Computational Discovery of Molecular C60 Encapsulants with an Evolutionary Algorithm
A function-led computational discovery using an evolutionary algorithm was used to find potential fullerene (C60) encapsulants within the chemical space of porous organic cages. This makes use of a tailored fitness function that includes consideration of the interaction energy between the cage and the C60 molecule, the shape persistence of the cage, and the symmetry of the assemblies. We find that the promising host cages for C60 evolve over the simulations towards systems that share features such as the correct cavity size to host C60, planar tri-topic aldehyde building blocks with a small number of rotational bonds, di-topic amine linkers with functionality on adjacent carbon atoms, high structural symmetry, and strong complex binding affinity towards C60. The proposed cages are chemically feasible and similar to cages already present in the literature, helping to increase the likelihood of the future synthetic realisation of these predictions. The presented approach is highly generalisable and can be tailored to target a wide range of properties in molecular encapsulants or other molecular material systems.