Exploring porous sulfur copolymers for efficient removal of heavy metal ions from wastewater: A computational study

This study aims to evaluate the efficacy of porous sulfur copolymers (PSSD and NaSD) in adsorbing heavy metals from wastewater through an inverse vulcanization process. A computational fluid dynamics (CFD) model is developed and validated with experimental data to analyze the heavy metal removal by these materials. The results indicate that Arsenic ions exhibit the highest adsorption capacity compared to cadmium, mercury, and lead, indicating a stronger affinity of porous materials for arsenic ions. Lead ions show lower adsorption due to their larger ionic radius and lower charge density in PSSD. The CFD modeling assesses the adsorption process based on material position, revealing that in PSSD, maximum adsorption occurs at 1.5 cm thickness, while in NaSD, lead inhibits adsorption around 1 cm, with other metals continuing slow adsorption until 2 cm. The results also indicate that two parameter isothermal models indicate that the Langmuir model best fits the adsorption data and three isothermal models stipulate that the sips model is suitable for adsorption data. In the case of PSSD, the maximum adsorption trend is; Arsenic (289 µg/g) > cadmium (228 µg/g) > mercury (207 µg/g) > lead (188 µg/g) ions, respectively. The adsorption efficiency of adsorbents is 60–85 % for heavy metal ions removal. This study holds promise for industrial applications due to the availability of bulk sulfur for porous copolymer production. Leveraging CFD simulations enables rapid determination of optimal process parameters tailored to individual chemical plants, thereby enhancing operational efficiency. This groundbreaking approach enables accurate prediction of adsorption data for various heavy metals under consistent conditions, revolutionizing industrial applications.