Ion sieving in 2D membranes from first principles

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{
  "id": "2279", 
  "created": "2024-07-29T09:19:03.884270+00:00", 
  "updated": "2025-05-26T11:10:30.677038+00:00", 
  "revision": 7, 
  "metadata": {
    "_files": [
      {
        "key": "data.zip", 
        "size": 273850233, 
        "description": "MD trajectories, energies and forces used to generate Fig. 4. See README.txt for detailed description.", 
        "checksum": "md5:0356d3d9e3e7ccdf6b3e273016a533ba"
      }
    ], 
    "license_addendum": null, 
    "edited_by": 576, 
    "publication_date": "May 26, 2025, 13:10:30", 
    "contributors": [
      {
        "email": "nicephore.bonnet@epfl.ch", 
        "affiliations": [
          "Theory and Simulation of Materials (THEOS), Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"
        ], 
        "givennames": "Nicephore", 
        "familyname": "Bonnet"
      }, 
      {
        "email": "nicola.marzari@epfl.ch", 
        "affiliations": [
          "Theory and Simulation of Materials (THEOS), Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"
        ], 
        "givennames": "Nicola", 
        "familyname": "Marzari"
      }
    ], 
    "description": "A first-principles approach for calculating ion separation in solution through 2D membranes is proposed. Ionic energy profiles across the membrane are obtained first, where solvation effects are explicitly simulated by machine-learning molecular dynamics, electrostatic corrections are applied to remove finite-size capacitive effects, and a mean-field treatment of the electrochemical double layer charging is used. Entropic contributions are assessed analytically and through a thermodynamic integration scheme. Ionic separations are then inferred through a microkinetic model of the filtration process, accounting for steady-state charge separation effects across the membrane. The approach is applied to Li+, Na+, K+ sieving through a crown-ether functionalized graphene membrane, with a case study of the mechanisms for a highly selective and efficient extraction of lithium from aqueous solutions.\nThis record contains the MD trajectories used to generate the energy and free energy profiles of Fig. 4.", 
    "id": "2279", 
    "owner": 950, 
    "references": [
      {
        "type": "Journal reference", 
        "citation": "Submitted"
      }
    ], 
    "version": 1, 
    "license": "Creative Commons Attribution 4.0 International", 
    "status": "published", 
    "title": "Ion sieving in 2D membranes from first principles", 
    "keywords": [
      "2D membrane", 
      "Ion sieving", 
      "Machine learning", 
      "Molecular dynamics"
    ], 
    "doi": "10.24435/materialscloud:mg-wh", 
    "mcid": "2025.85", 
    "is_last": true, 
    "_oai": {
      "id": "oai:materialscloud.org:2279"
    }, 
    "conceptrecid": "2278"
  }
}