Return Point Memory in Knitted Fabrics

Studying and tuning the mechanical response of knitted fabrics with physics have a plethora of applications, from soft robotics to artificial muscles to morphing electromagnetic field sensors. Elasticity in fabrics emerges from the bending of yarn in the knitted structure, however, properties beyond elasticity are relatively unexplored. In carefully designed experiments that measure the response of knitted fabrics to applied uniaxial stress, our measurements both exhibit significant hysteresis and demonstrate the remarkable ability of fabrics to ``remember" their response to previous deformations -- in a fashion quite analogous to classical return point memory phenomena in magnetic systems. The hysteretic behavior deviates remarkably from the two standard models of hysteresis that usually apply to solid-state materials, viscoelasticity and plasticity. Viscoelasticity is precluded as we observe that knitted fabic hysteresis is rate-independent over a modestly wide range of applied rates and conventional plasticity is additionally precluded due to the presence of the return-point phenomena. In this talk, we present these observations, develop a phenomenological model based on an extended Preisach model of hysteresis, and discuss implications of these results on the underlying mechanisms of memory formation in knitted fabrics.