Particle Size Distribution

Particles, including crystals, droplets, and bubbles, are present in the vast majority of manufacturing processes and their final products. The thorough understanding and proper control of particle size distribution is often a critical factor in final product quality and can greatly influence process efficiency.

For example, the effectiveness of medicines used to treat lung diseases has been shown to depend heavily on particle size. Large droplets (Figure A) deliver medicine in an ointment more slowly than small droplets (Figure B). It has also been reported that particulate process plants take longer to start up, and are less likely to achieve desired production rates, versus those processing liquids or gases. Multiphase systems involving combinations of particles, droplets, and bubbles result in additional complexity and magnify the challenge of understanding, optimizing, and controlling the processes used to produce, modify, or separate them. Crystallization in particular is a challenging particle formation process where the particle size after isolation can have a dramatic impact on all downstream processing operations. The separation time of a slurry (Figure C) can be heavily extended if small particles co-exist (Figure D).

Accurate offline analysis of particle and droplet systems depends on the successful removal and preparation of a representative sample from the process stream. This procedure is often complex, as most offline techniques impose strict constraints on the measurable range of particle concentration, size, and shape.

Sample preparation can be a labor-intensive and expensive multi-step process, potentially introducing errors that affect the final particle size distribution data. Common preparation methods, such as filtration, drying, subsampling, redispersion, and dilution, must be carefully controlled to prevent modifications to the sample.

Altered Sample Shape/Size Due to Changed Particle Environment

These sample preparation steps may significantly alter the particles or droplets of interest. Even with the utmost care and precision in the sampling and sample preparation methods, the actual particles that are analyzed may be significantly different from the particles that were initially present in the process vessel. For example, mannitol crystals image taken by real-time microscopy (Figure A) is significantly different from that taken by a standard offline light microscope (Figure B). Sampling and preparation for offline microscope analysis have resulted in significant breakage and delicate dendritic structures observed in process go undetected.

Assuming Spherical Shape

The particle size of non-spherical particles is often reported using an equivalent diameter. For example, in the right figures, particles with different shapes but equivalent volumes are depicted. If particle size is reported based on volume, the spherical sample and the needle-shaped sample are identical. However, the behavior and throughput of sieving the two samples might be quite different, because their sieve diameters and shapes are far from identical. Therefore, care should be taken to determine how shape influences particle size analysis results, and if possible to determine particle shape using a technique, such as EasyViewer imaging.

Effects of Time Delay

Since most particle process streams operate at a solids loading much higher than anything traditional particle size analyzers can handle, careful and time consuming sample preparation is needed for the measurement. The measurement and analysis takes time as well, from minimum minutes (e.g. by light scattering methods) to even longer (e.g. by sieving and offline microscopy).

In order to obtain continuous information, samples would have to be manually extracted frequently and analyzed on the fly. This approach may also impose unacceptable level of risk, especially for processes at elevated temperatures and pressures with toxic or explosive slurries and solvents. The inevitable time delay between sampling and the receipt of results with offline tools makes them difficult to implement for true real-time measurement, and makes them unsuitable for monitoring process continuously as it changes over time. Inline particle size analyzers are the recommended alternative.

Particle size, shape, and concentration are critical pieces of information at every stage or scale during a crystallization process and hence make critical quality attributes (CQA). Particle size analyzers quickly visualize and quantify particles and critical particle mechanisms for successful crystallization process development.

• Particle properties and particle mechanisms are recorded for review and analysis at all times, even if scientists cannot be in the lab.
• Interoperability between automated reactors and ParticleTrack and EasyViewer enable scientists to set up feedback control loops for particle size or count controlled cooling, or to set antisolvent dosing rates to minimize undesired particle populations, such as excessive fines.
• The intuitive "Start Experiment Wizard" makes it easy for every scientist to collect high-quality particle data quickly.

EasySampler is a fully automated, unattended sampling system optimized for delivering high-quality, representative samples essential for particle characterization and detailed analysis. Its probe-based design enables selective extraction of the solution phase even in the presence of suspended particles, ensuring precise and uncontaminated sampling critical for accurate crystallization and particle formation studies.

When integrated within a particle engineering workstation, EasySampler provides invaluable insights into solution-phase dynamics by generating comprehensive impurity profiles, revealing how supersaturation influences impurity incorporation, and facilitating the determination of kinetic and thermodynamic parameters governing crystallization. This functionality significantly advances the understanding of particle nucleation, growth, and morphology by correlating solution chemistry with solid-phase characteristics, thereby supporting rigorous scientific investigation and process optimization in particle engineering research.