Probleemstelling:

Crystalline, nanoporous materials such as metal-organic frameworks (MOFs) have been proposed for a variety of industrial applications, such as energy storage, gas separation, and the capture of greenhouse gases, due to their attractive properties and vast design opportunities. These scaffold-like materials, composed of inorganic moieties connected through organic ligands, were originally thought of as being perfectly ordered, crystalline materials. However, recent advances in experimental characterization tools have disproven this ideal picture, and it has become increasingly clear that spatial disorder is inherently present in these materials (see Figure 1) [1]. While these defects may jeopardize the mechanical stability of MOFs, they may also endow the material with a superior performance in gas adsorption, gas separation, or heterogeneous catalysis with respect to their defect-free analogues. As a result, spatial disorder in MOFs–especially isolated disorder that occurs on a nanometer length scale–has emerged as an alternative pathway to design defect-engineered MOFs towards specific applications [2].

To fully exploit the potential of defects to promote MOFs towards functional materials, it is essential to reliably predict how the presence and distribution of defects will alter the mechanical stability of these MOFs. Accurately taking into account spatial disorder and its effect on macroscopic properties has therefore been recognized as one of the three grand challenges within the computational modelling of MOFs. In a recent study by the Center for Molecular Modeling (CMM), the impact of localized defects on the mechanical stability of one of the prototypical MOFs, UiO-66, was investigated (see Figure 2) [3]. By including different linker defects in the material, as indicated in Figure 2, we were able to determine that the stability of the material is not only influenced by the number of defects, but also, and primarily, by the distribution of these defects in the material. In this research proposal, we intent to perform a similar study of isolated spatial disorder in ZIF-8 and explain their impact on the mechanical properties from the perfect crystal given the importance of this prototypical material.

Doelstelling:

Recently, Schmidt and co-workers performed an extensive study of possible localized defects in ZIF-8, an example of which is indicated in Figure 3 [4]. In this thesis proposal, we first aim to validate their findings by performing quantum mechanical calculations on the defective crystal and representative cluster models, and propose other defect mechanisms based on our earlier experience with defective MOFs. Furthermore, the energetics of these hypothetical defects will be systematically evaluated, which will allow us to formulate the most probable defect mechanisms present in ZIF-8. In addition, disorder in this material may also be introduced by allowing for mixed metal nodes, further tuning the mechanical performance of ZIF-8.  

In a next step, force field models for these defective structures will be developed, based on the generated quantum mechanical data using an in-house developed protocol [5]. A force field approximates the complex potential energy surface by simple analytical expressions and allows to simulate larger systems for a longer time in contrast with a full quantum mechanical treatment. Properties such as the bulk modulus, shear modulus, loss-of-crystallinity pressure, and thermal expansion will be determined using computational procedures which were recently developed at the CMM, and compared with available experimental data to confirm our atomistic models. In this way, we will be able to predict how the intrinsic spatial disorder in ZIF-8 impacts its mechanical properties for the first time. Moreover, if possible, these findings will be expanded to also account for ZIF-8 surfaces, so to account for the finite size of these MOF crystals.

The student will be actively coached to make him/her acquainted with the advanced simulations techniques early in the thesis year, and to transfer necessary programming skills needed to perform the research.