Literature DB >> 27627635

High-Throughput Screening of Metal-Organic Frameworks for CO2 Capture in the Presence of Water.

Song Li1, Yongchul G Chung2,3, Randall Q Snurr2.   

Abstract

Competitive coadsorption of water is a major problem in the deployment of adsorption-based CO2 capture. Water molecules may compete for adsorption sites, reducing the capacity of the material, and dehumidification prior to separating CO2 from N2 increases process complexity and cost. The development of adsorbent materials that can selectively adsorb CO2 in the presence of water would be a major step forward in the deployment of CO2 capture materials in practice. In this study, large-scale computational screening was carried out to search for metal-organic frameworks (MOFs) with high selectivity toward CO2 over H2O. Calculating framework charges for thousands of MOFs is a significant challenge, so initial screening used a fast, but approximate, charge calculation method. On the basis of the initial screening, 15 MOFs were selected, and Monte Carlo simulations were carried out to compute the adsorption isotherms for these MOFs using more accurate framework charges calculated by density functional theory. A detailed investigation was performed on the effect of using different methods for calculating partial charges, and it was found that electrostatic interactions contribute the majority of the adsorption energy of H2O in the selected MOFs.

Entities:  

Year:  2016        PMID: 27627635     DOI: 10.1021/acs.langmuir.6b02803

Source DB:  PubMed          Journal:  Langmuir        ISSN: 0743-7463            Impact factor:   3.882


  11 in total

1.  Modeling adsorption properties of structurally deformed metal-organic frameworks using structure-property map.

Authors:  WooSeok Jeong; Dae-Woon Lim; Sungjune Kim; Aadesh Harale; Minyoung Yoon; Myunghyun Paik Suh; Jihan Kim
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-10       Impact factor: 11.205

2.  High-Throughput Computational Screening of the Metal Organic Framework Database for CH4/H2 Separations.

Authors:  Cigdem Altintas; Ilknur Erucar; Seda Keskin
Journal:  ACS Appl Mater Interfaces       Date:  2018-01-18       Impact factor: 9.229

3.  Excavating hidden adsorption sites in metal-organic frameworks using rational defect engineering.

Authors:  Sanggyu Chong; Günther Thiele; Jihan Kim
Journal:  Nat Commun       Date:  2017-11-16       Impact factor: 14.919

4.  A deep neural network model for packing density predictions and its application in the study of 1.5 million organic molecules.

Authors:  Mohammad Atif Faiz Afzal; Aditya Sonpal; Mojtaba Haghighatlari; Andrew J Schultz; Johannes Hachmann
Journal:  Chem Sci       Date:  2019-07-09       Impact factor: 9.825

5.  Screening metal-organic frameworks for adsorption-driven osmotic heat engines via grand canonical Monte Carlo simulations and machine learning.

Authors:  Rui Long; Xiaoxiao Xia; Yanan Zhao; Song Li; Zhichun Liu; Wei Liu
Journal:  iScience       Date:  2020-12-09

6.  Effect of Metal-Organic Framework (MOF) Database Selection on the Assessment of Gas Storage and Separation Potentials of MOFs.

Authors:  Hilal Daglar; Hasan Can Gulbalkan; Gokay Avci; Gokhan Onder Aksu; Omer Faruk Altundal; Cigdem Altintas; Ilknur Erucar; Seda Keskin
Journal:  Angew Chem Int Ed Engl       Date:  2021-03-01       Impact factor: 15.336

7.  Fluorinated MIL-101 for carbon capture utilisation and storage: uptake and diffusion studies under relevant industrial conditions.

Authors:  Paola A Sáenz Cavazos; Mariana L Díaz-Ramírez; Elwin Hunter-Sellars; Sean R McIntyre; Enrique Lima; Ilich A Ibarra; Daryl R Williams
Journal:  RSC Adv       Date:  2021-04-12       Impact factor: 3.361

8.  Management of surgical mask waste to activated carbons for CO2 capture.

Authors:  Jarosław Serafin; Joanna Sreńscek-Nazzal; Adrianna Kamińska; Oliwia Paszkiewicz; Beata Michalkiewicz
Journal:  J CO2 Util       Date:  2022-03-13       Impact factor: 8.321

9.  Performance-Based Screening of Porous Materials for Carbon Capture.

Authors:  Amir H Farmahini; Shreenath Krishnamurthy; Daniel Friedrich; Stefano Brandani; Lev Sarkisov
Journal:  Chem Rev       Date:  2021-08-10       Impact factor: 60.622

10.  Ab Initio Evaluation of Henry Coefficients Using Importance Sampling.

Authors:  Steven Vandenbrande; Michel Waroquier; Veronique Van Speybroeck; Toon Verstraelen
Journal:  J Chem Theory Comput       Date:  2018-11-09       Impact factor: 6.006

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