Nucleation rate and stacking propensity of benzoic acid derivatives: an experimental and molecular dynamics study

The mechanism of nucleation remains poorly understood due to the lack of experimental techniques capable of directly observing it. Gaining insight into nucleation is crucial for controlling crystallization processes and for the design of drug molecules and functional materials with tailored properties. This study aims to investigate nucleation indirectly, by determining the nucleation rates of benzoic acid derivatives and performing molecular dynamics simulations [1,2]. Nucleation rates of 4-bromobenzoic acid and 4-(methoxycarbonyl)benzoic acid were determined using the Crystal16 automated crystallizer, based on induction time experiments [3,4]. Five different supersaturations in isopropanol at 20 °C were tested, repeating each experiment 80 times to account for the stochastic nature of nucleation, yielding a total of 400 experiments per compound. The experimentally determined nucleation rates were added to a dataset of other benzoic acid derivatives measured under identical conditions [3,4]. The nucleation propensity of each compound was evaluated by identifying the supersaturation at which a predefined nucleation rate is reached. Molecular dynamics simulations were carried out using the free, open-source MiCMoS software [5,6], to simulate the liquid phase above and below the melting points of selected benzoic acid derivatives with varying stacking energies. Stacking propensity was estimated by analysing frequency and persistence of stacking interactions, as observed in the simulations. Finally, the correlation between nucleation propensity and stacking behaviour was examined, offering insights into the role of stacking interactions in the nucleation process. [1] L. Sironi, G. Macetti, L. Lo Presti, Phys. Chem. Chem. Phys., 2023, 25, 28006-28019. [2] L. Sironi, G. Macetti, L. Lo Presti, J. Mol. Liq., 2024, B414, 126141. [3] A. J. Cruz-Cabeza, R. J. Davey, S. S. Sachithananthan, R. Smith, S. K. Tang, T. Vetter, Y. Xiao, Chem. Commun., 2017, 53, 7905-7908. [4] S. K. Tang, R. J. Davey, P. Sacchi, A. J. Cruz-Cabeza, Chem. Sci., 2021, 12, 993-1000. [5] G. Macetti, L. Sironi, L. Lo Presti, Classical molecular dynamics simulation of molecular crystals and materials: old lessons and new perspectives in Comprehensive Computational Chemistry, Elsevier, 2024, 777-803. [6] A. Gavezzotti, L. Lo Presti, S. Rizzato, CrystEngComm, 2022, 24, 922-930.