This paper presents van der Waals (vdW) contacted graphene field-effect transistors (GFETs) and logic circuits, both on rigid and flexible substrates. These logic gates exhibit stable performances after 100 cycles of bending. Realized with complementary metal oxide semiconductor (CMOS) compatible technology, the vdW contacted GFETs show performance comparable to the top-contacted GFETs and thus present excellent cost-effective alternatives to top- and edge-contacted GFETs for large-area electronic applications.

Sensory feedback from touch is critical for many tasks carried out by robots and humans, such as grasping objects or identifying materials. Electronic skin (e-skin) is a crucial technology for these purposes. Artificial tactile skin that can play the roles of human skin remains a distant possibility because of hard issues in resilience, manufacturing, mechanics, sensorics, electronics, energetics, information processing, and transport. Taken together, these issues make it difficult to bestow robots, or prosthetic devices, with effective tactile skins. Nonetheless, progress over the past few years in relation with the above issues has been encouraging, and we have achieved close to providing some of the abilities of biological skin with the advent of deformable sensors and flexible electronics. The naive imitation of skin morphology and sensing an impoverished set of mechanical and thermal quantities are not sufficient. There is a need to find more efficient ways to extract tactile information from mechanical contact than those previously available. Renewed interest in neuromorphic tactile skin is expected to bring some fresh ideas in this field. This article reviews these new developments, particularly related to the handling of tactile data, energy autonomy, and large-area manufacturing. The challenges in relation with these advances for tactile sensing and haptics in robotics and prosthetics are discussed along with potential solutions.

This paper presents a touch-based system for communication by deafblind people with humans and robots. With presented system the deafblind people can send control signal to robots by writing block letters on an array of 8 × 8 diamond-shaped capacitive touch sensors. For better conformability with curved surfaces, the touch sensors arrays have been fabricated on flexible polyvinyl chloride (PVC) substrate. The characters written by deafblind on the tactile sensing array are recognized by Convolution Neural Network (CNN), which is trained with data from Extended Modified National Institute of Standards and Technology (EMNIST) database. A mobile app was also developed to efficiently recognize and display the written letters. Finally, a Baxter robot was simulated using Robot Operating System (ROS) and was remotely controlled by deafblind through English block letters written on the tactile sensing array. The result shows that the robot could successfully execute the `pick or drop' task. The developed system demonstrates the efficacy of tactile based communication by deafblind people to independently interact with a robot and their environment.