Adsorption Performance Of Metal-organic Frameworks Research Articles

Graph Transformer with Convolution Parallel Networks for Predicting Single and Binary Component Adsorption Performance of Metal-Organic Frameworks.

Metal-organic frameworks (MOFs) are considered one of the most important materials for carbon capture and storage (CCS) due to the advantages of porosity, multifunction, diverse structure, and controllable chemical composition. With the continuous development of artificial intelligence (AI) technology, more and more machine learning models are used to identify MOFs with high performance within a massive search space. However, current works have yet to form a model that uses graph-structured data only, which can predict the adsorption properties of single and binary components. In this work, we proposed and developed a graph transformer, combined with convolution parallel networks, called GC-Trans. The model can accurately and efficiently predict the adsorption performance of MOFs under the single- and binary-component adsorption conditions using only the features of the crystal diagram as inputs. By extracting and fusing local and global feature information, the model has stronger expression and generalization abilities. Thus, we used it to screen the ARC-MOF database and analyze the MOF structures that meet the target requirements. Additionally, to demonstrate the transferability of the model, we applied transfer learning methods to predict the CO2/CH4 separations and CH4 uptake, both of which showed good predictive performance.

An XGBoost Algorithm Based on Molecular Structure and Molecular Specificity Parameters for Predicting Gas Adsorption

In this paper, an improved Extreme Gradient Boosting (XGBoost) algorithm based on the Graph Isomorphic Network (GIN) for predicting the adsorption performance of metal-organic frameworks (MOFs) is developed. It is shown that the graph isomorphic layer of this algorithm can directly learn the feature representation of materials from the connection of atoms in MOFs. Then, XGBoost can be used to predict the adsorption performance of MOFs based on feature representation. In this sense, it is not only possible to achieve end-to-end prediction directly from the structure of MOFs to adsorption performance but also to ensure the accuracy of prediction. The comparison between Grand Canonical Monte Carlo (GCMC) simulation and prediction supports the performance and effectiveness of the proposed algorithm.

Screening of hierarchical porous UiO-67 for efficient removal of glyphosate from aqueous solution

Defect engineering is essential for improving the adsorption performance of metal-organic frameworks (MOFs). Herein, hierarchical porous UiO-67(Zr) and analogs with controlled levels of defects were successfully obtained and applied to chemoselectively capture glyphosate (GP) from water. The obtained defective UiO-67 was stable at different pH values. The removal performance of defective UiO-67(Zr) was evaluated systematically as a function of different modulators, water chemistry and interfering ions. The maximum adsorption capacity of defective UiO-67(Zr) reached 322.58 mg/g, superior to most MOFs-based adsorbents. The defective UiO-67(Zr) also showed high selectivity for GP adsorption at high concentrations of humic acids (3 times) and interfering anions (100 times). In addition, the defective UiO-67(Zr) has shown good recovery performance and can effectively remove GP from a variety of contaminated water samples and multi-pollutant systems. The results of batch experiments and microscopic spectral characterization (XPS and FTIR) revealed that GP adsorption was mainly guided by electrostatic action, coordination, pore-filling and hydrogen bonding. These findings verified that the fabrication of defect sites played an important role in promoting the adsorption performance of MOFs. Our work provides a clue to the design of defective MOFs with high adsorption performance.

Elevating the stability and adsorption performance of metal-organic frameworks by chitosan and attapulgite for capturing methylene blue in the water

Here we firstly report a novel adsorbent based on metal-organic frameworks (MOFs) which were modified by chitosan (CS) and attapulgite (ATP), including ZIF-8@ATP-CS, Zr-MOF@ATP-CS, and Al-MOF@ATP-CS. The preservative CS constructed a network framework for uniform diffusion of MOFs powder. The ATP not only strengthened the stability, but also improved the adsorption ability. Among these materials, Zr-MOF@ATP-CS had the most optimal adsorption capacity for methylene blue (MB), which could reach the equilibrium within 30 min and obtained the maximum adsorption of 442.86 mg g-1. Zr-MOF@ATP-CS went through five regenerations without significant reduction, which meant Zr-MOF@ATP-CS owned excellent stability. The ratio of ATP: CS in Zr-MOF@ATP-CS was also explored, and it was found that the best modification effect ratio was 0.75: 1. More importantly, the potential practical application was presented in this article. Finally, a possible mechanism was proposed. The novel materials were expected to further expand MOFs materials.

In-situ growth of molecularly imprinted metal–organic frameworks on 3D carbon foam as an efficient adsorbent for selective removal of antibiotics

In recent years, Metal-organic frameworks (MOFs) have attracted extensive attention in the field of adsorption owing to their advantages such as large specific surface area and rich active sites, but the adsorption performance of MOFs is not ideal for the removal of macromolecular organics. In this study, a novel composite material for the efficient and selective removal of norfloxacin (NOR) from wastewater has been successfully prepared via combining molecular imprinting (MI) technology and in-situ growth strategy, in which evenly dispersed MOFs particles are perfectly anchored to three-dimensional porous carbon foam (CF). Owing to more active sites exposed by three-dimensional imprinted holes and the excellent transport properties of CF, the as-prepared MI-MOF/CF exhibits a maximum capacity of 456 mg/g for NOR, which is far superior to that of the pristine MOF. Moreover, the adsorption rate is significantly increased, and the adsorption equilibrium could be reached within 60 min. Interestingly, the selective pharmaceuticals adsorption performance of MI-MOF/CF depends not only on the pore size, but also on the specific recognition ability of the active sites where modified with carboxyl compounds. This work effectively solves the bottleneck encountered by MOFs in the removal of large size antibiotic molecules, and provides a new direction for the design and synthesis of MOFs in the future.

Use of breakthrough experiment to evaluate the performance of hydrogen isotope separation for metal-organic frameworks M-MOF-74 (M=Co, Ni, Mg, Zn)

The unique adsorption performance of metal-organic frameworks (MOFs) indicates a new direction for gas separation and purification. The low-temperature distillation, as a traditional technique for hydrogen isotope separation, is limited as it is a high energy- and cost-intensive process. Instead of utilizing such a conventional separation route, we use ordered microporous frameworks based on a physical adsorption mechanism to solve the challenge of hydrogen isotope separation. Herein we analyze M-MOF-74 (M=Co, Ni, Mg, Zn), featuring a hexagonal channel about 11 A and high density of open metal sites, for their ability to separate and purify deuterium from the hydrogen isotope mixture by dynamic column breakthrough experiments. Our results show that the combination of the strength of binding sites, density of coordinatively unsaturated metal sites and hydrogen isotope adsorption capacity of materials renders Co-MOF-74 as an optimal adsorbent for the capture of deuterium from hydrogen isotope mixtures in a simulated industrial process.

Role of Ionic Liquid [EMIM]+[SCN]- in the Adsorption and Diffusion of Gases in Metal-Organic Frameworks.

We study the adsorption performance of metal-organic frameworks (MOFs) impregnated of ionic liquids (ILs). To this aim we calculated adsorption and diffusion of light gases (CO2, CH4, N2) and their mixtures in hybrid composites using molecular simulations. The hybrid composites consist of 1-ethyl-3-methylimidazolium thiocyanate impregnated in IRMOF-1, HMOF-1, MIL-47, and MOF-1. We found that the increase of the amount of IL enhances the adsorption selectivity in favor of carbon dioxide for the mixtures CO2/CH4 and CO2/N2 and in favor of methane in the mixture CH4/N2. We also provide detailed analysis of the microscopic organization of ILs and adsorbates via radial distribution functions and average occupation profiles and study the impact of the ILs in the diffusion of the adsorbates inside the pores of the MOFs. Based on our findings, we discuss the advantages of using IL/MOF composites for gas adsorption to increase the adsorption of gases and to control the pore sizes of the structures to foster selective adsorption.

Metal-organic framework based in-syringe solid-phase extraction for the on-site sampling of polycyclic aromatic hydrocarbons from environmental water samples.

In-syringe solid-phase extraction is a promising sample pretreatment method for the on-site sampling of water samples because of its outstanding advantages of portability, simple operation, short extraction time, and low cost. In this work, a novel in-syringe solid-phase extraction device using metal-organic frameworks as the adsorbent was fabricated for the on-site sampling of polycyclic aromatic hydrocarbons from environmental waters. Trace polycyclic aromatic hydrocarbons were effectively extracted through the self-made device followed by gas chromatography with mass spectrometry analysis. Owing to the excellent adsorption performance of metal-organic frameworks, the analytes could be completely adsorbed during one adsorption cycle, thus effectively shortening the extraction time. Moreover, the adsorbed analytes could remain stable on the device for at least 7 days, revealing the potential of the self-made device for on-site sampling of degradable compounds in remote regions. The limit of detection ranged from 0.20 to 1.9ng/L under the optimum conditions. Satisfactory recoveries varying from 84.4 to 104.5% and relative standard deviations below 9.7% were obtained in real samples analysis. The results of this study promote the application of metal-organic frameworks in sample preparation and demonstrate the great potential of in-syringe solid-phase extraction for the on-site sampling of trace contaminants in environmental waters.