US-20260125578-A1 - SYSTEMS AND METHODS FOR IMPROVED MATERIAL SAMPLE ANALYSIS AND QUALITY CONTROL

US20260125578A1US 20260125578 A1US20260125578 A1US 20260125578A1US-20260125578-A1

Abstract

Provided herein are methods and systems for improved material sample analysis and quality control. A computing device may receive sample data associated with a plurality of material samples. The computing device may determine a first subset of the plurality of material samples and a second subset of the plurality of material samples. The computing device may determine the first subset based on a plurality of reference values and a plurality of analysis thresholds. The first subset may include samples associated with acceptable XRF spectra. The second subset may include samples associated with unacceptable XRF spectra. The computing device may generate and manipulate charts, graphs, or other visual displays of the data underlying the first subset and/or the second subset.

Inventors

Brandon Lee Goodchild Drake
Ry Nathaniel Zawadzki

Assignees

VERACIO LTD.
DECISION TREE, LLC

Dates

Publication Date: 20260507
Application Date: 20250904

Claims (20)

1 . A method comprising: receiving, at a computing device, spectral data associated with a plurality of material items, wherein the spectral data comprises x-ray fluorescence (XRF) spectra; determining, by the computing device, based at least in part on symmetry of the XRF spectrum about a peak energy, one or more material properties indicated by at least one XRF spectrum; determining, by the computing device, based on reliability of the one or more material properties, spectral quality of the XRF spectra using at least one quality metric comprising a match metric, a noise metric, and an intensity metric; classifying, based on the evaluation of spectral quality, the plurality of material items into at least two groups associated with different levels of spectral quality; and providing, at a user interface, an indication of the at least two groups.
2 . The method of claim 1 , wherein the match metric comprises a match percentage threshold indicating a degree to which an XRF spectrum conforms to one or more reference spectral values.
3 . The method of claim 1 , wherein the noise metric comprises a signal-to-noise threshold derived from a variance and a mean of a selected portion of an XRF spectrum.
4 . The method of claim 3 , wherein the signal-to-noise threshold comprises a Fano factor.
5 . The method of claim 1 , wherein the intensity metric comprises a counts-per-second threshold.
6 . The method of claim 5 , wherein the counts-per-second threshold comprises a percentile-based threshold.
7 . The method of claim 1 , wherein determining spectral quality further comprises applying a property-specific threshold based on a spectral feature indicative of a measurement condition of an x-ray fluorescence system, the spectral feature comprising at least one of: a percentage of Argon indicated by the XRF spectrum; or a spectral contribution associated with an anode material or an anode-equivalent reference.
8 . A non-transitory computer readable medium storing processor executable instructions that, when executed by at least one processor, cause the at least one processor to: receive spectral data associated with a plurality of material items, wherein the spectral data comprises x-ray fluorescence (XRF) spectra; determine, based at least in part on symmetry of the XRF spectrum about a peak energy, one or more material properties indicated by at least one XRF spectrum; determine, based on reliability of the one or more material properties, spectral quality of the XRF spectra using at least one quality metric comprising a match metric, a noise metric, and an intensity metric; classify, based on the evaluation of spectral quality, the plurality of material items into at least two groups associated with different levels of spectral quality; and cause display of an indication of the at least two groups at a user interface.
9 . The non-transitory computer readable medium of claim 8 , wherein the match metric comprises a match percentage threshold indicating a degree to which an XRF spectrum conforms to one or more reference spectral values.
10 . The non-transitory computer readable medium of claim 8 , wherein the noise metric comprises a signal-to-noise threshold derived from a variance and a mean of a selected portion of an XRF spectrum.
11 . The non-transitory computer readable medium of claim 10 , wherein the signal-to-noise threshold comprises a Fano factor.
12 . The non-transitory computer readable medium of claim 8 , wherein the intensity metric comprises a counts-per-second threshold.
13 . The non-transitory computer readable medium of claim 12 , wherein the counts-per-second threshold comprises a percentile-based threshold.
14 . The non-transitory computer readable medium of claim 8 , wherein determining spectral quality further comprises applying a property-specific threshold based on a spectral feature indicative of a measurement condition of an x-ray fluorescence system, the spectral feature comprising at least one of: a percentage of Argon indicated by the XRF spectrum; or a spectral contribution associated with an anode material or an anode-equivalent reference.
15 . An apparatus comprising: one or more processors; and memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to: receive spectral data associated with a plurality of material items, wherein the spectral data comprises x-ray fluorescence (XRF) spectra; determine, based at least in part on symmetry of the XRF spectrum about a peak energy, one or more material properties indicated by at least one XRF spectrum; determine, based on reliability of the one or more material properties, spectral quality of the XRF spectra using at least one quality metric comprising a match metric, a noise metric, and an intensity metric; classify, based on the evaluation of spectral quality, the plurality of material items into at least two groups associated with different levels of spectral quality; and cause display of an indication of the at least two groups at a user interface.
16 . The apparatus of claim 15 , wherein the match metric comprises a match percentage threshold indicating a degree to which an XRF spectrum conforms to one or more reference spectral values.
17 . The apparatus of claim 15 , wherein the noise metric comprises a signal-to-noise threshold derived from a variance and a mean of a selected portion of an XRF spectrum.
18 . The apparatus of claim 17 , wherein the signal-to-noise threshold comprises a Fano factor.
19 . The apparatus of claim 15 , wherein the intensity metric comprises a counts-per-second threshold.
20 . The apparatus of claim 19 , wherein the counts-per-second threshold comprises a percentile-based threshold.

Description

CROSS-REFERENCE TO RELATED PATENT APPLICATION This application is a continuation application of U.S. patent application Ser. No. 18/036,096, filed May 9, 2023, which is a National Stage Entry of International Application No. PCT/US 2021/058966, filed Nov. 11, 2021, which claims priority to U.S. Provisional Application No. 63/112,518, filed Nov. 11, 2020, the entireties of which are incorporated by reference herein. BACKGROUND Typically, quality control of extracted material samples requires shipping of the samples to a distant laboratory, where the samples are analyzed in a controlled environment by specially trained personnel. This analysis process is frequently associated with lengthy sample transport times, delays caused by limited access to the laboratory or limited trained personnel, and/or delays caused by detailed analysis and reporting. Additionally, existing quality control systems typically require extensive user training and certification before the systems can be used. These and other considerations are discussed herein. SUMMARY It is to be understood that both the following general description and the following detailed description are exemplary and explanatory only and are not restrictive. Provided herein are methods and systems for improved material sample analysis and quality control. As an example, it is an object of the presently described invention to provide computer-implemented systems and methods for quality control that improve analysis of material samples, such as core samples, rock samples, chip samples, solid puck samples, etc. For example, a computing device may receive sample data associated with a plurality of material samples. The sample data may be x-ray fluorescence (XRF) spectra data associated with the plurality of material samples. XRF spectra data for a sample may indicate one or more properties associated with the sample, such as one or elements present with the sample. The computing device may determine a first subset of the plurality of material samples and a second subset of the plurality of material samples. For example, the computing device may determine the first subset based on a plurality of reference values and a plurality of analysis thresholds. The first subset may include samples associated with acceptable XRF spectra. As another example, the computing device may determine the second subset based on the plurality of reference values and the plurality of analysis thresholds. The second subset may include samples associated with unacceptable XRF spectra. The computing device may include a user interface. The user interface may be used to review and analyze data underlying the first subset and/or the second subset. For example, the user interface may be used to generate and manipulate charts, graphs, or other visual displays of the data underlying the first subset and/or the second subset. Additional advantages will be set forth in part in the description which follows or may be learned by practice. The advantages will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are incorporated in and constitute a part of the present description serve to explain the principles of the methods and systems described herein: FIG. 1 shows an example material sample; FIGS. 2A-2D show example user interfaces; FIG. 3 shows an example machine learning system; FIG. 4 shows a flowchart for an example method; FIG. 5 shows an example system; FIG. 6 shows a flowchart for an example method; FIG. 7 shows a flowchart for an example method; FIG. 8 shows a flowchart for an example method; and FIG. 9 shows a flowchart for an example method. DETAILED DESCRIPTION As used in the specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Ranges may be expressed herein as from “about” one particular value, and/or to “about” another particular value. When such a range is expressed, another configuration includes from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms another configuration. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. “Optional” or “optionally” means that the subsequently described event or circumstance may or may not occur, and that the description includes cases where said event or circumstance occurs and cases where it does not. Throughout the description and claims of this specification, the word “comprise” and variations of the word, such as “comprising” and “comprises,” means “including but not limited to,” and is not intended to exclude, for example, other components, integers or