Highly elastic, frost-resistant and antimicrobial flexible sensor inspired by ramen noodles for human motion detection and deep learning of handwritten content

Biomaterial-based hydrogels have gained significant attention in the development of flexible multifunctional electronic devices for the future. However, it is a great challenge to prepare biomaterial-based hydrogels with high toughness, electrical conductivity and frost-resistant by a simple and low-cost way. Meanwhile, starch bio-based hydrogels have emerged as a popular area of research due to their abundant sources and degradability. Unfortunately, these hydrogels often exhibit poor mechanical properties and freeze resistance, which restrict their practical applications. Taking inspiration from the traditional food ramen, where a simple mixture of noodles can become remarkably stretchable and resilient, our study aims to enhance the performance of hydrogels by leveraging their toughening mechanism. We achieve this by combining polyvinyl alcohol (PVA), branched chain starch (Amy), wheat protein (WP), ethylene glycol (EG) with saline. The Amy/PVA/EG/WP/S (APEWS) organohydrogels demonstrated excellent mechanical properties (1.12 MPa) due to the combination of PVA as a hard backbone, a rich protein network, diverse functional groups, and saline components. Additionally, the binary solvent consisting of water and EG allowed the hydrogel to function effectively even at low temperatures (-20 °C). The APEWS organohydrogel exhibited promising sensing capability (GF = 1.46) and sensing stability (>500 times) as a human wearable strain sensor, making it suitable for detecting human motion and the hydrogel showed excellent antimicrobial properties against Escherichia coli (Gram-negative bacteria). Furthermore, we employed a Long Short-Term Memory (LSTM) artificial neural network for deep learning-based recognition of written content. The network achieved an accuracy of over 95.5% for different English letters and 100% for symbols. These results highlight the potential of this technology in applications such as writing sensing and information encryption. In conclusion, with the simple preparation method and low cost, APEWS organohydrogels are expected to be the next generation of green and sustainable bio-based strain sensors.