32+ Shape Parameters
Far beyond size-only instruments that give just one measurement
Direct Measurement
Measures the actual particle, not an indirect approximation
Number-Based
Individually measures every particle for statistically representative results
Identification Tool
Detects agglomerates, contamination, and lot-to-lot differences
Particle characterization is the process of measuring various properties of particles, such as size, shape, surface area, or other physical or chemical properties. Characterization is done using a broad range of commercially available techniques that can be used to measure particulate samples. Each has its strengths and limitations, and there is no universally applicable technique for all samples and all situations.
Initial use of characterization is typically done in the exploratory or research phase of any project involving raw particulate materials. Investigators use particle characterization methods to better understand key properties that can impact the end product or the manufacturing process. As development progresses, particle characterization methods are typically transferred to the manufacturing process, where the control of various parameters is measured to ensure the manufacturability and efficacy of the final product.
For many years, particle size has been a vital characterization method. Most of the established techniques for particle size characterization are indirect measurement techniques that render particle size information assuming all the measured particles are round. In reality, most particles in the industry are not round, leaving significant doubt on the ability of size-only techniques to offer enough characterization information. Irregular particle shape can significantly impact how particles interact with each other, how they flow, and how they compact, ultimately affecting the efficacy of products.
In 1963, the “Krumbein Scale” was presented for geologists who wanted a standardized way to measure particle roundness and sphericity. This scale was visual with sample images on a sheet of paper to compare particles and was subjective. However, this tells us that for many decades, the need to understand particle shape has been just about as critical as particle size.
It wasn’t until the early 1990s when improved machine vision cameras and higher performing computers were around to start analyzing the shape of particles in a more standardized way with a much higher sampling of particles. Image Analysis, whether the particles are static or dynamically moving, involves very fast image processing.
Commercial shape analysis systems began to appear on the market in the 1990s and 2000s. Although systems offered particle size as one of the 32+ available shape measures, it was still considered a new technique competing against well-established size-only instrumentation such as laser diffraction. Around 2014 we developed one of our systems to work not as a standalone system but as an accessory to other laser diffraction systems in the industry. From this, shape analysis has become known as a complementary method to different size-only techniques.
Many scientists and users today know how particle shape instrumentation can be used not only as a characterization but also as an identification tool. Regarding characterization, many use shape analysis to quantify the percentage of different particles in a mixed sample. For example, a user can characterize the percent of excipient to active pharmaceutical ingredients after mixing. A change in the percentage can be catastrophic to an end user and can be identified easily with shape analysis.
I believe that anyone that is doing material characterization understands particle shape and the importance it plays in their final product. This is why it is relatively new but growing at a very fast rate. Over the years, particle shape is playing a larger role as a complement to particle size. Particle shape analysis also offers many other benefits due to the nature of the dynamic image analysis technique, which makes it even faster growing.
The ability to make over 32 different shape calculations of every particle, as well as measuring concentration, awards us with the ability to use this information to identify issues where size-only instruments can’t. I have seen numerous instances where differences in shape, not size, were used to identify different lots of raw materials. Particle thumbnails help users to detect and identify large particles as either bubbles, agglomerates, or contamination.
Dynamic image analysis is a number-based technique. This means that it measures particles individually. In addition, dynamic image analysis is a direct measurement technique — measurements are being made of the actual particle. Highly popular indirect measurement techniques will always report particle size assuming the particles are round in shape. The ability to measure and detect individual particles and give you dozens of shape measurements for every particle, including size, are two reasons why dynamic image analysis is gaining popularity.
We are in the constant fight against physics to find faster and better ways of detecting, analyzing, and processing information that gives the end-user more information without having to guess. Continuous incorporation of technological improvements will enable particle shape analyzers to have a broader scope of applications. We have systems that are bench-top in nature, but we also have systems that are portable, and many are now online, offering immediate feedback on raw material process issues.
Particle Shape instrumentation uses Image Analysis and is either Static or Dynamic in operation. Static systems are automated microscopes that offer very good image quality but take significant time to get representative results. Dynamic Image Analysis systems enable the analysis of particles while in motion enabling the characterization of tens of thousands of particles in minutes, giving statistically representative results in a short time. It also allows detecting and characterizing rare events such as agglomerates or low quantity contamination with thumbnail images as objective evidence.
Users looking for particle shape systems typically understand particle size but feel they are missing some key information that’s having an impact on their final product. It is not the user’s responsibility to figure out how to use these 32 shape parameters. It is the responsibility of the instrument manufacturer to develop tools that take advantage of all of this information and offer tools such as particle classification, particle correlation, particle concentration, shape overlays, and many more.
About Vision Analytical
Vision Analytical, located in Miami, Florida, USA, was established in 2007 and is focused on using Dynamic Image Analysis as its core technique to develop instrumentation and software to assist numerous industries in their characterization methods. Numerous versions of the “Insight” product line have been developed for specific uses where size, shape, and concentration are critical particle characterization parameters to monitor.
