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Probing Self-Diffusion of Guest Molecules in a Covalent Organic Framework: Simulation and Experiment.

Lars GrunenbergChristopher KeßlerTiong Wei TehRobin SchuldtFabian HeckJohannes KarwounopoulosJoachim GroßNiels HansenBettina V Lotsch
Published in: ACS nano (2024)
Covalent organic frameworks (COFs) are a class of porous materials whose sorption properties have so far been studied primarily by physisorption. Quantifying the self-diffusion of guest molecules inside their nanometer-sized pores allows for a better understanding of confinement effects or transport limitations and is thus essential for various applications ranging from molecular separation to catalysis. Using a combination of pulsed field gradient nuclear magnetic resonance measurements and molecular dynamics simulations, we have studied the self-diffusion of acetonitrile and chloroform in the 1D pore channels of two imine-linked COFs (PI-3-COF) with different levels of crystallinity and porosity. The higher crystallinity and porosity sample exhibited anisotropic diffusion for MeCN parallel to the pore direction, with a diffusion coefficient of D par = 6.1(3) × 10 -10 m 2 s -1 at 300 K, indicating 1D transport and a 7.4-fold reduction in self-diffusion compared to the bulk liquid. This finding aligns with molecular dynamics simulations predicting 5.4-fold reduction, assuming an offset-stacked COF layer arrangement. In the low-porosity sample, more frequent diffusion barriers result in isotropic, yet significantly reduced diffusivities ( D B = 1.4(1) × 10 -11 m 2 s -1 ). Diffusion coefficients for chloroform at 300 K in the pores of the high- ( D par = 1.1(2) × 10 -10 m 2 s -1 ) and low-porosity ( D B = 4.5(1) × 10 -12 m 2 s -1 ) samples reproduce these trends. Our multimodal study thus highlights the significant influence of real structure effects such as stacking faults and grain boundaries on the long-range diffusivity of molecular guest species while suggesting efficient intracrystalline transport at short diffusion times.
Keyphrases
  • molecular dynamics simulations
  • magnetic resonance
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