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Ion Sieving in Two-Dimensional Membranes from First Principles.

Nicéphore Bonnet1, Nicola Marzari1

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Summary
This summary is machine-generated.

This study introduces a novel computational method to predict ion separation by 2D membranes, enabling efficient lithium extraction from aqueous solutions.

Keywords:
2D membraneselectrochemical double layerfirst-principles calculationsion sievingmachine learningmicrokinetic modelmultiscale modeling

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Separation Science

Background:

  • Accurate prediction of ion separation through membranes is crucial for various applications, including water purification and resource recovery.
  • Existing methods often struggle to capture the complex interplay of solvation, electrostatic, and entropic effects in confined membrane environments.

Purpose of the Study:

  • To develop and validate a first-principles computational framework for calculating ion separation in two-dimensional (2D) membranes.
  • To investigate the selective sieving of Li+, Na+, and K+ ions through a functionalized graphene membrane.
  • To elucidate the mechanisms behind efficient lithium extraction from aqueous solutions.

Main Methods:

  • Simulating ionic energy profiles using machine-learning molecular dynamics for explicit solvation effects.
  • Applying electrostatic corrections and mean-field theory for electrochemical double-layer charging.
  • Analytically assessing entropic contributions and validating with thermodynamic integration.
  • Employing a microkinetic filtration model to infer ionic separations.

Main Results:

  • The proposed approach accurately calculates ion energy profiles across 2D membranes.
  • Demonstrated selective sieving of Li+, Na+, and K+ ions through a crown-ether functionalized graphene membrane.
  • Identified key mechanisms for highly selective and efficient lithium extraction.

Conclusions:

  • The developed first-principles method provides a robust tool for designing and optimizing 2D membranes for ion separation.
  • This framework facilitates the understanding of ion transport phenomena at the nanoscale.
  • The study highlights the potential for advanced membrane technologies in critical resource recovery, such as lithium extraction.