Algae-Based Sorbents for Removal of Metallic Contaminants from Semiconductor Manufacturing Wastewater: Process Modeling and Reactor Design

Abstract

Removal of various soluble metallic impurities from wastewater in semiconductor fabrication plants (fabs) is a critical issue facing the microelectronics industry. Considering the large volume of wastewater and a highly variable concentration of these contaminants, finding a robust adsorption process using a low-cost sorbent is of great value and interest to this industry. Of particular interest is the development of a flow-through abatement method for treating the process-tool effluent before it is mixed with other wastewaters. In this work, a strain of freshwater green algae (Chlorella sorokiniana), representing an algae-based sorbent, and a simulated wastewater, containing soluble gallium as the metallic impurity, are used as model compounds. The choice of gallium is based on its increased use, and the lack of related adsorption data compared to the information available for other metals such as copper and arsenic. Both batch and continuous flow operations were used in this study. Comprehensive process models were developed and validated for both batch and flow systems. These models were found to be valuable for understanding the process steps as well as for obtaining the fundamental parameters that are needed for process design and scale-up. The sorbent was found to have high adsorption capacity even at low pH values (14.1 mg/g at pH of 2.3, and 38.5 mg/g at pH of 2.8). Based on the comparison of adsorption rate and capacity with data on previously studied and conventional sorbents, such as activated carbon and ion-exchange resins, the use of this algae-based sorbent is potentially an attractive option for the removal of gallium from the process-tool wastewater. The semiconductor fab wastewater often contains differently charged metal ions to be removed. Due to their adsorption different responses to pH trends and variations, the best way to handle the adsorption treatment of the complex multicomponent wastes is by using a two-stage configuration where the two stages of the system are operated at two different pH. In this and other similar multicomponent processes, the adsorption of each component affects that of others through competition for surface sites, surface charge, and the effects of pH and ionic species in the liquid phase. Process models are developed to simulate the process kinetics and reactor configurations. The results show that the modeling and parametric study are powerful methods for the design of new systems as well as for the optimization of operation in existing systems. Comparisons of different reactor configurations shows that a two-stage fixed-bed reactor system is an effective system for the combined removal of gallium and arsenic species as well as other vastly different ionic impurities.