About 10 years ago, a new class of synthetic materials, metal-organic frameworks (MOFs, figure 1(left)), was discovered. These are crystalline materials consisting of metal ions or clusters connected by organic linkers to form a network of 1D, 2D or 3D channels with a diameter of a few nanometers. The main attractive property of these materials is the large internal surface area, going up to 5640 m²/gr for MOF-177. This means that one gram of material contains an internal surface as large as a football field. Hence enormous amounts of guest molecules can adsorb on this surface (cfr. a molecular sponge), leading to diverse industrial applications such as energy storage, CO2 capture, gas sensing, and so on. For certain MOFs, the selective adsorption of guest molecules is strongly influenced by the so-called breathing effect (figure 1(right)): the crystal framework changes its shape as function of temperature and loading. These exceptional properties have lead to a surge of interest in academia and industry, which is evident from the large number of MOF publications in highly-ranked journals.

Figure 1.

Zeolites (figure 2) are another kind of porous materials, they are inorganic crystals with well-defined cavities. Generally they contain silicon, aluminum and oxygen in their framework and cations, water and/or other molecules within their pores. Many occur naturally as minerals, and are extensively mined in many parts of the world. Others are synthetic, and are made commercially for specific uses, or produced by research scientists trying to understand more about their chemistry. Because of their unique porous properties, zeolites are used in a variety of applications with a global market of several million tonnes per annum. In the western world, major uses are in petrochemical cracking, ion-exchange (water softening and purification), and in the separation and removal of gases and solvents. Other applications are in agriculture, animal husbandry, pharmaceuticals and cosmetics.

Figure 2.

Macroscopic properties of such nanoporous materials can be predicted with simulations of nanoscale models. This facilitates the systematic assessment of a large number of different (even hypothetical) materials for industrial applications: a first screening of the MOF database in search of the optimal material is performed in silico, prior to expensive wet-lab experiments. The two most common techniques are Molecular Dynamics (MD) and Monte Carlo (MC) simulations. For both methods, one relies on the Born-Oppenheimer approximation: atomic nuclei are treated as classical point particles on a potential energy surface (PES) governed by the surrounding electrons. In principle, the electronic structure must be solved with quantum mechanical methods (ab initio) to derive the potential energy felt by the nuclei. However, for simulations on nanoporous materials, this becomes computationally infeasible and one has to use so-called force fields to compute the PES without explicitly describing the electronic structure. Such a force field approximates the potential energy of a molecule by means a priori postulated energy terms. An example of such an energy term is a harmonic contribution for describing the chemical bond between two atoms by means of a simple spring (figure 3). These energy terms contain unknown parameters (e.g. spring equilibrium length and force constant). The main obstacle of a force-field simulation is this set of empirical parameters that must be determined. Historically, such parameters were determined from experimental reference data but today this is intractable due to the complexity of modern materials.

Figure 3.

In literature, there is an abundance of force fields available for zeolites. For metal-organic frameworks, however, there are very few. Furthermore, all kinds of new nanoporous materials are being investigated such as hypothetical MOFS and zeolites, ZIFs, PoSiSils, … for which there exist very little force fields or none at all. A new procedure was proposed at the Center for Molecular Modeling (CMM) for deriving force fields from ab initio reference data. This methodology is already implemented in QuickFF, an in-house developed Python package, allowing easy derivation of force fields from the quantum mechanical input data. The goal of the thesis is to apply this procedure to a large set of existing (Mil-47, Mil-68, …) and hypothetical materials and calculate important properties such as cell parameters, framework flexibility, strain, thermal expansion coefficients, adsorption and diffusion of guest molecules. This will allow to identify potentially interesting (and possibly not yet synthesized) materials for certain applications. An important part of this thesis is to evaluate the accuracy of the force fields and if necessary adjust, tune or expand the methodology to improve the overall accuracy of the force fields.

This topic involves the development of new algorithms and theoretical models, and the implementation of these models in our in-house simulation software. If needed, programming skills will be transferred during the thesis.