Understanding and predicting the diffusivity of organic compounds in polydimethylsiloxane material for passive...

Area of Science:

• Environmental Chemistry
• Materials Science
• Physical Chemistry

Background:

• Polydimethylsiloxane (PDMS) is widely used, necessitating understanding of compound diffusion within it.
• Accurate diffusivity data is crucial for applications like passive sampling and environmental monitoring.
• Existing data on compound diffusion in PDMS is fragmented, requiring consolidation and analysis.

Purpose of the Study:

• To determine the diffusivity of 145 compounds in PDMS using a film stacking technique.
• To compile a comprehensive dataset of 198 compounds with PDMS diffusivity (D_PDMS) by integrating literature data.
• To identify key molecular properties influencing penetrant diffusivity in PDMS and develop a predictive model.

Main Methods:

• Utilized a film stacking technique for laboratory determination of diffusivity.
• Aggregated experimental results with existing literature data to create an extensive dataset.
• Employed quantitative structure-property relationship (QSPR) modeling to establish predictive correlations.

Main Results:

• Established a dataset of 198 compounds with D_PDMS spanning approximately 5 log units.
• Identified molecular volume, rotatable bonds, topological polar surface area, and O/N atom count as significant predictors.
• Developed a nonlinear QSPR model with R² = 0.81 and a mean absolute error of 0.26 log units.

Conclusions:

• Molecular properties like dipole moment, size, and flexibility significantly control compound diffusivity in PDMS.
• The developed QSPR model provides a reliable and accessible tool for predicting PDMS diffusivity.
• This model supports analytical chemists in passive sampler design and other applications without requiring deep theoretical chemistry expertise.