MXene‐Induced Flexible, Water‐Retention, Semi‐Interpenetrating Network Hydrogel for Ultra‐Stable Strain Sensors with Real‐Time Gesture Recognition

Abstract

Abstract As water‐saturated polymer networks, hydrogels are a growing family of soft materials that have recently become promising candidates for flexible electronics application. However, it remains still difficult for hydrogel‐based strain sensors to achieve the organic unity of mechanical properties, electrical conductivity, and water retention. To address this challenge, based on the template, the excellent properties of MXene nanoflakes (rich surface functional groups, high specific surface area, hydrophilicity, and conductivity) are fully utilized in this study to prepare the P(AA‐co‐AM)/MXene@PDADMAC semi‐interpenetrating network (semi‐IPN) hydrogel. The proposed hydrogel continues to exhibit excellent strain response and flexibility after 30 days of storage at room temperature, and its performance do not decrease after 1100 cycles. Considering these characteristics, a hydrogel‐based device for converting sign language into Chinese characters is successfully developed and optimized using machine learning. Therefore, this study provides novel insight and application directions for hydrogel families.

Keywords

• machine learning
• MXene hydrogel
• strain sensors
• ultra‐stable
• water retention