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

## TL;DR

This paper presents a computational approach to design zeolites that efficiently remove siloxane pollutants from water.

## Contribution

The study introduces a rational computational screening method to identify and enhance zeolite frameworks for siloxane removal.

## Key findings

- Framework RWY was identified as the top zeolite for adsorbing siloxane pollutants.
- Doping RWY improved its adsorption performance for siloxane derivatives.
- A practical computational method was developed for screening sorbent materials.

## Abstract

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.