Controlling polymorphism
Using particle shape to identify different polymorphic crystal forms
Using particle shape to identify different polymorphic crystal forms
In this article we consider the issue of polymorphism detection with reference to the example of L-glutamic acid, a compound widely used in the food industry for the production of monosodium glutamate. Images and analyses produced using the Morphologi G2, a high sensitivity particle image analyser, show how particle shape parameters can be used to differentiate between polymorphic forms. This analytical approach is a cost-effective way of identifying and characterising polymorphism in the processing environment.
L-glutamic acid is a monotropic polymorphic compound. Transformation between the _- and _-polymorphs is solution-mediated. The _-polymorph of L-glutamic acid has a granular consistency (Figure 1a) whilst the _-form has a needle-like flaky structure (Figure 1b). For the production of monosodium glutamate the _-form is preferred as it is more robust; the _-polymorph tends to break during downstream handling and therefore processes less well. The _-polymorph is, however, the less stable form and therefore care needs to be taken during preparation to ensure that material with the required polymorphic specification is produced.
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| Figure 1a. _-form of L-glutamic acid | Figure 1b. _-form of L-glutamic acid | Figure 1c. _-Form of L-glutamic acid with _-Form nucleating off it and indication of polymorph transition from _- to _-Form |
Batches of the _-polymorph are produced by rapid cooling crystallisation. Slower cooling rates are associated with the formation of the _-form, often through a process of nucleation on the _-polymorph. The identification of particles showing evidence of this process is therefore important for the detection of polymorphic transformation (Figure 1c). If using volumetric particle size distribution analysis alone is not enough to differentiate between polymorphic forms, shape analysis can often allow variation between different batches to be identified.
The Morphologi G2 (Malvern Instruments) uses automated microscopy coupled with digital image analysis to measure particle size and shape in a statistically significant way. Size and shape data are easily generated and individual images of all the particles analysed are produced for visual scrutiny. Three batches of L-glutamic acid, A, B and C, were measured using the 2.5X magnification and a preset Standard Operating Procedure (SOP).
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| Figure 2. Overlay of size distribution plot of the three samples |
The volume equivalent size distribution of the three samples is broadly similar (Figure 2). A shape distribution, generated using the image analysis toolbox, reveals that sample C is, however, significantly different in terms of circularity from samples A and B (Figure 3).
Circularity is a measure of the ‘closeness’ of the particle to the shape of a perfect circle. High sensitivity circularity is calculated using the following formula:
HS Circularity = 4πA/P2
Where A=area and P=actual perimeter.
The Morphologi G2 stores the images of all the particles measured, together with the individual morphological parameters. The system also stores the x and y coordinates of every particle it measures, so individual particles can be examined more closely in manual microscope mode if required, at, for example, higher magnification. A study of the individual particle images for sample C reveals that many of the _-polymorph particles have _-polymorph crystals nucleated on their surfaces (Figure 1c). This indicates that with batch C there was a problem with the cooling process.
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| Figure 3. Overlay of the circulatory plot of the three samples |
This study demonstrates how the Morphologi G2 can be used as a tool for monitoring batch crystallisation processes for the production of crystals with the required polymorphic form. Using shape parameters different polymorphs may be rapidly and cost effectively identified in a way that is not possible using particle size distribution data alone. Early diagnosis of crystallisation problems allows downstream processing problems to be prevented, eliminating a source of process inefficiency.