金属-有机骨架材料CO<sub>2</sub>捕获性能的大规模计算筛选

王磊; 方桂英; 阳庆元

doi:10.11949/j.issn.0438-1157.20181079

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金属-有机骨架材料CO₂捕获性能的大规模计算筛选

材料化学工程与纳米技术 | 更新时间：2026-07-24

- 金属-有机骨架材料CO₂捕获性能的大规模计算筛选
- Performance of metal-organic frameworks for CO₂ capture from large-scale computational screening
- 化工学报 2019年70卷第3期页码：1135-1143
- 作者机构：
  
  1.北京化工大学有机无机复合材料国家重点实验室，北京 100029
  2.江西农业大学理学院，江西南昌 330045
- 作者简介：
  
  王磊（1993—），男，硕士研究生，evacolin@163.com
  方桂英（1964—），女，学士，副教授，guiyingfang1012@163.com
  阳庆元（1976—），男，博士，教授，qyyang@mail.buct.edu.cn
- 基金信息：
  
  国家重大基础研究计划项目(2016YFA0201701);中央高校基本科研业务费专项资金(buctrc201727)
- DOI：10.11949/j.issn.0438-1157.20181079
  中图分类号： TQ 028.8
- 收稿：2018-09-26，
  
  修回：2018-12-10，
  
  网络首发：2026-07-24，
  
  纸质出版：2019-03-05
- 稿件说明：
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王磊, 方桂英, 阳庆元. 金属-有机骨架材料CO₂捕获性能的大规模计算筛选[J]. 化工学报, 2019, 70(3): 1135-1143 DOI: 10.11949/j.issn.0438-1157.20181079.

WANG Lei, FANG Guiying, YANG Qingyuan. Performance of metal-organic frameworks for CO₂ capture from large-scale computational screening[J]. CIESC Journal, 2019, 70(3): 1135-1143 DOI: 10.11949/j.issn.0438-1157.20181079.
王磊, 方桂英, 阳庆元. 金属-有机骨架材料CO₂捕获性能的大规模计算筛选[J]. 化工学报, 2019, 70(3): 1135-1143 DOI: 10.11949/j.issn.0438-1157.20181079. DOI：

WANG Lei, FANG Guiying, YANG Qingyuan. Performance of metal-organic frameworks for CO₂ capture from large-scale computational screening[J]. CIESC Journal, 2019, 70(3): 1135-1143 DOI: 10.11949/j.issn.0438-1157.20181079. DOI：

摘要

全球性温室效应形势的日趋严重，迫切需要研究和开发可用于CO

捕集的高性能材料。对于含有双铜船桨型片段(Cu

(COO)

)的MOF材料，因其结构中含有配位不饱和的Cu金属位点，在低压区域的CO

捕获方面展现出优异的性能。目前，大规模计算筛选工作主要是基于传统的分子力场，无法对此类Cu-MOFs中主客体分子间的相互作用进行准确描述。基于量化计算获得的精确分子力场，利用Monte Carlo分子模拟方法考察了常温常压条件下763个基于Cu-OMS的MOF材料对CO

存储和CO

的分离行为。不仅筛选出潜在的高性能材料，而且揭示出了材料的结构与其性能之间的关系和具有优良性能的材料结构特征，可为面向特定应用的新材料设计和合成提供理论参考。

Abstract

The global greenhouse effect situation is becoming more and more serious

and there is an urgent need to research and develop high-performance materials that can be used for CO

capture. Metal‒organic frameworks (MOFs) containing an inorganic unit of copper paddle-wheel (Cu

(COO)

) have excellent performance in CO

capture in low pressure region because of their coordinatively unsaturated Cu sites. However

large-scale computational screening work available so far mainly used conventional molecular force field

which cannot accurately describe the host-guest molecules involved in current study. Thus

on the basis of accurate molecular force fields derived from quantum mechanics calculations

grand canonical Monte Carlo simulation method was adopted to investigate CO

storage and CO

separation behaviors of 763 MOFs with Cu-OMS under ambient conditions. Not only were promising MOFs found through large-scale screening

but the established structure-performance relationships and the structural characteristics of high-performance materials were revealed

providing a theoretical foundation for design and synthesis of new materials for targeted applications.

关键词

Keywords

references

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金属-有机骨架材料CO2捕获性能的大规模计算筛选

Performance of metal-organic frameworks for CO2 capture from large-scale computational screening

DOI：10.11949/j.issn.0438-1157.20181079

摘要

Abstract

关键词

Keywords

references

金属-有机骨架材料CO₂捕获性能的大规模计算筛选

Performance of metal-organic frameworks for CO₂ capture from large-scale computational screening