A data analysis algorithm for programmed field-flow fractionation

An algorithm that employs numerical integration for analysis of field-flow fractionation (FFF) data is presented. The algorithm utilizes detector resp onse, field strength, and channel flow rate data, monitored at discrete tim e intervals during sample elution to generate a distribution of sample comp onents according to particle size or molecular weight. The field strength a nd channel flow rate may either be held constant or programmed as functions of time, and it is not necessary for these programs to follow specific mat hematical functions. If experimental conditions are monitored during a run, the algorithm can account for any deviation from nominal set conditions. T he algorithm also allows calculation of fractionating power for the actual conditions as monitored during the run. The method provides greatly increas ed flexibility in the application of the FFF family of techniques. It remov es the limitations on experimental conditions incur-red by adherence to ana lytically available solutions to FFF theory, allowing ad hoc variation of f ield strength and other experimental parameters as necessary to increase se nsitivity and specificity of the method. An implementation of the algorithm is described that is independent of the FFF technique (i.e., independent o f field type) and mode of operation. To reduce computation time, it uses ma thematical techniques to reduce the required number of numerical integratio ns. This is of particular importance when the perturbations to ideal FFF th eory, such as those due to the effects of hydrodynamic lift forces, particl e-wall or particle-particle interactions, and secondary relaxation, necessi tate relatively lengthy numerical calculations.