Crystal morphology is known to significantly influence the end-use efficacy of solid products generating immense interest in the ability to predict and engineer crystal morphology. We make efforts to improve upon classical mechanistic models of crystal shape to develop understanding and quantitative platforms to engineer crystal morphology for specific applications. The classical Burton, Cabrera and Frank spiral growth model for crystal growth fails to work satisfactorily for many real systems such as active pharmaceutical ingredients (APIs), non-linear optical compounds, etc., due to the inherent assumption of a simple Kossel crystal structure in the model, which essentially means dealing with symmetric systems experiencing isotropic conditions on all faces. The development of a more general mechanistic spiral growth model that is not just limited to the traditional centric systems but enables morphology prediction for all kinds of organic molecular crystals is outlined and validated for many important real systems. The first three chapters describe the classical methodology and the development and demonstration of the new spiral growth model for non-centrosymmetric growth units.

Foreign molecules such as additives or impurities may influence the crystal morphology to a significant extent by inhibiting the growth mechanism of certain crystal faces. A generic probabilistic scheme for quantitatively estimating imposter recognition on each crystal face and hence computing modified crystal habits is presented. The fourth chapter describes the growth model for additives. Finally, a contextual analysis for organic salts and polar crystals is investigated in the fifth chapter.