Towards automated sampling of polymorph nucleation and free energies with SGOOP and metadynamics

Abstract: Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process as well as correctly calculating the relative free energies of different polymorphs. Here we demonstrate, for the prototypical case of urea nucleation from melt, how one can learn such a 1-dimensional reaction coordinate as a function of pre-specified order parameters, and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of generic thermodynamic and structural order parameters using the "Spectral Gap Optimization of Order Parameters (SGOOP)" approach [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. (2016)], and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insight into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. We believe the ideas demonstrated in thus work will facilitate efficient sampling of nucleation in complex, generic systems.