Improved EDS calibration

Abstract

To provide an efficient calibration method in standards-less EDS analysis.SOLUTION: A method comprises providing reference data indicative of at least one reference energy-dispersive x-ray spectrum, providing measured data indicative of at least one measured energy-dispersive x-ray spectrum obtained from a sample, and determining a transformation based on a comparison of the measured data with the reference data.SELECTED DRAWING: Figure 8

Description

[Technical field]

[0001] The present invention relates generally to methods and arrangements for identifying sample composition using an energy dispersive spectroscopy system. [Background technology]

[0002] Mineral analysis systems such as the QEMSCAN® (Quantitative Evaluation of Minerals by Scanning electron microscopy) and MLA (Mineral Liberation Analyzer) from FEI Company, the assignee of the present invention, have been used for many years to determine the presence of valuable minerals in mines. Such systems direct an electron beam at a sample and measure the energy of X-rays coming from the material in response to the electron beam. One such process is called "Energy Dispersive X-ray Analysis" or "EDS" and can be used for elemental analysis or chemical characterization of a sample. Determining the elements present in a mineral sample is referred to as "elemental decomposition". Beams other than electron beams can be used to excite the sample. For example, X-ray beams or ion beams can be used as alternatives.

[0003] EDS systems rely on the emission of X-rays from a sample to perform elemental analysis. Each element has a unique atomic structure, so the X-rays that are characteristic of the element's atomic structure are unique to that element. To stimulate the emission of X-rays from the sample, a beam is directed at the sample, which ejects electrons from the inner shells. Electrons from the outer shells attempt to fill this electron void, and the difference in energy between the high and low energy shells is emitted as X-rays, which can be detected by a suitable detector.

[0004] The unknown elemental composition of a specimen can be determined by measuring the number and energy of X-rays emitted from the specimen using an energy dispersive spectrometer and comparing the measured spectrum to a reference library. The reference library may include reference signatures of known compositions. The reference signatures may include, for example, reference spectra and / or reference elemental intensity values. EDS analysis, especially when combined with back-scattered electron (BSE) analysis, can be used to quantify a wide range of mineral properties such as mineral abundance, grain size, and degree of resolution, i.e., how easy it is to separate the desired minerals from background material. Existing EDS analysis systems include QEM / SEM technology assigned to FEI Company, Inc., the assignee of the present invention.

[0005] A mineral classification system must be able to compare the measured spectrum of each unknown to a library of known mineral signatures and then make a selection based on which known mineral is most similar to the measured spectrum. Typically, finding the most similar known mineral requires the use of a metric that expresses the degree of similarity between the measured data and the known material.

[0006] This type of mineral analysis system is also used in the oil and gas industry. Cutting cuttings (fragments of rock caused by the drill bit) and diamond drill cores can be analyzed to enable geologists to determine the exact nature of the material encountered during cutting, which in turn allows for more accurate predictions regarding the material ahead of the drill, thus reducing the risks in exploration and production. During cutting, liquids called "mud" are injected into the wellbore to lubricate the drill and return the cuttings from the wellbore. Samples can be taken from the mud, including the cuttings from the drill. Recording the cuttings and cores as accurately as possible, both during and after cutting, is an important aspect of analyzing the cutting process. Information obtained from cuttings and coring samples allows for the characterization of downhole lithological variations in reservoir arrays, a key requirement in exploration and production wells, as well as mineralogical and petrological studies, supporting a fundamental understanding of reservoir and seal properties. Conventional optical, scanning electron microscope (SEM), electron probe micro-analyzer (EPMA) and x-ray diffraction (XRD) analytical methods are well established and widely used within the industry.

[0007] Mineral analysis attempts to identify the minerals present and their relative proportions at any point the electron beam is directed at. The analytical instrument typically measures the X-ray signal to determine which elements are present and then, using a database of mineral definitions, translates the list of elements into a mineral identification.

[0008] A particular mineral will always have peaks at specific energies in the X-ray spectrum. In order to accurately determine which peaks correspond to which minerals, it is necessary to calibrate the instrument utilized before the unknown mineral can be identified. For this reason, instrument calibration techniques are particularly important for meaningful analysis.

[0009] EDS instruments are typically calibrated using either standard-based or standard-less calibration. In standard-based calibration, known materials, called "standards," are analyzed and the results are used to establish a reference library. Unknown samples are then compared to the reference library to determine which elements are present. The calibration standards must be analyzed under conditions identical to those used to analyze the unknown materials. Because the conditions within the measurement instrument depend on a number of factors, traditional standard-based calibration requires the measurement of a complete set of standards each day the machine is used. For example, the QemScan instrument mentioned above currently identifies up to 72 different elements found in mineral samples. Traditional standard-based calibration requires each instrument to have a set of 72 element / mineral standards to generate a complete set of elemental signatures. This type of calibration is prohibitively expensive, both in terms of the cost of supplying standard blocks containing a complete set of elemental and mineral standards, as well as the operator time required and reduced instrument throughput. In addition, there are some elements that are only present in minerals and cannot be measured individually, so it is not possible to perform this calibration for these elements.

[0010] Because traditional standards-based decomposition requires that the X-ray spectra of all elemental standards be acquired on the same machine under the same conditions as the X-ray spectrum of the mineral being analyzed, factory calibration using the methods of the prior art is impractical. The prior art suggests that standards-based elemental analysis requires that elemental X-ray spectra must be measured on the same machine and cannot be acquired from a different machine. This is because variations in how a user sets up a particular instrument, including, for example, a particular sample geometry, height, etc., will change the characteristics of the X-ray spectrum and affect the calibration.

[0011] Using standardless EDS analysis, the analysis of a particular mineral sample is performed without comparison to a known standard. Based on the characteristics of the collected spectrum, the element list is narrowed and finally an element is selected. Standardless analysis is much more complex and subject to greater imprecision than standard-based analysis, but it offers an easier set-up for the user since the instrument does not need to be calibrated with specific parameters for all possible elements.

[0012] Therefore, what is needed is an efficient calibration method and apparatus that is cheaper, simpler, easier to implement, and that allows samples to be measured more quickly. Summary of the Invention

[0013] The present invention relates to a method that includes providing reference data indicative of at least one reference energy dispersive X-ray spectrum, providing measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from a sample, and determining a transformation based on a comparison of the measured data to the reference data.

[0014] An objective of the present invention may be to increase the agreement between measured data and reference data through a determined transformation, which in turn may provide a better identification of the materials that make up the sample.

[0015] In particular, it may be advantageous for the measured data and the reference data to be matched. This means that the X-ray emission lines of an element in the reference data and the measured data have the same energy. Typically, an X-ray emission line of an element can be represented in the measured data and the reference data by a corresponding spectral peak. Ideally, for the same X-ray emission line, the peak of the measured spectrum and the peak of the reference spectrum should be identical. However, for various reasons, this may not be the case. That is, there may be differences in how the X-ray emission line is represented in the reference data and how the X-ray emission line is represented in the measured data.

[0016] There may be several reasons for this difference or discrepancy. One such reason may be related to hardware inaccuracies. Different hardware devices may introduce different errors in obtaining measured data or reference data. Even if the same hardware device is used to obtain reference data and measured data, hardware drift may still cause differences between the reference data and the measured data. Another reason may be related to the process of obtaining the measured data. For efficiency reasons, the accuracy of the measurement data acquisition may be reduced, resulting in measurement data with inherent inaccuracies. Other reasons may be related to inefficient matching or calibration algorithms and / or user errors.

[0017] In addition, this difference can lead to misidentification of the substances that make up the sample when the sample is analyzed, for example, using an EDS instrument. This can typically be the case for substances with similar chemical properties that can be misidentified with each other.

[0018] Therefore, the present invention can alleviate these problems by determining a transformation between measured data and reference data.

[0019] The measured data may include measured spectral peaks. The measured spectral peaks may typically have a bell curve shape. They may typically resemble a Gaussian function. The measured spectral peaks may indicate a particular energy level at which the sample emitted a significant number of x-rays. Additionally, each measured spectral peak may provide information regarding the number of x-rays detected at that particular energy level. In general, each measured spectral peak may indicate, for a range of continuous energy levels, a respective count of x-rays emitted within that range.

[0020] Each measured spectral peak can represent a respective element in the sample.

[0021] In particular, each measured spectral peak can represent a specific X-ray emission line of a respective element in the sample.

[0022] The method may include detecting measured spectral peaks in the measured data, the detection process typically including identifying portions of the measured spectrum where the x-ray counts exceed background radiation and any other noise sources by a predetermined detection threshold.

[0023] Throughout this specification, the terms "X-ray counts" and "X-ray intensity" are used interchangeably.

[0024] The reference data may include reference spectral peaks. The above discussion of measured spectral peaks applies mutatis mutandis to the reference spectral peaks.

[0025] Each reference spectrum peak can represent a respective element.

[0026] Each reference spectrum peak can represent a specific X-ray emission line of a respective element.

[0027] The method may further comprise detecting a calibration peak on the measured data. The calibration peak may be a peak in the measured spectrum that may be used for calibration, i.e. to increase the agreement between the measured data and the reference data. In particular, the calibration peak may be used to determine the transformation. It may be advantageous that the calibration peak may be such that it can clearly indicate how a particular X-ray emission was detected during the acquisition of the measured data. Thus, the calibration peak may serve as a ground truth for how a particular instrument (i.e. the instrument used to obtain the measured data) can detect the particular X-ray emission represented by the calibration peak. Using this information, a corresponding correction may be performed on the reference data.

[0028] The calibration peaks may include intensities that may be higher than the background radiation intensity. In this way, it is possible to ensure that the calibration peaks represent elements present in the sample, i.e., that they represent X-rays emitted by the sample and not other sources.

[0029] The intensity of a calibration peak may refer to the maximum intensity of the calibration peak.

[0030] Additionally, the term "intensity" can refer to X-ray counts.

[0031] Background radiation intensity can refer to the intensity of background radiation that includes energies similar to those of the calibration peak. That is, for different calibration peaks, the background radiation intensity can be different depending on the energy of the calibration peak. For example, to determine the intensity of the background radiation, an energy range that encompasses the calibration peak can be defined. This can be, for example, the average of the intensity of the background radiation in that energy range.

[0032] Additionally, background radiation intensity may be used herein to refer to the intensity of radiation produced by any source other than the sample.

[0033] For each calibration peak, the ratio between the intensity of the calibration peak and the background radiation intensity may be higher than an intensity ratio threshold. The intensity ratio threshold may be a user-defined parameter. Additionally, the intensity ratio threshold may be adjustable.

[0034] The intensity ratio thresholds can be configured to ensure that the calibration peaks can be attributed to X-rays actually emitted by the sample. Additionally, the intensity ratio thresholds can be configured to ensure that they can be attributed to elements in the sample that have a significant weight percentage in the sample. In this way, the calibration peaks can be well-defined peaks that can allow for a more accurate reading of their energy levels.

[0035] Each calibration peak may be undisturbed such that any other spectral peak in the measured data that is present in the same measured spectrum as the calibration peak has an energy difference from the calibration peak that is greater than a disturbance threshold.

[0036] The calibration peaks may be a subset of the measured spectral peaks. Advantageously, the calibration peaks may be such that they can clearly indicate how a particular X-ray emission was detected during acquisition of the measured data. That is, the calibration peaks may be advantageously well-defined peaks. Thus, not all measured spectral peaks in the measured data can be used as calibration peaks, but rather a subset thereof. The subset may consist of measured spectral peaks that satisfy a predefined criteria.

[0037] Detecting calibration peaks on the measured data may include classifying at least some of the measured spectral peaks as calibration peaks.

[0038] Classifying at least some of the measured spectral peaks as calibration peaks may be based on the intensities of each of the measured spectral peaks.

[0039] Classifying at least some of the measured spectral peaks as calibration peaks may be based on intensities of the measured spectral peaks relative to a background radiation intensity.

[0040] A measured spectral peak may be classified as a calibration peak if the ratio between the intensity of the measured spectral peak and the background radiation intensity may be higher than an intensity ratio threshold.

[0041] Classifying at least some of the measured spectral peaks as calibration peaks may be based on energies of the measured spectral peaks.

[0042] A particular measured spectral peak may be classified as a calibration peak if any other measured spectral peak in the measured data that is present in the same measured spectrum as the particular measured spectral peak is not disturbed such that its energy difference with the particular measured spectral peak exceeds a disturbance threshold.

[0043] At least one measured spectral peak may be classified as a calibration peak if it is the highest of the measured spectral peaks in the measured data corresponding to the same X-ray emission line.

[0044] In some embodiments, detecting calibration peaks on the measured data may include, for each measured spectrum in the measured data, detecting all measured spectral peaks in the measured spectrum. The method may further include, for each measured spectrum in the measured data, rejecting measured spectral peaks in the measured spectrum that include a peak-to-background ratio less than an intensity ratio threshold, the peak-to-background ratio being a ratio between an intensity of the measured spectral peak and a background radiation intensity. Alternatively or additionally, the method may include, for each measured spectrum, rejecting measured spectral peaks in the measured spectrum that overlap with other measured spectral peaks in that measured spectrum, where two peaks in the measured spectrum overlap if they include an energy difference less than a jamming threshold.

[0045] The unrejected measured spectral peaks may be grouped into groups according to the X-ray emission lines they represent, i.e., each group contains unrejected measured spectral peaks that can represent the same X-ray emission line.

[0046] From each of the groups, the non-rejected measured spectral peak with the highest peak-to-background ratio can be determined as the calibration peak. Thus, if there are multiple non-rejected measured spectral peaks in the measured data, the most distinct peak can be determined to be the calibration peak. In other words, in general, any non-rejected measured spectral peak can be the calibration peak. However, if there are multiple non-rejected measured spectral peaks for the same X-ray emission line, only one of them may be sufficient. In such a case, the one with the highest peak-to-background ratio can be determined as the calibration peak and selected as the calibration peak.

[0047] Determining the transformation may include determining at least one piecewise transformation based on the calibration peaks and the reference data.

[0048] Piecewise transformations can allow for fine matching between the reference data and the measured data. This can be particularly advantageous because it can mitigate nonlinear mismatches between the reference data and the measured data. That is, typically, there may be cases where the mismatch between the reference data and the measured data may be a nonlinear function of energy. Thus, in such cases, simply performing a linear transformation of the entire reference data may not be sufficient. Piecewise transformations address this by allowing the application of different transformations for different energy regions.

[0049] At least one piecewise transform may be applicable to a portion of the total energy range of the reference data. The portion may be between the minimum and maximum energies of the calibration peak, inclusive. In other words, one or more piecewise transforms may be applicable to a portion of the total energy range of the reference data. Assuming that the piecewise transform may be determined based on the calibration peak, the portion to which the piecewise transform may be applicable may be bounded by the minimum energy and by the maximum energy of the calibration peak.

[0050] Outside that portion, transformations other than the piecewise transformation may be applicable.

[0051] Each of the at least one piecewise transformation can be determined based on a respective pair of consecutive calibration peaks, and two calibration peaks can be consecutive if no other calibration peak in the measured data can contain an energy between the energies of the two consecutive calibration peaks.

[0052] Each of the at least one piecewise transformation may be selectively applied to a respective piecewise energy region of the reference data that encompasses energies between or equal to the respective energies of a respective pair of calibration peaks.

[0053] In simple terms, two consecutive calibration peaks may be used to determine a piecewise transformation, which may be applicable to an energy region bounded by the energies of the two consecutive calibration peaks. Outside of the energy region bounded by the energies of the two consecutive calibration peaks, other piecewise transformations and / or transformations other than the piecewise transformation may be applicable. The above may apply to any pair of consecutive calibration peaks.

[0054] Determining the transformation can include determining a plurality of piecewise transformations, each transformation can be determined based on a respective pair of consecutive calibration peaks, where two calibration peaks can be consecutive if no other calibration peaks in the measured data can be positioned therebetween.

[0055] Each piecewise transform may be selectively applied to a respective piecewise energy region of the reference data encompassing energies between or equal to the respective energies of a respective pair of target measurement peaks.

[0056] Each piecewise transform of the at least one piecewise transform may be a linear transform.

[0057] The method may include storing the piecewise transform in a memory device.

[0058] The method may include storing coefficients representing the piecewise transform in a memory device.

[0059] Each of the at least one piecewise transformation may be a subfunction of the piecewise function.

[0060] The method can include calculating a reference peak width parameter for each of a plurality of reference spectral peaks.

[0061] Each reference peak width parameter may indicate the energy range encompassed by the respective reference spectral peak.

[0062] Each reference peak width parameter may indicate the spread of a respective reference spectral peak along the energy axis.

[0063] Each reference peak width parameter may indicate the standard deviation of the respective reference spectral peak.

[0064] Each reference peak width parameter may include the variance of the respective reference spectral peak.

[0065] The method may include calculating a measured peak width parameter for each of a plurality of measured spectral peaks.

[0066] The method may include calculating a measured peak width parameter only for undisturbed measured spectral peaks, where a particular measured spectral peak may be undisturbed if any other spectral peaks in the measured data present in the same measured spectrum as the particular measured spectral peak have an energy difference from the particular measured spectral peak that exceeds a disturbance threshold. It may be advantageous to utilize the measured peak width parameter of only the undisturbed measured peaks. These measured spectral peaks may clearly indicate how a particular X-ray emission ray was detected during acquisition of the measured data. Thus, these measured spectral peaks may serve as a ground truth for how a particular instrument (i.e., the instrument used to obtain the measured data) may detect a particular X-ray emission ray. This information may be used to implement a corresponding correction to the reference data.

[0067] Each measured peak width parameter can indicate the energy range encompassed by the respective measured spectral peak.

[0068] Each measured peak width parameter may indicate the broadening of a respective measured spectral peak along the energy axis.

[0069] Each measured peak width parameter may indicate the standard deviation of the respective measured spectral peak.

[0070] Each measured peak width parameter may include the variance of the respective measured spectral peak.

[0071] Determining the transformation may include determining a peak width transformation based on a reference peak width parameter and a measured peak width parameter.

[0072] Peak width transformation can be advantageous because it can adjust the shape, particularly the width, of the peaks in the reference data so that they can better match the measured data.

[0073] The peak width transformation may be applicable to the entire energy range of the reference data.

[0074] The method may include fitting a reference peak width function to the reference peak width parameter and fitting a measured peak width function to the measured peak width parameter. The reference peak width function may thus represent the reference peak width parameter. Similarly, the measured peak width function may thus represent the measured peak width parameter.

[0075] The reference and measured peak width functions can be extrapolated over the full range of energies of the reference data.

[0076] The peak width transform may be determined based on a reference peak width function and a measured peak width function.

[0077] The peak width transform can be determined based on the difference between the reference peak width function and the measured peak width function.

[0078] The peak width transformation can be determined based on the square root of the difference between the squares of the reference peak width function and the measured peak width function.

[0079] The method may include storing the peak width transform in a memory device.

[0080] The method may include storing a function indicative of the peak width transform in a memory device.

[0081] The peak width transformation can be energy dependent.

[0082] Applying the peak width transform can include adjusting a reference peak width parameter of at least one reference spectral peak using the peak width transform. In this manner, the width of the reference spectral peak can be adjusted to better match the width of the measured data.

[0083] Determining the transformation can include determining an end-to-end transformation based on the first measured spectral peak, the second measured spectral peak, and the reference data, i.e., the end-to-end transformation can utilize only two measured spectral peaks.

[0084] The end-to-end transformation may be applicable to the entire energy range of the reference data.

[0085] The end-to-end transformation may be a linear transformation.

[0086] The first measured spectral peak may be a first undisturbed measured spectral peak having the lowest energy in the measured data, the second measured spectrum may be a second undisturbed measured spectral peak having the highest energy in the measured data, and a particular measured spectral peak may be undisturbed if any other spectral peak in the measured data present in the same measured spectrum as the particular measured spectral peak has an energy difference with the particular measured spectral peak that exceeds a disturbance threshold. In other words, the undisturbed peaks of the measured data having the lowest and highest energy may be used to determine the end-to-end transform.

[0087] Applying the end-to-end transform may include applying the end-to-end transform in an energy region encompassing an energy less than the minimum energy of the calibration peak and an energy greater than the maximum energy of the calibration peak. In other words, application of the end-to-end transform may be limited to an energy region that is outside the range defined by the calibration peaks having the lowest and highest energies. In simple terms, the end-to-end transform may not be necessary within the energy region in which the piecewise transform may be applied.

[0088] The method may further include applying a transformation to the reference data to generate calibrated reference data, such that the calibrated reference data may better match the measured data, i.e., the calibrated reference data may include fewer differences from the reference data.

[0089] Applying the transformation to the reference data to generate calibrated reference data may include modifying the reference data based on the transformation.

[0090] Applying the transformation may include applying at least one piecewise transformation.

[0091] Applying the transformation may include applying a peak width transformation.

[0092] Applying the transformation may include applying an end-to-end transformation.

[0093] Applying the transform may include applying a peak width transform prior to applying the at least one piecewise transform.

[0094] Applying the transform may include applying at least one piecewise transform in an energy region encompassing an energy between a minimum energy and a maximum energy of the calibration peak, inclusive, and applying an end-to-end transform in an energy region encompassing an energy less than the minimum energy of the calibration peak and greater than the maximum energy of the calibration peak.

[0095] The method may further include determining the elements contained in the sample by comparing the measured data with calibrated reference data.

[0096] The method may further include determining the elemental composition of the sample by elemental decomposition based on a comparison of the measured data to calibrated reference data.

[0097] Providing the reference data may include generating the reference data using the source instrument by emitting a beam toward one or more elemental standards using a beam source of the source instrument, obtaining an energy dispersive X-ray spectrum of the one or more elemental standards using an X-ray detector of the source instrument, and generating the reference data from the spectrum of the one or more elemental standards.

[0098] Obtaining the spectrum of the elemental standard may include obtaining the spectrum of the elemental standard at a high resolution instrument setting capable of detecting at least one million X-ray counts.

[0099] Obtaining spectra of elemental standards may include obtaining spectra of all naturally occurring elements in mineral analysis.

[0100] Providing the reference data may include generating measured data using the field device by emitting a beam toward a sample using a beam source of the field device, obtaining at least one energy dispersive X-ray spectrum of the sample using an X-ray detector of the field device, and generating measured data from the at least one energy dispersive X-ray spectrum of the sample.

[0101] Obtaining at least one energy dispersive X-ray spectrum of the sample may include obtaining at least one energy dispersive X-ray spectrum of the sample at a lower resolution instrument setting than the high resolution instrument setting used to generate the reference data.

[0102] The method may further include identifying the sample.

[0103] The invention may also relate to a method of calibrating an instrument for an analysis comprising the method described above.

[0104] The invention may also relate to a system comprising a beam source for emitting a beam onto a sample, an X-ray detector for detecting X-rays emitted from the sample upon impact of the beam, and a computer readable memory storing reference data indicative of at least one reference energy dispersive X-ray spectrum and measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from the sample, and determining a transformation based on a comparison of the measured data to the reference data.

[0105] The computer readable memory may further store computer instructions for applying a transformation to the reference data to generate calibrated reference data.

[0106] The computer readable memory may further store computer instructions for comparing the measured data with calibrated reference data to determine the elements contained in the sample.

[0107] The device may further comprise a data processing system configured to receive the computer instructions from the computer readable memory and execute the computer instructions.

[0108] The system may be configured to proceed with any of the method embodiments discussed above and below.

[0109] The present disclosure also relates to the following embodiments in certain embodiments: M1. A method comprising: providing reference data representing at least one reference energy dispersive X-ray spectrum; providing measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from the sample; and determining the transformation based on a comparison of the measured data to reference data. M2. The method of any one of the preceding embodiments, wherein the measured data includes measured spectral peaks. M3. The method of any preceding embodiment, wherein each measured spectral peak represents a respective element in the sample. M4. The method of any one of the preceding two embodiments, wherein each measured spectral peak represents a specific X-ray emission line of a respective element in the sample. M5. The method is 13. The method of any one of the preceding embodiments, comprising detecting measured spectral peaks for the measured data. M6. Standard data is 13. The method of any one of the preceding embodiments, comprising a reference spectral peak. M7. The method of any preceding embodiment, wherein each reference spectrum peak represents a respective element. M8. The method of any one of the two preceding embodiments, wherein each reference spectrum peak represents a specific X-ray emission line of a respective element. M9. The method of any one of the preceding embodiments, further comprising detecting a calibration peak on the measured data. M10. The method of any preceding embodiment, wherein the calibration peak comprises an intensity greater than a background radiation intensity. M11. The method of any one of the preceding two embodiments, wherein for each calibration peak, the ratio between the intensity of the calibration peak and the background radiation intensity is higher than an intensity ratio threshold. M12. The method of any one of the preceding three embodiments, wherein each calibration peak is undisturbed such that any other spectral peak in the measured data that is present in the same measured spectrum as the calibration peak has an energy difference from the calibration peak that is greater than a disturbance threshold. M13. The method of any one of the preceding four embodiments having the features of embodiment M2, wherein the calibration peaks are a subset of the measured spectral peaks. M14. The method having the feature of embodiment M2 of any one of the preceding five embodiments, wherein detecting calibration peaks in the measured data includes classifying at least some of the measured spectral peaks as calibration peaks. M15. The method of any preceding embodiment, wherein classifying at least some of the measured spectral peaks as calibration peaks is based on the intensities of each of the measured spectral peaks. M16. The method of any one of the preceding two embodiments, wherein classifying at least some of the measured spectral peaks as calibration peaks is based on intensities of the measured spectral peaks relative to a background radiation intensity. M17. The method of any one of the preceding three embodiments, wherein the measured spectral peak is classified as a calibration peak if the ratio between the intensity of the measured spectral peak and the background radiation intensity is higher than an intensity ratio threshold. M18. The method of any one of the preceding four embodiments, wherein classifying at least some of the measured spectral peaks as calibration peaks is based on energies of the measured spectral peaks. M19. The method of any one of the preceding five embodiments, wherein a particular measured spectral peak is classified as a calibration peak if it is undisturbed such that any other measured spectral peaks in the measured data that are present in the same measured spectrum as the particular measured spectral peak have an energy difference with the particular measured spectral peak that exceeds a disturbance threshold. M20. The method of any one of the preceding six embodiments, wherein at least one measured spectral peak is classified as a calibration peak if it is the highest of the measured spectral peaks in the measured data corresponding to the same X-ray emission line. M21. Detecting calibration peaks in measured data (a) For each measured spectrum in the measured data, (a1) detecting all measured spectral peaks in a measured spectrum; (a2) rejecting measured spectral peaks in the measured spectrum that contain a peak-to-background ratio that is less than an intensity ratio threshold, the peak-to-background ratio being the ratio between the intensity of the measured spectral peak and the intensity of background radiation; (a3) rejecting a measured spectral peak in the measured spectrum that overlaps with another measured spectral peak in the measured spectrum, where the two peaks in the measured spectrum include an energy difference that is less than a jamming threshold; and (b) grouping all unrejected measured spectral peaks from (a) into groups according to the X-ray emission lines they represent; The method having the features of embodiment M9 of any one of the preceding embodiments, comprising: (c) determining as a calibration peak the non-rejected measured spectral peak having the highest peak-to-background ratio from each of the groups. M22. The method having the feature of embodiment M9 of any one of the preceding embodiments, wherein determining the transformation includes determining at least one piecewise transformation based on the calibration peaks and the reference data. M23. The method of any preceding embodiment, wherein at least one piecewise transformation is applicable to a portion of the total energy range of the reference data. M24. The method of any preceding embodiment, wherein the portion is between a minimum energy and a maximum energy, inclusive, of the calibration peak. M25. Each of the at least one piecewise transformation is determined based on a respective pair of consecutive calibration peaks; 13. The method of any one of the preceding three embodiments, wherein two calibration peaks are consecutive if no other calibration peak in the measured data contains an energy between the energies of the two consecutive calibration peaks. M26. The method according to the preceding embodiment, wherein each of the at least one piecewise transformation is selectively applied to a respective piecewise energy region of the reference data encompassing energies between or equal to the respective energies of a respective pair of calibration peaks. M27. Determining the transformation includes determining a plurality of piecewise transformations; Each transformation is determined based on a respective pair of consecutive calibration peaks; The method having the features of embodiment M9 of any one of the preceding embodiments, wherein two calibration peaks are consecutive if no other calibration peak in the measured data is positioned between them. M28. The method according to the preceding embodiment, wherein each of the piecewise transforms is selectively applied to a respective piecewise energy region of the reference data encompassing energies between or equal to the respective energies of a respective pair of target measurement peaks. M29. The method of any one of the preceding seven embodiments, wherein each piecewise transformation of the at least one piecewise transformation is a linear transformation. M30. The method of any one of the preceding eight embodiments, wherein the method includes storing the piecewise transformation in a memory device. M31. The method of any one of the preceding nine embodiments, wherein the method includes storing coefficients indicative of the piecewise transform in a memory device. M32. The method of any one of the preceding ten embodiments, wherein each of the at least one piecewise transformation is a subfunction of a piecewise function. M33. The method of any one of the preceding embodiments, wherein the method includes calculating a reference peak width parameter for each of a plurality of reference spectral peaks. M34. The method according to any preceding embodiment, wherein each reference peak width parameter indicates an energy range encompassed by a respective reference spectral peak. M35. The method of any one of the preceding two embodiments, wherein each reference peak width parameter indicates the spread of a respective reference spectral peak along an energy axis. M36. The method of any one of the preceding three embodiments, wherein each reference peak width parameter indicates the standard deviation of a respective reference spectral peak. M37. The method of any one of the preceding four embodiments, wherein each reference peak width parameter comprises a variance of a respective reference spectral peak. M38. The method of any one of the preceding embodiments, wherein the method includes calculating a measured peak width parameter for each of a plurality of measured spectral peaks. M39. The method of any preceding embodiment, wherein the method includes calculating a measured peak width parameter only for undisturbed measured spectral peaks, and a particular measured spectral peak is undisturbed if any other spectral peaks in the measured data that are present in the same measured spectrum as the particular measured spectral peak have an energy difference from the particular measured spectral peak that exceeds a disturbance threshold. M40. The method of any one of the preceding two embodiments, wherein each measured peak width parameter indicates the energy range encompassed by a respective measured spectral peak. M41. The method of any one of the preceding three embodiments, wherein each measured peak width parameter indicates the broadening of a respective measured spectral peak along an energy axis. M42. The method of any one of the preceding four embodiments, wherein each measured peak width parameter indicates the standard deviation of a respective measured spectral peak. M43. The method of any one of the preceding five embodiments, wherein each measured peak width parameter comprises a variance of a respective measured spectral peak. M44. The method having the features of embodiments M33 and M38 of any one of the preceding embodiments, wherein determining the conversion comprises determining a peak width conversion based on a reference peak width parameter and a measured peak width parameter. M45. The method of any preceding embodiment, wherein the peak width transformation is applicable to the entire energy range of the reference data. M46. The method of any one of the preceding two embodiments, wherein the method includes fitting a base peak width function to the base peak width parameters, and fitting a measured peak width function to the measured peak width parameters. M47. The method of any preceding embodiment, wherein the peak width transformation is determined based on a reference peak width function and a measured peak width function. M48. The method of any one of the two preceding embodiments, wherein the peak width transformation is determined based on the difference between a reference peak width function and a measured peak width function. M49. The method of any one of the preceding three embodiments, wherein the peak width transform is determined based on the square root of the difference between the squares of the reference peak width function and the measured peak width function. M50. The method of any one of the preceding six embodiments, wherein the method includes storing the peak width transform in a memory device. M51. The method of any one of the preceding seven embodiments, comprising storing a function indicative of a peak width transformation in a memory device. M52. The method of any one of the preceding eight embodiments, wherein the peak width transform is energy dependent. M53. The method of any one of the preceding nine embodiments, wherein applying a peak width transform comprises adjusting a reference peak width parameter of at least one reference spectral peak using the peak width transform. M54. 13. A method as in any one of the preceding embodiments, wherein determining the transformation includes determining an end-to-end transformation based on the first measured spectral peak, the second measured spectral peak, and the reference data. M55. The method of any preceding embodiment, wherein the end-to-end transformation is applicable to the entire energy range of the reference data. M56. the first measured spectral peak is a first undisturbed measured spectral peak having a lowest energy in the measured data; the second measured spectrum being a second undisturbed measured spectral peak having the highest energy in the measured data; 13. The method of any one of the preceding two embodiments, wherein a particular measured spectral peak is not disturbed if any other spectral peak in the measured data that is present in the same measured spectrum as the particular measured spectral peak has an energy difference from the particular measured spectral peak that exceeds a disturbance threshold. M57. The method having the feature of embodiment M9 of any one of the preceding three embodiments, wherein applying the end-to-end transform includes applying the end-to-end transform in an energy region encompassing an energy less than a minimum energy of the calibration peak and an energy greater than a maximum energy of the calibration peak. M58. The method of any one of the preceding embodiments, further comprising applying a transformation to the reference data to generate calibrated reference data. M59. The method of any preceding embodiment, wherein applying a transformation to the reference data to generate calibrated reference data includes modifying the reference data based on the transformation. M60. The method having the feature of embodiment M22 of any one of the preceding two embodiments, wherein applying a transformation includes applying at least one piecewise transformation. M61. The method having the feature of embodiment M44, of any one of the preceding three embodiments, wherein applying a transformation includes applying a peak width transformation. M62. The method having the feature of embodiment M54 of any one of the preceding four embodiments, wherein applying the transformation includes applying an end-to-end transformation. M63. The method having the features of embodiments M22 and M44 of any one of the preceding five embodiments, wherein applying a transform comprises applying a peak width transform prior to applying the at least one piecewise transform. M64. Applying transformations applying at least one piecewise transformation in an energy region encompassing energies between a minimum and a maximum energy of the calibration peak, inclusive; The method having the features of embodiments M22 and M54 of any one of the preceding six embodiments, comprising applying an end-to-end transform in an energy domain encompassing energies less than the minimum energy of the calibration peaks and greater than the maximum energy of the calibration peaks. M65. The method of any one of the preceding seven embodiments, further comprising determining the elements contained in the sample by comparing the measured data with calibrated reference data. M66. The method of any one of the preceding eight embodiments, further comprising determining the elemental composition of the sample through elemental decomposition based on a comparison of the measured data to calibrated reference data. M67. Providing reference data is done by using a source device to provide reference data, directing a beam toward one or more elemental standards using a beam source of a source instrument; obtaining an energy dispersive X-ray spectrum of one or more elemental standards using an X-ray detector of a source instrument; 4. The method of any one of the preceding embodiments, comprising generating reference data from spectra of one or more elemental standards. M68. The method of any preceding embodiment, wherein obtaining a spectrum of the elemental standard includes obtaining a spectrum of the elemental standard at a high resolution instrument setting at which at least one million X-ray counts are detected. M69. The method of any one of the preceding two embodiments, wherein obtaining spectra of elemental standards comprises obtaining spectra of all naturally occurring elements in mineral analysis. M70. Providing measured data is using a source device to provide measured data, directing a beam toward the sample using a beam source of the field device; obtaining at least one energy dispersive X-ray spectrum of the sample using an X-ray detector of the field device; 4. The method of any one of the preceding embodiments, comprising generating measured data from at least one energy dispersive X-ray spectrum of the sample. M71. The method of any preceding embodiment, wherein obtaining at least one energy dispersive X-ray spectrum of the sample includes obtaining at least one energy dispersive X-ray spectrum of the sample at a lower resolution instrument setting than a high resolution instrument setting used to generate the reference data. M72. The method of any one of the preceding embodiments, further comprising identifying the sample. M73. The method having the feature of embodiment M54 of any one of the preceding embodiments, wherein the end-to-end transformation is a linear transformation. M74. A method of calibrating an instrument for sample analysis, comprising the method of any one of the preceding embodiments. S1. A system comprising: a beam source for emitting a beam onto a sample; an X-ray detector for detecting X-rays emitted from the sample upon impact of the beam; Reference data representing at least one reference energy dispersive X-ray spectrum; obtaining measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from the sample; and determining a transformation based on a comparison of the measured data to reference data. S2. A computer readable memory comprising: The system of the preceding embodiment, further storing computer instructions for applying a transformation to the reference data to generate calibrated reference data. S3. The computer readable memory comprises: 20. The system of any one of the preceding embodiments, further storing computer instructions for comparing the measured data with calibrated reference data to determine elements contained in the sample. S4. The system of any one of the preceding three embodiments, further comprising a data processing system configured to receive computer instructions from the computer-readable memory and execute the computer instructions. S5. A system as described in any one of the preceding four embodiments, wherein the system is configured to perform a method as described in any one of the preceding method embodiments. [Brief description of the drawings]

[0110] [Figure 1] FIG. 2 shows a measured spectrum and a corresponding reference spectrum. [Diagram 2] FIG. 1 illustrates misidentification within a mineral. [Diagram 3] 1 illustrates standard deviations for several reference and several measured spectral peaks and their respective fits. [Figure 4] 4 illustrates the extrapolation applied to the standard deviations of FIG. 3 . [Diagram 5]5 illustrates an example of a peak width transformation determined based on the extrapolation of FIG. 4. [Figure 6] Illustrates calibration peaks in the spectrum. [Figure 7] 1 illustrates piecewise energy portions along a spectrum to which each piecewise transform can be selectively applied. [Figure 8] 8 illustrates respective piecewise transformations that can be applied to the piecewise energy portions of FIG. 7; [Figure 9] FIG. 2 shows a measured spectrum and corresponding reference and calibrated reference spectra. [Figure 10] FIG. 1 illustrates different phases in a mineral sample identified using the teachings of the present disclosure. [Figure 11] 1 illustrates the peak energy differences between three different measured data and the corresponding reference data for scenarios where the reference data is not calibrated, where the reference data is calibrated using existing techniques, and where the reference data is calibrated using the teachings of the present disclosure. [Figure 12] 1 illustrates a method that can be used to calibrate the reference data. [Figure 13] 1 shows a scanning electron beam with an X-ray detector suitable for analyzing standards according to a preferred embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0111] A preferred embodiment of the present invention provides a method for calibrating a local energy dispersive spectroscopy (EDS) instrument using measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from a sample. Preferably, the local EDS instrument may store reference data that may contain high quality spectra of all elements being analyzed. The measured data is compared to the reference data, and this comparison is used to define a transformation. The transformation may then be applied to the reference data to generate calibrated reference data that may include a calibrated spectrum for each spectrum in the original reference data. As a result, the spectra contained in the reference data may be much closer to the spectra that would result if the respective elements were analyzed on the same local instrument using the same instrument settings. The spectra generated by the local EDS instrument may then be compared to the calibrated reference data to determine the elements in the sample. This may help to significantly improve the accuracy of elemental identification.

[0112] FIG. 1 is an illustration of a measured spectrum 14 and a corresponding reference spectrum 12. Throughout this disclosure, unless otherwise implied by context, the term spectrum will be understood to refer to an energy dispersive X-ray spectrum, i.e., a spectrum obtained using energy dispersive X-ray spectroscopy. In the figure, the horizontal axis indicates the energy of the detected X-rays emitted from the sample in keV (kiloelectronvolts), and the vertical axis indicates the number of X-rays collected at each energy level, i.e., the number of photons or photon count. Thus, each spectrum shows the number of X-rays detected at different energy levels. The number of X-rays is sometimes referred to as the intensity.

[0113] The measured spectrum 14 may be part of the measured data and may be obtained during analysis of a sample using an EDS instrument. Those skilled in the art will understand that each peak in the measured spectrum 14, and in particular the energy of each peak, is indicative of a respective chemical element. Throughout this disclosure, the terms chemical element and element are used interchangeably, unless otherwise implied by the context.

[0114] The corresponding reference spectrum 12 may be part of the reference data. As any spectrum in the reference data, it may typically be obtained by analyzing an elemental standard, i.e. a reference material whose composition is known, using the EDS instrument. Furthermore, the reference data may typically be obtained using a high resolution setting of the EDS instrument. Furthermore, it may be preferable to obtain the reference data with the same type of EDS detector and / or using the same beam voltage as that used to obtain the measured data. That is, it may be preferable to use similar conditions to obtain the reference data and the measured data. This may increase the similarity between the measured data and the corresponding reference data, which in turn increases the identification of elements or phases in the sample.

[0115] Nevertheless, since it may be difficult to guarantee the exact conditions for obtaining the reference and measured data, differences between them may be expected. Such differences are illustrated in FIG. 1, which again shows a measured spectrum 14 and a corresponding reference spectrum 12, both depicting the same material, which in this example is quartz (SiO2). A first difference 15 is illustrated at about 0.5 keV, indicating that there may be a shift 15 between the detection energy of the measured spectrum peak and the energy of the corresponding reference spectrum peak. In this example, both peaks represent oxygen. A second difference 17, 19 is illustrated between 1.5-2 keV, indicating that there may be a difference between the width 17 of the measured spectrum peak and the width 19 of the reference spectrum peak. As used herein, the width of a peak refers to the spread of the peak along the energy axis.

[0116] Such differences can contribute to errors in identifying unknown elements or phases in a sample. Such misidentifications can typically appear for phases with similar elemental compositions, such as chalcopyrite (CuFeS2), cobaltite (CuS), chalcocite (Cu2S), and bornite (Cu5FeS4), etc. In particular, misidentifications can appear at boundaries between phases with similar elemental compositions.

[0117] FIG. 2 illustrates a misidentification of phases within a mineral sample. In the figure, the materials contained in each zone of the sample are indicated by their respective diagonal lines. In particular, EDS analysis of the sample shows that it contains bornite 26, chalcopyrite 22, chalcocite 24, covellite 27, tetrahedrite 25 and other materials 29. The sample zone shown with a thick outline represents at least a part of the sample whose composition is misidentified. In particular, the zone in question is at the boundary between chalcopyrite 22 and chalcocite 24 and is misidentified as being composed of bornite 26. Such misidentification appears due to the high similarity in the elemental composition of these materials, which in turn means that they contain similar spectra. Thus, differences between measured data (e.g., as illustrated in FIG. 1) and reference data can lead to these phases being misidentified from one another.

[0118] The present disclosure provides different techniques for mitigating differences between measured data and reference data, thereby mitigating false identifications. In particular, the present disclosure teaches calculating a peak width transform (FIGS. 3-5) and at least one piecewise transform (FIGS. 6-8). The present disclosure teaches applying a peak width transform to the reference data to adjust the width of a reference spectral peak 19 (see FIG. 1) and applying at least one piecewise transform to selected energy portions of the reference data to reduce or eliminate a shift 15 (see FIG. 1) between the detected energy of a measured spectral peak and the energy of the corresponding reference spectral peak.

[0119] FIG. 3 depicts a scatter plot of the standard deviations 32, 37 of the measured and reference spectral peaks. In particular, the squares 32 indicate the standard deviations of the measured spectral peaks, and the circles 37 indicate the standard deviations of the reference spectral peaks present in the reference data. As can be noted, there may be more standard deviations of the reference spectral peaks than the standard deviations of the measured spectral peaks. In the plot, the horizontal axis indicates energy in keV, and the vertical axis is unitless and indicates the standard deviation values. As shown, in this example, the standard deviation of the measured spectral peaks is higher than the corresponding standard deviation of the reference spectral peaks. Those skilled in the art will appreciate that the measured spectral peaks and the reference measurement peaks correspond if they contain similar energy levels and thus represent the same material. It will be further appreciated that the measured spectral peaks and their corresponding reference measurement peaks ideally contain the same energy levels.

[0120] Although the plot only shows the standard deviation of the reference spectral peaks up to 10 keV, it will be understood that the standard deviation of all reference spectral peaks present in the reference data can be used.

[0121] Further, a respective function 34, 35 can be fitted to each set of standard deviations 32, 37. In particular, the reference peak width function 35 can be fitted to the standard deviation of the reference spectral peaks, and the measured peak width function 34 can be fitted to the standard deviation of the measured spectral peaks. As an example, a weighted least squares function can be utilized to calculate the functions 34, 35. The weights can be calculated based on the concentrations of the elements in the sample, which can be obtained by comparing the measured data to reference data (i.e., reference data before calibration). Again, the reference peak width function 35 can extend beyond the depicted energy range, and in fact can extend across the entire energy range of the reference data.

[0122] Figure 4 illustrates the extrapolation applied to the standard deviations of Figure 3. In particular, the calculated functions 34, 35 can be used to extrapolate the standard deviations 32, 37 of the measured and reference spectral peaks over a wider range of energy levels and higher densities. As can be noted in Figure 3, the standard deviation of the measured spectral peak lies between 0 and 8 keV and has been extrapolated to a wider range of 0 to 20 keV. In addition, further values ​​can be calculated for the standard deviations of the measured and reference spectral peaks, so that the standard deviations are more tightly distributed over the energy range.

[0123] More specifically, as illustrated in Figure 4, a measured peak width function 34 can be used to calculate a respective standard deviation for each energy bin defined across the entire energy range of the reference data, in this example 0-20 keV. Similarly, a reference peak width function 35 can be used to calculate a respective standard deviation for each energy bin defined across the entire energy range of the reference data.

[0124] FIG. 5 illustrates an example of a peak width transform 50 determined based on the extrapolation of FIG. 4. In this example, for each energy bin defined among the entire energy range of the reference data, a respective peak width transform value can be calculated based on the difference between the standard deviation 32 of the measured spectral peak for that energy bin and the standard deviation 37 of the reference spectral peak for that energy bin. The calculated peak width transform values ​​can be stored in a memory device for future use. Alternatively or alternatively, a function such as a polynomial function can be fitted to the peak width transform values ​​and the function can be stored in a memory device for future use.

[0125] In the examples illustrated in Figures 3-5, the standard deviation was used to determine the peak width transform 50, but it will be understood that in general any other measure of the width of the spectral peak can be used. That is, in general, a peak width parameter of the spectral peak can be used. The peak width parameter can indicate the spread of the spectral peak along the energy axis. In some embodiments (as illustrated in Figures 3-5), the peak width parameter can indicate the standard deviation 32, 37 of the spectral peak. Alternatively or additionally, the peak width parameter can indicate the dispersion of the spectral peak.

[0126] FIG. 6 illustrates a calibration peak 60 in a spectrum. The calibration peak 60 may be a subset of all spectral peaks present in the spectrum. The calibration peak 60 may be a spectral peak that meets a predetermined requirement. The calibration peak 60 may be detected by first detecting spectral peaks in the measured spectrum, then determining which of the spectral peaks meet one or more predetermined requirements, and classifying the spectral peaks that meet the one or more requirements as calibration peaks 60. Alternatively or additionally, the calibration peak 60 may be detected by storing descriptive data of the calibration peak 60 in a memory device, and then searching the measured spectrum for the calibration peak 60 by utilizing the data describing the calibration peak. The descriptive data of the calibration peak 60 may include at least one predetermined requirement.

[0127] Calibration peak 60 may preferably be an unobstructed spectral peak.

[0128] Furthermore, where multiple spectral peaks are detected in a sample for a particular element or at a particular energy level, it may be advantageous to select the highest spectral peak (i.e., the spectral peak with the highest photon count) as calibration peak 60. For example, where a sample has various phases that all contain silicon, the silicon peak of the phase that has the highest silicon peak may be selected as calibration peak 60. Alternatively or additionally, where a sample has various phases that all contain silicon, the silicon peak of the phase that does not contain other materials that interfere with silicon is selected as calibration peak 60. Silicon is used herein merely as an example, and it will be understood that the definition of selecting a calibration peak applies to any particular element.

[0129] In Fig. 6, eight calibration peaks 60a-60h are depicted. In the depicted example, the first calibration peak 60a corresponds to the Kα (K-alpha) X-ray emission line of oxygen, the second calibration peak 60b corresponds to the Kα X-ray emission line of sodium, the third calibration peak 60c corresponds to the Kα X-ray emission line of magnesium, and the fourth emission line 60e corresponds to the Kα X-ray emission line of aluminum. The fifth to eighth calibration peaks 60f, 60g, and 60h likewise correspond to specific X-ray emission lines of elements.

[0130] Consecutive pairs of calibration peaks 60 can be utilized to determine a piecewise transformation. Two calibration peaks 60 are consecutive if no other calibration peak 60 contains an energy between the energies of the two consecutive calibration peaks. In the example of FIG. 6, a first calibration peak 60a and a second calibration peak 60b form a first pair of consecutive calibration peaks 60a-60b. Similarly, a second calibration peak 60b and a third calibration peak 60c form a second pair of consecutive calibration peaks 60b-60c. The third through seventh pairs of consecutive calibration peaks are similarly formed by calibration peaks 60c-60d, 60d-60e, 60e-60f, 60f-60g, and 60g-60h.

[0131] It will be understood that the spectrum may include other peaks as well. For example, the spectrum may include a peak 61 that is not a calibration peak 60. As illustrated, another peak 61 that is not a calibration peak 60 may be present between consecutive calibration peaks 60. For example, peak 61 is present between consecutive calibration peaks 60e and 60f.

[0132] Each successive calibration peak 60, and in particular their respective energies, defines a respective piecewise energy region within which a respective piecewise transformation is applicable.

[0133] FIG. 7 illustrates such piecewise energy regions 70 outlined across the spectrum of FIG. 6. For each pair of consecutive calibration peaks 60 of FIG. 6, there may be a respective piecewise energy region 70. In particular, a first pair of consecutive calibration peaks 60a-60b may define a first piecewise energy region 70a. A second pair of consecutive calibration peaks 60b-60s may define a second piecewise energy region 70b. Similarly, a third through seventh pair of consecutive calibration peaks 60c-60d, 60d-60e, 60e-60f, 60f-60g, and 60g-60h may define third through seventh piecewise energy regions 70c, 70d, 70e, 70f, and 70g, respectively.

[0134] For each piecewise energy region 70, a respective piecewise transform may be applicable.

[0135] FIG. 8 illustrates each of the piecewise transforms 80 outlined across the spectrum of FIG. 6. In the depicted example, each piecewise transform 80 is a linear transform, as indicated by the respective lines describing each piecewise transform 80. That is, in FIG. 8, lines 80a-80g may indicate parameters of each piecewise transform 80 (which in this example are of linear type), and filled circles depict boundaries of respective piecewise energy regions 70 to which each piecewise transform 80 is applicable. The boundaries coincide with the energies of the calibration peaks 60 of FIG. 6.

[0136] Thus, the first piecewise transform 80a may be applicable to the first piecewise energy region 70a. That is, all reference data for energies within the first piecewise energy region 70 may be transformed using the first piecewise transform 80a. Similarly, the second piecewise transform 80b may be applicable to the second piecewise energy region 70b. That is, all reference data for energies within the second piecewise energy region 70 may be transformed using the second piecewise transform 80a. Similarly, the third through seventh piecewise transforms 80c, 80d, 80e, 80f, and 80g may be applicable to the third through seventh piecewise energy regions 70c, 70d, 70e, 70f, and 70g, respectively.

[0137] The piecewise transform 80 may be defined by a piecewise defined function (also called a piecewise function).

[0138] FIG. 9 illustrates a measured spectrum 96 (dashed line), a corresponding reference spectrum 92 (dotted line), and a calibrated reference spectrum 94 (bold line). That is, for the measured spectrum 96, FIG. 9 depicts the corresponding reference spectrum before calibration (spectrum 92) and after calibration (spectrum 96). The calibrated reference spectrum 94 can be obtained by applying at least the peak width transform 50 and / or the piecewise transform 80. As can be noted, the calibrated reference spectrum 94 is more similar to the measured spectrum 96 than the pre-calibration reference spectrum 92. In this example, it was observed that the correlation between the measured spectrum 96 and the pre-calibration reference spectrum 92 was 97.65%, and the correlation between the measured spectrum 96 and the calibrated reference spectrum 94 was 99.62%.

[0139] 10 illustrates phase identification in the mineral sample of FIG. 2 using reference data calibrated according to the techniques of the present disclosure. As can be seen, at the boundary between chalcopyrite 22 and chalcocite 24, the presence of bornite 26 (which is an artifact) is significantly reduced.

[0140] FIG. 11 illustrates the peak energy differences between three different measured data and the corresponding reference data for scenarios where the reference data is not calibrated, the reference data is calibrated using existing techniques, and the reference data is calibrated using the teachings of the present disclosure.

[0141] In particular, the horizontal axis indicates the energy level in keV and the vertical axis depicts the peak energy delta in eV. The peak energy delta (or peak energy difference) is defined as the difference between a peak in the measured data and the corresponding peak in the (calibrated) reference data. Thus, the peak energy delta is a measure of the difference that exists between the measured data and the corresponding (calibrated) reference data. It will be appreciated that the peak energy delta should be as small as possible, ideally zero.

[0142] In the top plot, the reference data is uncalibrated. In the middle plot, the reference data is calibrated using conventional techniques. In the bottom plot, the reference data is calibrated using the techniques of the present disclosure. Dotted lines 102, 112, and 122 depict the peak energy delta for the spectrum of a first sample. Dashed lines 106, 116, and 126 depict the peak energy delta for the spectrum of a second sample. Solid lines 104, 114, and 124 depict the peak energy delta for the spectrum of a third sample.

[0143] The conventional technique used to calibrate the reference data for the scenario illustrated in the center plot of Figure 11 involves the use of a single linear transform across the entire range of the reference data, which is generated using the minimum and maximum undisturbed peaks on the measured data.

[0144] As depicted, the peak delta for all three samples is smaller in the middle plot than in the top plot, i.e., the prior art calibration technique provides some improvement, whereas the disclosed technique provides a larger improvement, as depicted by the scale of the vertical axis, i.e., it is observed that the disclosed technique provides a peak delta that is approximately 1000 times smaller than the prior art technique.

[0145] 12 shows a flow chart of the method. The method can be used to generate calibrated reference data. For example, the method can be used to calibrate an EDS instrument.

[0146] The method includes step S1 of providing reference data and / or measured data. The method may further include step S2 of determining a peak width transformation. S2 may be performed as described with reference to Figs. 3-5. The method may further include step S3 of determining at least one piecewise transformation. S3 may be performed as described with reference to Figs. 6-8. Optionally, the method may include step S4 of determining a single end-to-end transformation. S4 may be performed according to the prior art discussed with reference to Fig. 11 (middle plot). The method may further include step S5 of applying a peak width transformation and / or at least one piecewise transformation. Preferably, both a peak width transformation and the at least one piecewise transformation are determined and applied. More preferably, the peak width transformation is applied before the at least one piecewise transformation. Optionally, the method may include step S6 of applying an end-to-end transformation. Preferably, the end-to-end transformation is applied to an energy region outside of the energy region in which the at least one piecewise transformation is applied. The method includes step S7 of generating calibrated reference data.

[0147] The method may further include determining the elemental composition of the sample by elemental decomposition based on a comparison of the measured data to calibrated reference data.

[0148] 13 shows an example of a system 300 having an X-ray detector 340 suitable for analyzing a sample. A beam source 341 may be provided in the system 300 along with a power and control unit 345. A beam 332 may be emitted using the beam source 341. The beam 332 may be an electron beam, an ion beam or an X-ray beam.

[0149] A system controller 333 may control the operation of various parts of the system 300. The vacuum chamber 310 may be evacuated using an ion pump 368 and a mechanical pumping system 369 under the control of a vacuum controller 334.

[0150] The electron beam 332 may be focused onto a sample 302, which may be provided on a sample stand 304. The sample stand 304 may be a movable XY stage 304 in a lower vacuum chamber 310. When the beam strikes the sample 302, the sample 302 emits X-rays whose energy correlates to the elements in the sample 302. In the vicinity of the beam incidence area, X-rays are produced that have an energy specific to the elemental composition of the sample. The emitted X-rays are collected by an X-ray detector 340, preferably an energy dispersive detector of the silicon drift detector type, although other types of detectors capable of producing a signal having an amplitude proportional to the energy of the detected X-rays may also be employed.

[0151] The output from the detector 340 may be amplified and sorted by a processor 320 capable of counting and sorting the total number of x-rays detected during a specified time period at a selected energy and energy resolution, and channel width typically between 2.5 and 20 eV per channel. The processor 320 may comprise a computer processor, operator interface means (such as a keyboard or computer mouse), program memory 322 for storing data and executable instructions, interface means for data input and output, executable software instructions embodied in executable computer program code, and a display 344 for displaying the results of the multivariate spectral analysis by means of a video circuit 342.

[0152] The processor 320 may be part of a standard laboratory personal computer and will typically be coupled to at least some form of computer readable media. Computer readable media, including both volatile and non-volatile media, removable and non-removable media, may be any available media that can be accessed by the processor 320. By way of example and not limitation, computer readable media include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules, or other data. For example, computer storage media includes RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by the processor 320.

[0153] The program memory 322 can include computer storage media in the form of removable and / or non-removable, volatile and / or non-volatile memory, and can provide storage of computer readable instructions, data structures, program modules, and other data. Typically, the processor 320 is programmed by instructions stored at different times on the various computer readable storage media of the computer. Programs and operating systems are typically distributed, for example, on floppy disks or CD-ROMs. From there, they are installed or loaded into the secondary memory of the computer. At execution, they are loaded at least partially into the primary electronic memory of the computer. The invention described herein includes these and various other types of computer readable storage media, when such media contain instructions or programs for implementing the steps described below in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein.

[0154] The x-ray spectrum obtained as described above may be stored in a portion of memory 322, such as measured spectrum memory portion 323. Reference data is also stored in measured spectrum memory 323.

[0155] Although the illustrated embodiment includes a scanning electron microscope, related embodiments may use a transmission electron microscope or a scanning transmission electron microscope to generate x-rays from the sample. X-ray fluorescence systems may also be used to generate x-rays from the sample. Other embodiments may detect other characteristic radiation, such as gamma rays, from the sample.

[0156] The preferred method or apparatus of the present invention has many novel aspects, and since the invention can be embodied in different methods or apparatus for different purposes, not all aspects need to be present in all embodiments. Moreover, many of the aspects of the described embodiments may be separately patentable. The present invention has broad applicability and can provide many benefits as described and illustrated in the examples above. The embodiments will vary widely depending on the particular application, and not all embodiments will provide all of the benefits or meet all of the objectives achievable by the present invention.

[0157] It should be appreciated that embodiments of the present invention may be implemented through computer hardware, a combination of both hardware and software, or by computer instructions stored in non-transitory computer-readable memory. The methods may be implemented in computer programs using standard programming techniques, including non-transitory computer-readable storage media configured with computer programs in accordance with the methods and figures described herein, the storage media so configured causing a computer to operate in a specific predefined manner. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, the programs may be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the programs may run on dedicated integrated circuits programmed for that purpose.

[0158] Furthermore, the methods may be implemented in any type of computing platform, including, but not limited to, personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, computer platforms separate from, integrated with, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, RAM, ROM, etc., so as to be readable by a programmable computer to configure and operate the computer when the storage medium or device is read by the computer to perform the procedures described herein. Furthermore, the machine-readable code or portions thereof may be transmitted over a wired or wireless network. The invention described herein includes these and various other types of non-transitory computer-readable storage media, when such media contain instructions or programs for implementing the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein.

[0159] Computer programs can be applied to input data to perform the functions described herein, thereby transforming the input data to generate output data. The output information is applied to one or more output devices, such as a display monitor. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including causing particular visual depictions of the physical and tangible objects to occur on a display.

[0160] In the following discussion and claims, the terms "including" and "comprising" are used in an open-ended manner and, therefore, unless any term is specifically defined herein to be interpreted as meaning "including, but not limited to," the intention is for the term to be given its plain and ordinary meaning. The accompanying drawings are intended to aid in the understanding of the invention and, unless otherwise indicated, are not drawn to scale. Particle beam systems suitable for practicing the invention are commercially available, for example, from FEI Company, the assignee of the present application.

[0161] Although the present invention and its advantages have been described in detail, it should be understood that various changes, substitutions, and alterations can be made to the embodiments described herein without departing from the spirit and scope of the present invention as defined by the appended claims. Moreover, the scope of the present application is not intended to be limited to the particular embodiments of the processes, machines, manufacture, compositions, means, methods, and steps described herein. As one skilled in the art will readily appreciate from the present disclosure, any currently existing or later developed process, machine, manufacture, composition, means, method, or step that performs substantially the same function or achieves substantially the same result as the corresponding embodiments described herein may be utilized in accordance with the present invention. It is therefore intended that the appended claims include within their scope such processes, machines, manufacture, compositions, means, methods, or steps.

Claims

1. 1. A method comprising: providing reference data representing at least one reference energy dispersive X-ray spectrum; providing measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from the sample; determining a transformation based on a comparison of the measured data and the reference data; The method further includes detecting a calibration peak in the measured data; The method, wherein determining a transformation comprises determining at least one piecewise transformation based on the calibration peaks and the reference data.

2. the measured data includes measured spectral peaks; the calibration peaks are a subset of the measured spectral peaks; The method of claim 1 , wherein detecting calibration peaks on the measured data comprises classifying at least some of the measured spectral peaks as calibration peaks.

3. The method of claim 2 , wherein classifying at least some of the measured spectral peaks as calibration peaks is based on intensities of the measured spectral peaks relative to a background radiation intensity.

4. 3. The method of claim 2, wherein a particular measured spectral peak is classified as a calibration peak if it is undisturbed such that any other measured spectral peak in the measured data that is present in the same measured spectrum as the particular measured spectral peak has an energy difference from the particular measured spectral peak that exceeds a disturbance threshold.

5. Detecting a calibration peak on the measured data, (a) for each measured spectrum in the measured data, (a1) detecting all measured spectral peaks in the measured spectrum; (a2) rejecting measured spectral peaks in the measured spectrum that contain a peak-to-background ratio that is less than an intensity ratio threshold, the peak-to-background ratio being a ratio between the intensity of the measured spectral peak and a background radiation intensity; (a3) rejecting a measured spectral peak in the measured spectrum that overlaps with another measured spectral peak in the measured spectrum, where the two peaks in the measured spectrum include an energy difference that is less than a jamming threshold; and (b) grouping all unrejected measured spectral peaks from (a) into groups according to the X-ray emission lines they represent; and (c) determining as a calibration peak the non-rejected measured spectral peak having the highest peak-to-background ratio from each of the groups.

6. each of the at least one piecewise transformation is determined based on a respective pair of consecutive calibration peaks; The method of claim 1 , wherein two calibration peaks are consecutive if no other calibration peak in the measured data contains an energy between the energies of the two consecutive calibration peaks.

7. 7. The method of claim 6, wherein each of the at least one piecewise transformation is selectively applied to a respective piecewise energy region of the reference data that encompasses energies between or equal to the respective energies of a respective pair of the calibration peaks.

8. The method of claim 1 , wherein each piecewise transformation of the at least one piecewise transformation is a linear transformation.

9. The method further comprising: calculating a reference peak width parameter for each of a plurality of reference spectral peaks, each reference peak width parameter being indicative of an energy range encompassed by a respective one of said reference spectral peaks; calculating a respective measured peak width parameter for a plurality of measured spectral peaks, each measured peak width parameter being indicative of an energy range encompassed by a respective said measured spectral peak; The method of claim 1 , wherein determining a transformation comprises determining a peak width transformation based on the base peak width parameter and the measured peak width parameter.

10. determining a transformation includes determining an end-to-end transformation based on the first measured spectral peak, the second measured spectral peak, and the reference data; the first measured spectral peak is a first undisturbed measured spectral peak having a lowest energy in the measured data; the second measured spectrum being a second undisturbed measured spectral peak having the highest energy in the measured data; 2. The method of claim 1, wherein a particular measured spectral peak is not disturbed if any other spectral peak in the measured data that is present in the same measured spectrum as the particular measured spectral peak has an energy difference from the particular measured spectral peak that exceeds a disturbance threshold.

11. The method of claim 1 , further comprising applying the transformation to the reference data to generate calibrated reference data.

12. applying said transformation applying said at least one piecewise transformation in an energy region encompassing energies between a minimum and a maximum energy of said calibration peak, inclusive; and applying the end-to-end transform in an energy region encompassing energies less than the minimum energy of the calibration peaks and greater than the maximum energy of the calibration peaks.

13. The method further comprising: calculating a reference peak width parameter for each of a plurality of reference spectral peaks, each reference peak width parameter being indicative of an energy range encompassed by a respective one of said reference spectral peaks; calculating a respective measured peak width parameter for a plurality of measured spectral peaks, each measured peak width parameter being indicative of an energy range encompassed by a respective said measured spectral peak; determining a transformation includes determining a peak width transformation based on the base peak width parameter and the measured peak width parameter; 12. The method of claim 11, wherein applying the peak width transform comprises adjusting the reference peak width parameter of at least one reference spectral peak using the peak width transform.

14. 12. The method of claim 11, further comprising determining the elements contained in the sample by comparing the measured data with the calibrated reference data.

15. 1. A system comprising: a beam source for emitting a beam onto the sample; an x-ray detector for detecting x-rays emitted from the sample upon impact of the beam; and a computer readable memory, the computer readable memory storing reference data indicative of at least one reference energy dispersive X-ray spectrum; obtaining measured data indicative of at least one measured energy dispersive X-ray spectrum obtained from the sample; and determining a transformation based on a comparison of the measured data to the reference data. A system, said system being configured to carry out a method according to any one of claims 1 to 14.

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