Christopher Muir

Papers

Total Citations

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About

Christopher Muir is a researcher at the forefront of additive manufacturing and sensor integration, with a primary focus on developing novel 3D-printed capacitive sensors for robotics and fluid-level monitoring. His most cited work, "3D Printed Capacitive Tilt Sensor" (2020), introduces an innovative approach to tilt sensing by embedding four interdigitated capacitive sensors within a single 3D-printed structure, immersed in liquid Ecoflex™. This design enables precise measurement of fluid level and orientation changes, offering a low-cost, customizable solution for robotic systems. Though his citation count is still growing—with 2 citations to date—Muir’s work stands out for its creative fusion of 3D printing and flexible electronics, demonstrating how additive manufacturing can simplify complex sensing tasks. His contributions are particularly notable for advancing the field of embedded sensors, where traditional fabrication methods often fall short. As a researcher, Muir exemplifies the potential of interdisciplinary engineering, combining materials science, mechanical design, and electrical sensing to create practical, scalable devices. His work holds promise for applications in soft robotics, industrial automation, and environmental monitoring, marking him as an emerging voice in the next generation of sensor technology.