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Double network conductive hydrogels for bio-hybrid robots
Conductive networks based on a conductive polymer network will be developed with the purpose of being integrated in engineered tissues for bio-hybrid robots during the biofrabrication process. The conductive hydrogels need to combine good piezoresistive properties, biocompatibility and rheological behavior that allows them to be printed with a bio-printer
Bio-hybrid robots use biological muscle tissue for actuation. These bio-actuators are promising as they are self-healing materials with the ability to adapt to the ever-changing conditions of the natural environment in an autonomous manner. The materials used in bio-hybrid robotics need to be biocompatible and on the same time comply with the softness of the muscle tissue, a challenge for the conventional electronics.
In order to generate bio-hybrid soft robots, constructs of skeletal muscle cells are fabricated in 3D geometry via 3D bioprinting. As integrating soft sensors in such soft living structures via conventional molding methods is challenging: sensors that can be bioprinted are needed. Multimaterial 3D bioprinting allows sensors to be integrated inside the tissue constructs during the biofabrication process. Understanding the rheological properties of the conductive composite can help tune the composition parameters, as well those of the manufacturing process. The resulting biohybrid soft robots will be controlled through electrical stimulation of the muscle fibers and the contraction of the actuator will be monitored by the sensing elements.
Bio-hybrid robots use biological muscle tissue for actuation. These bio-actuators are promising as they are self-healing materials with the ability to adapt to the ever-changing conditions of the natural environment in an autonomous manner. The materials used in bio-hybrid robotics need to be biocompatible and on the same time comply with the softness of the muscle tissue, a challenge for the conventional electronics. In order to generate bio-hybrid soft robots, constructs of skeletal muscle cells are fabricated in 3D geometry via 3D bioprinting. As integrating soft sensors in such soft living structures via conventional molding methods is challenging: sensors that can be bioprinted are needed. Multimaterial 3D bioprinting allows sensors to be integrated inside the tissue constructs during the biofabrication process. Understanding the rheological properties of the conductive composite can help tune the composition parameters, as well those of the manufacturing process. The resulting biohybrid soft robots will be controlled through electrical stimulation of the muscle fibers and the contraction of the actuator will be monitored by the sensing elements.
Goal: Realization of 3D engineered muscle tissue constructs with integrated sensing elements, produced in one-step multi-material bio-fabrication process.
Work Packages
- Mixing the double network gel with different carbon filler contents
- Analysis of the rheological properties of the conductive hydrogels
- Extrusion and printability assessment with the bioprinter
- Biocompatibility assessment of the conductive hydrogels
- Characterization, actuation, and control of the realized robot
Goal: Realization of 3D engineered muscle tissue constructs with integrated sensing elements, produced in one-step multi-material bio-fabrication process. Work Packages - Mixing the double network gel with different carbon filler contents - Analysis of the rheological properties of the conductive hydrogels - Extrusion and printability assessment with the bioprinter - Biocompatibility assessment of the conductive hydrogels - Characterization, actuation, and control of the realized robot
Antonia Georgopoulou-Papadonikolaki, antonia.georgopoulou@empa.ch, High Performance Ceramics Lab (Empa).
Miriam Filippi, mfilippi@ethz.ch, Soft Robotics Lab, Institute of Robotics and Intelligent Systems, D-MAVT, ETH Zurich.
Antonia Georgopoulou-Papadonikolaki, antonia.georgopoulou@empa.ch, High Performance Ceramics Lab (Empa).
Miriam Filippi, mfilippi@ethz.ch, Soft Robotics Lab, Institute of Robotics and Intelligent Systems, D-MAVT, ETH Zurich.