Online Monitoring of the Concentrations of Amorphous and Crystalline Mesoscopic Species Present in Solution

Mesoscale Clusters in the Crystallisation of Organic Molecules

The early stages of the molecular self-assembly pathway leading to crystal nucleation have a significant influence on the properties and purity of organic materials. This mini review collates the work on organic mesoscale clusters and discusses their importance in nucleation processes, with a particular focus on their critical properties and susceptibility to sample treatment parameters. This is accomplished by a review of detection methods, including dynamic light scattering, nanoparticle tracking analysis, small angle X-ray scattering, and transmission electron microscopy. Considering the challenges associated with crystallisation of flexible and large-molecule active pharmaceutical ingredients, the dynamic nature of mesoscale clusters has the potential to expand the discovery of novel crystal forms. By collating literature on mesoscale clusters for organic molecules, a more comprehensive understanding of their role in nucleation will evolve and can guide further research efforts.

The interplay between nucleation and patterning during shear-induced crystallization from solution in a parallel plate geometry

Cooling crystallization of small organic molecules from solution is an important operation for the separation and purification of drug products. In this research, shear-induced nucleation from a supersaturated solution is studied in a parallel plate geometry. Under conditions of shear and small gap sizes, narrow mesoscale circular bands of small crystals appeared spontaneously and reproducibly on the plate's surface. We have investigated the connection between nucleation and the emergence of these circular patterns. Our results show that nucleation occurs preferably in zones with high local shear rate (located at the outer edges of the plates), compared to zones with low local shear rate (at the center of the plates). The time before nucleation occurs decreases significantly for increasing mean shear rate and time. The circular crystalline patterns appear at the plate's surface, where heterogeneous nucleation first occurs. Multiple hypotheses are explored to understand the pattern formation in crystallization. Since no satisfactory explanation is found, a new mechanism is proposed. This hypothesis involves crystals initially forming on the surface of the plates and undergoing stick-slip motion, which influences the local nucleation kinetics. This results in an interplay between (secondary) nucleation and stick-slip motion at the start of the crystallization process. By modifying the surface of the plates, their ability to act as a heterogeneous nucleation site can be altered, allowing control over the formation of patterns.

Conceptual Validation of Stochastic and Deterministic Methods To Estimate Crystal Nucleation Rates

This work presents a generalized framework to assess the accuracy of methods to estimate primary and secondary nucleation rates from experimental data. The crystallization process of a well-studied model compound was simulated by means of a novel stochastic modeling methodology. Nucleation rates were estimated from the simulated data through multiple methods and were compared with the true values. For primary nucleation, no method considered in this work was able to estimate the rates accurately under general conditions. Two deterministic methods that are widely used in the literature were shown to overpredict rates in the presence of secondary nucleation. This behavior is shared by all methods that extract rates from deterministic process attributes, as they are insensitive to primary nucleation if secondary nucleation is sufficiently fast. Two stochastic methods were found to be accurate independent of whether secondary nucleation is present, but they underestimated rates in the case where a large number of primary nuclei are formed. We hence proposed a criterion to probe the accuracy of stochastic methods for arbitrary data sets, thus providing the theoretical foundations required for their rational use. Finally, we showed how both primary and secondary nucleation rates can be inferred from the same set of detection time data by combining deterministic and stochastic considerations.