Understanding MOF nucleation from solution with Evolving Graphs

Molecular modeling is ordinarily employed to understand the synthesis of complex materials. In this work, we investigate the collective assembly of building units that have been experimentally observed to initiate Metal-Organic Framework (MOF) nucleation. MOFs exhibit attractive characteristics such as remarkable surface area and diverse porosities, however, a mechanistic understanding of their synthesis and scale-up remains underexplored due to the complicated nature of the building block interactions. Here, we tackle this problem with large-scale molecular dynamics simulations under a variety of synthesis conditions and mixture compositions. We observe that the connectivity of building units, as well as their level of crystalline order and fractal dimension, largely vary depending on the synthesis conditions. However, these properties naturally emerge when interpreting the self-assembly process of MOF nuclei as the time-evolution of an undirected graph. The results show that solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly, such diversity is captured by key features of the graph representation. Principal Component Analysis (PCA) on graph properties successfully deconvolutes MOF self-assembly to be characterized by a small number of molecular descriptors, such as average coordination number between half-secondary building units (half-SBUs) and fractal dimension, which can be followed by time-resolved spectroscopy. We conclude that graph theory can be used to understand complex processes such as MOF nucleation by providing molecular descriptors accessible by both simulation and experiment.