron Franklin1
Duke University1
Peter Ballentine1,Brittany Smith1,Nicholas Williams1,Aaron Franklin1
Duke University1
The dynamic range and sensitivity of sensors are essential characteristics to optimize to maximize the utility of sensors, especially those used for biomedical applications. For sensors involving electrical transduction of an analyte signal, optimized dynamic range and sensitivity can be achieved by increasing device area. However, in scenarios where analyte volume is limited, such as biomedical sensors, the use of three-dimensional (3D) structures can increase the surface area of the working electrode without increasing required analyte volume. Current fabrication methods to fabricate conductive 3D structures frequently utilize templates that are removed in post-processing, creating additional fabrication steps and environmentally hazardous waste. In this work, aerosol jet printing is utilized to fabricate conductive 3D structures out of recyclable graphene ink without the need for templates or post-processing. Graphene is selected due to its high theoretical specific area (2630 m<sup>2</sup>/g), its prevalence as a sensor material, and its demonstrated recyclability. Graphene ink composition and printing conditions are developed to realize free-form fabrication of 3D graphene structures via aerosol jet printing. We report pillars and 2-member trusses with heights of ~670 microns and ~590 microns, respectively, which are printed on paper and glass substrates. Two-terminal conductance in the truss structures is 2.87±1.98 kΩ. The impact of these aerosol jet printed pillars on the sensitivity and dynamic range of a printed, graphene-based, electrochemical sensor will be described. By eliminating templating and post-processing while demonstrating optimization of a sensors’ sensitivity and dynamic range, this work opens the doors for the creation of environmentally friendly, highly tunable graphene sensors that can more readily achieve relevant operational ranges and sensitivities.