A scaling law for large-deformation contact in soft materials
Tong Mu, Shizhuo Weng, Changhong Linghu, Ruozhang Li, Jingyi Yu, Zhonghao Xu, Yingjie Fu, Lin Yang, Domenico Campolo, Yanju Liu, Jinsong Leng, K. Jimmy Hsia, Huajian Gao
公開日: 2025/9/23
Abstract
Compression of soft bodies is central to biology, materials science, and robotics, yet existing contact theories break down at large deformations. Here, we develop a general framework for soft-body compression by extending the method of dimensionality reduction into the nonlinear regime. Analytical solutions for contact force and radius are derived and validated against finite element simulations and experiments on canonical geometries (cone, hemisphere, cylinder), achieving high accuracy up to 50% compression. From this framework emerges a universal scaling law that unifies the nonlinear force-displacement response across diverse shapes and even irregular soft objects such as gummy candies. Leveraging this principle, we design a vision-based tactile sensor that reconstructs real-time pressure maps and enables delicate robotic manipulation of fragile items. By bridging nonlinear contact mechanics with practical sensing, this work both advances fundamental understanding of large-strain mechanics and opens a route to robust tactile technologies for soft robotics and biomedical applications.