A Ca2+-mediated crosslinked dual-conductive hydrogel with intrinsic self-adhesion for long-term, motion-tolerant bioelectronic interfaces

Conductive hydrogels are promising for wearable electronics and biomedicine due to their flexibility, biocompatibility, and tunable conductivity, but synergizing high conductivity, robust mechanics, and tissue adhesion remains challenging. Herein, a novel stretchable, dual-conductive, self-adhesive poly(2-hydroxyethyl methacrylate)-MXene-Ca 2+ (pMC) hydrogel was fabricated via facile physical crosslinking. The underlying mechanism involves a dynamic non-covalent network, where reversible hydrogen bonds within pHEMA chains and Ca²⁺-mediated coordination bonds bridging pHEMA and MXene collectively dissipate energy during deformation. This process confers outstanding stretchability and enables reliable self-adhesion through strong interfacial bonding with tissues. Furthermore, synergistic ionic conduction from Ca 2+ transport in pHEMA hydrophilic channels and electronic conduction through a percolating MXene network achieves optimal conductivity of 1.02 S/m under deformation. This synergistic mechanism enables high-fidelity monitoring of human physiological signals, ranging from large-scale joint movements to subtle arterial pulses, with long-term stability of 2,800 s. A sandwich-structured 4-channel electrode array was developed for high-performance electromyography (EMG) and electrocardiography (ECG) acquisition. The array exhibits superior performance over commercial Ag/AgCl electrodes with a signal-to-noise ratio of 21.9, lower skin-electrode impedance, and reliable electrocardiography recording stability over 3,800 s. Combining scalable fabrication, excellent biocompatibility, and synergistic multifunctionality, the pMC hydrogel holds great promise for next-generation wearable bioelectronics in health monitoring and human-machine interfaces. Fabrication of the pHEMA–MXene–Ca²⁺ (pMC) conductive hydrogel and its application in real-time monitoring of human movement and physiological signals (ECG, EMG, finger and knee bending).