Augmenting the Carbon Dioxide Uptake and Selectivity of Metal-Organic Frameworks by Metal Substitution: Molecular Simulations of LMOF-202

Unraveling metal effects on CO2 uptake in pyrene-based metal-organic frameworks

Pyrene-based metal-organic frameworks (MOFs) have tremendous potential for various applications. With infinite structural possibilities, the MOF community often relies on simulations to identify the most promising candidates for given applications. Among thousands of reported structures, many exhibit limited reproducibility - in either synthesis, performance, or both - owing to the sensitivity of synthetic conditions. Geometric distortions that may arise in the functional groups of pyrene-based ligands during synthesis and/or activation cannot easily be predicted. This sometimes leads to discrepancies between in silico and experimental results. Here, we investigate a series of pyrene-based MOFs for carbon capture. These structures share the same ligand (1,3,6,8-tetrakis(p-benzoic acid)pyrene (TBAPy)) but have different metals (M-TBAPy, M = Al, Ga, In, and Sc). The ligands stack parallel in their orthorhombic crystal structure, creating a promising binding site for CO2. As predicted, the metal is shown to affect the pyrene stacking distance and, therefore, the CO2 uptake. Here, we investigate the metal's intrinsic effects on the MOFs' crystal structure. Crystallographic analysis shows the emergence of additional phases, which thus impacts the overall adsorption characteristics of the MOFs. Considering these additional phases improves the prediction of adsorption isotherms, enhancing our understanding of pyrene-based MOFs for carbon capture.

Computational and Machine Learning Methods for CO2 Capture Using Metal-Organic Frameworks

Machine learning (ML) using data sets of atomic and molecular force fields (FFs) has made significant progress and provided benefits in the fields of chemistry and material science. This work examines the interactions between chemistry and materials computational science at the atomic and molecular scales for metal-organic framework (MOF) adsorbent development toward carbon dioxide (CO2) capture. Herein, a connection will be drawn between atomic forces predicted by ML algorithms and the structures of MOFs for CO2 adsorption. Our study also takes into account the successes of atomic computational screening in the field of materials science, especially quantum ML, and its relationship to ML algorithms that clarify advancements in the area of CO2 adsorption by MOFs. Additionally, we reviewed the processes for supplying data to ML algorithms for algorithm training, including text mining from scientific articles, and MOF's formula processing linked to the chemical properties of MOFs. To create ML algorithms for future research, we recommend that the digitization of scientific records can help efficiently synthesize advanced MOFs. Finally, a future vision for developing pioneer MOF synthesis routes for CO2 capture is presented in this review article.

Self-luminescent europium based metal organic frameworks nanorods as a novel electrochemiluminescence chromophore for sensitive ulinastatin detection in biological samples

In this work, we developed a novel electrochemiluminescence (ECL) biosensor for ulinastatin (UTI) detection based on self-luminescent metal-organic framework (L-MOF) nanomaterials. The L-MOFs could be simply prepared by one-pot methods using Eu³⁺ and 4,4',4″-s-triazine-1,3,5-triyltri-m-aminobenzoic acid (H₃TATAB) as the metallic center and organic ligand, respectively. The Eu-TATAB exhibited high efficiency and stable ECL performance when using K₂S₂O₈ as coreactant. For the established biosensor, Eu-TATAB was both used as the ECL chromophore and protein carrier due to its outstanding biocompatibility and large superficial area, which could load sufficient antibodies to link with antigen in the biosensor for subsequent detection. The established sandwich ECL biosensor showed a wide linear range of 0.1 ng mL^-1 - 10⁵ ng mL^-1 and a low limit of detection of 9.7 pg mL^-1 for UTI detection. In addition, the developed ECL biosensor could also be successfully applied to the real UTI sample determination in serum. The reported biosensor strategy could provide a guide for developing more other novel and promising high-performance ECL nanomaterials, and also be used as a potential method for ultrasensitive UTI detection in disease research.

An anthracene-based microporous metal–organic framework for adsorbing CO2 and detecting TNP sensitivity

An anthracene-based microporous MOF of CUST-607 was synthesized by a solvothermal method. CUST-607 possesses a large surface area and shows strong adsorption toward CO2. In the fluorescence experiments, CUST-607 exhibits total quenching for TNP.

Molecular dynamics study of water confined in MIL-101 metal-organic frameworks

Molecular dynamics simulations of water adsorbed in Material Institute Lavoisier MIL-101(Cr) metal-organic frameworks are performed to analyze the kinetic properties of water molecules confined in the framework at 298.15 K and under different vapor pressures and clarify the water adsorption mechanism in MIL-101(Cr). The terahertz frequency-domain spectra (THz-FDS) of water are calculated by applying fast Fourier transform to the configurational data of water molecules. According to the characteristic frequencies in the THz-FDS, the dominant motions of water molecules in MIL-101(Cr) can be categorized into three types: (1) low-frequency translational motion (0-0.5 THz), (2) medium-frequency vibrational motion (2-2.5 THz), and (3) high-frequency vibrational motion (>6 THz). Each type of water motion is confirmed by visualizing the water configuration in MIL-101(Cr). The ratio of the number of water molecules with low-frequency translational motion to the total number of water molecules increases with the increase in vapor pressure. In contrast, that with medium-frequency vibrational motion is found to decrease with vapor pressure, exhibiting a pronounced decrease after water condensation has started in the cavities. That with the high-frequency vibrational motion is almost independent of the vapor pressure. The interactions between different types of water molecules affect the THz-FDS. Furthermore, the self-diffusion coefficient and the velocity auto-correlation function are calculated to clarify the adsorption state of the water confined in MIL-101(Cr). To confirm that the general trend of the THz-FDS does not depend on the water model, the simulations are performed using three water models, namely, rigid SPC/E, flexible SPC/E, and rigid TIP5PEw.

Facile Preparation of Porous Carbon Derived from Industrial Biomass Waste as an Efficient CO2 Adsorbent

A porous carbon CO₂ adsorbent based on soybean cake (industrial biomass waste) has been successfully prepared by direct carbonation, following KOH activation. The prepared porous carbon adsorbent exhibits efficient CO₂ capture performance with the highest adsorption capacity of 4.19 and 6.61 mmol/g at 298 and 273 K under atmospheric pressure, respectively. Moreover, the porous carbon adsorbent also shows good static CO₂ adsorption capacity at a low pressure (0.15 bar) with an uptake of 1.26 mmol/g and an equally ideal dynamic CO₂ capture capability with an uptake of 1.28 mmol/g (15% CO₂) at 298 K. Additionally, the ideal adsorbed solution theory (IAST) model has been used to measure the selectivity of the porous carbon, and the IAST factors of CO₂/N₂ (15/85, fuel gas), CO₂/CH₄ (40/60, biogas), and CH₄/N₂ (50/50, coalbed gas) are about 27, 6, and 6, respectively. The dynamic breakthrough test reveals the strong interaction between the porous carbon and CO₂, which also verifies the considerable selective capture ability of this material for CO₂. Furthermore, the soybean cake-based CO₂ adsorbent also presents prominent cyclic regeneration capacity (a five-time cyclic test) with lower isosteric heats (34-18 kJ/mmol) of CO₂ adsorption.