Machine Learning-Enhanced Biomass Pressure Sensor with Embedded Wrinkle Structures Created by Surface Buckling

Abstract

Flexible piezoresistive sensors are core components of many wearable devices to detect deformation and motion. However, it is still a challenge to conveniently prepare highprecision sensors using natural materials and identify similar short vibration signals. In this study, inspired by microstructures of human skins, biomass flexible piezoresistive sensors were prepared by assembling two wrinkled surfaces of konjac glucomannan and kcarrageenan composite hydrogel. The wrinkle structures were conveniently created by hardness gradient-induced surface buckling and coated with MXene sheets to capture weak pressure signals. The sensor was applied to detect various slight body movements, and a machine learning method was used to enhance the identification of similar and short throat vibration signals. The results showed that the sensor exhibited a high sensitivity of 5.1 kPa −1 under low pressure (50 Pa), a fast response time (104 ms), and high stability over 100 cycles. The XGBoost machine learning model accurately distinguished short voice vibrations similar to those of individual English letters. Moreover, experiments and numerical simulations were carried out to reveal the mechanism of the wrinkle structure preparation and the excellent sensing performance. This biomass sensor preparation and the machine learning method will promote the optimization and application of wearable devices.

Flexible Ionic Conductive Hydrogels with Wrinkled Texture for Flexible Strain Transducer with Language Identifying Diversity

“…Similarly, morphology of the materials also plays a vital role in the properties of the material which endows extra functionality and diversifies the practical applicability. According to early reported literature wrinkles on the hydrogels surface improved various properties such as resistance to stresses, surface area, adhesiveness, etc. , Such type of hydrogels was developed through diffusion of hydrophobic photo initiator from oil–water or organic solvent–water to prepolymer solution through the interface. The first phase (oil or organic solvent) decrease the energy barrier at the interface, and the cross-linking gradient is setup in the hydrogels, on polymerization wrinkled surface of the hydrogels was obtained. , A similar approach was adopted, replacing the oil phase with the surfactant, which also decreased the surface energy, resulting in a cross-linking gradient for hydrogel.…”

Multifunctional Sensors Made with Conductive Microframework and Biomass Hydrogel for Detecting Packaging Pressure and Food Freshness

“…A flexible pressure sensor is a potential approach to food packaging testing by measuring the pressure acting on food packaging caused by a transportation collision and food spoilage gas. The sensor performance depends on its structures such as biomimetic microstructures based on skin surfaces, protrusions on lotus leaves, and hydrophobic structures of rose petals . Among these structures, conductive three-dimensional fiber network structure produces significant resistance changes during deformation, leading to excellent sensing performances with high sensitivity. − The performance of the fiber network structure relies on the loose network, large specific surface area, and strong matrix.…”