Performance of sp-ICP-TOFMS with signal distributions fitted to a compound Poisson model

摘要: Accurate separation of signals from individual nanoparticles (NPs) background ion is decisive to correct sizing and number-concentration determinations in single-particle (sp) ICP-MS analyses. In typical sp-ICP-MS approaches, NP are identified via outlier analysis based on the assumption normally distributed (i.e. Gaussian) or Poisson-distributed signals. However, for with a Time-of-Flight (TOF) mass spectrometer that digitizes MS signal by fast analog-to-digital conversion (ADC), neither Gaussian nor Poisson. Instead, steady-state ICP-TOFMS follow compound Poisson distribution reflects noise contributions arrival ions gain statistics microchannel-plate-based detection. Here, we characterize this Monte Carlo simulations establish net critical values (LC(ADC)) as detection decision levels discrimination discrete NPs sp-ICP-TOFMS We apply LC(ADC) gold-silver core–shell (Au–Ag NPs), compare these results conventional sigma-based NP-detection thresholds. Additionally, investigate how accurate modelling TOFMS enables overlapping distributions; demonstrate size measurement 20 nm Au have mean intensity less than four counts.