Skip to main content
Go to the home page of the European Commission (opens in new window)
English English
CORDIS - EU research results
CORDIS

Novel Characterisation Platform for Formulation Industry

Periodic Reporting for period 1 - NoChaPFI (Novel Characterisation Platform for Formulation Industry)

Reporting period: 2020-02-01 to 2021-07-31

Industry often deals with solids in the form of small particles suspended in liquids. The size of the particles ranges from nanometers to microns (where 1 micron is one thousandth of a millimetre, and one nanometer is one thousandth of a micron). Such particles are in ceaseless motion because they are continually bombarded unevenly on all sides by the molecules in the liquid, which are themselves in ceaseless motion. Monitoring and quantitatively explaining the Brownian motion of sub-micron sized suspended particles was how Jean-Baptist Perrin and Albert Einstein first demonstrated conclusively the reality of molecules.

The rapidity of this Brownian motion is determined, amongst other things, by the size of the suspended particle: the smaller it is, the more rapid its Brownian motion. Dynamic light scattering (DLS) has long been a standard method of determining particle size via the monitoring of Brownian motion. However, the method suffers from a number of drawbacks, especially in industrial applications. First, its application depends on the suspension being optically transparent. This is not the case with most industrial suspensions at particle concentrations that are of interest. Secondly, real suspensions always contain particles of many sizes, such ‘polydispersity’ becomes increasing problematic for DLS when the range of sizes broadens. Finally, DLS requires the use of lasers and a specialised piece of electronics known as a ‘correlator’. It is therefore desirable to explore alternative methods for particle sizing via monitoring Brownian motion that do not suffer from one or more of these drawbacks. In this project, we explore the use of differential dynamic microscopy (DDM) to do so.

In DDM, one takes a low-resolution movie of the Brownian motion of particles in a suspension and then put the movies through a sophisticated computer analysis of the images to back out the rapidity of the Brownian motion of many hundreds or thousands of particles, from which one may deduce something about their average size and the spread in their sizes (the polydispersity). One way of implementing DDM was first invented 2008 by a Swiss team. Since then, a number of variants have been implemented worldwide. Supported by a grant from the Engineering and Physical Sciences Research Council in the UK and an ERC Advance Grant, the team at the University of Edinburgh (UoE) explored one implementation to measure the motion of swimming bacteria. Partly supported by an ERC Proof of Concept Grant, the UoE team subsequently commercialised the method for measuring the motility of bull sperms on the farm. A spin out company, Dyneval, is now exploiting this invention. In the current ERC Proof of Concept project, the same team explored the application of DDM to the sizing of particles in suspensions used in chemical manufacturing with an industrial partner.

The intention was to move the method from the academic research laboratory into an industrial environment, and explore suspensions ‘as they come’, rather than specially optimised to make DDM easy to perform. Another intention was to learn how to apply the method to suspensions during processing, e.g. when the samples are flowing or otherwise changing with time. Although somewhat disrupted by the COVID-19 pandemic, the project was successful in achieving these aims. We demonstrated that DDM is superior to DLS in its various forms in being able to size optically turbid suspensions. This should significantly expand the range of systems that can be characterised in industry. We also figured out how to implement DDM to size particles under flow, potentially opening up the method for use in in-line process monitoring. The team has also commissioned market research to help it to understand the range of potential applications in key industrial sectors.
My booklet 0 0