Automated standard dilution analysis
Standard dilution analysis (SDA) is a recently described calibration method that combines internal standardization and standard additions to improve accuracy and precision. By combining these two traditional methods, SDA offers corrections for sample matrix effects while also minimizing signal fluctuations due to changes in the excitation source and the sampling process. In its most basic form, SDA is performed by introducing a constant amount of sample into an instrument while varying the amount of standard solution added to the sample. The procedure is simple to perform by hand, but automation of the process is challenging because the dilution of the standard solution by a blank occurs on-line while the measurement is taking place. The experiments presented here are aimed at improving the automation of the SDA process. Inductively coupled plasma optical emission spectrometry (ICP OES) is used as a model for SDA applications, although the calibration method is applicable to any technique that accepts samples as a liquid flow. The end goal of automation is for successive samples to be analyzed quickly by using an automatic sampler to switch from sample to sample, as it is the case in routine analytical methods. The required dilution of the standard by a blank mixture is achieved through the use of a two-channel pinch valve, with dilution occurring by diffusion as the solution is pulled from the valve toward the plasma by a second channel in the instrument's peristaltic pump. The proposed automated SDA method is effective, with analyte recoveries within a few percent of 100 for the elements evaluated (i.e. Al, Cd, Co, Cr, Cu, Fe, Ni and Pb) and nine different sample matrices. The method also provides promising results when analyzing real-world samples. The limits of detection obtained with the automated SDA method are similar to those typically found for external standard calibration and ICP OES, falling within the single-digit μg L−1 range.
- This article is part of the themed collection: JAAS Emerging Investigator Lectureship winners