Accelerated screening and assembly of promising MOFs with open Cu sites for isobutene/isobutane separation using a data-driven approach

As the by-products of catalytic cracking or alkane dehydrogenation, isobutene (2-methyl-propylene) and isobutane (2-methyl-propane) are important chemical feedstocks, but the separation of their mixture is a challenging issue in the petrochemical industry. Herein, we report the first example of large-scale computational screening of metal-organic frameworks (MOFs) with copper open metal sites (Cu-OMS) on the adsorptive separation of isobutene/isobutane using configuration-bias Monte Carlo (CBMC) simulations and machine learning among >330 000 MOFs data. We discovered that the optimal structural features governing the MOFs-based separation of isobutene/isobutane were density (ρ) and porosity (φ), with ranges of 0.2-0.5 g cm^-3 and 0.8-0.9, respectively. Furthermore, the key genes (metal nodes or linkers of frameworks) contributing to such adsorptive separation were data-mined by feature engineering of ML. These genes were cross-assembled into novel frameworks using a material-genomics strategy. The screened AVAKEP, XAHPON, HUNCIE, Cu₂O₈-mof177-TDPAT_No730 and assembled Cu₂O₈-BTC_B-core-4_No1 possessed high isobutene uptake and isobutene/isobutane selectivity of >19.5 mmol g^-1 and 4.7, with high thermal stability (as validated by molecular-dynamics simulations) overcoming the critical "trade-off" problem to some extent. The macroporous structures (pore-limiting diameter >12 Å) of these five promising frameworks with multi-layer adsorption on isobutene resulted in high isobutene loading, as validated by adsorption isotherms and CBMC simulations. The higher adsorption energy and heat of adsorption of isobutene than those of isobutane indicated that the thermodynamic equilibrium drove their selective adsorption. Generalized charge decomposition analysis and localized orbit locator calculations based on density functional theory wavefunctions suggested that high selectivity was due to complexation of feedback π bonds between isobutene and Cu-OMS, but also the strong π-π stacking interaction induced by the CC bond of isobutene with the multiple aromatic rings and unsaturated bonds of frameworks. Our theoretical results and data-driven approach may provide insights into the development of efficient MOF materials for the separation of isobutene/isobutane and other mixtures.

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.

Materials genomics methods for high-throughput construction of COFs and targeted synthesis

Materials genomics represents a research mode for materials development, for which reliable methods for efficient materials construction are essential. Here we present a methodology for high-throughput construction of covalent organic frameworks (COFs) based on materials genomics strategy, in which a gene partition method of genetic structural units (GSUs) with reactive sites and quasi-reactive assembly algorithms (QReaxAA) for structure generation were proposed by mimicking the natural growth processes of COFs, leading to a library of 130 GSUs and a database of ~470,000 materials containing structures with 10 unreported topologies as well as the existing COFs. As a proof-of-concept example, two generated 3D-COFs with ffc topology and two 2D-COFs with existing topologies were successfully synthesized. This work not only presents useful genomics methods for developing COFs and largely extended the COF structures, but also will stimulate the switch of materials development mode from trial-and-error to theoretical prediction-experimental validation.

The discovery of new covalent organic framework (COF) topologies is often led by trial-and-error experiments. Here, the authors present a methodology for high throughput construction of COFs based on a materials genomics strategy and demonstrate the synthesis of the generated 2D and 3D-COFs.

DFT studies on storage and adsorption capacities of gases on MOFs

Metal-organic frameworks (MOFs) are highly porous crystalline materials, consisting of metal ions linked together with organic bridging ligands, exhibiting high surface areas. Lately, they have been utilized for gas sorption, storage, sensing, drug delivery, etc. The chemistry of MOFs is expanding with an extraordinary speed, constituting both theoretical and experimental research, and MOFs have proved to be promising candidates so far. In this work, we have reviewed the density functional theory studies of MOFs in the adsorption and separation of the greenhouse gas, CO2, as well as the storage efficiencies for fuel gases like H2, CH4 and C2H2. The role of organic ligands, doping with other metal ions and functional groups, open metal sites and hybrid MOFs have been reviewed in brief.

Computational Screening of MOFs for Acetylene Separation

Efficient separation of acetylene (C₂H₂) from CO₂ and CH₄ is important to meet the requirement of high-purity acetylene in various industrial applications. Metal organic frameworks (MOFs) are great candidates for adsorption-based C₂H₂/CO₂ and C₂H₂/CH₄ separations due to their unique properties such as wide range of pore sizes and tunable chemistries. Experimental studies on the limited number of MOFs revealed that MOFs offer remarkable C₂H₂/CO₂ and C₂H₂/CH₄ selectivities based on single-component adsorption data. We performed the first large-scale molecular simulation study to investigate separation performances of 174 different MOF structures for C₂H₂/CO₂ and C₂H₂/CH₄ mixtures. Using the results of molecular simulations, several adsorbent performance evaluation metrics, such as selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability were computed for each MOF. Based on these metrics, the best adsorbent candidates were identified for both separations. Results showed that the top three most promising MOF adsorbents exhibit C₂H₂/CO₂ selectivities of 49, 47, 24 and C₂H₂/CH₄ selectivities of 824, 684, 638 at 1 bar, 298 K and these are the highest C₂H₂ selectivities reported to date in the literature. Structure-performance analysis revealed that the best MOF adsorbents have pore sizes between 4 and 11 Å, surface areas in the range of 600–1,200 m²/g and porosities between 0.4 and 0.6 for selective separation of C₂H₂ from CO₂ and CH₄. These results will guide the future studies for the design of new MOFs with high C₂H₂ separation potentials.