Supervisors: Prof. Scott Habershon, Prof. David Quigley Organic molecular crystals can form in different polymorphs that may exhibit vastly different properties, such as melting point, light absorption, solubility and pharmaceutical activity. However, predicting the mechanisms by which different polymorphs crystallize remains a frontier challenge for the chemical sciences. In this project, we will develop a new simulation strategy to predict the key mechanistic pathways that form different polymorphs. Here, we will develop and test new strategies based on directed random walks in contact-map space to enable generation of intermediate ensembles associated with nucleation and crystallization to different polymorphs. Background Rationalising and controlling the formation of different polymorphs of organic molecular crystals is a frontier challenge spanning computational and synthetic chemistry. Importantly, different polymorphs of a molecular material can exhibit vastly different properties, such as melting point, light absorption and solubility. These difference in turn have important implications in areas spanning from drug development in the traditional pharmaceutical industry to organic solar material design. Here, we propose to develop and test an entirely new computational strategy for predicting the kinetic pathways that form different polymorphs. Specifically, this project aims to adapt our well-established graph-driven sampling (GDS) strategy to enable generation of intermediate ensembles associated with nucleation and crystallization to different polymorphs. GDS is a `directed walk’ strategy that operates by seeking out pathways connecting defined end-point structures – repeated GDS simulations can rapidly build up a picture of the landscape of intermediates that lie along the pathways connecting these end-points, providing detailed insight into competing mechanisms. GDS has to date been used to generate large-scale chemical reaction networks associated with catalysis, organic synthesis and interstellar chemistry - and has most recently been adapted to study the challenging problem of protein-folding pathway generation. Hypothesis and objectives Building on these varied proof-of-concepts, we hypothesise that GDS can equally be adapted to study crystallization/nucleation mechanisms towards different polymorphs; this project aims to deliver and validate this new strategy, as well as explore how information about kinetics can be used to enhance reaction-coordinate identification in polymorph prediction. Anticipated objectives are: Adapt our existing GDS code to model nucleation of solvent/solute systems towards user-defined polymorphs; Apply updated GDS strategy to generate nucleation pathways for well-studied toy model (e.g. Yukawa potential) and small-molecule (e.g. urea and glycine) examples; Using GDS-generated nucleation paths as a dataset, develop ML strategies to identify key reaction-coordinates for polymorph nucleation. About HetSys The EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems (HetSys), based at the University of Warwick, is an exceptional environment for students from physical sciences, life sciences, mathematics, statistics, and engineering. HetSys specializes in applying advanced mathematical methods to tackle complex, real-world problems across a variety of research areas. Our research themes span exciting topics such as nanoscale devices, innovative catalysts, superalloys, smart fluids, space plasmas, and more. HetSys provides: A vibrant, interdisciplinary student community. Flexible, tailored training opportunities. A collaborative environment that fosters creativity and growth. Interested? Join HetSys and help shape the future of sustainable technology through groundbreaking research. For more information about this project and how to apply, visit: https://warwick.ac.uk/fac/sci/hetsys/themes/projects2025. Funding Details Additional Funding Information For more details visit: https://warwick.ac.uk/fac/sci/hetsys/apply/funding/ Awards for both UK residents and international applicants pay a stipend to cover maintenance as well as paying the university fees and a research training support. The stipend is at the standard UKRI rate. Fully funded