Experimental and Density Functional Theory Studies on a Zinc(II) Coordination Polymer Constructed with 1,3,5-Benzenetricarboxylic Acid and the Derived Nanocomposites from Activated Carbon

A data-guided approach for the evaluation of zeolites for hydrogen storage with the aid of molecular simulations

CONTEXT

This study employs a data-guided approach to evaluate zeolites for hydrogen storage, utilizing molecular simulations. The development of efficient and practical hydrogen storage materials is crucial for advancing clean energy technologies. Zeolites have shown promise as potential candidates due to their unique porous structure and tunable properties. However, the selection and design of suitable zeolites for hydrogen storage remain challenging. Therefore, this work aims to address this materials science question by utilizing molecular simulations and data-guided approaches to evaluate zeolites' performance for hydrogen storage. The results obtained from this study provide valuable insights into the evaluation of zeolites for hydrogen storage. Through molecular simulations, we analyze the adsorption behavior of hydrogen molecules in various zeolite structures. The performance of different zeolite frameworks in terms of hydrogen storage capacity, adsorption energy, and diffusion properties is assessed. Linde type A zeolite (LTA) had the highest capacity with a hydrogen capacity of 4.8wt% out of the 233 investigated zeolites. Furthermore, we investigate the influence of different factors such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) on the hydrogen storage performance of zeolites. The results show that Di, D, and M have a negative effect on the percentage weight capacity, while GSA and VSA have the highest positive contribution to the percentage weight. This study, therefore, provides new insights into the factors that affect their hydrogen storage capacity by exhibiting the importance of considering multiple factors when evaluating the performance of zeolites and demonstrates the potential of combining different computational methods to provide a more comprehensive understanding of materials. The current study contributes to the understanding of zeolite-based materials for hydrogen storage applications, aiding in the development of more efficient and practical hydrogen storage systems.

METHODS

Computational techniques were employed to investigate the hydrogen storage properties of zeolites. Molecular simulations were performed using classical force fields and molecular dynamics methods. The calculations were carried out at a force field level of theory with the GGA functional. To accurately capture the thermodynamics and kinetics of hydrogen adsorption, enhanced sampling techniques such as Monte Carlo simulations and molecular dynamics with metadynamics were utilized. We employed Grand Canonical Monte Carlo (GCMC) simulations to model hydrogen adsorption in zeolite structures for hydrogen storage. Our approach involved performing a substantial number of Monte Carlo steps (10,000) to ensure system equilibration and precise results. We defined a cutoff distance for particle interactions as 12.5 Ǻ and considered 0.000e framework charge per cell and 0.000e sorbate charge in energy calculations. The choice of an appropriate simulation cell size (50 × 50 × 50) Ǻ was crucial, mirroring real-world conditions. We specified lower and upper fugacity values (1 to 10 atm) to capture the range of gas pressures in the simulations. These methodical steps collectively enabled us to accurately model hydrogen adsorption within zeolites, forming the core of our hydrogen storage evaluation. In this research, we utilized DFT calculations to thoroughly investigate the interactions between zeolites and hydrogen. We employed pseudopotentials to describe electron behavior in zeolite systems, choosing them in line with DFT norms and basis set compatibility. Our simulation cell design replicated zeolite periodicity and eliminated boundary effects. Pre-geometry optimization was performed with HyperChem29, ensuring stable conformations with strict convergence criteria. We utilized 6-31 + G(d) and LanL2DZ basis sets for light and heavy atoms, aligning with field standards for computational efficiency and precision. A machine learning algorithm was used to rank the importance of various structural features such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) and how they affect the capacity of the zeolites. Machine learning analysis was performed with the Scikit-learn library, an open-source Python tool. We employed a range of machine learning models, including SVMs, random forests, and neural networks, primarily for data analysis and feature extraction. Pearson correlation analysis, a classical statistical technique, was used to evaluate linear relationships between variables and assess the strength and direction of these relationships. It served as a complementary tool to understand the interplay of variables in our dataset, distinguishing it from machine learning algorithms. Further quantum chemical calculations were also performed to calculate the adsorption energy, global reactivity electronic descriptors, and natural bond orbital analysis in order to provide insights into the interaction of the zeolites with hydrogen. The simulations and data analysis were performed using BIOVIA material studio software, Gaussian, and Origin Pro software.

Thyroid hormone transporters binding affinity of methoxypoly chlorinated biphenyls: Insights from molecular simulations and fluorescence competitive binding experiment

Triiodothyronine (T3) and thyroxine (T4) are essential for regulating cell metabolic rate and promoting the development and differentiation of brain tissue, especially in fetuses and newborns. In particular, it has been proved that MeO-PCBs have high binding to thyroid hormone transporters and can competitively bind to thyroid carrier proteins, thus destroying the transport of the thyroid hormone. Fluorescence competition binding experiments and docking results showed that the binding affinity decreased with the increase in number of chlorine atoms of MeO-PCBs. The interaction mechanism of MeO-PCBs with thyroid transporter (TTR) and thyroid binding globulin (TBG) was compared by computational simulation and the binding free energies were calculated by the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method. Electrostatic potential analysis, Hirshfeld surface analysis and electron density difference maps confirmed the existence of electrostatic interactions. Secondly, noncovalent interaction (NCI) analysis further indicated that the main driving force for the combination of MeO-PCBs to TTR and TBG were electrostatic interaction and van der Waals interaction. The conformational changes of the protein after binding were studied by a molecular dynamic simulation.

Syntheses, Structural Characterization, and Cytotoxicity Assessment of Novel Mn(II) and Zn(II) Complexes of Aroyl-Hydrazone Schiff Base Ligand

This work describes the syntheses, structural characterization, and biological profile of Mn(II)- and Zn(II)-based complexes 1 and 2 derived from the aroyl-hydrazone Schiff base ligand (L1). The synthesized compounds were thoroughly characterized by elemental analysis, Fourier transform infrared spectroscopy (FTIR), UV-vis, electron paramagnetic resonance (EPR), nuclear magnetic resonance (NMR), and single-crystal X-ray diffraction (s-XRD). Density functional theory (DFT) studies of complexes 1 and 2 were performed to ascertain the structural and electronic properties. Hirshfeld surface analysis was used to investigate different intermolecular interactions that define the stability of crystal lattice structures. To ascertain the therapeutic potential of complexes 1 and 2, in vitro interaction studies were carried out with ct-DNA and bovine serum albumin (BSA) using analytical and multispectroscopic techniques, and the results showed more avid binding of complex 2 than complex 1 and L1. The antioxidant potential of complexes 1 and 2 was examined against the 2,2-diphenyl picrylhydrazyl (DPPH) free radical, which revealed better antioxidant ability of the Mn(II) complex. Moreover, the antibacterial activity of synthesized complexes 1 and 2 was tested against Gram-positive and Gram-negative bacteria in which complex 2 demonstrated more effective bactericidal activity than L1 and complex 1 toward Gram-positive bacteria. Furthermore, the in vitro cytotoxicity assessment of L1 and complexes 1 and 2 was carried out against MDA-MB-231 (triple negative breast cancer) and A549 (lung) cancer cell lines. The cytotoxic results revealed that the polymeric Zn(II) complex exhibited better and selective cytotoxicity against the A549 cancer cell line as was evidenced by its low IC₅₀ value.

Synthesis and characterization of ZnBTC-based MOFs: effect of solvents and salt

In this work, we studied the optimization of synthetic approaches to creating structurally modified metal-organic frameworks under various synthesis conditions. We investigated the influence of the various solvents and zinc salts on the structural characteristics of the metal-organic framework based on benzene-1,3,5-tricarboxylic acid (H3BTC). The results indicate that the variation of the types of both solvent and salt is a parameter affecting the crystallinity, phase purity, and morphology of the metal-organic framework. This was confirmed by comprehensive structural characterization (SEM, EDX, PXRD).

Probing the Reactions of Thiourea (CH4N2S) with Metals (X = Au, Hf, Hg, Ir, Os, W, Pt, and Re) Anchored on Fullerene Surfaces (C59X)

Upon various investigations conducted in search for a nanosensor material with the best sensing performance, the need to explore these materials cannot be overemphasized as materials associated with best sensing attributes are of vast interest to researchers. Hence, there is a need to investigate the adsorption performances of various metal-doped fullerene surfaces: C₅₉Au, C₅₉Hf, C₅₉Hg, C₅₉Ir, C₅₉Os, C₅₉Pt, C₅₉Re, and C₅₉W on thiourea [SC(NH₂)₂] molecule using first-principles density functional theory computation. Comparative adsorption study has been carried out on various adsorption models of four functionals, M06-2X, M062X-D3, PBE0-D3, and ωB97XD, and two double-hybrid (DH) functionals, DSDPBEP86 and PBE0DH, as reference at Gen/def2svp/LanL2DZ. The visual study of weak interactions such as quantum theory of atoms in molecule analysis and noncovalent interaction analysis has been invoked to ascertain these results, and hence we arrived at a conclusive scientific report. In all cases, the weak adsorption observed is best described as physisorption phenomena, and CH₄N₂S@C₅₉Pt complex exhibits better sensing attributes than its studied counterparts in the interactions between thiourea molecule and transition metal-doped fullerene surfaces. Also, in the comparative adsorption study, DH density functionals show better performance in estimating the adsorption energies due to their reduced mean absolute deviation (MAD) and root-mean-square deviation (RMSD) values of (MAD = 1.0305, RMSD = 1.6277) and (MAD = 0.9965, RMSD = 1.6101) in DSDPBEP86 and PBE0DH, respectively.