3D-printed hierarchical microstructures from allyl cellulose-based ionic conductors for intelligent flexible pressure...

Flexible pressure sensors require simultaneous optimization of mechanical robustness, ionic conductivity, and structural programmability, properties that are rarely achieved in a single bio-based material system. Here, we report an allyl cellulose-based ternary ionic conductor that resolves these competing requirements through a dual-network architecture, in which covalent allyl cellulose-acrylamide crosslinks and dynamic hydrogen-bonding interactions with sulfobetaine methacrylate act synergistically. This design enables systematic tunability, with the optimized formulation achieving exceptional mechanical properties (3.33 MPa maximum compressive strength, 88% strain tolerance), stable ionic conductivity (0.04 S/m), and outstanding optical clarity (76.9% transmittance). Through DLP 3D printed template replication, we translate this material versatility into biomimetic multistage dome arrays that exploit sequential contact mechanics to achieve extraordinary piezoresistive sensitivity (1.71 kPa^-1), outperforming uniform architectures by 40.1%. The resulting sensors demonstrate exceptional performance including ultra-low detection thresholds (220 Pa), rapid response time (<100 ms), and outstanding durability exceeding 10,000 cycles. Furthermore, integration with a convolutional neural network enables deep learning-enhanced tactile intelligence, achieving 99% internal validation accuracy across five object categories through short-time Fourier transform-based tactile signal analysis of signals acquired under a standardized press-and-slide protocol. Comprehensive validation spanning physiological monitoring, robotic tactile perception, and human-machine interfaces confirms the technology's versatility. These results establish allyl cellulose-based dual-network ionic conductors as a versatile bio-derived platform in which material composition, microstructural geometry, and data-driven signal processing can be co-designed to meet the divergent requirements of next-generation flexible pressure sensing.