On the two-phase sample transport of carbon in LA-ICP-MS and its practical implications for trace metal analysis in polymer matrices: classification and sensitivity

Abstract

Background Analyzing the (trace) metal content of synthetic polymers is of interest both for manufacturing and recycling industries where inorganic additives and contaminations must be monitored. Additionally, the metal content of microplastics has recently gained more and more attention as a means to assess their environmental impact. LA-ICP-MS is commonly used for this task as it provides superior sensitivity and allows direct analysis of non-conductive samples. Nevertheless, LA-ICP-MS comes with the need for matrix-matched standards for accurate quantification which implies that information about the polymer type under investigation is required. Results In this work, we study the influence of the polymer type as well as the LA parameters on the sensitivity of Pb. We analyze standards containing different levels of Pb for five different polymer types by recording the single pulse response (SPR) signal allowing us to monitor both the distinct two-phase sample transport of C and the signal for Pb. By varying the laser energy, we find significant changes in the ratio of particulate and gaseous C species formed upon ablation for the different polymers with Pb being transported exclusively in the particulate phase. Additionally, we find that the ratio of formed gaseous carbon species influences the signal observed for Pb. Finally, we demonstrate the possibility of utilizing the characteristic two-phase sample transport of C when analyzing polymers in order to identify the polymer type both in prepared thin-films and a sample containing different microplastics embedded in acrylic resin. Significance The findings of this work are highly significant when analyzing carbon-based samples as we demonstrate a relationship between the analyte's sensitivity and the ratio of gaseous carbon species formed. Additionally, the proof-of-concept for LA-ICP-MS based polymer classification enables easier selection and application of matrix-matched standards for quantitative analysis in polymers.