Multi-objective PEDOT:PSS conductive nonwoven fabric performance optimization based on GA-BP.

Aimed at the problems of unstable conductivity and worse mechanical properties of poly (3, 4-ethylenedioxythiophene): poly(styrenesulfonic acid) (PEDOT: PSS) conductive nonwoven fabric, a neural network model was used to optimize the properties of PEDOT: PSS conductive nonwoven fabrics.The experimental data of PEDOT: PSS conductive nonwoven fabrics were collected as the input and output of GA-BP neural network, and the optimization model for the ratio of PEDOT: PSS conductive polymers was established.The results showed that the optimized process parameters to prepare PEDOT: PSS conductive nonwoven fabric included the molar ratio of EDOT and PSS as 0.334 5, the concentration of ammonium persulfate as 0.029 7 mol/L,the concentration of iron sulfate as 0.048 7 mol/L, and the mass fraction of hydrochloric acid as 6.963 0%.The conductivity of optimized conductive nonwoven fabric was 6.713 S/m, the tensile strength of nonwoven fabric was 4.581 MPa. The conductivity of prepared PEDOT : PSS conductive nonwoven fabric after 20 min friction was decreased from 6.329 S/m to 5.348 S/m. After 60 min washing, the conductivity was decreased from 6.536 S/m to 5.435 S/m and the decrease trend was slow. It means that the prepared conductive nonwoven fabrics had excellent stability and durability. [ABSTRACT FROM AUTHOR]