Cluster analysis of unknowns in SEM-EDS dataset
First Claim
1. A method for determining the mineral content of a sample, said method comprising:
- directing an electron beam toward multiple point of unknown composition;
detecting x-rays emitted as a result of the electron beam impacting the sample to acquire an a-ray spectrum, and forming a data point;
classifying the data point from a sample by comparison to a set of known data points as a classified data point, wherein said classified data point is classified as a similar data point if the characteristics of the classified data point are similar to the characteristics of a known data point and alternatively the classified data point is classified as a dis-similar data point if the characteristics of the classified data point are not similar to that of a known data point;
placing the data point into a group wherein the characteristics of the data points within the group have characteristics similar to that of the classified data point;
repeating the previous steps until all data points are classified data points and are placed in groups with similar characteristics; and
analyzing the groups with dis-similar data points to for use in processing the mineral sample.
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Abstract
The present invention discloses a method for determining the mineral content represented by the entire SEM-EDS dataset, including initially unknown data points. SEM-EDS data points are taken and compared to a set of known data points. Any data point that is not sufficiently similar to the known data point is classified as unknown and clustered with like unknown data points. After all data points are analyzed, any clusters of unknown data points with a sufficient number of data points are further analyzed to determine their characteristics. All clusters of unknown data points with an insufficient number of data points to allow further analysis are considered outliers and discarded.
88 Citations
14 Claims
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1. A method for determining the mineral content of a sample, said method comprising:
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directing an electron beam toward multiple point of unknown composition; detecting x-rays emitted as a result of the electron beam impacting the sample to acquire an a-ray spectrum, and forming a data point; classifying the data point from a sample by comparison to a set of known data points as a classified data point, wherein said classified data point is classified as a similar data point if the characteristics of the classified data point are similar to the characteristics of a known data point and alternatively the classified data point is classified as a dis-similar data point if the characteristics of the classified data point are not similar to that of a known data point; placing the data point into a group wherein the characteristics of the data points within the group have characteristics similar to that of the classified data point; repeating the previous steps until all data points are classified data points and are placed in groups with similar characteristics; and analyzing the groups with dis-similar data points to for use in processing the mineral sample. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A scanning electron microscope x-ray spectroscopy device comprising:
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a source of a charged particle beam or photon beam and means for directing the beam towards a mineral sample; a detector for detecting emissions from the sample in response to the beam and for forming a data set comprising multiple data points; a processor for controlling the scanning electron microscope; and a computer readable data storage storing computer instruction to; classify an x-ray spectroscopy data point taken from the sample by comparison to a set of known data points as a classified data point wherein said classified data point is classified as a similar data point if the characteristics of the classified data point are similar to the characteristics of a known data point and alternatively the classified data point is classified as a dis-similar data point if the characteristics of the classified data point are not similar to that of a known data point; place the x-ray spectroscopy data point into a group wherein the characteristics of the data points within the group have characteristics similar to that of the classified data point; repeat the previous steps until all x-ray spectroscopy data points are classified data points and are placed in groups with similar characteristics; analyze the groups with dis-similar data points to for use in processing the mineral sample.
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Specification