Flow peak detection using penalized asymmetric least squares in on-line isotope dilution-laser ablation-inductively coupled plasma-mass spectrometry

Yanagisawa, Kayo   ; Yokota, Hiromi*; Fujimoto, Katsushige*; Takagai, Yoshitaka*

On-line isotope dilution-laser ablation-inductively coupled plasma-mass spectrometry (on-line ID-LA-ICP-MS) is capable of quantification for each point ablated by laser, then the quantitative mapping of elements can be also conducted by reconstruction of the obtained each point data. The volume of data obtained as flow peaks in this system as a flow injection analysis, will be multiplied by each data such as number of m/z, scan time, time resolution and measurement position, and the total amount of data is enormous, resulting in a large human power and time consumption for data processing. In this paper, an original application software using Python to improve the efficiency of data processing in on-line ID-LA-ICP-MS was developed. To discriminate between the time-to-peak intensity and the background noise, an automatic peak detection using penalized asymmetric least squares was developed.