Mechanistic study of pH effect on organic solvent nanofiltration using carboxylated covalent organic framework as a modeling and experimental platform

Phuoc H.H. Duong, Yun Kyung Shin, Valerie A. Kuehl, Mohammad M. Afroz, John O. Hoberg, Bruce Parkinson, Adri C.T. van Duin, Katie D. Li-Oakey

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Covalent organic framework (COF) membranes for organic solvent nanofiltration (OSN) have attracted growing interest due to their high stability, well-defined pore size, and controllable pore functionality. In aqueous nanofiltration processes, solution pH has a significant effect on membrane permeability, selectivity, and fouling. However, our understanding of pH effects on OSN processes is still limited. Here, we present experimental and reactive force field molecular dynamics (ReaxFF MD) simulation results on the effect of pH on OSN using a well-characterized carboxylated COF (C-COF) membrane. Filtration experimental and modeling results both demonstrate that pH changes can affect solvent permeance and solute rejection dramatically. Specifically, methanol permeance decreases with the increase of NaOH and HCl concentration, respectively. When Alcian Blue dye was used as the solute in methanol, the selectivity increased from 23% to 98% when changing the feed pH from 2.2 to 10.1, respectively. While ReaxFF MD results show that C-COF solvated pore size is only marginally affected by the pH of solution, methanol diffusion is affected by the size of methanol-solvated Na+ and Cl- ions, which increase with increasing Na+ and Cl- concentrations. Solution pH change also affected solute solvation layer thicknesses and C-COF pore charges, contributing to the significant AB dye selectivity increase with pH increase. To summarize, we have shown that dramatic changes in C-COF selectivity are not anomalous in OSN, but are instead controllable by varying feed solution pH to modify solvated solute radii and surface charge.

Original languageEnglish (US)
Article number120028
JournalSeparation and Purification Technology
StatePublished - Feb 1 2022

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Filtration and Separation

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