Computer modeling of materials structure and behaviour has led to many insights aiding the design of new materials. Coupling real experiments with virtual models allows companies to not only create new materials but also to understand why the new material is better than previous ones. A recent paper published by ExxonMobil[i] demonstrates the value of combining virtual and real experiments in the discovery of a new zeolite material.
Zeolites are ordered porous materials that have regular shaped pores arranged in two and three dimensions[ii]. Oil and Gas organizations tend to use them mostly in catalysis as the size of the pores allows certain molecules to enter and react whilst stopping similar molecules from reacting. This means that zeolites have good selectivity and can improve yields from reactions. They can also serve as separation membranes for gas molecules[iii].
The chemistry and size of the pore, specified by the number of tetrahedral atoms in the ring, determine the application for which the zeolite is most suitable. Typically, zeolites with 8-ring pores are useful in gas separation such as separating CO2 from methane. Zeolites with 10-ring pores are used in refining applications like dewaxing whilst 12-ring pores can assist with reactions on organic molecules. Interestingly, zeolites with an odd number of ring atoms are quite rare and those that have commercial applications are even rarer.
In 1992, Imperial Chemical Industries claimed discovery of a new zeolite, NU-86, which showed improved properties for industrial catalysis. They published a partial structure, which showed it to be an 11-ring pore structure – unique at the time. However, they never published the full structure of NU-86 and, with limited information on the synthesis, it has proven difficult to reproduce with reasonable purity.
A zeolite with an 11-ring pore structure, such as NU-86, and relevant aluminosilicate composition that can improve catalytic isomerization of important industrial processes would be very valuable.
Scientists at ExxonMobil recently published a paper in which they used a combination of real experiments combined with virtual simulations that lead to the discovery of such a zeolite – EMM-17.
The ExxonMobil scientists initially performed the synthesis as part of a high-throughput screening exercise. They have since replicated the synthesis multiple times. With a large enough sample available, they have also performed characterization techniques such as electron microscopy, x-ray powder diffraction and solid-state NMR to understand the structure better.
They have subsequently used the data from these characterization experiments to develop and validate atomistic models that represent the three polymorphs of EMM-17. Using these atomistic models, they calculated the adsorption of n-hexane, cyclo-hexane and mesitylene onto both EMM-17 and the well-known ZSM-5 zeolite (see Figure 1). The results showed excellent agreement with experiment and demonstrated that cyclohexane can pack more efficiently into the pore of EMM-17.
Combining physical experimentation with virtual characterization is a powerful way to discover and understand new materials. Further supporting this with machine learning in an environment like the Dassault Systèmes 3DEXPERIENCE® platform, which combines virtual and real data, will lead to a revolution in new materials discovery.