High‐throughput computational screening of porous polymer networks for natural gas sweetening based on a neural network-Reference-Cited by-同舟云学术

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High‐throughput computational screening of porous polymer networks for natural gas sweetening based on a neural network

Published:2021-09-20 Issue:1 Volume:68 Page:
ISSN:0001-1541
Container-title:AIChE Journal
language:en
Short-container-title:AIChE Journal

Author:

Lu Xiuyang¹,Wu Yujing¹,Wu Xuanjun¹,Cao Zhixiang¹,Wei Xionghui²,Cai Weiquan³⁴

Affiliation:

1. School of Chemistry, Chemical Engineering and Life Sciences Wuhan University of Technology Wuhan China

2. College of Chemistry and Molecular Engineering Peking University Beijing China

3. School of Chemistry and Chemical Engineering Guangzhou University Guangzhou China

4. School of Materials Science and Engineering Zhengzhou University Zhengzhou China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aic.17433

Reference52 articles.

1. Highly selective separation of H2S and CO2 using a H2S-imprinted polymers loaded on a polyoxometalate@Zr-based metal–organic framework with a core–shell structure at ambient temperature

2. Identifying Optimal Zeolitic Sorbents for Sweetening of Highly Sour Natural Gas

3. Analysis of sulfur poisoning on a PEM fuel cell electrode

4. Highly reversible sorption of H2S and CO2 by an environmentally friendly Mg-based MOF

5. The chemistry of metal–organic frameworks for CO2 capture, regeneration and conversion

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