Abstract
Separation processes relying on interfacial interactions, such as the stir bar sorptive extraction represent one of the most critical methods of analyte trace organic detection and extraction in environmental, food, and biomedical samples. While the use of polydimethylsiloxane (PDMS) as a sorptive coating in SBSE has exhibited high sensitivity and efficiency; the molecular mechanisms involved are less explored. We report molecular simulation studies using molecular dynamics (MD) to investigate the absorption of organic compounds including phenol, chlorophenol, guaiacol, benzyl alcohol, and phenethyl alcohol at the aqueous-PDMS interface, and focus on temperature-dependent behavior. By employing an appropriate force field for PDMS, organic compounds, and water, these simulations directly predict PDMS-water partition coefficients, log P [PDMS/water], diffusion coefficients, and solubilities in the PDMS phase without relying on octanol-water partitioning as a surrogate. An important result of the MD simulations in this work is our ability to predict the temperature dependence of the log p(PDMS/water). Results reveal a nonmonotonic temperature-dependent sorption trend for log P [PDMS/water] values. However, we find that with increasing temperature, the absolute number of organic molecules in the PDMS phase increases, driven by enhanced molecular diffusion and PDMS's significant sorption capacity. The findings demonstrate that performing SBSE at elevated temperatures can enhance analyte uptake, improving the analytical sensitivity of trace level extractions, where achieving sufficient analyte concentration in the sorptive phase is critical for reliable detection and quantification in a wide variety of applications in environmental monitoring, food safety, and biomedical analysis. These simulations predict that temperature is a good parameter for the optimization of operating conditions of SBSE. Our results also highlight the ability of MD simulations to reliably capture complex molecular level interactions governing SBSE performance, aligning well with experimental trends and observed behaviors.