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Abstract Integration of conductive electrodes with 3D tissue models can have great potential for applications in bioelectronics, drug screening, and implantable devices. As conventional electrodes cannot be easily integrated on 3D, polymeric, and biocompatible substrates, alternatives are highly desirable. Graphene offers significant advantages over conventional electrodes due to its mechanical flexibility and robustness, biocompatibility, and electrical properties. However, the transfer of chemical vapor deposition graphene onto millimeter scale 3D structures is challenging using conventional wet graphene transfer methods with a rigid poly (methyl methacrylate) (PMMA) supportive layer. Here, a biocompatible 3D graphene transfer method onto 3D printed structure using a soft poly ethylene glycol diacrylate (PEGDA) supportive layer to integrate the graphene layer with a 3D engineered ring of skeletal muscle tissue is reported. The use of softer PEGDA supportive layer, with a 10⁵times lower Young's modulus compared to PMMA, results in conformal integration of the graphene with 3D printed pillars and allows electrical stimulation and actuation of the muscle ring with various applied voltages and frequencies. The graphene integration method can be applied to many 3D tissue models and be used as a platform for electrical interfaces to 3D biological tissue system. 

Abstract Advancing biologically driven soft robotics and actuators will involve employing different scaffold geometries and cellular constructs to enable a controllable emergence for increased production of force. By using hydrogel scaffolds and muscle tissue, soft biological robotic actuators that are capable of motility have been successfully engineered with varying morphologies. Having the flexibility of altering geometry while ensuring tissue viability can enable advancing functional output from these machines through the implementation of new construction concepts and fabrication approaches. This study reports a forward engineering approach to computationally design the next generation of biological machines via direct numerical simulations. This was subsequently followed by fabrication and characterization of high force producing biological machines. These biological machines show millinewton forces capable of driving locomotion at speeds above 0.5 mm s⁻¹. It is important to note that these results are predicted by computational simulations, ultimately showing excellent agreement of the predictive models and experimental results, further providing the ability to forward design future generations of these biological machines. This study aims to develop the building blocks and modular technologies capable of scaling force and complexity of these devices for applications toward solving real world problems in medicine, environment, and manufacturing.