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Journal Abstract Search

318 related items for PubMed ID: 36312414

  • 1. Computational Screening of Metal-Organic Frameworks for Ammonia Capture from H2/N2/NH3 Mixtures.
    Zhu Z, Wang H, Wu XY, Luo K, Fan J.
    ACS Omega; 2022 Oct 25; 7(42):37640-37653. PubMed ID: 36312414
    [Abstract] [Full Text] [Related]

  • 2. In Silico Screening of Metal-Organic Frameworks for Formaldehyde Capture with and without Humidity by Molecular Simulation.
    Li W, Liang T, Lin Y, Wu W, Li S.
    Int J Mol Sci; 2022 Nov 08; 23(22):. PubMed ID: 36430151
    [Abstract] [Full Text] [Related]

  • 3. High-throughput computational screening of hypothetical metal-organic frameworks with open copper sites for CO2/H2 separation.
    Li M, Cai W, Wang C, Wu X.
    Phys Chem Chem Phys; 2022 Aug 10; 24(31):18764-18776. PubMed ID: 35903942
    [Abstract] [Full Text] [Related]

  • 4. Computational investigation of multifunctional MOFs for adsorption and membrane-based separation of CF4/CH4, CH4/H2, CH4/N2, and N2/H2 mixtures.
    Demir H, Keskin S.
    Mol Syst Des Eng; 2022 Nov 28; 7(12):1707-1721. PubMed ID: 36561661
    [Abstract] [Full Text] [Related]

  • 5. Identifying UiO-67 Metal-Organic Framework Defects and Binding Sites through Ammonia Adsorption.
    Swaroopa Datta Devulapalli V, McDonnell RP, Ruffley JP, Shukla PB, Luo TY, De Souza ML, Das P, Rosi NL, Karl Johnson J, Borguet E.
    ChemSusChem; 2022 Jan 10; 15(1):e202102217. PubMed ID: 34725931
    [Abstract] [Full Text] [Related]

  • 6. 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]

  • 7. Tunable Ammonia Adsorption within Metal-Organic Frameworks with Different Unsaturated Metal Sites.
    Zhang D, Shen Y, Ding J, Zhou H, Zhang Y, Feng Q, Zhang X, Chen K, Wang J, Chen Q, Zhang Y, Li C.
    Molecules; 2022 Nov 14; 27(22):. PubMed ID: 36431945
    [Abstract] [Full Text] [Related]

  • 8. High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures.
    Ercakir G, Aksu GO, Keskin S.
    J Chem Phys; 2024 Feb 28; 160(8):. PubMed ID: 38415834
    [Abstract] [Full Text] [Related]

  • 9. Halogen-Decorated Metal-Organic Frameworks for Efficient and Selective CO2 Capture, Separation, and Chemical Fixation with Epoxides under Mild Conditions.
    Karmakar A, Santos AACD, Pagliaricci N, Pires J, Batista M, Alegria ECBA, Martin-Calvo A, Gutiérrez-Sevillano JJ, Calero S, Guedes da Silva MFC, Pettinari R, Pombeiro AJL.
    ACS Appl Mater Interfaces; 2024 Apr 11. PubMed ID: 38605636
    [Abstract] [Full Text] [Related]

  • 10. Anchoring LiCl in the Nanopores of Metal-Organic Frameworks for Ultra-High Uptake and Selective Separation of Ammonia.
    Shi Y, Wang Z, Li Z, Wang H, Xiong D, Qiu J, Tian X, Feng G, Wang J.
    Angew Chem Int Ed Engl; 2022 Nov 21; 61(47):e202212032. PubMed ID: 36180385
    [Abstract] [Full Text] [Related]

  • 11. High-Throughput Screening of MOF Adsorbents and Membranes for H2 Purification and CO2 Capture.
    Avci G, Velioglu S, Keskin S.
    ACS Appl Mater Interfaces; 2018 Oct 03; 10(39):33693-33706. PubMed ID: 30193065
    [Abstract] [Full Text] [Related]

  • 12. In Silico Screening of Metal-Organic Frameworks and Zeolites for He/N2 Separation.
    Grenev IV, Gavrilov VY.
    Molecules; 2022 Dec 20; 28(1):. PubMed ID: 36615216
    [Abstract] [Full Text] [Related]

  • 13. Tailoring ammonia capture in MOFs and COFs: A multi-scale and machine learning comprehensive investigation of functional group modification.
    Stavroglou GK, Tylianakis E, Froudakis GE.
    Chemphyschem; 2024 Apr 02; 25(7):e202300721. PubMed ID: 38446052
    [Abstract] [Full Text] [Related]

  • 14. Solvent-Directed Construction of a Nanoporous Metal-Organic Framework with Potential in Selective Adsorption and Separation of Gas Mixtures Studied by Grand Canonical Monte Carlo Simulations.
    Salimi S, Akhbari K, Farnia SMF, Tylianakis E, Froudakis GE, White JM.
    Chempluschem; 2024 Jan 02; 89(1):e202300455. PubMed ID: 37864516
    [Abstract] [Full Text] [Related]

  • 15. Computational Characterization of Zr-Oxide MOFs for Adsorption Applications.
    Oktavian R, Schireman R, Glasby LT, Huang G, Zanca F, Fairen-Jimenez D, Ruggiero MT, Moghadam PZ.
    ACS Appl Mater Interfaces; 2022 Dec 28; 14(51):56938-56947. PubMed ID: 36516445
    [Abstract] [Full Text] [Related]

  • 16. 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]

  • 17. A Combined Experimental and Computational Study on the Adsorption Sites of Zinc-Based MOFs for Efficient Ammonia Capture.
    Zhang D, Shen Y, Ding J, Zhou H, Zhang Y, Feng Q, Zhang X, Chen K, Xu P, Zhang P.
    Molecules; 2022 Aug 31; 27(17):. PubMed ID: 36080380
    [Abstract] [Full Text] [Related]

  • 18. Machine learning potential for modelling H2 adsorption/diffusion in MOFs with open metal sites.
    Liu S, Dupuis R, Fan D, Benzaria S, Bonneau M, Bhatt P, Eddaoudi M, Maurin G.
    Chem Sci; 2024 Apr 03; 15(14):5294-5302. PubMed ID: 38577379
    [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. 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]

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