Development of green photocatalytic geopolymers for dye removal

The use of photocatalysts for water and air depollution processes that utilize light irradiation as an energy source is a well-known and popular research field. Geopolymers, as new sustainable three-dimensional porous inorganic polymers that have the potential to be tailored and used in different applications, are a novel promising candidate as adsorbent and catalyst for depollution applications. In this study, new green geopolymer photocatalysts were developed using rice husk, rice husk ash, metakaolin, ground granulated blast furnace slag, palm oil fuel ash, and TiO2. The depollution performance of the prepared TiO2-based geopolymers was evaluated using the methylene blue (MB) removal test; the geopolymers exhibited more than 95% efficiency in optimum conditions. Artificial neural network (ANN) was employed to predict the adsorption efficiency/capacity of MB adsorption on the developed geopolymer photocatalyst. The proposed ANN model performed well for the adsorption experimental dataset. MB adsorption on the geopolymer photocatalyst was optimized, and different kinetic theories were applied to the experimental data. The pseudo-second-order model explained the adsorption kinetics most effectively. With the high MB removal performance (higher than 95%) of the selected geopolymers, a new green and sustainable adsorbent could be introduced for wastewater depollution application. [Display omitted] •Developed green geopolymers were investigated for depollution performance.•RH, RHA, GGBS and POFA waste materials used as resource for geopolymer preparation.•Effects of various operating parameters on adsorption studied and predicted by ANN.•The experimental data of adsorption fit to a pseudo-second-order kinetic equation.•The developed green geopolymer exhibit ∼95% efficiency as sustainable adsorbent.