The production rate of industrial and agricultural waste is increasing due to population growth. Soil is the most important receiver of industrial and agricultural waste. Contaminants such as heavy metals in various waste after reception by the soil, immediately become part of the cycle that has different impacts on the environment. Geopolymer, as a chemical stabilizer has the potential to stabilize heavy metals in the soil. In this research, several geopolymers for the stabilization of heavy metals in soil were synthesized. Silicon dioxide (SiO2) and aluminosilicate (Al2SiO4) must be used to produce the geopolymers. Rice husk ash was used as the SiO2 source. Also, Iranian zeolite and sepiolite, and red clay soil were utilized as the source of Al2SiO4. The synthesized geopolymers were investigated for the adsorption of nickel and cadmium. Also, batch and column studies of using geopolymers for the chemical stabilization of heavy metals in soil were conducted. The results revealed a high adsorption capacity of the geopolymers. The zeolite, sepiolite, and red clay geopolymer-soil samples adsorbed 100% of the heavy metals (i.e., Ni and Cd) at a concentration of 100 ppm. The zeolite geopolymer adsorbent adsorbed 57% and 96% of Ni and Cd at a concentration of 1000 ppm, respectively. In general, it was concluded that the use of geopolymer compounds in soils with high heavy metal adsorption capacity could be an efficient approach to prevent groundwater resource pollution.

In this study, the adsorptive removal of two dyes (crystal violet (CV) and methylene blue (MB)) with HNO3 pre-treated water hyacinth powder (WHP) adsorbent was analysed. The experiments were designed using response surface methodology (RSM) with variable input parameter pH (2-12), adsorbent dose (0.5-3 g/L), initial dyes concentration (25-200 mg/L) and time (10-180 min). The optimization condition for dye removal were (pH = 7.22, adsorbent dose = 3.0 g/L, initial dye concentration = 195.28 mg/L and time of contact = 99.29 min) for CV with removal of 98.20% and (pH = 9.82, adsorbent dose = 2.96 g/L, initial dye concentration = 199.36 mg/L and contact time = 111.74 min) for MB with removal of 97.843%. The above findings observed that pre-treated water hyacinth powder can be utilised as a cost-effective and efficient adsorbent for dye effluent wastewater treatment.

This work explores the synthesis and characterization of two novel nanocomposites that can be used in various applications, such as aqueous solution adsorption of pollutants. The first nanocomposite consists of tin (Sn)-doped titanium dioxide (TiO2) on activated carbon, while the other one consists of polypyrole (PPy), chitosan (CS), and Sn-doped TiO2. A contrast was made of their effective adsorbent materials for the removal of Cibacron Brilliant Yellow dye from aqueous solutions. Different analytical techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), energy dispersive X-ray analysis (EDX), and Fourier transform - infrared (FT-IR) were used to analysis the nanocomposite samples. SEM images show that the average particle diameter of PPy-CS/Sn-doped TiO2 NC is 75 ± 3 nm, while Sn-doped TiO2/AC particles have an average diameter of 40 ± 2 nm. The greater PPy-CS/Sn-doped TiO2 nanocoposite particle diameter indicates that the polymers cover the Sn-doped TiO2 nanoparticles, which leads to higher in the diameter of the particles. The adsorption efficiency of Sn-doped TiO2/AC was higher than that of PPy-CS/Sn-doped TiO2 sample due to its smaller particle size which resulted in a higher surface area which provides more adsorption sites. However, both samples showed remarkable adsorption capacity, where the adsorption capacity of Sn-doped TiO2/AC and PPy-CS/Sn-doped TiO2 were 104 and 103 mg/g, respectively.

In this study natural bentonite (NB) and acid-thermal co-modified bentonite (MB) were utilized as adsorbents for the removal of Thymol Blue (TB) from aqueous solution. The batch adsorption experiments were conducted under different experimental conditions. The artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS) were applied to estimate removal percentage (%) of TB. Mean squared error (MSE), root mean square error (RMSE) and coefficient of determination (R2) values were used to evaluate the results. In addition, the experimental data were fitted isotherm models (Langmuir, Freundlich and Temkin) and kinetic models (pseudo first order (PFO), pseudo second order (PSO) and intra-particle diffusion (IPD)). The adsorption of TB on both the NB and MB followed well the PSO kinetic model, and was best suited Langmuir isotherm model. When the temperature was increased from 298 K to 323 K for 20 mg/L of TB initial concentration, the removal percentage of TB onto the NB and MB increased from 74.91% to 84.07% and 81.19% to 93.12%, respectively. This results were confirmed by the positive ΔH° values indicated that the removal process was endothermic for both the NB and MB. The maximum adsorption capacity was found as 48.7805 mg/g and 117.6471 mg/g for the NB and MB, respectively (at 323 K). As a result, with high surface area and adsorption capacity, the MB is a great candidate for TB dye removal from wastewater, and the ANFIS model is better than the ANN model at estimating the removal percentage of the dye.