衍生多孔碳材料在固相微萃取中的应用研究进展

固相微萃取是一种集采样、萃取、富集和进样于一体的样品前处理技术,其萃取效果与涂层材料密切相关。多孔碳材料具有比表面积大、多孔结构可控、活性位点多和化学稳定性好等优点,广泛应用于电池、超级电容器、催化、吸附和分离等领域,也是一种热门的用作固相微萃取探针的涂层材料。衍生多孔碳材料因种类丰富、可设计性强被广泛研究,研究主要集中在对衍生多孔碳材料的结构优化方面。但是衍生多孔碳材料在固相微萃取中的应用还存在如下问题:(1)共价有机框架衍生多孔碳材料的制备已取得较大进展,但将其应用于固相微萃取领域的研究仍较少;(2)有待进一步明确制备出的衍生多孔碳材料用作固相微萃取涂层表现出优异提取能力的机理;(3)有待进一步深入研究将衍生多孔碳材料用作固相微萃取涂层以实现对不同物理化学性质污染物的广谱高灵敏度分析。文章综述了近3年衍生多孔碳材料在固相微萃取中的应用研究,并展望了未来衍生多孔碳材料在固相微萃取中的研究前景。引用文献共56篇,主要来源于Elsevier。     

面向丙烯/丙烷吸附分离的金属有机骨架材料的高通量计算筛选

丙烯、丙烷作为分子尺寸相近的共沸物,其分离一直是化工领域研究热点。金属有机骨架(MOFs)材料因其高度可调的孔道结构,在丙烯/丙烷分离应用上已展现出诱人潜能。本文基于Core MOF 2019数据库,采用巨正则蒙特卡洛基高通量计算筛选技术,获得了分离性优异的MOFs结构,发现其拥有适中的丙烯吸附量和较弱的丙烷吸附能力,且骨架孔径为3.70～4.10?、孔隙率中等(0.35～0.44),并揭示了孔道中心吸附位的选择性与丙烯/丙烷分离系数间关系。本研究阐明了高丙烯/丙烷分离性的骨架材料的结构和性能特征,为设计MOFs实现丙烯/丙烷的高效分离提供理论指导和数据支撑。     

Vapor-assisted epitaxial growth of porphyrin-based MOF thin film for nonlinear optical limiting

Fabrication of metal-organic frameworks(MOFs) thin films has been an efficient way to expand their functionalities and applications. Here, we use the vapor-assisted deposition(VAD) method to epitaxially grow a porphyrin-based MOF PCN-222 film. That is, vapor source assists to deposit pre-treated precursor solution on quartz substrate to form a continuous PCN-222 film. Furthermore, utilizing the post-treated encapsulation of functional carbon-based nanoparticles, the carbon nanodots(CND)and Pt doped CND(Pt/CND) are well loaded into the pores of PCN-222 film, the size(～3.1 nm) of which is highly close to the pore size of the corresponding MOF(～3.7 nm). The Z-scan results reveal that PCN-222 film exhibits high reverse saturable absorption. In addition, encapsulation of carbon based nanodots into PCN-222 film could enhance the nonlinear optical limiting effect benefiting from the host-guest combination. This study serves to present both the available toolbox of thin film preparation and high potential for precise synthetic nanocomposite films in optical limiting devices.     

Separation and molecular-level segregation of complex alkane mixtures in metal-organic frameworks

In this computational work we explore metal-organic frameworks (MOFs) for separating alkanes according to the degree of branching. We show that the structure MOF-1 shows an adsorption hierarchy for a 13-component light naphtha mixture precisely as desired for increasing the research octane number of gasoline. In addition we report an unusual molecular-level segregation of molecules based on their degree of branching.     

Free energy landscapes for the thermodynamic understanding of adsorption-induced deformations and structural transitions in porous materials

Soft porous crystals are flexible metal-organic frameworks that respond to physical stimuli such as temperature, pressure, and gas adsorption by large changes in their structure and unit cell volume. While they have attracted a lot of interest, molecular simulation methods that directly couple adsorption and large structural deformations in an efficient manner are still lacking. We propose here a new Monte Carlo simulation method based on non-Boltzmann sampling in (guest loading, volume) space using the Wang-Landau algorithm, and show that it can be used to fully characterize the adsorption properties and the material's response to adsorption at thermodynamic equilibrium. We showcase this new method on a simple model of the MIL-53 family of breathing materials, demonstrating its potential and contrasting it with the pitfalls of direct, Boltzmann simulations. We furthermore propose an explanation for the hysteretic nature of adsorption in terms of free energy barriers between the two metastable host phases.     

Liquid-phase adsorption on metal-organic frameworks

This work is focusing on the potential application of metal-organic frameworks as porous materials in heterogeneous catalysis where the substrate is in solution. The understanding of such a liquid-phase heterogeneous catalytic process requires adsorption equilibrium data in solution. For this purpose several metal-organic frameworks were synthesized as reference materials and tested as adsorbents for the adsorption of substrate molecules such as styrene or ethylcinnamate from the liquid phase. The adsorption capacity strongly depends on the polarity of the substrate with respect to the solvent. In several instances solvent and polarity effects are heavily superimposed on the pore size effects. Adsorption isotherms, rates and hydrogenation of the substrates are reported and discussed.     

Synthesis and modification of spherical/hollow metal-organic frameworks for efficient extraction of sulfonamides in aqueous environments

In this study, two novel spherical/hollow metal-organic frameworks were successfully synthesized, and further modified by a mild non-covalent modification strategy with dopamine and 1,4-benzenedithiol(BDT) as polymeric monomers to obtain pB DT@PDA-Ni-MOF and p BDT@PDA-Ni/Co-MOF, respectively. The results showed that the above MOFs possessed extremely fast adsorption rates and ideal adsorption capacities for sulfonamides(SAs) and the modified MOFs exhibited enhanced adsorption capacities for SAs ...     

固相萃取吸附材料在植物激素样品前处理中的应用新进展

植物激素在植物生长过程中具有重要作用,调节植物生长、发育及抗逆的各个过程。植物激素超微精准定量分析一直是植物生理学研究的瓶颈问题。植物激素的准确、高效检测目前大多是基于液相色谱-串联质谱联用技术。样品前处理是植物激素色谱-质谱分析中必不可少的一个步骤,直接影响后续检测方法的灵敏度和准确性。在植物激素各种前处理方法中,固相萃取(SPE)技术应用非常广泛。在萃取小柱基础上发展了多种新形式(分散固相萃取、磁性固相萃取、固相微萃取等,称之为SPE相关方法)。在上述SPE相关方法中,吸附材料的选择均是关键因素,决定了样品前处理过程的目标物提取、净化和富集效果。碳基材料(包括碳纳米管、石墨烯、碳氮化合物等)和有机骨架材料(包括金属有机骨架、共价有机材料)拥有结构可设计、比表面积大、稳定性良好等特性,非常适合作为吸附材料。分子印迹聚合物和超分子化合物依靠主-客体特异性分子识别作用,能显著提高样品前处理方法的选择性。本文重点针对植物激素样品前处理中的SPE技术,综述了近5年来上述几类功能化吸附材料的最新应用进展,并对其发展趋势进行展望。     

Present and Perspectives of Photoactive Porous Composites Based on Semiconductor Nanocrystals and Metal-Organic Frameworks

This review focuses on the recent developments in synthesis, properties, and applications of a relatively new family of photoactive porous composites, integrated by metal halide perovskite (MHP) nanocrystals and metal-organic frameworks (MOFs). The synergy between the two systems has led to materials (MHP@MOF composites) with new functionalities along with improved properties and phase stability, thus broadening their applications in multiple areas of research such as sensing, light-harvesting solar cells, light-emitting device technology, encryption, and photocatalysis. The state of the art, recent progress, and most promising routes for future research on these photoactive porous composites are presented in the end.     

Homochiral 3D lanthanide coordination networks with an unprecedented 4(9)6(6) topology

Homochiral 3D metal-organic open frameworks based on enantiopure atropisomeric dicarboxylic acid bridging ligands and dilanthanide secondary building units exhibit an unprecedented 4(9)6(6) topology, and possess ethoxy-protected BINOL functionalities that are pointing toward the open channels.     

Infusion of Variable Chemical Structure to Tune Stacking among Metal-Organic Layers in 2D Nano MOF

Thickness of two-dimensional (2D) metal-organic frameworks (MOFs) govern their intriguing functionalities. Primarily this thickness is controlled by the stacking between the metal-organic layers (MOL). It is observed that until now such modulating factors for stacking efficiency of MOL are not well studied. Here, we report a fundamental hypothesis to comprehend regulation of stacking efficiency among MOLs as a function of chemical structure of organic ligands (dicarboxylic acids and pillar linkers). This basically involves a series of isostructural three-dimensional (3D) MOFs which contain linkers of variable chemical nature that could be depillared to generate 2D stacked MOFs of different thickness. Depending on the linkers, we encountered the formation of single MOL to stacked multiple MOLs as evidenced from atomic force microscopic and other experimental analysis. The present study gives a concrete correlation between the stacking within 2D MOFs (from monolayer to multilayers), and their 3D counter parts, which may provide a thickness tuning pathway for 2D MOFs.     

Two-dimensional Covalent Organic Frameworks for Electrochromic Switching

The electrochromic materials have received immense attention for the fabrication of smart optoelectronic devices. The alteration of the redox states of the electroactive functionalities results in the color change in response to electrochemical potential. Even though transition metal oxides, redox-active small organic molecules, conducting polymers, and metallopolymers are known for electrochromism, advanced materials demonstrating multicolor switching with fast response time and high durability are of increasing demand. Recently, two-dimensional covalent organic frameworks (2D COFs) have been demonstrated as electrochromic materials due to their tunable redox functionalities with highly ordered structure and large specific surface area facilitating fast ion transport. Herein, we have discussed the mechanistic insights of electrochromism in 2D COFs and their structure-property relationship in electrochromic performance. Furthermore, the state-of-the-art knowledge for developing the electrochromic 2D COFs and their potential application in next-generation display devices are highlighted.     

Surface,Interface and Structure Optimization of Metal-Organic Frameworks: Towards Efficient Resourceful Conversion of Industrial Waste Gases

Industrial waste gas emissions from fossil fuel over-exploitation have aroused great attention in modern society. Recently, metal-organic frameworks (MOFs) have been developed in the capture and catalytic conversion of industrial exhaust gases such as SO₂, H₂S, NO_x, CO₂, CO, etc. Based on these resourceful conversion applications, in this review, we summarize the crucial role of the surface, interface, and structure optimization of MOFs for performance enhancement. The main points include (1) adsorption enhancement of target molecules by surface functional modification, (2) promotion of catalytic reaction kinetics through enhanced coupling in interfaces, and (3) adaptive matching of guest molecules by structural and pore size modulation. We expect that this review will provide valuable references and illumination for the design and development of MOF and related materials with excellent exhaust gas treatment performance.     

Recent Progress of Atmospheric Water Harvesting Using Metal-Organic Frameworks

Atmospheric water harvesting based on vapor adsorption is a newly emerged and potential technology to supply portable water for arid areas.To efficiently harvest vapor from the air,sorbents are required to have conside-rable adsorption capacity,easy regeneration and high stability.With the advantages of porous structure,tunable pore size and tailorable hydrophilicity,metal-organic frameworks(MOFs)have demonstrated excellent performance in vapor adsorption and water generation.In this review,we first discuss the degradation mechanisms of MOFs exposed to water and summarize the structure-stability relationship;by centering on the adsorption isotherms,the connection between the structure of MOFs and the water adsorption property is illuminated;finally,some prospects are suggested in order to push forward the progress of this technology.     

Adsorption properties of the MOF-5 metal-organic framework in relation to water and benzene

Adsorption properties of synthesized metal-organic frameworks based on 1,4-dicarboxylate ligands and zinc ions were studied. It was shown that the adsorption properties of these metal-organic frameworks in relation to water and benzene are much higher than those for the known adsorbents: KT-1 and KT-2 coals, USY and ZSM-5 zeolites, and pentasil.     

多孔金属有机框架的组装与性能研究进展

对多孔金属有机框架的组装及其对气体的吸附性能的研究进展进行了评述,并对磁性和手性多孔金属有机框架进行了介绍.     

稀土金属-有机框架在同分异构体传感材料中的应用

基于稀土金属离子独特的电子结构,稀土金属-有机框架的光致发光具有发射峰尖锐、量子产率高和发光寿命长等特点,可应用于针对特定功能化学物种的光学传感材料.稀土金属离子高的配位数和丰富的配位模式,使得稀土金属-有机框架具有结构多样性和可调性,可与不同的化学物种在结构和能级两个方面相匹配,是其具有传感功能的基础.关于同分异构体...     

机器学习筛选用于气体吸附分离和存储的金属有机骨架材料

金属有机框架（Metal-organic framework ,MOF）因其高孔隙率、高比表面积和结构可调性,在气体吸附分离领域广泛应用。随着MOF数量激增,传统分子模拟和实验方法验证MOF性能成本高且速度慢,因此目前MOF筛选工作已转向高通量计算辅助的机器学习（Machine-learning,ML）。机器学习作为一种高效的大数据处理方法,能够在高通量筛选（High-Throughput Computational Screening,HTCS）的基础上对数据进行拟合,从而快速而准确地筛选出气体吸附分离材料,并深入挖掘其结构与性能之间的关系。本文回顾了近年机器学习应用于MOF筛选的研究。本文重点讨论了一些运用机器学习从大量结构中筛选出可用于CH4、H2和CO2等气体吸附分离与储存的MOF材料的工作。同时,我们梳理了当前MOF材料筛选工作中的研究思路和进展,并指出了机器学习在筛选MOF材料工作中面临的一些瓶颈和挑战。最后,对该领域的未来发展前景进行了展望。