化学学报 ›› 2018, Vol. 76 ›› Issue (4): 303-310.DOI: 10.6023/A18010026 上一篇    下一篇

研究论文

基于高通量计算筛选的金属有机骨架材料甲醛吸附性能

卞磊a,b, 李炜a,b, 魏振振a,b, 刘晓威a,b, 李松a,b   

  1. a 华中科技大学 能源与动力工程学院 煤燃烧国家重点实验室 武汉 430074;
    b 深圳华中科技大学研究院 深圳 518057
  • 收稿日期:2018-01-16 出版日期:2018-04-15 发布日期:2018-03-23
  • 通讯作者: 李松 E-mail:songli@hust.edu.cn
  • 基金资助:

    项目受国家自然科学基金(No.51606081)和深圳市基础研究项目基金(No.JCYJ20160506170043770)资助.

Formaldehyde Adsorption Performance of Selected Metal-Organic Frameworks from High-throughput Computational Screening

Bian Leia,b, Li Weia,b, Wei Zhenzhena,b, Liu Xiaoweia,b, Li Songa,b   

  1. a State Key Laboratory of Coal Combustion, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074;
    b Shenzhen Research Institute of Huazhong University of Science and Technology, Shenzhen 518057
  • Received:2018-01-16 Online:2018-04-15 Published:2018-03-23
  • Contact: 10.6023/A18010026 E-mail:songli@hust.edu.cn
  • Supported by:

    Project supported by the National Natural Science Foundation of China (No. 51606081) and Basic Research Foundation of Shenzhen (No. JCYJ20160506170043770).

随着大量新型金属有机骨架(MOFs)吸附材料的出现,传统“试错式”的甲醛吸附剂研究方法具有效率低、周期长、成本高等问题.为实现高性能甲醛净化MOFs的快速研发,采用基于巨正则蒙特卡洛模拟(GCMC)的高通量计算筛选方法对2932种MOFs材料进行了甲醛吸附性能的快速评价.基于高通量计算筛选结果,我们挑选并制备出Y-BTC、ZnCar和Ni-BIC等3种对甲醛有较高吸附量的吸附剂,并采用粉末X射线衍射(PXRD)、比表面积分析(BET)对材料进行了表征.通过甲醛吸附实验,明确了筛选出的MOFs以及参照材料(Cu-BTC、活性炭)在甲醛初始浓度为100 mg/m3条件下的甲醛吸附量分别为0.38、0.25、0.11、0.08、0.06 mol/kg.同时,筛选出的吸附剂还具有良好的甲醛吸附循环利用性能.该结果表明筛选出的Y-BTC、ZnCar和Ni-BIC的甲醛吸附量均高于Cu-BTC和活性炭等参照吸附剂,证明了高通量计算筛选方法在指导甲醛吸附材料开发方面的有效性.

关键词: 金属有机骨架, 高通量计算筛选, 甲醛吸附, 蒙特卡洛分子模拟, 可再生性能

With the rapidly increasing number of reported metal-organic frameworks (MOFs), conventional trial-and-error method is obviously not applicable to the development of high-performance MOFs for formaldehyde adsorption, due to its low efficiency, high cost and long developing period. Thus, high-throughput computational screening (HTCS) strategy based on grand canonical Monte Carlo (GCMC) simulation is proposed to quickly explore the top-performing MOFs with high adsorption capability towards formaldehyde. In this work, the computation-ready experimental (CoRE)-MOF database consisting of 2932 MOF structures carrying density derived electrostatic and chemical (DDEC) charges obtained from density function (DFT) theory calculations, were employed in high-throughput GCMC simulations for formaldehyde adsorption from the air. The structure-property relationship from HTCS revealed that the MOF candidates with high formaldehyde uptakes exhibited small pore sizes, relatively high selectivity and moderate heat of adsorption (Qst). Afterwards, the top MOFs with both high uptake and selectivity towards formaldehyde were chosen for further experimental evaluation. Three selected MOFs Y-BTC, ZnCar and Ni-BIC were successfully synthesized and characterized by powder X-ray diffraction (PXRD) and BET surface area analysis. In order to validate our HTCS strategy, the representative Cu-BTC and activated carbon (AC) were also adopted as controls. The formaldehyde adsorption test was performed in a sealed container with the formaldehyde concentration of 100 mg/m3 at 298 K. After 24 h adsorption, the formaldehyde uptakes of the adsorbents were obtained according to the concentration changes prior to and after formaldehyde exposure by UV-vis spectrometer. It was found that the adsorption capacities of Y-BTC, ZnCar and Ni-BIC were 0.38, 0.25 and 0.11 mol/kg, respectively, which were remarkably higher than Cu-BTC (0.08 mol/kg) and AC (0.06 mol/kg). The recyclability of the best performer Y-BTC was also verified. These findings open up the possibility of employing HTCS strategy for highly efficient exploration of MOF adsorbents for formaldehyde removal.

Key words: metal-organic frameworks, high-throughput computational screening, formaldehyde adsorption, grand canonical Monte Carlo simulations, recyclability