Engineering Interconnected Nanofluidic Channel in a Hydrogel Supernetwork toward K + Ion Accelerating Transport and Efficient Sensing.
Rui ZhuPeng SunGuofeng CuiJie ZhaoYaoguang YuPublished in: ACS applied materials & interfaces (2024)
Ion transportation via the mixed mechanisms of hydrogels underpins ultrafast biological signal transmission in nature, and its application to the rapid and sensitive sensing detection of human specific ions is of great interest for the field of medical science. However, current research efforts are still unable to achieve transmission results that are comparable to those of bioelectric signals. Herein, 3D interconnected nanochannels based on poly(pyrrole- co -dopamine)/poly(vinyl alcohol) (P(Py- co -DA)/PVA) supernetwork conductive hydrogels are designed and fabricated as stimuli-responsive structures for K + ions. Distinct from conventional configurations, which exhibit rapid electron transfer and permeability to biosubstrates, interconnected nanofluidic nanochannels collaborated with the P(Py- co -DA) conductive polymer in the supernetwork conductive hydrogel significantly improve conductivity (88.3 mS/cm), ion transport time (0.1 s), and ion sensitivity (74.6 mV/dec). The faster ion response time is attributed to the synergism of excellent conductivity originating from the P(Py- co -DA) polymer and the electronic effect in the interconnected nanofluidic channels. Furthermore, the supernetwork conductive hydrogel demonstrates K + ion selectivity relative to other cations in biofluids such as Na + , Mg 2+ , and Ca 2+ . The DFT calculation indicates that the small solvation energy and low chemical transfer resistance are the main reasons for the excellent K + ion selectivity. Finite element analysis (FEA) simulations further support these experimental results. Consequently, the P(Py- co -DA)/PVA supernetwork conductive hydrogels enriched with the 3D interconnected nanofluidic channels developed in this work possess excellent sensing of K + ions. This strategy provides great insight into efficient ion sensing in traditional biomedical sensing that has not been explored by previous researchers.