Integrating Multiscale Simulation with Machine Learning to Screen and Design FIL@COFs for Ethane-Selective Separation-Reference-Cited by-同舟云学术

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Integrating Multiscale Simulation with Machine Learning to Screen and Design FIL@COFs for Ethane-Selective Separation

Published:2024-05-17 Issue:21 Volume:16 Page:27360-27367
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Cao Xiaohao¹²,Han Qi¹³,Han Rongmei¹³,Zhang Shitong¹³^ORCID,Wang Min¹³,Zhang Zhengqing¹³^ORCID,Zhong Chongli¹³^ORCID

Affiliation:

1. State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, P. R. China

2. School of Material Science and Engineering, Tiangong University, Tianjin 300387, P. R. China

3. School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, P. R. China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.4c03089

Reference42 articles.

1. Immobilization of Lewis Basic Sites into a Stable Ethane-Selective MOF Enabling One-Step Separation of Ethylene from a Ternary Mixture

2. Molecular insights into the role of O2 in reversed C2H6/C2H4 separation on metal–organic frameworks

3. Pore Size Reduction in Zirconium Metal–Organic Frameworks for Ethylene/Ethane Separation

4. Cage-Interconnected Metal–Organic Framework with Tailored Apertures for Efficient C2H6/C2H4 Separation under Humid Conditions

5. Recent advances in adsorptive separation of ethane and ethylene by C2H6-selective MOFs and other adsorbents

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