Development of a fully automated slurry sampling introduction system for GF-AAS and its application for the determination of cadmium in different matrices

Abstract

Background

Graphite Furnace-Atomic Absorption Spectrometry (GF-AAS) is a powerful technique for trace element analysis, offering high sensitivity and precision. However, its effectiveness is limited by sample preparation challenges for solid samples like soils and microplastics. Traditional methods include sample preparation, such as digestion, which is time-consuming and involves reagents, like acids, contributing to measurement uncertainty and higher carbon footprints. Slurry sampling allows direct analysis of suspensions, offering a more efficient alternative. However, maintaining suspension stability is challenging, requiring robust autosampler systems to streamline the process and enhance analytical performance.

Results

We present a novel autosampler extension for slurry sample introduction into GF-AAS. This system ensures suspension stability with a stirring device and closed vessels to prevent evaporation and contamination, incorporating a cooling unit to reduce solvent and analyte losses. It installs and removes in minutes without additional connections. Validation with cadmium analysis in BAM-U110 (Soil) and BAM-H010 (ABS) showed high reliability. For BAM-U110 (Soil), we achieved recovery rates of 94 % ± 13 % in water suspension. The recovery rate for BAM-H010 (ABS) was 104 % ± 11 % in acetonitrile suspension. These results demonstrate the system’s robustness, versatility, and accuracy for different matrices.

Significance

The autosampler extension helps solve key problems in trace element analysis of solid samples, making the process faster and more accurate. It works well with complex materials, making it useful for areas like microplastic or nanoparticle analysis. This improvement also helps meet regulations for monitoring environmental and polymer samples, offering a reliable and flexible tool for high-throughput analysis with fewer errors.