Chemists, engineers, and biologists are often challenged by processes involving particle or droplet systems. Solid or liquid dispersion, homogenization, agglomeration, or precipitation can create variability in product stability and manufacturing throughput. To develop and manufacture world class products at competitive costs, scientists and engineers use inline particle size measurements to optimize process conditions and consistently meet product quality specifications, at the bench or in manufacturing.
From suspensions to emulsions to crystallizations, inline particle size, shape, and count measurements are applied at full process concentration and in translucent or opaque systems to understand, optimize, and control a process. Companies like Ajinomoto, Proctor & Gamble, Dupontand Nalcoare well known to apply best practices with inline particle size characterization for:
Improving Product Stability
Consistently Meeting Particle Size Specifications
Ensuring Product Repeatability
Detecting Fines Formation To Improve Solid/Liquid Separations
A challenge with traditional particle and droplet size measurement techniques is that most technologies are offline and require sampling, sample preparation, and remote analysis. Offline samples are often prepared and then altered through dilution, dispersion, or drying, which can alter or destroy particle or droplet components, and offline measurements cannot be applied to make real-time process optimization and control decisions.
With established particle characterization technology, scientists and engineers can measure particle and droplet phase behavior in situ without sampling or dilution. They can track the particle and droplet system at full concentration and operating temperature and pressure. This enables real-time decisions to improve process performance, and optimize product quality.
The White Paper – Best Practice for Inline Particle Size Characterization – shows how scientists and engineers apply inline particle size and count measurements to troubleshoot and improve process performance and product quality. By implementing inline technologies, companies avoid offline sampling and sample preparation errors as well as enable the real-time optimization of processes.