Malvern Instruments guide to using automated image analysis to detect agglomerates
Published by Katherine Guenioui,
Editor
World Cement,
Malvern Instruments has published new guidance on the use of automated image analysis to detect and quantify agglomerates. This is vital across a number of industries because uncontrolled agglomeration impacts the performance and value of powder products.
The guidance, called ‘Identification of agglomerates using automated image analysis’, presents practical strategies for efficiently and robustly differentiating agglomerates from primary particles, to support product development, QC and process troubleshooting. To view the application note, go to http://www.malvern.com/identifying-agglomerates.
Agglomerates are formed through the adhesion or cohesion of smaller primary particles. They can have serious implications for product performance, value and, in the case of pharmaceutical products, safety. Any tendency towards agglomeration must therefore be thoroughly investigated during product development, controlled during manufacture and checked in final product QC.
Automated imaging is a fast and efficient technique for studying the morphological characteristics of particulate materials. The new guidance shows how the combination of size and shape data can be used to securely classify particles as agglomerates, enabling the amount of agglomerated material present in a blend to be quantified. In particular, shape parameters such as particle convexity and circularity are shown to be important in differentiating primary particles and agglomerates.
Malvern’s Sysmex FPIA 3000 and Morphologi G3 image analysis-based particle characterisation systems employ advanced optics to record and analyse images of thousands of particles within suspensions, emulsions and dry powders in a matter of minutes. The Morphologi G3-ID extends the capabilities of image analysis by applying the technique of Morphologically Directed Raman Spectroscopy to enable the chemical identification of multi-component agglomerates that cannot be reliably classified on the basis of size and shape alone. Together, these automated imaging systems provide an efficient solution for robust agglomeration detection.
Adapted from press release by Katherine Guenioui
Malvern, Malvern Instruments and Morphologi are registered trademarks of Malvern Instruments Ltd
Read the article online at: https://www.worldcement.com/product-news/13112014/malvern-instruments-guide-to-using-image-analysis-to-detect-agglomerates-850/
You might also like
World Cement Podcast
In the latest episode of the World Cement Podcast, Senior Editor David Bizley is joined by Dr Andrew Minson of the GCCA to discuss the ins and outs of the recently launched Low Carbon Ratings (LCR) system.
Molins announce first quarter results
Net profit reached €48 million, equivalent to earnings per share of 0.73 euros, 6% lower than the same period of the previous year.