Modeling, Validation, and Application of Instrument Response Function in the Form of Mixed Poisson Distribution for Single-Particle ICP-MS

Abstract

Single-particle inductively coupled plasma mass spectrometry (spICP-MS) is a sensitive and convenient technique for characterizing nanoparticles in suspension, enabling the determination of particle size, particle size distribution (PSD) and particle number concentration (PNC) from time-resolved signals of particle events. Accurate acquisition and modeling of event intensity distributions (EIDs) are critical steps in expanding functionality and improving measurement accuracy. In this work, we explored the broadening factors of EID, establishing and validating a robust instrument response function (IRF) in the form of a mixed Poisson distribution that reliably correlates PSD with EID across varying operating conditions. The EID tailing caused by particle coincidence is quantified and eliminated through Monte Carlo simulations grounded in the homogeneous Poisson process, and then the recovered EID is deconvoluted by IRF to yield high-fidelity PSD, improving the accuracy of PSD and PNC obtained by spICP-MS. For monodisperse gold nanoparticles (AuNPs) and AuNP mixtures, stable PSDs can be recovered from the broadened EIDs by IRF deconvolution, yielding results closely aligned with those obtained by transmission electron microscopy, thus increasing the size resolution to about 7 nm in both simulated and actual samples. The application of IRF to the measurement of nanoparticle agglomerates was also demonstrated, and the probability mass function of agglomeration numbers was successfully resolved. This technique is expected to leverage the high-throughput advantages of spICP-MS in the quantification of nanoparticle mixtures or agglomerates.