高通量筛选金属-有机框架:分离天然气中的硫化氢和二氧化碳  

High-Throughput Screening of Metal-Organic Frameworks for the Separation of Hydrogen Sulfide and Carbon Dioxide from Natural Gas

作　　者：杨文远 梁红 乔智威 Yang Wenyuan;Liang Hong;Qiao Zhiwei(Guangzhou Key Laboratory for New Energv and Green Catalysis,School of Chemistry and Chemical Engineering,Guangzhou University,Guangzhou 510006,China)

机构地区：[1]广州大学化学化工学院能源与催化研究所,广州510006

出　　处：《化学学报》2018年第10期785-792,共8页Acta Chimica Sinica

基　　金：国家自然科学基金(Nos.21676094和21576058)资助~~

摘　　要：采用分子模拟高通量筛选的方法研究了6013种实验已经合成的金属-有机框架(MOFs)对天然气五元混合物(CH_4,C_2H_6,C_3H_8,H_2S和CO_2)中H_2S和CO_2的吸附分离性能.为了综合吸附量和选择性这两项指标,我们首先比较了三种权衡方法[权衡α法(Tradeoff between S_(H_2S+CO_2/C1-C3_ and N_(H_2S+CO_2), TSN),标准值法(Standard normal method, SNM)和权衡β法(Tradeoff between selectivity and capacity, TSC)].接着,针对四种MOF描述符[最大孔径(LCD),孔隙率(φ),比表面积(VSA)和吸附热(Q_(st)~0)],通过Pearson相关系数分析了每种描述符分别对三种权衡变量的相关性,结果显示TSC法与四种MOF描述符的相关性最佳.然后,使用多元线性回归方法定量地分析了四种MOF描述符分别对TSC的影响程度;而决策树模型则被用于规划性能高效MOFs的设计路径.最后, 20种性能最优MOFs从数据库中脱颖而出,它们将为净化天然气技术的发展提供坚实的理论指导.In this work, the adsorption performance of 6013 computation-ready, experimental metal-organic frameworks（Co RE-MOFs） for the capture of H2 S and CO2 from natural gas mixture（CH4, C2 H6, C3 H8, H2 S and CO2） is calculated by high-throughput screening of grand canonical Monte Carlo（GCMC） simulation in 298 K and 10 bar. For the comprehensive consideration of both adsorption capacities and selectivities of H2 S＋CO2, first, we compare three different tradeoff methods（α tradeoff method（Tradeoff between S（H2 S＋CO2/C1-C3） and N（H2 S＋CO2）, TSN）, standard normal method（SNM）, β tradeoff method（Tradeoff between selectivity and capacity, TSC））. The effect of selectivity on the new tradeoff variables are appropriately reduced by these tradeoff methods, because some of selectivities are very high. Thus, the new tradeoff variables can comprehensively evaluate the adsorption performance of CoRE-MOFs. Moreover, the correlation of each MOF descriptor（including the largest cavity diameter（LCD）, void fraction（φ）, surface area（VSA） and isosteric heat（Q（st）~0）） with three tradeoff variables are analyzed by Pearson correlation coefficient, respectively. The LCDs are calculated by Zeo＋＋ software, but the φ and VSA are simulated by RASPA using probes of He and N2, respectively. The Q（st）~0 of each adsorbate gas are calculated at infinite dilution condition using NVT-MC method. All GCMC simulations for the screening are carried out using RASPA software. The results show that TSC has the best correlation with four MOF descriptors and the linear model could sufficiently describe the relationship between TSC and four MOF descriptors. Pearson correlation coefficients of four descriptors were-0.613,-0.717,-0.673 and 0.536 on TSC, respectively. Multiple linear regression is applied to quantitatively determine the influencing degree of four descriptors on performance, respectively. Among the four descriptors, Q（st）~0, ？, and LCD have larger standardized regressio

关 键 词：分子模拟 金属-有机框架 吸附 H2S CO2 

分 类 号：TE645[石油与天然气工程—油气加工工程]