IMX Seminar Series - Understanding the mechanisms and predicting the polymorphic outcome of crystallization processes with molecular dynamics simulations

Controlling and predicting the nucleation and growth of crystalline materials is fundamentally and practically relevant in many applications involving organic and inorganic systems alike. For instance, despite their crucial role in directing material synthesis, the mechanisms of self-assembly that initiate crystal precipitation remain elusive, limiting our ability to predict the polymorphic outcome expected from the manufacturing process of technologically important materials such as Active Pharmaceutical Ingredients (API). 
Molecular dynamics (MD) simulations can resolve the spatial and temporal scales associated with the formation of crystalline precursors and offer insight into the collective processes at the heart of crystallization. 
MD-based methods can be used either as a "virtual microscope", offering insight into details otherwise inaccessible to experiments, or as a tool to perform computational experiments to improve our understanding of structural stability and persistence. In this seminar, I will discuss recent results belonging to these two application areas of molecular simulations in crystallization. 

In the first part of the seminar, I will focus on the role of MD simulations in unveiling mechanistic aspects of the crystal precipitation process.
I will cover recent results on deviations from ideality of NaCl(aq) solutions in contact with the surface of graphite electrodes, discussing their potential role in the emergence of complex crystallization pathways associated with the heterogeneous nucleation of NaCl. [1,2]

In the second part, I will discuss the application of MD-based strategies to improve our ability to predict the polymorphic outcome of organic crystallization, which is essential to limit the risks associated with APIs manufacturing. In this context, MD simulations are used as computational experiments to introduce finite-temperature effects in a typical crystal structure prediction workflow applied to molecular systems of increasing complexity.
Here I will cover the advantages and current limitations of these approaches in rationally reducing the number of putative polymorphs predicted by traditional crystal-structure prediction methods based on static lattice energy calculations. [3,4]
 
[1] Multiple Pathways in NaCl Homogeneous Crystal Nucleation AR Finney, M Salvalaglio, Finney, A. and Salvalaglio, M., Faraday Discussions, 2021.
[2] Electrochemistry, Ion Adsorption and Dynamics in the Double Layer: A Study of NaCl(aq) on Graphite, AR Finney, IJ McPherson, PR Unwin, M Salvalaglio, Chemical Science 2021 (12), 11166-11180, 2021
[3] Reducing Crystal Structure Overprediction of Ibuprofen with Large Scale Molecular Dynamics Simulations N Francia, L Price, M Salvalaglio CrystEngComm 2021 (23), 5575-5584, 2021
[4] Systematic finite-temperature reduction of crystal energy landscapes NF Francia, LS Price, J Nyman, SL Price, M Salvalaglio, Crystal Growth & Design 20 (10), 6847-6862, 2020
Bio: Matteo obtained his PhD in Chemical Engineering from Politecnico di Milano, in 2011. After conducting postdoctoral research at ETH Zurich in a joint position between Chemical and Mechanical Engineering Departments, in 2015 Matteo joined the Chemical Engineering Department at University College London where he leads the Molecular Modelling & Engineering group (MME, https://www.ucl.ac.uk/molecular-modelling). The research activity of the MME group focuses on understanding nucleation and self-assembly from multicomponent liquid phases, polymorphic transitions in molecular materials, and crystal growth using molecular dynamics simulations and enhanced sampling methods.