How To Measure Crystal Size Distribution

• Introducing Crystallization and Precipitation
• Fundamentals: Solubility and Metastable Zone Width
• Supersaturation: The Driving Force for Crystallization

Offline analysis is commonly used to determine crystal distribution at the end of an experiment or during a production run. While such an approach is common, there are limitations to offline analysis which are relevant for crystals:

• Crystals are delicate and change with temperature – making representative sampling and analysis particularly difficult
• Many crystal systems are toxic and do not lend themselves well to sampling
• It is difficult to take enough offline samples to determine how a fast changing process, such as crystallization, behaves with respect to time.
• The time delay between sampling and offline analysis is often too long, especially in production, to make relevant decisions that can improve product quality

This set of ParticleView images neatly illustrates the complex size, shape, and structure of various crystals. From large round “boulders” to beautifully delicate “dendrites”, crystal product is often varied, posing challenges to effective separation and downstream manipulation.

• The crystals in Image A will likely filter quickly and consistently. The larger boulders will leave plenty of space for the filtrate to pass through rapidly.
• Flat plates like these in Image B can be some of the most difficult to filter. Plates tend to stack on top of each other creating a layer of crystals that the filtrate cannot get through. This leads to long and potentially variable filtration times, depending on how the crystals are discharged from the crystallizer.
• Image C illustrates another case where filtration times can be long. Small crystals will plug the gaps left by the larger crystals making it difficult for the filtrate to pass through the bed of crystals. This is a common problem because many crystallization processes are designed with a fast cool or anti-solvent addition step at the end of the crystallization (to increase yield) that leads to excessive secondary nucleation. Additionally, in many cases the agitation is increased at the end of the batch to help with discharge and this leads to crystal breakage.
• Image D is more common than many would expect, at least in organic crystallization systems that are seeded. A structure such as this would be difficult to observe using an offline microscope as it will be crushed during sampling and preparation. However, ParticleView reveals a beautiful dendritic structure. A dendrite such as this often forms when crystallization is seeded with milled seed. Imperfections on the crystal surface lead to crystal growth from these areas and long crystal branches growing from a seed core. It is difficult to predict how something like this will filter, but it is likely to break apart resulting in variable filtration times.

By studying crystals in real time, scientists can develop detailed and reliable process understanding on a routine basis. ParticleView V19 with PVM technology allows scientists to directly observe crystals and crystal structures in process without having to take a sample.

Crystallization mechanisms such as nucleation, growth, breakage, and shape changes can be observed under dynamic changing process conditions and the most suitable process parameters can be chosen with confidence. A simple image-based trend that indicates how crystal size, shape, and count complements high resolution real time images and allows important process events to be identified and investigated immediately.

Using ParticleTrack, scientists can:

• Study crystal count in individual size classes – to optimize fine and coarse ends of the crystal size distribution
• Identify the root cause of a poorly performing crystallization process
• Choose the correct process parameters for optimal crystallization performance using process-based evidence
• Monitor processes for repeatability and consistency
• Correlate in-process measurements to offline particle size analysis
• Model the influence of crystal size and count on product and process quality

A ParticleTrack probe with FBRM technology is immersed into a flowing slurry or droplet system with no dilution necessary. A focused laser scans the surface of the probe window and tracks individual chord lengths - measurements of particle size, shape, and count. This real-time measurement is presented as a distribution and statistics (eg. mean, counts) are trended over time.

Crystallization unit operations offer the unique opportunity to target and control an optimized crystal size and shape distribution. Doing so can dramatically reduce filtration and drying times, avoid storage, transport, and shelf life issues, and ensure a consistent and repeatable process at a lower cost.

This white paper series covers basic and advanced strategies to optimize crystal size and shape distribution.

Discover how image-based process trending can reduce crystallization cycle time and improve quality while maintaining a similar crystal size and shape.

This white paper discusses best practices for designing a seeding strategy and what parameters should be considered when implementing a seeding protocol. Although crystallization understanding has improved over the last thirty years, the seeding step still presents challenges.