title: Optimization of charged species separation by autogenous electric field-flow fractionation in nano-scale channels.
abstract: Numerical methods are employed to examine the resolution and optimization of a relatively new technique for charged species separation that is based on flow along nano-scale channels having an electric double-layer thickness comparable to the channel size. In such channels, the electric field inherent to the double-layer produces transverse species distributions that depend on the species charge. Flow along the channel thus yields mean axial species speeds that also depend on the species charge, enabling species separation and identification. Building on earlier work describing retention and plate heights, here we characterize this new type of field-flow fractionation via the classic metric of resolution. Sample results are presented and discussed for a wide range of conditions for both pressure-driven and electroosmotic flows. Optimum design and operating conditions are also examined. We find that resolution is maximized for optimum values of the zeta potential and Debye layer thickness and that these optima depend strongly on the species charge or range of charges of interest. Under optimum conditions, acceptable resolution can be obtained over a wide range of species charges for pressure-driven flows. This separable range of charges is much smaller for electroosmotic flows. Finally, sample calculations are presented showing that all species in the range of charge between -8 to 10 can be separated simultaneously with resolutions above unity, and this is possible in less than 6 s under optimum conditions that are readily achievable.
authors.affiliation: Sandia National Laboratories, Livermore, CA, USA. skgriff@sandia.gov
authors.forename: Stewart K
authors.initials: SK
authors.lastname: Griffiths
authors.forename: Robert H
authors.initials: RH
authors.lastname: Nilson
mesh_terms: D000465:Algorithms; D004586:Electrophoresis / Q000379:methods*; D031521:Fractionation, Field Flow / Q000379:methods*; D007477:Ions / Q000737:chemistry; D008956:Models, Chemical; D036103:Nanotechnology / Q000379:methods*
chemical_list: D007477:Ions