Focus Session 1

Gijs Krijnen

University of Twente, the Netherlands
Presenter Bio

Dr. Gijs Krijnen's interests are in bio-inspired transducers, parametric sensing schemes and additive manufacturing (embedded sensing). He currently is professor in the Robotics and Mechatronics group of the University of Twente. He has (co-) authored over 110 refereed journal papers, 11 book chapters and 245 conference contributions on a variety of subjects including nonlinear integrated optics, micro-mechanical sensors and actuators, biomimetic flow and inertial sensors and parametric and nonlinear transduction. He holds a PhD (cum laude) from the University of Twente, has been a fellow of the Royal Netherlands Academy of Arts and Sciences and was awarded a VICI grant by the Netherlands Organisation for Scientific Research in 2005 for research on bio-inspired flow-sensors (BioEARS).

Abstract: Towards 3D printed, embedded sensors
Traditionally, to sense particular quantities, sensors are mounted on structures and both are optimised independently. Such optimised sensors generally perform very well. However, giving their characteristics, such as form-factor and measurement range, they may not be the best solution and only allow for limited complexity as assembling and interfacing become increasingly complex with increasing sensor count. Over the last decade the interest in 3D printing of functional structures, rather than rapid prototyping of non-functional structures, has seen a considerable increase; technologies like multi-material 3D printing allow to incorporate electrically conductive materials in dielectric embedding. This opens the route to 3D print electrical connections and sensors _while_ printing entire structures. This has the potential to integrate many sensors and connections and holistically optimise for specific intended applications. For mechanical sensing principles that seem rather suitable for 3D multi-material printing include piezo-resistive and capacitive sensing, although piezo-electric, optic and many others have been shown as well. Next to mechanical sensing also bio-potential, chemical, and magnetic sensors have been demonstrated, alongside 3D printed batteries. In my lab we focus on the development of 3D printing technology for sensing, addressing challenges like print quality, anisotropic conduction, nonlinear mechanical and electrical behaviour, etc. Intended applications are in biopotential measurements and interaction sensing for wearable robotics and medical aids, flow-sensing, beam deflection control, thrust control for UAV applications, etc. In this presentation I will describe developments in these fields as well as multiple examples of our own work.

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