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Manipulating Ion Transport Regimes in Nanomembranes via a "Pore-in-Pore" Approach Enabled by the Synergy of Metal-Organic Frameworks and Solid-State Nanochannels.

Juan A AllegrettoGregorio LauciricaAngel L HuamaniMichael F WagnerAlberto G AlbesaMaria Eugenia Toimil-MolaresMatias RaftiWaldemar A MarmisolléOmar Azzaroni
Published in: ACS nano (2024)
Solid-state nanochannels (SSNs) have emerged as promising platforms for controlling ionic transport at the nanoscale. SSNs are highly versatile, and this feature can be enhanced through their combination with porous materials such as Metal-Organic Frameworks (MOF). By selection of specific building blocks and experimental conditions, different MOF architectures can be obtained, and this can influence the ionic transport properties through the nanochannel. Herein, we study the effects of confined synthesis of Zr-based UiO-66 MOF on the ion transport properties of single bullet-shaped poly(ethylene terephthalate) (PET) nanochannels. We have found that emerging textural properties from the MOF phase play a determinant role in controlling ionic transport through the nanochannel. We demonstrate that a transition from ion current saturation regimes to diode-like regimes can be obtained by employing different synthetic approaches, namely, counterdiffusion synthesis, where MOF precursors are kept separate and forced to diffuse through the nanochannel, and one-pot synthesis, where both precursors are placed at both ends of the channel. Also, by considering the dependence of the charge state of the UiO-66 MOF on the protonation degree, pH changes offered a mechanism to tune the iontronic output (and selectivity) among different regimes, including anion-driven rectification, cation-driven rectification, ion current saturation, and ohmic behavior. Furthermore, Poisson-Nernst-Planck (PNP) simulations were employed to rationalize the different iontronic outputs observed experimentally for membranes modified by different methods. Our results demonstrate a straightforward tool to synthesize MOF-based SSN membranes with tunable ion transport regimes.
Keyphrases
  • metal organic framework
  • solid state
  • ionic liquid
  • machine learning
  • mass spectrometry
  • high resolution
  • positron emission tomography
  • high speed