These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

211 related items for PubMed ID: 33443312

  • 1. Effect of Metal-Organic Framework (MOF) Database Selection on the Assessment of Gas Storage and Separation Potentials of MOFs.
    Daglar H, Gulbalkan HC, Avci G, Aksu GO, Altundal OF, Altintas C, Erucar I, Keskin S.
    Angew Chem Int Ed Engl; 2021 Mar 29; 60(14):7828-7837. PubMed ID: 33443312
    [Abstract] [Full Text] [Related]

  • 2. Database for CO2 Separation Performances of MOFs Based on Computational Materials Screening.
    Altintas C, Avci G, Daglar H, Nemati Vesali Azar A, Velioglu S, Erucar I, Keskin S.
    ACS Appl Mater Interfaces; 2018 May 23; 10(20):17257-17268. PubMed ID: 29722965
    [Abstract] [Full Text] [Related]

  • 3.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 4. High-Throughput Computational Screening of the Metal Organic Framework Database for CH4/H2 Separations.
    Altintas C, Erucar I, Keskin S.
    ACS Appl Mater Interfaces; 2018 Jan 31; 10(4):3668-3679. PubMed ID: 29313343
    [Abstract] [Full Text] [Related]

  • 5.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 6.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 7.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 8. Molecular Simulations of MOF Membranes and Performance Predictions of MOF/Polymer Mixed Matrix Membranes for CO2/CH4 Separations.
    Altintas C, Keskin S.
    ACS Sustain Chem Eng; 2019 Jan 22; 7(2):2739-2750. PubMed ID: 30701144
    [Abstract] [Full Text] [Related]

  • 9. Evaluating CH4/N2 Separation Performances of Hundreds of Thousands of Real and Hypothetical MOFs by Harnessing Molecular Modeling and Machine Learning.
    Gulbalkan HC, Uzun A, Keskin S.
    ACS Appl Mater Interfaces; 2023 Dec 11. PubMed ID: 38082488
    [Abstract] [Full Text] [Related]

  • 10.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 11.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 12. Computational Screening of MOFs for Acetylene Separation.
    Nemati Vesali Azar A, Keskin S.
    Front Chem; 2018 Dec 11; 6():36. PubMed ID: 29536004
    [Abstract] [Full Text] [Related]

  • 13. Metal Exchange Boosts the CO2 Selectivity of Metal Organic Frameworks Having Zn-Oxide Nodes.
    Avci G, Altintas C, Keskin S.
    J Phys Chem C Nanomater Interfaces; 2021 Aug 12; 125(31):17311-17322. PubMed ID: 34413923
    [Abstract] [Full Text] [Related]

  • 14. Computational Screening of Metal-Organic Frameworks for Membrane-Based CO2/N2/H2O Separations: Best Materials for Flue Gas Separation.
    Daglar H, Keskin S.
    J Phys Chem C Nanomater Interfaces; 2018 Aug 02; 122(30):17347-17357. PubMed ID: 30093931
    [Abstract] [Full Text] [Related]

  • 15. Zr-MOFs for CF4/CH4, CH4/H2, and CH4/N2 separation: towards the goal of discovering stable and effective adsorbents.
    Demir H, Keskin S.
    Mol Syst Des Eng; 2021 Aug 02; 6(8):627-642. PubMed ID: 34381619
    [Abstract] [Full Text] [Related]

  • 16.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 17.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 18. Combination of High-Throughput Screening and Assembly to Discover Efficient Metal-Organic Frameworks on Kr/Xe Adsorption Separation.
    Du XM, Xiao ST, Wang X, Sun X, Lin YF, Wang Q, Chen GH.
    J Phys Chem B; 2023 Sep 28; 127(38):8116-8130. PubMed ID: 37725055
    [Abstract] [Full Text] [Related]

  • 19. Large-Scale Computational Screening of Metal Organic Framework (MOF) Membranes and MOF-Based Polymer Membranes for H2/N2 Separations.
    Azar ANV, Velioglu S, Keskin S.
    ACS Sustain Chem Eng; 2019 May 20; 7(10):9525-9536. PubMed ID: 31157127
    [Abstract] [Full Text] [Related]

  • 20. High-Throughput Screening of the CoRE-MOF-2019 Database for CO2 Capture from Wet Flue Gas: A Multi-Scale Modeling Strategy.
    Kancharlapalli S, Snurr RQ.
    ACS Appl Mater Interfaces; 2023 Jun 14; 15(23):28084-28092. PubMed ID: 37262369
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 11.