DLP 3D-Printed Conic-Pyramid Hydrogel Sensor for Wearable Devices and Handwritten Fingerprint Recognition

Flexible hydrogel sensors have attracted significant attention in wearable applications due to their excellent flexibility and biocompatibility. However, challenges such as insufficient long-term stability, limited sensitivity range, and reliance on traditional molds for microstructure design urgently need to be addressed. This study constructs a dual-ion conductive hydrogel sensor with multilevel conic-pyramid microstructures via Digital Light Processing (DLP) 3D printing, breaking through existing technical bottlenecks. Using an acrylamide (AM)-poly(ethylene glycol) diacrylate (PEGDA) double-network matrix loaded with a Mg²⁺/Na⁺ ion system, combined with 30 wt % glycerol modification, the water retention rate of the hydrogel is increased to over 90%, solving the ion concentration fluctuation problem in traditional hydrogels caused by water loss. Simulations comparing six single microstructures show that the conic-pyramid structure, relying on a stepwise compression deformation mechanism (three-level structures sequentially contacting the electrode layer), achieves a sensitivity of 0.544 kPa^-1 in the 0-0.8 kPa pressure range, representing a 78% improvement over traditional pyramid structures. It features a response time of 30 ms, a recovery time of 40 ms, and a signal attenuation <4% after 10,000 cycle tests, with stability improved by 56% compared to single Na⁺ systems. The sensor enables real-time monitoring of finger joint bending (55% resistance variation at 90° bending) and wrist movements (64% resistance variation) through a 9 × 9 orthogonal electrode grid and achieves "handwriting fingerprint" recognition for different writers (signal differences >2.5%) using combined pressure-trajectory features. The high-resolution characteristics (7.8 μm precision, size error <9.13%) of DLP printing breaks through the limitations of traditional molds for complex structures, providing a new paradigm for rapid microstructure prototyping. Compared with existing flexible sensors, this study demonstrates significant improvements in the synergistic performance of sensitivity and stability. The conic-pyramid structure design principle and dual-ion regulation strategy proposed herein offer a universal solution to address sensor performance degradation in complex environments. The "handwriting fingerprint" technology shows broad application potential in identity authentication, medical monitoring, and intelligent anticounterfeiting fields.