The classical Burton−Cabrera−Frank (BCF) spiral growth model fails to work satisfactorily for many non-centrosymmetric organic molecules such as active pharmaceutical ingredients (APIs), nonlinear optical compounds, etc., due to the inherent assumption of Kossel crystal structure in the solid-state. We develop a more general mechanistic spiral growth model that enables morphology prediction for all kinds of organic molecules. We develop generalized expressions for kink density, kink incorporation rate, and step velocities for such molecules. Stable and unstable edges arising due to the complex bonding pattern are discussed and treated. We demonstrate the applicability of the model by correctly predicting the experimental morphologies of paracetamol and lovastatin grown from solution.
Crystallization is an important separation and particle formation technique in the manufacture of high-value-added products. During crystallization, many physicochemical characteristics of the substance are established. Such characteristics include crystal polymorph, shape and size, chemical purity and stability, reactivity, and electrical and magnetic properties. However, control over the physical form of crystalline materials has remained poor, due mainly to an inadequate understanding of the basic growth and dissolution mechanisms, as well as of the influence of impurities, additives, and solvents on the growth rate of individual crystal faces. Crystal growth is a surface-controlled phenomenon in which solute molecules are incorporated into surface lattice sites to yield the bulk long-range order that characterizes crystalline materials. In this article, we describe some recent advances in crystal morphology engineering, with a special focus on a new mechanistic model for spiral growth. These mechanistic ideas are simple enough that they can be made to work and accurate enough that they are useful.
Foreign molecules such as additives or impurities may influence crystal morphology to a significant extent by disrupting the growth mechanism and inhibiting the growth rate of certain crystal faces. The additives can be byproducts of a preceding reaction step, or they could be specially designed to obtain specific crystal morphologies for particular applications. Because of the specific chemical structure of structurally similar additives, they can incorporate or lock into the original lattice only in certain configurations; hence, only some of the crystal faces are able to recognize these additive molecules. Once attached, they interfere with the first turn of a rotating growth spiral and hence slow down the growth rate of the face. In this article, we develop a generic probabilistic scheme for quantitatively estimating imposter recognition on each crystal face using a combination of mean field theory and configurational energy minimization. On the basis of this recognition, the mechanistic effect of an impurity on the first turn of the spiral and hence the modified growth rates and modified crystal habits are computed. These concepts are generalized for all molecular crystals, including non-centrosymmetric molecules. We demonstrate the applicability of the model by correctly predicting the experimental morphologies of α-glycine with l-alanine impurity and paracetamol with p-acetoxyacetanilide impurity grown from water.
Crystal habit of drug molecules can have significant influence on the processing and performance of pharmaceutical products. During the development of Trilipix, a pharmaceutical product used for the treatment of mixed dyslipidemia, several crystal habits were observed for the active ingredient choline fenofibrate. The dissolution and performance of the drug product were not impacted by changes in crystal habit of the active ingredient due to high solubility of the drug. However, the formulation process was impacted by variations in crystal habit of the active ingredient, requiring robust control of the crystal habit. The crystal habit was greatly influenced by supersaturation during crystallization from a mixed solvent system comprising methanol and isopropanol. In addition to supersaturation, trace levels of a polymeric impurity in the starting material fenofibrate had a detrimental effect on the crystal habit. This article discusses the effects of these factors on the crystal habit of choline fenofibrate and the design of a crystallization process to deliver the target crystal habit, most suited to the formulation process. The article also provides preliminary mechanistic insights into the crystal habit of this organic salt using an extension of the spiral growth model for morphology prediction of organic molecular crystals. An attempt is made to explain the effect of supersaturation and impurity on the crystal habit of choline fenofibrate using the concepts of stability of surfaces, building units, periodic bond chain theory, and the spiral growth model.
There is a growing interest in predicting and controlling the size and shape of crystalline particles. Multidimensional population balances have been developed to accomplish this task but they suffer from the drawback of needing rate laws for the absolute growth rate for every family of faces that may appear on the crystal surface. Such growth rates are known for only a handful of crystalline materials and prospects are bleak for extending the library of growth rate data. This raises the question of where the surface growth rates for all the families of faces will come from to drive multidimensional population balance engineering technology. One answer is “from first principles.” We reformulate multidimensional population balances in terms of relative growth rates and show how to create first principles mechanistic models to calculate these quantities for real molecular crystals as a function of supersaturation. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3468–3474, 2013
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.