REDUCTION OF INJECTION VARIANCE IN FLOW-INJECTION ANALYSIS

In order to achieve maximum sensitivity in flow-injection analysis, sample dispersion must be kept to a minimum. This dispersion process, however, is not well understood. Studies of the dispersion process have concentrated on dispersion within the flow manifold while dispersion due to the injection process has been largely ignored. Here sample injection loops packed with inert glass beads and a Serpentine II (distorted) empty loop were constructed and compared to traditional empty sample loops. Digitization of the response curves and subsequent calculation of the statistical moments were used to compare the contribution of each sample loop type to the total system dispersion. Both packed and Serpentine II sample loops were shown to decrease dispersion and increase throughput in flow-injection systems. Plots of peak variance vs. injection volume show variance increasing 1.67 times faster with traditional open sample loops compared to packed loops. When combined with other peak width minimization techniques, this method should further lower concentration limits of detection.