Machine Learning Assisted Electronic/Ionic Skin Recognition of Thermal Stimuli and Mechanical Deformation for Soft Robots.

Soft robots have the advantage of adaptability and flexibility in various scenarios and tasks due to their inherent flexibility and mouldability, which makes them highly promising for real-world applications. The development of electronic skin (E-skin) perception systems is crucial for the advancement of soft robots. However, achieving both exteroceptive and proprioceptive capabilities in E-skins, particularly in terms of decoupling and classifying sensing signals, remains a challenge. This study presents an E-skin with mixed electronic and ionic conductivity that can simultaneously achieve exteroceptive and proprioceptive, based on the resistance response of conductive hydrogels. It is integrated with soft robots to enable state perception, with the sensed signals further decoded using the machine learning model of decision trees and random forest algorithms. The results demonstrate that the newly developed hydrogel sensing system can accurately predict attitude changes in soft robots when subjected to varying degrees of pressing, hot pressing, bending, twisting, and stretching. These findings that multifunctional hydrogels combine with machine learning to decode signals may serve as a basis for improving the sensing capabilities of intelligent soft robots in future advancements.

Strong, tough and anisotropic bioinspired hydrogels.

Soft materials are widely used in tissue engineering, soft robots, wearable electronics, etc. However, it remains a challenge to fabricate soft materials, such as hydrogels, with both high strength and toughness that are comparable to biological tissues. Inspired by the anisotropic structure of biological tissues, a novel solvent-exchange-assisted wet-stretching strategy is proposed to prepare anisotropic polyvinyl alcohol (PVA) hydrogels by tuning the macromolecular chain movement and optimizing the polymer network. The reinforcing and toughening mechanisms are found to be "macromolecule crystallization and nanofibril formation". These hydrogels exhibit excellent mechanical properties, such as extremely high fracture stress (12.8 ± 0.7 MPa) and fracture strain (1719 ± 77%), excellent modulus (4.51 ± 0.76 MPa), high work of fracture (134.47 ± 9.29 MJ m-3), and fracture toughness (305.04 kJ m-2) compared with other strong hydrogels and even natural tendons. In addition, excellent conductivity, strain sensing capability, water retention, freezing resistance, swelling resistance, and biocompatibility can also be achieved. This work provides a new and effective method to fabricate multifunctional anisotropic hydrogels with high tunable strength and toughness with potential applications in the fields of regenerative medicine, flexible sensors, and soft robotics.