Abstract: Systems and methods for iterative removal of outlier data from spectrometry data to determine one or more of a particle baseline and a detection threshold for nanoparticles are described. Ion signal intensity values that exceed an outlier threshold value associated with a sum of a first multiple of an average of the count distribution of ion signal intensity and a first multiple of a standard deviation of the count distribution of ion signal intensity are iteratively removed from the raw data set until no outliers remain, providing a background data set. A nanoparticle baseline intensity value is set as a sum of a second multiple of an average of the background data set and a second multiple of a standard deviation of the background data set to differentiate between signal intensity values that are associated with background interference and that are associated with the presence of nanoparticles in the sample.

Abstract: Systems and methods for iterative removal of outlier data from spectrometry data to determine one or more of a particle baseline and a detection threshold for nanoparticles are described. Ion signal intensity values that exceed an outlier threshold value associated with a sum of a first multiple of an average of the count distribution of ion signal intensity and a first multiple of a standard deviation of the count distribution of ion signal intensity are iteratively removed from the raw data set until no outliers remain, providing a background data set. A nanoparticle baseline intensity value is set as a sum of a second multiple of an average of the background data set and a second multiple of a standard deviation of the background data set to differentiate between signal intensity values that are associated with background interference and that are associated with the presence of nanoparticles in the sample.

Abstract: Systems and methods are described for analyzing local minimum data from spectrometry data for the determination of nanoparticle detection thresholds are described. In aspects, a histogram of the spectrometry data is used to search for potential local minimum values, which are subsequently validated to establish a nanoparticle detection threshold for the spectrometry data, with ion intensity values less than the nanoparticle detection threshold being attributable to signal background.

Abstract: Systems and methods are described for automatically utilizing multiple data processing methods on a given spectrometry dataset for the determination of nanoparticle detection factors including nanoparticle baseline and detection threshold.