Fractal Chromatography: A New Phase in Separation Science?


The Column

ColumnThe Column-09-04-2014
Volume 10
Issue 16

The Column spoke to Tony Edge of Thermo Fisher Scientific about the development of a new type of stationary phase based on fractal-shaped particles.

The Column spoke to Tony Edge of Thermo Fisher Scientific about the development of a new type of stationary phase based on fractal-shaped particles.

Q: Why do we need a new type of particle for chromatography?

A. Chromatography is used in many industries, many of which are working with very large molecules such as proteins. When analyzing these large molecules, the larger mass results in dispersion issues because of the slower diffusion rates. This is a physical effect that relates to the porous nature of a traditional chromatography particle. By creating a surface where these effects are not observed the peak shape will be substantially improved.


Q: What are the limitations of current particles that are available?

A. There are currently two types of particles that are used in the analysis of proteins. The first type of particle is non-porous and suffers from a limited surface area, which will reduce the retentiveness of the stationary phase and also reduce the ability to load on sample.

Tony Edge

The second type of material that can be used is a porous material, which has a larger surface area, and hence a greater retentiveness for the compounds that can aid the separation process. Unfortunately, when looking at the physical dispersion processes that occur within the column a larger analyte molecule will diffuse at a slower rate in the porous region of the stationary phase because the stationary phase pores are not uniform. This will result in a difference in retention times of the analyte and hence broader peaks.

Q: You think that "fractal particles" offer a new alternative for separations. Can you explain why?

A. Fractal structures have some unique features; the space they occupy can be defined a fractional dimension, and for a true fractal there is self-similarity, that is the same shape is observed from close up as from a distance. In this way fractal particles offer the advantages of both non-porous and fully porous media. The fractal surface results in an increase in the effective surface area; however, the self-similarity associated with fractal particles means that they do not suffer from molecules effectively seeing regions of the stationary phase which inherently give greater retention of a compound because of a difference in the pore structure. This can be likened to a ship trying to dock on a coastline. At a large scale, say a few miles, it may appear that the coastline is very similar along its whole length, and hence no matter where the ship wants to dock, it will always experience the same type of interactions with the sea and the coastline; however, as we zoom in it becomes very apparent that this is not the case and that some parts of the coastline will be better for docking than others. The same analogy can be applied to a silica particle, which at a larger scale may appear to be fairly uniform, but as we zoom into the pores it becomes very evident that the pores have different depths and shapes which will affect the retention of the analyte molecules. With a true fractal structure there is scalability and so we can see the same surface structure no matter what scale we are looking at, and hence the analyte will experience the same type of interactions no matter where it is on the surface of the stationary phase. Figure 1 gives an example of this with the Koch Curve, zooming in on the structure will always give you the same shape.

Figure 1: An example of a scalable fractal structure. (a) The shape if made by replacing all straight lines with the primary shape, and (b) (c) keep repeating this process ad infinitum. For the final shape no matter what scale we view it at it will always have the same structure.

Q: How do you "grow" a particle? How easy is it to control this process?

A. The process of growing a particle is not so different from that used in the production of traditional fully porous media. A monomer is initially added to the vessel with an initiator that starts the polymerization reaction. The addition of a porogen (a surfactant molecule) will result in pores being generated within the structure.

Modification or removal of the porogen or some of the other reagents will result in a different morphology being generated. In terms of controlling the process, we have demonstrated that we can replicate the different morphologies that we have created on a regular basis. We have thus been able to create fully porous spherical structures, a solid core structure, a solid core with a few small solid spheres on the surface, a solid core with large spheres on the surface, and quite a few other types of structures as well, with and without porosity. Some of these shapes are shown in Figure 2. All of these different structures have been mapped out as a function of the ingredients to manufacture them so that we can then ascertain not only how to reproducibly make a specific morphology, but also to make as yet uncreated morphologies, by interpolation of the data. The parameters that we have investigated include the use of different pHs, different modifiers, different porogens, and different starting reagents.

Figure 2: Some examples of the different morphologies that can be created by varying the silica recipe.

Q: Have you any examples of "fractal chromatography" in practice?

A. Yes, the laboratory at Liverpool has started to develop these particles and we have very recently started to test them with real peptides and proteins. When we compare these particles with traditional media we are already obtaining comparable performance. We have yet to go to very big analytes, which is where we anticipate that we will see the biggest performance gains.

Q: Can you see this technology being readily embraced? What are the main obstacles that have to be overcome to make this approach viable in practice?

A. The field of protein analysis is very interesting because it brings a whole new generation of chromatographer, whose previous focus was biology, into separation science. This band of scientists are very open minded to new ideas and are ready to learn new technology, particularly in the field of separation science. We are therefore very hopeful that the technology will be embraced by this pioneering group.

In terms of obstacles, we have to demonstrate that we can manufacture the product at a commercial scale. Currently we can make pot sizes up to 50 g, but we will have to increase this by a factor of 10 to allow full commercialization. As mentioned previously, we also have yet to test the particles with very large proteins.

Q: What are your next steps?

A. The Liverpool team is still looking at developing other particle morphologies that have fractal properties, and then working with external collaborators who have real challenges that they cannot resolve using conventional technology. We are hopeful that we will be in a position where we will have a range of morphologies that will be suitable for different sizes of analytes.


The author would like to acknowledge the contributions made by Richard Hayes, Dr Adham Ahmed, Dr Haifei Zhang, and Professor Peter Myers from Liverpool University who generated all of the particles discussed in this article.

Tony Edge is currently the R&D Principal for the chromatography consumables division within Thermo Scientific. Tony has over 15 publications in refereed journals including a book chapter on turbulent flow chromatography. In 2008 he was fortunate enough to be awarded the Desty memorial lecture for his contributions to innovating separation science, and in the same year also won a clinical excellence award from AstraZeneca. Tony's current interests are centred on improving the extraction process and high temperature chromatography. Tony was recently awarded an honorary fellowship at the local university, where he lectures on separation science.



This article is from The Column. The full issue can be found here:

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