The Development of Computational High-Throughput Approaches for Screening Metal-Organic Frameworks in Adsorptive Separation Applications
Creators: name: Tao, Andi
Publisher: name: Apollo - University of Cambridge Repository
Year: 2019
Subjects: MOF
molecular simulation
computational high-throughput screening

description: Chemical separation undoubtedly accounts for a large proportion of process industries’ activities. In the past few decades, 10-15% of the world’s energy consumed was resulted from separation process. Tremendous efforts have been made in separating the components of large quantities of chemical mixtures into pure or purer forms in most industrial chemists. In addition, industrial development and population growth would lead to a further increase in the global demand for energy in the future. This makes the effective and efficient energy separation process one of the most challenging tasks in engineering. Adsorptive separation using porous materials is widely used in industry today. In order for an adsorptive separation process to be efficient, the essential requirement is a selective adsorbent that possesses high surface area and preferentially adsorbs one component (or class of similar components). Metal-organic frameworks (MOFs) are promising materials for separation purposes as their diversity, due to their building block synthesis from metal clusters and organic linker, gives rise to a wide range of porous structures. Engineering of a separation process is a multi-disciplinary problem that requires a holistic approach. In particular, material selection for industrial applications in the field of MOFs is one of the most significant engineering challenges. The complexity of a screening exercise for adsorptive separations arises from the multitude of existing porous adsorbents including MOFs. There are more than 80,000 structures that have been synthesised so far, as well as the multivariate nature of that performance criteria that need to be considered when selecting or designing an optimal adsorbent for a separation process. However, it is infeasible to assess all the potential materials experimentally to identify the promising structure for a particular application. Recently, molecular simulation and mathematical modelling have seen an ever- growing contribution to the research field of MOFs. The development of these computational tools offers a unique platform for the characterisation, prediction and understanding of MOFs, complementary to experimental techniques. In the first part of this research, Monte Carlo molecular simulation and a number of advanced mathematical methods were used to investigate newly synthesised or not well-known MOFs. These computational techniques allowed not only to characterise materials with their textural properties, but also to predict and understand adsorption performances at the atomic level. Based on the insight gained from the molecular simulation, two computational high-throughput screening approaches were designed and assessed. A multi-scale approach has been proposed and used which combined high-throughput molecular simulation, data mining and advanced visualisation, process system modelling and experimental synthesis and testing. The focus here was on two main applications. On one hand, the challenging CO/N2 separation, which is critical for the petrochemical sector, where two molecules have very similar physical properties. On the other hand, the separation of chiral molecules. For CO/N2 separation, a database of 184 Cu- Cu paddle-wheels MOFs, which contains unsaturated metal centres as strong interaction sites, was extracted from CSD (Cambridge Structural Database) MOF subset for material screening. In the case of chiral separation, an efficient high-throughput approach based on calculation of Henry’s constant was developed in this research. Owning to the nature of chirality, this separation of relevance to the pharmaceutical sector is crucially important. A database of 1407 homochiral MOFs was extracted, again, from CSD MOF subset for material screening of enantioselective adsorption. The results obtained in these computational high-throughput approaches allows the screening of interesting, existing structures, and would have a huge impact on making MOFs to be industrially interesting adsorbents as well as guiding the synthesis of these materials. From the many different possibilities, the ultimate interest of this work is in developing an integrated systematic study of the structure-adsorption performance relationship working with a limited library of candidate MOF structures in order to identify promising trends and materials for the specific applications mentioned above. In summary, the overall aim of this research was exploiting different computational techniques, developing novel high-throughput approaches in order to tackle important engineering challenges.