title: Understanding and design of existing and future chromatographic support formats.
abstract: The present contribution reviews the use of alternative support formats as a means to surpass the chromatographic performance of the packed bed of spheres. First, a number of idealized structures are considered to obtain a general insight in how the performance of a chromatographic support depends on its shape and size, using the isocratic peak-capacity generation speed as the main performance indicator. Using this criterion, it is found that the packing density or, equivalently, the external porosity, is the most important of all geometrical shape factors. Depending on whether the sample consists of weakly or strongly retained components, the optimal external porosity can be expected to vary between 60% and a value near 100%. The optimal exploitation of a high external porosity, however, also requires overall shrinkage of the domain size, towards and into the sub-micron range. With the current fabrication technologies, this requirement seems difficult to achieve. In the presence of a lower limit on the characteristic support size, each range of desired plate numbers or peak capacities has its own optimal external porosity, ranging from a very low value (high packing density) for high speed, small peak capacity applications, to very high external porosities (low packing density) for applications requiring a very large peak capacity. Subsequently, the obtained theoretical insights are used to review and discuss the past and current research on alternative support formats. Finally, a number of emerging micro- and nano-fabrication technologies are introduced and their potential for the future production of supports with improved shape and homogeneity is discussed.
authors: Department of Chemical Engineering, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium.
authors: J
authors: J
authors: Billen
authors: G
authors: G
authors: Desmet
mesh_terms: D002853:Chromatography, Liquid / Q000295:instrumentation* / Q000379:methods; D005544:Forecasting; D008433:Mathematics; D016062:Porosity; D012822:Silicon Dioxide / Q000737:chemistry
chemical_list: D012822:Silicon Dioxide