Estudo computacional da separação de gás natural em APMOFs MOFOUR: uma abordagem integrada com DFT, monte carlo, dinâmica molecular e parametrização

Abstract

Highly porous crystalline materials, known as Metal-Organic Frameworks (MOFs) or Porous Coordination Polymers (PCPs), represent a class of compounds with applications across multiple fields. These materials exhibit great potential for electrochemical applications, gas storage, conductivity, optical sensing, among others. The versatility of MOFs arises primarily from the ability to tune their structural characteristics through the selection of different metals or metal clusters, known as Secondary Building Units (SBUs), along with a variety of organic linkers (spacers) during synthesis. An important subclass, the Anion Pillared Metal-Organic Frameworks (APMOFs), incorporates inorganic anions that enable gas separation based on kinetic diameter, resulting in a molecular sieving effect. Moreover, the active sites in these materials act as efficient hydrogen bond acceptors, enhancing selectivity for the target gas in the desired process. This structural adaptability enables the development of materials with specific functionalities. In this work, we investigate the APMOFs CrOFOUR-1-Ni and MoOFOUR-1-Ni, designed for the separation of industrially relevant gases. These materials have been previously reported in the literature and have demonstrated high selectivity and affinity for CO2 in comparison to other gases. We studied the interactions between CO2, N2, and CH4—supported by experimental data—as well as extrapolations to other gases such as C2H6 and C3H8, and to higher pressure ranges. We performed electronic structure analysis using periodic-boundary Density Functional Theory (DFT) calculations with the Quantum ESPRESSO 7.2 package. This included geometry optimizations, extraction of the Hubbard U parameter, and analysis of band structure, density of states (DOS), and projected density of states (PDOS). To improve the description of phenomena in classical simulations, we parametrized Lennard-Jones (LJ) parameters for molybdate. Classical Monte Carlo simulations were carried out with the RASPA software to construct adsorption isotherms for the gases mentioned, using supercells based on the optimized structures, and to compute adsorption enthalpies. Binary mixtures were also analyzed to evaluate MOF selectivity under different molar compositions. Additionally, molecular dynamics simulations were performed to investigate molecular behavior over time, employing tools such as mean squared displacement (MSD), radial distribution function (RDF), and velocity autocorrelation function (VACF). Non-covalent interaction (NCI) analyses were conducted to understand the mechanisms behind selectivity and adsorbent–adsorbate interactions, alongside quantum-level adsorption energy calculations. Finally, the structures show potential for the adsorption of species such as CO2 and C3H8, and parametrization was found to be essential for accurately describing these systems within classical mechanics.