Nanoparticle baseline and particle detection threshold determination through iterative outlier removal
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.
1 . A method for iterative determination of outlier data from a spectrometry data set, comprising:
transferring a fluid sample containing nanoparticles to a spectrometry sample analyzer;
generating a spectrometry data set via the spectrometry sample analyzer associated with detected ion signal intensity over time;
generating from the spectrometry data set, via one or more computer processors, a raw data set that includes a count distribution of counts of ion signal intensity and a frequency of the ion signal intensity of each count;
iteratively removing, via the one or more computer processors, 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 until no count values exceed the outlier threshold value to provide a background data set; and
setting, via the one or more computer processors, a nanoparticle baseline intensity value 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, wherein the first multiple of the standard deviation of the count distribution of ion signal intensity differs from the second multiple of a standard deviation of the background data set.
2 . The method of claim 1 , wherein the spectrometry sample analyzer is an inductively coupled plasma mass spectrometer (ICPMS).
3 . The method of claim 2 , wherein transferring a fluid sample containing nanoparticles to a spectrometry sample analyzer includes transferring the fluid sample from a fluid source to an inductively coupled plasma torch and subsequently to the ICPMS.
4 . The method of claim 3 , wherein transferring the fluid sample from a fluid source to an inductively coupled plasma torch includes transferring the fluid sample from the fluid source via autosampler control of a sample probe to the inductively coupled plasma torch.
5 . The method of claim 1 , further comprising removing from the spectrometry data set, via the one or more computer processors, data values less than the nanoparticle baseline intensity value to remove portions of the ion signal intensity values attributable to background interference.
6 . The method of claim 1 , wherein the first multiple of the average of the count distribution of ion signal intensity is the same as the first multiple of the average of the background data set.
7 . A system for iterative determination of outlier data from a spectrometry data set, comprising:
a spectrometry sample analyzer configured to receive a fluid sample containing nanoparticles from a sample source and to generate a spectrometry data set associated with detected ion signal intensity over time;
one or more computer processors; and
a non-transitory computer readable-medium bearing one or more instructions for execution by the one or more computer processors to cause the one or more computer processors to perform the steps of:
generating from the spectrometry data set, via one or more computer processors, a raw data set that includes a count distribution of counts of ion signal intensity and a frequency of the ion signal intensity of each count;
iteratively removing, via the one or more computer processors, 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 until no count values exceed the outlier threshold value to provide a background data set; and
setting, via the one or more computer processors, a nanoparticle baseline intensity value 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, wherein the first multiple of the standard deviation of the count distribution of ion signal intensity differs from the second multiple of a standard deviation of the background data set.
8 . The system of claim 7 , wherein the spectrometry sample analyzer is an inductively coupled plasma mass spectrometer (ICPMS).
9 . The system of claim 8 , further comprising an inductively coupled plasma torch fluidically coupled between the sample source and the ICPMS.
10 . The system of claim 9 , further comprising an autosampler directing control of a sample probe to introduce the fluid sample to the inductively coupled plasma torch.
11 . The system of claim 7 , wherein the one or more instructions further include one or more instructions for execution by the one or more computer processors to cause the one or more computer processors to perform the steps of removing from the spectrometry data set data values less than the nanoparticle baseline intensity value to remove portions of the ion signal intensity values attributable to background interference.
12 . The system of claim 7 , wherein the first multiple of the average of the count distribution of ion signal intensity is the same as the first multiple of the average of the background data set.