Precision in differential field‐flow fractionation: A chemometric study

Abstract

In the present paper, the capabilities of differential field-flow fractionation, i. e., the determination of an incremental quantity of a colloidal species, e. g., an uptake adsorbed mass, determined by the joint use of two independent FFF measurements, over a species and the same modified species respectively, are considered. The different error types, those related to the retention time determinations and those coming from the operating parameter fluctuations were considered. The different components were computed with reference to SdFFF determinations of bare polystyrene (PS) submicronic particles and the same PS particles covered by IgG. Comparison was made between theoretically computed precision and experiments. The error coming from the experimental measurement of retention times was identified to be the main source of errors. Accordingly, it was possible to make explicit the detection limits and the confidence intervals of the adsorbed mass uptake, as a function of experimental quantities such as the retention ratio, the detector calibration ratio, the injected quantity, the baseline noise, and the void time relative error. An experimentally determined and theoretically foreseen dependence of both the experimental detection and confidence limits (approximately +/- 10(-17) g) on the square root of the injected concentration, for constant injected volume, was found.

Asymmetric flow field-flow fractionation as a multifunctional technique for the characterization of polymeric nanocarriers

“…In general, the amount of bound polymer can be accurately quantified only for high degrees of functionalization on small solutes of well-defined size, such as in the preparation of PEGylated asparaginase for the treatment of lymphoblastic leukemia and non-Hodgkin's lymphoma [116]. This method of monitoring particle formation by measuring its mass or size before and after the addition of a reagent is sometimes called "differential FFF" [117,118]. Differential FFF is perhaps more suited for SdFFF (v. list of references in [118]), thanks to its superior mass and size selectivity, although also AF4 can prove itself useful, especially for materials that lie below the operational size limits of SdFFF (d ≲ 100 nm) [119,120].…”

Critical Experimental Evaluation of Key Methods to Detect, Size and Quantify Nanoparticulate Silver

“…All samples appear quite monodispersed with the exception of the AgNP60, whose main peak come along with secondary peaks of sizes spanning between 70 and 110 nm, sizes which could correspond to aggregates or to a particles of different shapes (e.g., rods), as seen in Figure S-2 C1, Supporting Information). The peaks in the relative weight distribution plots were fitted with Gaussian functions to get the most reliable position of the maxima and the width ( w ) . Table summarizes all numerical data, including the dispersion index (DI), i.e., the ratio between the peak variance and the squared average size (DI = ( w 2 / )), a rough index to measure the sample polydispersity, when the particle size distributions are normalized Gaussian functions.…”

“…The peaks in the relative weight distribution plots were fitted with Gaussian functions to get the most reliable position of the maxima and the width (w). 34 Table 1 summarizes all numerical data, including the dispersion index (DI), i.e., the ratio between the peak variance and the squared average size (DI = (w 2 /d 2 )), a rough index to measure the sample polydispersity, when the particle size distributions are normalized Gaussian functions.…”