Abstract Freezing hydrogels at subzero temperatures severely compromises mechanical flexibility, ionic conductivity, and structural integrity, thereby limiting their application in low‐temperature environments. Hydrogel freezing involves both ice nucleation and ice growth; however, simultaneously inhibiting these two processes remains a significant challenge. In nature, freeze‐tolerant organisms do not rely on completely preventing ice formation to survive freezing conditions. Instead, they utilize bacterial membrane‐anchored ice nucleating protein (BMIP) to promote ice nucleation and ice binding protein (IBP) to regulate ice growth, thereby achieving freeze protection through precise ice management. Inspired by this biological strategy of “selective nucleation of small ice crystals with restricted growth,” we developed anti‐freezing hydrogels by incorporating both BMIP and IBP. The anti‐freezing hydrogels exhibit enhanced mechanical and electrical performance at low temperatures, with a non‐freezing matrix stable down to −30°C and excellent structural integrity over multiple freeze‐thaw cycles. When employed as a functional component of a robotic hand designed for low‐temperature operation and integrated with machine learning algorithms, the anti‐freezing hydrogels enable precise recognition of object stiffness and size under ultra‐low temperature conditions. This bioinspired approach provides a promising strategy for the development of next‐generation anti‐freezing hydrogels capable of supporting stable human‐robot‐environment interactions in harsh, low‐temperature environments.
Du et al. (Sun,) studied this question.