In silico discovery of metal-organic frameworks for precombustion CO 2 capture using a genetic algorithm-Reference-Cited by-同舟云学术

In silico discovery of metal-organic frameworks for precombustion CO 2 capture using a genetic algorithm

Published:2016-10-07 Issue:10 Volume:2 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Chung Yongchul G.¹,Gómez-Gualdrón Diego A.¹²,Li Peng³^ORCID,Leperi Karson T.¹^ORCID,Deria Pravas³^ORCID,Zhang Hongda¹,Vermeulen Nicolaas A.³,Stoddart J. Fraser³,You Fengqi¹^ORCID,Hupp Joseph T.³,Farha Omar K.³⁴,Snurr Randall Q.¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA.

2. Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, CO 80401, USA.

3. Department of Chemistry, Northwestern University, Evanston, IL 60208, USA.

4. Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah 22254, Saudi Arabia.

Abstract

A genetic algorithm was used to accelerate the computational discovery of new nanoporous materials for capturing CO 2 .

Funder

U.S. Department of Energy

King Abdulaziz City for Science and Technology

Northwestern University

Stanford University

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference66 articles.

1. J. Wilcox Carbon Capture (Springer 2012).

2. B. Smit J. A. Reimer C. M. Oldenburg I. C. Bourg Introduction to Carbon Capture and Sequestration (Imperial College Press 2014).

3. 2015 Paris agreement under the United Nations framework convention on climate change; http://ec.europa.eu/clima/policies/international/negotiations/paris.

4. Persistent growth of CO2 emissions and implications for reaching climate targets;Friedlingstein P.;Nat. Geosci.,2014

5. Purification of hydrogen by pressure swing adsorption;Sircar S.;Sep. Sci. Technol.,2000

Cited by 244 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combining machine learning and molecular simulation to explore MOF materials that contribute to CF4/N2 separation;Inorganic Chemistry Communications;2024-10

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

3. Metal–Organic Framework Stability in Water and Harsh Environments from Data-Driven Models Trained on the Diverse WS24 Data Set;Journal of the American Chemical Society;2024-07-10

4. Efficient Removal of Greenhouse Gases: Machine Learning-Assisted Exploration of Metal–Organic Framework Space;ACS Nano;2024-07-01

5. Porous Cu-BTC Metal–Organic Frameworks Anchored on Dialdehyde Wood Sponge as Material for CO₂ Capture and Separation;ACS Applied Nano Materials;2024-06-15