US 12,085,497 B1
Nanoparticle analysis for ultra-low level concentrations of nanoparticles in fluid samples
Myung Hwan Kim, Omaha, NE (US); Daesung Kim, Omaha, NE (US); Austin Schultz, Omaha, NE (US); Cole Nardini, Omaha, NE (US); David Diaz, Omaha, NE (US); Kyle Uhlmeyer, Omaha, NE (US); Daniel R. Wiederin, Omaha, NE (US); Jaeyoung Kim, Suwon-si (KR); Min-Soo Suh, Suwon-si (KR); So Young Kim, Suwon-si (KR); Sooyeon Kim, Suwon-si (KR); Junghee Shin, Suwon-si (KR); and Suyeon Jeong, Suwon-si (KR)
Assigned to Elemental Scientific, Inc., Omaha, NE (US); and Samsung Electronics Co., Ltd., Suwon-Si (KR)
Filed by Elemental Scientific, Inc., Omaha, NE (US); and Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed on Dec. 29, 2023, as Appl. No. 18/400,300.
Claims priority of provisional application 63/458,680, filed on Apr. 12, 2023.
Int. Cl. G01N 15/1429 (2024.01); G01N 30/72 (2006.01); H01J 49/10 (2006.01); H01J 49/36 (2006.01); G01N 15/10 (2024.01)
CPC G01N 15/1429 (2013.01) [G01N 30/72 (2013.01); H01J 49/105 (2013.01); H01J 49/36 (2013.01); G01N 2015/1029 (2024.01)] 21 Claims
OG exemplary drawing
 
1. A method for analyzing ultra-low level concentration nanoparticles in semiconductor cleaning chemicals by single particle inductively coupled plasma mass spectrometry (spICP-MS), the method comprising:
obtaining, via a processor in a computing device, an initial data set corresponding to ion signal intensity as a function of time of a sample processed by a spICP-MS system, the sample having a chemical matrix associated with a semiconductor cleaning chemical with an ultra-low level concentration of nanoparticles;
determining, via the processor, a particle baseline intensity value to isolate signal intensities associated with the nanoparticles from data background signal intensities through iteratively filtering the initial data set, wherein iteratively filtering the dataset includes:
determining, via the processor, a pulse count distribution of the initial data set corresponding to a plurality of data points, each data point corresponding to an ion signal intensity and a frequency of the ion signal intensity detected by the spICP-MS system; and
iteratively removing from the pulse count distribution pulse count, via the processor, data points that exceed a particle threshold value associated with a sum of a first multiple of an average of the pulse count distribution and a first multiple of a standard deviation of the pulse count distribution, wherein subsequent iterations adjust the particle threshold value based on the removed pulse count data points until no pulse count data points exceed the particle threshold value to provide a resultant pulse count distribution, wherein the particle baseline intensity value corresponds to a sum of a second multiple of an average of the resultant pulse count distribution and a second multiple of a standard deviation of the resultant pulse count distribution, wherein each of the first multiple of the average, the first multiple of the standard deviation, the second multiple of the average, and the second multiple of the standard deviation are specific to each of the chemical matrix and a type of analyte associated with the nanoparticles;
subtracting, via the processor, the particle baseline intensity value from the pulse count distribution to provide a baseline data set;
integrating, via the processor, contiguous data points of the baseline data set within a specified time period and forming a histogram of the integrated contiguous data points; and
determining, via the processor, a nanoparticle detection threshold through local window analysis of frequency values for counts associated with a window width of the histogram, wherein the window width is specific to each of the chemical matrix and a type of analyte associated with the nanoparticles.