Rational Design of Zeolites to Remove Siloxane-Related Pollutants with High Adsorption Loading and Enhanced Adsorption Energy

Though siloxanes and their derivatives have been widely used, they are emerging and persistent pollutants in water systems. Developing high-performance and low-cost adsorbents to remove siloxane-related pollutants is an essential strategy for removing these contaminants. Through Grand Canonical Monte Carlo (GCMC) simulations, we computed and evaluated the adsorption performances of 246 experimentally available zeolite frameworks toward three silanols, namely, trimethylsilanol (TMS), dimethylsilanediol (DMSD), monomethylsilanetriol (MMST), and the coexisting contaminant in siloxane-impacted environments, dimethylsulfone (DMSO₂), and obtained the best sorbents for each pollutant. To seek multifunctional zeolites, we first screened out the top 10 zeolite frameworks based on the loading values, among which the framework RWY showed the best performance. We further demonstrated that introducing dopants can enhance adsorption performance by taking RWY as an example. This work not only identified the most promising zeolite frameworks for removing linear siloxanes and derivatives, but also provided a relatively efficient and practical computational approach for screening sorbent materials for other emerging pollutants, balancing accuracy with tractable computational cost.