High-Throughput Screening of the CoRE-MOF-2019 Database for CO<sub>2</sub> Capture from Wet Flue Gas: A Multi-Scale Modeling Strategy-Reference-Cited by-同舟云学术

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High-Throughput Screening of the CoRE-MOF-2019 Database for CO₂ Capture from Wet Flue Gas: A Multi-Scale Modeling Strategy

Published:2023-06-01 Issue:23 Volume:15 Page:28084-28092
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Kancharlapalli Srinivasu¹²³^ORCID,Snurr Randall Q.¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States

2. Theoretical Chemistry Section, Chemistry Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085, India

3. Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094, India

Funder

United States - India Educational Foundation

Institute of International Education

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.3c04079

Reference70 articles.

1. Powering the planet: Chemical challenges in solar energy utilization

2. The role of CO2 capture and utilization in mitigating climate change

3. Recent developments in first-principles force fields for molecules in nanoporous materials

4. Hydrogen energy systems: A critical review of technologies, applications, trends and challenges

5. Cutting the cost of carbon capture: a case for carbon capture and utilization

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1. Computational prediction of MOFs with the potential to improve the efficiency of industrial CO2 capture;Separation and Purification Technology;2025-02

2. Cu-based metal-organic framework with dual open metal sites for efficient separation of CO2 from flue gas;Journal of Solid State Chemistry;2024-11

3. How the planarity of two dimensional covalent organic frameworks affect gas adsorption and diffusion: A data mining, simulation, and experiment united study;AIChE Journal;2024-08-28

4. Computational and Machine Learning Methods for CO₂ Capture Using Metal–Organic Frameworks;ACS Nano;2024-08-22

5. Computational Simulations of Metal–Organic Frameworks to Enhance Adsorption Applications;Advanced Materials;2024-07-27

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