Method and system for element identification by optical emission spectroscopy

Abstract

The present invention relates to a computer-implemented method for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy. The method comprises the following steps: obtaining sample spectral data from the sample; obtaining a list of one or more predetermined emission wavelengths for each element in the periodic table quantifiable by optical emission spectroscopy, each predetermined emission wavelength being associated with a list of one or more potentially interfering emission wavelengths; determining a list of one or more analyte wavelengths corresponding to spectral peaks in the sample spectral data based on the list of emission wavelengths; determining, for each analyte wavelength, whether the corresponding spectral peak has a probability of being affected by an interfering emission wavelength that causes spectral interference based on the list of one or more potentially interfering emission wavelengths corresponding to the analyte wavelengths; determining a revised list of one or more analyte wavelengths by removing analyte wavelengths corresponding to spectral peaks having a probability of being affected by an interfering emission wavelength from the list of analyte wavelengths; and determining a confidence level that one or more elements are present in the sample based on a set of criteria applied to the revised list of analyte wavelengths.

Description

Technical Field

[0001] The present invention relates to a method and system for element identification by optical emission spectroscopy, such as inductively coupled plasma optical emission spectroscopy (ICP-OES) (also known as inductively coupled plasma atomic emission spectroscopy (ICP-AES)), although the scope of the invention is not necessarily limited in this regard. Background Art

[0002] Spectrometric techniques are used to identify the presence of target chemicals, or analytes, in a sample. Some spectrometric techniques rely on the interaction of the analyte with an excitation source (e.g., light) either in the visible spectrum or at invisible wavelengths. Depending on the specific spectrometric technique employed, the collected spectrum reveals the intensity of light absorbed or emitted by the sample following the interaction of the light beam with the sample.

[0003] In other spectrometry techniques, the excitation source is a plasma source, typically made of argon gas, which provides plasma energy to an atomized sample, causing the constituent atoms to become excited and emit light. The emitted light is directed into a spectrometer via an entrance slit or aperture that limits the amount of light entering the system. Optical devices disperse the light entering the system to separate the different wavelengths of the emission spectrum. A detector simultaneously records multiple wavelength ranges to capture emission from multiple elements in different parts of the emission spectrum. The detector, typically an integrated array of photosensitive elements, collects the light passing through the spectrometry system. The spatial separation of the individual spectra on the array detector is used to distinguish between the different wavelengths of light absorbed or emitted by the sample.

[0004] Peaks or valleys in the spectral profile of the detected light indicate the presence of specific chemicals in the sample.In some spectrometric techniques, the amount or relative amount of each chemical can thus be derived from the spectrum.

[0005] Traditional methods in ICP-OES typically require users to specify exactly which elements they wish to quantify with any given analytical method. This approach requires the operator to have prior knowledge of which elements of interest are present in the sample.

[0006] Typically, the operator will be provided with a list of elements from a pre-existing prescribed method, which will include all elements that are considered to be of potential interest during method validation.

[0007] This approach has significant limitations because the operator cannot assess the composition of the sample beyond the elements specified in the method. This can lead to important sample components being overlooked, particularly in anomalous samples that may contain components rarely found in similar samples.

[0008] In addition to requiring users to specify their elements of interest, existing methods in ICP-OES also require the user to specify one or more wavelengths to be used for quantification of any given element. Typically, wavelengths must be specified before the analysis begins. In some cases, when a sufficiently large spectral region encompassing many analytical wavelengths has been collected during the measurement, wavelengths can be specified later. However, both scenarios require experienced users to select wavelengths appropriate for the sample being analyzed.

[0009] Selecting the appropriate wavelength for elemental quantification in ICP-OES is complex, and incorrect wavelength selection is a common source of error for this analytical technique. There are several documented effects that can cause any given wavelength to give incorrect results when quantifying an element by ICP-OES.

[0010] Spectral interferences and non-spectral interferences are two means by which the measured intensity of an element in a sample solution at any given analytical wavelength can be affected and return potentially incorrect results.

[0011] Non-spectral interferences occur when components in the sample affect sample introduction or plasma conditions and can result in enhancement or suppression of one or more analytical wavelengths for a given element.

[0012] Spectral interferences occur when the analytical wavelength is partially or completely overlapped by the emission of another element or molecule, or is affected by unstructured background radiation. The presence and magnitude of spectral interferences are highly sample-dependent, even within the same method.

[0013] One current approach to avoiding spectral interferences in samples is to select analytical wavelengths that are suspected of not interfering with the sample being analyzed. This process is entirely manual and relies on the experience and knowledge of the instrument operator. To ensure valid results for all samples, operators typically include multiple wavelengths for the same element in their methods. However, this approach provides users with multiple results for each element in each sample, which must then be interpreted to determine which is the most appropriate.

[0014] Instead of trying to avoid spectral interferences, some alternative approaches rely on various calibration techniques, such as inter-element correction (IEC), to correct for their effects.

[0015] These methods are widely accepted and provide reasonably accurate results. However, they rely on the instrument operator to correctly identify the interfering element and then prepare appropriate chemical standards so that interference corrections can be calculated and applied. Consequently, these current methods require the operator to have prior knowledge of the interfering elements that may be present in their samples. When the interference is not obvious or common, or when the operator is analyzing a sample type with which they are unfamiliar, it is often difficult for the operator to successfully predict the presence of interfering elements.

[0016] Embodiments of the present invention may provide a method and system for element identification by optical emission spectroscopy that overcomes or ameliorates one or more of the above-mentioned disadvantages or problems, or at least provides consumers with a useful choice. Summary of the Invention

[0017] According to one aspect of the present invention, there is provided a computer-implemented method for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy, the method comprising the steps of:

[0018] obtaining sample spectral data from the sample;

[0019] obtaining a list of one or more predetermined emission wavelengths for each element in the periodic table quantifiable by optical emission spectroscopy, each predetermined emission wavelength being associated with a list of one or more potentially interfering emission wavelengths; and determining a list of one or more analyte wavelengths corresponding to spectral peaks in the sample spectral data based on the list of emission wavelengths;

[0020] determining, for each analyte wavelength, based on the list of one or more potential interfering emission wavelengths corresponding to the analyte wavelength, whether the corresponding spectral peak has a likelihood of being affected by an interfering emission wavelength that causes spectral interference;

[0021] determining a revised list of one or more analyte wavelengths by removing from the list of analyte wavelengths analyte wavelengths corresponding to spectral peaks having a likelihood of being affected by interfering emission wavelengths; and

[0022] A confidence level that one or more elements are present in the sample is determined based on a set of criteria applied to the revised analyte wavelength list.

[0023] Advantageously, prior to the step of determining the presence of any element in the sample, the revised list of analyte wavelengths is substantially pre-processed to remove those analyte wavelengths that may be susceptible to spectral interferences. In this manner, the computer-implemented method can be used by an operator on any uncharacterized sample without requiring any experience or knowledge of the sample or the workings of the associated instrument.

[0024] In one embodiment, the sample spectral data includes data representing emission intensities corresponding to wavelengths within a sample spectral range.

[0025] Sample spectral data from a sample can be obtained using any suitable analyzer in optical emission spectroscopy. For example, an optical emission spectrometer can be used to obtain sample spectral data. In particular, an ICP-OES or ICP-AES instrument can be used to obtain sample spectral data from a sample.

[0026] In one embodiment, the analyzer is interfaced with a computer having a processor. The interface can be a wired or wireless connection. The computer processor may include a software application installed thereon for performing one or more steps of the computer-implemented method. In alternative embodiments, the software application may be a cloud-based application accessible via a network such as the Internet. In some embodiments, the software application can be accessed remotely via a local network.

[0027] Typically, a list of one or more predetermined emission wavelengths is compiled based on standard emission wavelength measurements for each element performed for a particular type of analyzer (eg, an ICP-OES instrument).

[0028] A list of one or more potentially interfering emission wavelengths can be determined based on the proximity of adjacent emission wavelengths to each standard emission wavelength associated with a particular element. Adjacent emission wavelengths may be associated with different elements of a particular element and cause spectral interference in the intensity measurement of the particular element at the emission wavelength.

[0029] The list of one or more predetermined emission wavelengths and associated potentially interfering emission wavelengths can be stored in a database in a computer memory. In some embodiments, the database can be stored remotely and accessed via a network or the Internet. The database can be accessed during execution of the software program to implement the steps of the computer-implemented method.

[0030] Furthermore, the step of determining the analyte wavelength list may include analyzing a region of interest of the sample spectral range corresponding to each predetermined emission wavelength of each element, and determining whether a peak of emission intensity is located within the region of interest.

[0031] In general, if a peak in emission intensity is localized, the emission wavelength corresponding to the localized spectral peak for an element in the sample is referred to herein as the analyte wavelength corresponding to the element in the sample.

[0032] Specifically, the step of determining the analyte wavelength list may include: analyzing the region of interest of the sample spectral range corresponding to each predetermined emission wavelength of each element, determining whether the saturation result is located within the region of interest, and when it is determined that the saturation result is not located within the region of interest, determining whether the peak in the emission intensity is located within the region of interest.

[0033] Saturated results can be associated with emission intensity measurements that are outside the analyzer instrument’s measurement range. Typically, saturated results can be encountered when there are spectral interferences and / or high concentrations of the corresponding element in the sample.

[0034] The step of determining the analyte wavelength list may further comprise determining whether the saturation result represents a peak in emission intensity having a flat top.

[0035] The step of determining the analyte wavelength list may be performed by a software program installed on the processor using information on emission and interference wavelengths from a database.

[0036] Additionally, the step of determining the analyte wavelength list may further comprise determining a confidence level that the peak in emission intensity has been identified in the region of interest based on a threshold test.

[0037] Any suitable means may be used to indicate the confidence level. For example, the confidence level may be represented by a confidence factor. The confidence factor may be represented by a value within a predetermined range.

[0038] In some embodiments, determining a confidence level that a peak in the emission intensities has been identified in the region of interest may include calculating a standard deviation of the emission intensities about the peak to determine a confidence factor.

[0039] The step of determining the confidence level may be performed by a software program installed on the processor.

[0040] In some embodiments, an element associated with a peak can be considered identified if the confidence factor is greater than a predetermined threshold. The predetermined threshold can be calculated based on historical and / or experimental sample data. The predetermined threshold can also be adjusted based on the specific type of analyzer instrument or the specific instrument based on experimental data collected using the instrument.

[0041] In some embodiments, the step of determining whether the corresponding spectral peak of each analyte wavelength has a possibility of being affected by an interfering emission wavelength may include the following steps:

[0042] Determine the clean interfering emission wavelength associated with each analyte wavelength, and

[0043] Determine whether the clean interfering emission wavelength corresponds to a spectral peak in the sample spectral data.

[0044] The step of determining whether the corresponding spectral peak of each analyte wavelength has a possibility of being affected by an interfering emission wavelength may be performed by a software program installed on a processor.

[0045] A clean or cleanest interfering emission wavelength is typically the one least likely to be affected by the spectral interference itself, among all potential interfering emission wavelengths relative to the analyte wavelength. Alternatively, the cleanest interfering emission wavelength can be the primary emission wavelength associated with the corresponding interfering element, thus providing a clear intensity measurement if the interfering element is detected in the sample.

[0046] In some embodiments, the step of determining a clean interfering emission wavelength may include determining an interfering emission wavelength that is least likely to be affected by spectral interference.

[0047] In some embodiments, the method may further comprise

[0048] For each analyte wavelength corresponding to a spectral peak affected by a spectral interference, the significance of the spectral interference is determined based on any one or more of the following:

[0049] a distance between a spectral peak corresponding to the clean interfering emission wavelength and a spectral peak corresponding to the associated analyte wavelength;

[0050] a ratio of a spectral peak corresponding to the clean interfering emission wavelength to a spectral peak corresponding to the associated analyte wavelength; and

[0051] The ratio of the emission intensity corresponding to the clean interfering emission wavelength and the emission intensity corresponding to the associated analyte wavelength.

[0052] The emission intensity can be predetermined based on the spectral line intensity.

[0053] The step of determining the significance of the spectrally interfering emission wavelength may be performed by a software program installed on the processor.

[0054] In one embodiment, the set of criteria used to determine the confidence level that one or more elements are present in the sample may include any one or more of the following:

[0055] whether the number of detected primary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a first threshold; and

[0056] whether the number of detected primary and secondary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a second threshold,

[0057] wherein the primary analyte wavelength of the element corresponds to an emission wavelength having a high peak spectral intensity, and the secondary analyte wavelength of the element corresponds to an emission wavelength having a peak spectral intensity lower than that of the primary analyte wavelength.

[0058] The first and second thresholds may be determined based on a desired minimum confidence level.The desired minimum confidence level may be determined based on user requirements, industry standards, and / or regulatory requirements.

[0059] In one embodiment, for elements having at least three primary analyte wavelengths, the first threshold is two, and for elements having two or fewer primary analyte wavelengths, the first threshold is one, and the second threshold is at least one primary analyte wavelength and one secondary analyte wavelength.

[0060] The computer-implemented method may further include adding one or more elements to the list of identified elements based on the determined confidence level.The list of identified elements may be stored in a memory of the computer device.

[0061] In some embodiments, after executing the computer-implemented method, each analyte wavelength is ranked according to a confidence factor that indicates the confidence level of the corresponding analyte element in the sample. For example, analyte wavelengths that are unlikely to be affected by spectral interferences can be given a relatively high confidence factor, while analyte wavelengths that are likely to be affected by spectral interferences can be given a relatively low confidence factor.

[0062] In some embodiments, if the number of detected primary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a first threshold, those detected primary analyte wavelengths can be assigned a first confidence factor. The first confidence factor can be a relatively high confidence factor. The corresponding analyte element can also be assigned a first confidence factor.

[0063] Additionally, if the number of detected primary and secondary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a second threshold, those detected primary and secondary analyte wavelengths may be assigned a second confidence factor. The corresponding analyte element may also be assigned a second confidence factor. The second confidence factor is lower than the first confidence factor.

[0064] If the number of detected primary analyte wavelengths corresponding to each element in the revised analyte wavelength list is below a first threshold, and the number of detected primary and secondary analyte wavelengths corresponding to each element in the revised analyte wavelength list is below a second threshold, then those detected primary and secondary analyte wavelengths can be assigned a third confidence factor. The corresponding analyte elements can also be assigned a third confidence factor. The third confidence factor is lower than the second confidence factor.

[0065] In some embodiments, the elements in the list of identified elements are ordered according to their associated confidence factors.

[0066] In some embodiments, the computer-implemented method may further include

[0067] verifying each element in the identified element list to determine whether a peak in the sample spectral data associated with an analyte wavelength may be affected by an interfering emission wavelength causing spectral interference, and

[0068] Upon determining that an analyte wavelength having a corresponding element in the identified element list may be affected by an interfering emission wavelength causing spectral interference, the corresponding element is removed from the identified element list.

[0069] The step of verifying each element may be performed by a software program installed on the processor.

[0070] Advantageously, the step of verifying each element provides an opportunity for each element in the list of identified elements to be re-evaluated so that any potentially mischaracterized elements found in the sample and added to the list of identified elements are removed.

[0071] The computer-implemented method may further include selectively displaying the analyte wavelength corresponding to each element in the list of identified elements based on a selection criterion. The selection criterion may include any one or more of the following:

[0072] whether the analyte wavelength is associated with a saturation result,

[0073] the maximum number of analyte wavelengths displayed for each corresponding element, and

[0074] Whether the analyte wavelength is associated with the user selection.

[0075] The computer-implemented method may further comprise calculating a concentration of each element in the list of identified elements. Calculating the concentration of each element may comprise measuring the emission intensity of a spectral peak associated with the corresponding element and correcting for background emission.

[0076] The computer-implemented method can further include identifying an anomalous analyte wavelength and, based on measurements associated with the anomalous analyte wavelength, reducing the confidence level that the corresponding element is present in the sample. In some embodiments, the confidence level that the corresponding element is present in the sample is inferred based on the confidence level of the detected analyte wavelength associated with the element.

[0077] According to another aspect of the present invention, there is provided a system for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy, the system comprising:

[0078] an optical emission spectrometer for obtaining sample spectral data from the sample; and

[0079] A processor for performing the computer-implemented methods described herein.

[0080] According to another aspect of the present invention, one or more tangible, non-transitory computer-readable media having computer-executable instructions for performing the computer-implemented method as described herein are provided.

[0081] According to yet another aspect of the present invention, there is provided a computer system for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy, the system comprising:

[0082] a sample data retrieval module, which is used to obtain sample spectrum data from the sample;

[0083] a wavelength data retrieval module for obtaining, for each element of the periodic table quantifiable by optical emission spectroscopy, a list of one or more predetermined emission wavelengths, each predetermined emission wavelength being associated with a list of one or more potentially interfering emission wavelengths;

[0084] a peak search module for determining a list of one or more analyte wavelengths corresponding to spectral peaks in the sample spectral data based on the emission wavelength list;

[0085] an interference search module for determining, for each analyte wavelength, whether the corresponding spectral peak has a possibility of being affected by an interfering emission wavelength that causes spectral interference based on the list of one or more potential interfering emission wavelengths corresponding to the analyte wavelength;

[0086] a wavelength processing module that determines a revised list of one or more analyte wavelengths by removing from the list of analyte wavelengths analyte wavelengths corresponding to spectral peaks having a likelihood of being affected by interfering emission wavelengths; and

[0087] An element identification module is configured to determine a confidence level that one or more elements are present in the sample based on a set of criteria applied to the revised analyte wavelength list.

[0088] The sample data retrieval module may interface with the optical emission spectrometer to obtain sample spectral data from the sample.

[0089] The wavelength data retrieval module can retrieve wavelength data from the database.

[0090] The peak search module can be configured to

[0091] analyzing a region of interest of the sample spectral range corresponding to each predetermined emission wavelength of each element to determine whether a saturated result is located within the region of interest, and

[0092] When it is determined that the saturation result is not located within the region of interest, it is determined whether a peak in the emission intensity is located within the region of interest.

[0093] The peak search module may be further configured to determine whether the saturation result represents a peak in emission intensity having a flat top.

[0094] The peak search module may be further configured to determine a confidence level that the peak in the emission intensity has been identified in the region of interest based on a threshold test.Determining the confidence level that the peak in the emission intensity has been identified in the region of interest may include calculating a standard deviation of the emission intensity near the peak to determine a confidence factor.

[0095] The interference search module may be further configured to determine a clean interfering emission wavelength associated with each analyte wavelength, and determine whether the clean interfering emission wavelength corresponds to a spectral peak in the sample spectral data.

[0096] The computer system may be further configured to determine, for each analyte wavelength corresponding to a spectral peak affected by a spectral interference, the significance of the spectral interference based on any one or more of the following:

[0097] The distance between the spectral peak corresponding to the clean interfering emission wavelength and the spectral peak corresponding to the associated analyte wavelength;

[0098] • the ratio of the spectral peak corresponding to the clean interfering emission wavelength to the spectral peak corresponding to the associated analyte wavelength; and

[0099] • The ratio of the emission intensity corresponding to the clean interfering emission wavelength and the emission intensity corresponding to the associated analyte wavelength.

[0100] The element identification module may be configured to determine a confidence level that one or more elements are present in the sample based on any one or more of the following:

[0101] whether the number of detected primary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a first threshold; and

[0102] whether the number of detected primary and secondary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a second threshold,

[0103] wherein the primary analyte wavelength of the element corresponds to an emission wavelength having a high peak spectral intensity, and the secondary analyte wavelength of the element corresponds to an emission wavelength having a peak spectral intensity lower than that of the primary analyte wavelength.

[0104] The element identification module may be configured to add one or more elements to the list of identified elements based on the determined confidence level.

[0105] The computer system may further include a verification module for verifying each element in the identified element list to determine whether the spectral peak of the sample spectral data associated with the corresponding element may be affected by an interfering emission wavelength that causes spectral interference, and when it is determined that an element in the identified element list may be affected by an interfering emission wavelength that causes spectral interference, removing the corresponding element from the identified element list.

[0106] The computer system may further include a result selection module for selectively displaying the analyte wavelength corresponding to each element in the list of identified elements based on a selection criterion, wherein the selection criterion includes any one or more of the following:

[0107] whether the analyte wavelength is associated with a saturation result,

[0108] the maximum number of analyte wavelengths displayed for each corresponding element, and

[0109] Whether the analyte wavelength is associated with the user selection.

[0110] The computer system may further include a concentration calculation module for calculating the concentration of each element in the identified element list. Calculating the concentration of each element may include measuring the emission intensity of a spectrum peak associated with the corresponding element and correcting for background emission.

[0111] The computer system may further include an anomaly detection module for identifying anomalous analyte wavelengths and, based on measurements associated with the anomalous analyte wavelengths, reducing the confidence level that a corresponding element is present in the sample.

[0112] Advantageously, embodiments of the present invention automatically identify elemental emission wavelengths in uncharacterized solutions to identify all elements potentially present that are available with the ICP-OES technique, without requiring an operator to preselect elemental emission wavelengths.

[0113] In order that the invention may be more readily understood and implemented, one or more preferred embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0114] Figure 1a is a schematic diagram illustrating a system for element identification using optical emission spectroscopy according to one embodiment of the present invention. Figure 1a Further shown is a process flow diagram outlining the process steps of a computer-implemented method for element identification according to one embodiment of the present invention.

[0115] Figure 1b Shown with Figure 1a Display information related to background emission correction and concentration calculations in a computer-implemented method.

[0116] Figure 2a It is an explanation Figure 1a , a process flow chart of the data acquisition sub-process of the computer-implemented method shown in .

[0117] Figure 2b It is an explanation Figure 1a , a process flow chart of the data loading sub-process of the computer-implemented method shown in .

[0118] Figure 2c Shown by Figure 2b The illustrated sub-process provides display information related to standard emission wavelength data and associated potentially interfering emission wavelength data.

[0119] Figure 3 It shows Figure 1a A process flow diagram of an element search process of a computer-implemented method is shown.

[0120] Figure 4 It means Figure 3 A process flow chart of the sub-process of determining spectral peaks in the element search process is shown.

[0121] Figure 5a Shows display information according to an exemplary embodiment of the present invention, which is consistent with the display information according to Figure 1a The method shown relates to the concentration results determined for some identified elements for samples 1 to 10.

[0122] Figure 5bShows further results related display information including analyte wavelength, corresponding confidence rating and Figure 5a A graphical representation of spectral data at the analyte wavelength for elemental lithium (Li) in Sample 1 is shown.

[0123] Figure 5c Shows display information according to an exemplary embodiment of the present invention, which is consistent with the display information according to Figure 1a The method shown relates to the concentration results determined for some identified elements for samples 1 to 10.

[0124] Figure 5d Shows further results related display information including analyte wavelength, corresponding confidence rating and Figure 5c A graphical representation of spectral data at the analyte wavelength for elemental lithium (Li) in Sample 7 is shown.

[0125] Figure 6 It shows that Figure 3 A process flow chart of the sub-process of determining interfering spectral peaks in the element search process is shown.

[0126] Figure 7a Shows display information according to an exemplary embodiment of the present invention, which is consistent with the display information according to Figure 1a The method shown relates to the concentration results determined for some identified elements for samples 1 to 10.

[0127] Figure 7b Further result related display information is shown, including analyte wavelength, corresponding confidence rating and Figure 7a A graphical representation of the spectral data for the analyte wavelengths in Sample 5 is shown.

[0128] Figure 7c Shows display information according to an exemplary embodiment of the present invention, which is consistent with the display information according to Figure 1a The method shown relates to the concentration results determined for some identified elements for samples 1 to 10.

[0129] Figure 7d Further result related display information is shown, including analyte wavelength, corresponding confidence rating and Figure 7c A graphical representation of spectral data at the wavelengths of the analytes in sample 10 is shown.

[0130] Figure 8 It shows that Figure 3 A process flow diagram of the sub-process within the element search process for determining the presence of an analyte element is shown.

[0131] Figure 9 It means Figure 1aFlowchart of the process for verifying and re-evaluating the presence of spectral interferences in the method shown.

[0132] Figure 10 is shown for selectively determining the Figure 1a A flow chart showing the process of selecting acceptable analyte wavelengths is shown in the method.

[0133] Figure 11 It is shown in Figure 1a A process flow diagram of the process for determining outlier results in the illustrated method.

[0134] Figure 12 It means Figure 1a Flowchart of the process of selecting the best available result for display in the illustrated method.

[0135] Figure 13 Shown is the display of information in the form of a graphical representation of identified analyte wavelengths and analyte elements in a selected portion of sample spectral data, according to an exemplary embodiment of the present invention.

[0136] Figure 14 is an excerpt from the user interface of a system according to one embodiment of the present invention, showing the automatic identification of several common and problematic spectral interferences at wavelengths for As, Mn, and V in HJ781-2016 solid waste digestate.

[0137] Figure 15 is an excerpt from the user interface of a system according to one embodiment of the present invention, illustrating that no Cl was detected in "Soil 4" due to the technician's oversight in adding acid prior to digestion, as well as the absence of Sb in "Soil 4." This was likely not dissolved in this sample due to the lack of HCl in the digestate.

[0138] Figure 16a and Figure 16b is an excerpt from the user interface of a system according to one embodiment of the present invention, showing a visualization of a periodic table heat map comparing multiple samples. In this embodiment, color coding based on concentration can provide a visually intuitive way to identify differences between measurement solutions.

[0139] Figure 17 is an excerpt from the user interface of a system according to one embodiment of the present invention, showing a confidence rating table for the Mn analyte wavelength. The user interface also provides an information box that displays possible Fe interferences on the two Mn main lines upon user request.

[0140] Figure 18 Further illustrated are heat maps showing the relative concentrations of all other elements in the samples. DETAILED DESCRIPTION

[0141] like Figure 1a As shown, a system 100 for automatically identifying the presence of one or more elements in a sample by optical emission spectroscopy includes an optical emission spectrometer 102, such as an inductively coupled plasma optical emission spectrometry (ICP-OES) instrument, also known as inductively coupled plasma atomic emission spectrometry (ICP-AES). The ICP-OES instrument 102 obtains spectral data from one or more samples for analysis. The system 100 further includes a processor (not shown) on which an application is installed for executing a software-implemented method 106 that analyzes the sample spectral data obtained from the instrument 102 and identifies the presence of one or more elements in the sample with a certain confidence level. In some cases, if the elements in the sample are below the detection level, the instrument 102 may not be able to identify the presence of any elements. A display device 104 is connected to the processor for providing a user interface to facilitate user interaction with the system 100 and displaying output from the sample analysis.

[0142] The computer-implemented method 106 obtains sample spectral data from one or more uncharacterized sample solutions loaded into the instrument 102 and automatically analyzes the samples in a series of functional steps to identify the presence of one or more elements in each sample, as described in further detail below. The method 106 is described with respect to a single sample. However, it should be understood that the method 106 is not limited to analyzing a single sample and can process any suitable number of samples.

[0143] In the start step 200, sample spectral data is acquired from the sample solution loaded into the instrument 102, and theoretical emission wavelength data is loaded from the data repository. The data repository provides a list of all elements in the periodic table that can be quantified by optical emission spectroscopy (also referred to herein as the element list) and theoretical emission wavelength data for each element in the element list. The theoretical emission wavelength data can be manually compiled based on measurements of standard samples and / or based on standard data (such as those in the atomic spectral database published by the National Institute of Standards and Technology (NIST)). In particular, the theoretical emission wavelength data includes the standard emission wavelength for each element in the element list, as well as potential interfering wavelength data associated with each standard emission wavelength. More details about step start step 200 will be referred to below. Figures 2a to 2c Describe in more detail.

[0144] At query step 108, method 106 checks whether element search process 300 has been performed for each element in the element list for the sample solution under analysis. If so, method 106 continues to process 700. If not, method 106 continues to process 300 for the next element in the element list.

[0145] In summary, process 300 compares theoretical emission wavelength data with sample spectral data from a sample solution to determine a list of analyte wavelengths that are likely free of spectral interferences and that correspond to spectral peaks in the sample spectral data. Process 300 then further determines the confidence level that one or more elements are present in the sample by evaluating the analyte wavelength list against predetermined criteria. Process 300 generates a list of elements that may be present in the sample based on the predetermined criteria and the analyte wavelength list (identified element and analyte wavelength list 110) used to identify these elements. Process 300 is an iterative process applied to each element in the element list. Reference Figure 3 Process 300 is described in more detail.

[0146] At process 700, the method 106 verifies and re-evaluates the list of identified elements and analyte wavelengths 110 to determine any further spectral interferences. Any analyte wavelength from the list 110 that is determined to be affected by spectral interferences is removed from the list 110 and / or given a low confidence rating. Figure 9 Process 700 is described in further detail.

[0147] At process step 800 , the method 106 further evaluates the list of identified elements and analyte wavelengths 110 and selects the most appropriate analyte wavelength for each element in the list 110 for display on the display device 104 .

[0148] At step 112, for each analyte wavelength in list 110, background emission correction is applied to determine the net spectral peak intensity associated with the analyte wavelength. Any standard ICP-OES background correction technique can be used. For example, a fitted background correction technique can be used due to its robustness. At step 112, for each analyte wavelength in list 110, a semi-quantitative concentration of the element of interest is calculated using a predetermined intensity-concentration calibration curve. Any standard ICP-OES calibration curve can be used, for example, the calibration curve can be linear or quadratic.

[0149] For example, Figure 1b As shown, the displayed information generated by method 106 includes a list of analyte wavelengths associated with the element sodium (Na) identified in the sample. The first analyte wavelength 116 of 589.892 nm for Na has a confidence rating 118 of 3 stars, a calculated concentration of 0.51 mg / L, an intensity of 7874.7 c / s, and a background emission of 36933.7 c / s.

[0150] Figure 1b Graph 126 is a graph of intensity versus wavelength and shows a comparison of a peak 128 in the sample spectral data for the Na analyte at a wavelength of 589.892 nm with an estimate of background emission 130 .

[0151] Similarly, graphs 132 and 134 illustrate portions of sample spectral data associated with Na analyte wavelengths of 588.995 nm and 568.821 nm, respectively.

[0152] Now refer to Figure 1a At process step 900 , method 106 evaluates the analyte wavelengths in list 110 to obtain possible outlier results for each element and adjusts the confidence rating associated with the corresponding analyte wavelength. Figure 11 Process 900 is described in more detail.

[0153] At process step 1000, method 106 weights the analyte wavelengths in list 110 based on a weighting criterion to identify the most appropriate result for display. Figure 12 Process 900 is described in more detail.

[0154] Now refer to Figure 2a and Figure 2b , which illustrate sub-processes 202 , 212 associated with the sample data acquisition and database loading step 200 of the method 106 .

[0155] During subprocess 202 , sample spectral data is obtained from an uncharacterized sample solution using instrument 102 .

[0156] At start step 204, an uncharacterized sample solution is loaded into the instrument 102. Although this specification describes the process with respect to a single sample solution, those skilled in the art will appreciate that the instrument is typically configured to sequentially retrieve spectral data from multiple sample solutions.

[0157] At step 206, the instrument 102 obtains spectral sample data from the uncharacterized sample solution. The spectral sample data provides measured intensities of wavelengths within the sample spectral range. Typically, the sample spectral data will consist of many data points covering a wide range of wavelengths and signal intensities.

[0158] Output 208 from step 206 is stored in a data repository 210 of system 100 for use in method 106 and is referred to herein as sample spectral data.

[0159] During subprocess 212 , standard atomic emission wavelength data is loaded from data repository 218 for use during execution of method 106 .

[0160] At query step 214, subprocess 212 checks whether standard atomic emission wavelength data has been retrieved for all elements in the element list. If so, subprocess 212 completes; if not, subprocess 212 proceeds to step 216 for each remaining element. Subprocess 212 is an interactive process, and the steps described below are applied to each element in the element list until all relevant emission wavelength data has been loaded for all elements in the element list.

[0161] At step 216 , subprocess 212 retrieves the top ten primary element emission wavelengths from data repository 218 and stores the emission wavelengths in list 222 .

[0162] At step 220 , for each emission wavelength retrieved in step 216 , subprocess 212 retrieves a list of potentially interfering emission wavelengths associated with that emission wavelength from data repository 218 and also stores the list of potentially interfering emission wavelengths in list 222 .

[0163] The standard emission wavelength and interfering emission wavelength list 222 may be generated in any suitable structure or form, such as a lookup table containing a list of the top 10 emission wavelengths for each element in the list of elements and a set of potential interfering emission wavelengths for each emission wavelength.

[0164] Figure 2c The displayed information in shows information available from the data repository 218. For example, for an element in the element list, such as manganese (Mn), the second order emission wavelength 224 of 259.372 nm may encounter spectral interference from adjacent emission wavelengths of zirconium (Zr) 226 at 259.371 nm, molybdenum (Mo) 228 at 259.371 nm, iron (Fe) 230 at 259.373 nm, niobium (Nb) 232 at 259.376 nm, and so on.

[0165] Now refer to Figure 3 The element search process 300 of the method 106 is described. The process 300 uses the data from the standard emission wavelength and interfering emission wavelength lists 222 loaded in the subprocess 212.

[0166] At query step 302, process 300 checks whether the associated process steps 400 to 500 for identifying spectral peaks and interferences have been applied to each emission wavelength in list 222. If so, process 300 proceeds to step 308. If not, process 300 proceeds to sub-process 400 for identifying spectral peaks in the sample spectral data. Query step 302 iterates through each emission wavelength in list 222 until all emission wavelengths in list 222 have been processed. Figure 4 、 Figure 5a and Figure 5d Sub-process 400 is explained in more detail.

[0167] At query step 304, if the corresponding peak in the sample spectral data has been identified with at least a certain confidence level, process 300 proceeds to query step 306. If a peak has been found, the corresponding emission wavelength is referred to herein as the analyte wavelength. The list of analyte wavelengths is compiled in analyte wavelength list 310. If not, process 300 returns to query step 302 to locate the next emission wavelength in list 222 for analysis.

[0168] At query step 306, process 300 determines whether the corresponding analyte wavelength is associated with a set of potential interfering emission wavelengths based on the data from list 222. If so, process 300 proceeds to subprocess 500 to identify the spectral peak of the interfering emission wavelength in the sample spectral data. If not, the process returns to query step 302 to locate the next emission wavelength in list 222 for analysis. Figure 6 、 Figure 7a and Figure 7d Sub-process 500 is explained in more detail.

[0169] At step 308, those analyte wavelengths identified as being associated with spectral peaks that are likely to be affected by spectral interferences are removed from list 310 as a result of process steps 400 through 500. Thus, list 310 is modified to omit analyte wavelengths corresponding to spectral peaks that are determined to be likely to be affected by spectral interferences (referred to herein as revised analyte wavelength list 312).

[0170] In subprocess 600, a set of rules are applied to the revised analyte wavelength list 312 to determine the presence of one or more elements in the sample with a certain confidence level. Figure 8 The sub-process 600 is explained in more detail. The revised list 312 may include multiple sub-lists. Each sub-list includes a list of analyte wavelengths associated with a specific element.

[0171] Now refer to Figure 4 A sub-process 400 for identifying spectral peaks for each analyte wavelength to compile the list 310 is described.

[0172] At step 402, sample spectral data from the data repository 210 is used for analysis. The subprocess 400 determines a relevant region of the sample spectral data corresponding to the corresponding analyte wavelength and sets the relevant region as a region of interest for the corresponding analyte wavelength.

[0173] At step 404, subprocess 400 performs a constrained search within the region of interest to locate the relevant peak portion of the corresponding analyte wavelength. The search is constrained to prevent incorrectly locating an incorrect peak portion associated with an adjacent spectral peak.

[0174] At query step 406, subprocess 400 determines whether a saturated intensity result is located within the region of interest by determining whether a substantially flat portion exists at the upper end of the spectral peak. A saturated result includes intensity measurements that exceed the measurable range of instrument 102. If a substantially flat portion is located, subprocess 400 proceeds to step 408. Otherwise, subprocess 400 proceeds to step 412.

[0175] At step 408, subprocess 400 evaluates whether the located peak having a substantially flat portion resembles a flat-top peak at the corresponding analyte wavelength (eg, see FIG. 5B).

[0176] At query step 410, if a flat-top peak was located in step 408, subprocess 400 proceeds to step 416. Otherwise, subprocess 400 for the corresponding analyte wavelength ends, and output indicating that no spectral peak corresponding to the analyte wavelength was located is provided as input to step 304 of process 300.

[0177] At step 416, subprocess 400 determines that a peak associated with the analyte wavelength has been found. However, due to the difficulty in accurately determining flat-top peaks and saturated intensity results, a confidence rating indicating the confidence level that the peak corresponding to the analyte wavelength has been identified is given a low score. The output indicating that the peak corresponding to the analyte wavelength has been located is provided as input to step 304 of process 300.

[0178] At step 412, subprocess 400 evaluates the sample spectral data for a region of interest for regular spectral peaks (eg, not saturation results or flat-topped peaks). There may be more than one spectral peak in the region of interest.

[0179] At step 414 , subprocess 400 determines an appropriate local background location based on the peak portion located at step 404 to calculate the background standard deviation at step 420 .

[0180] At query step 418, if step 414 determines that a spectral peak exists in the associated peak portion, then subprocess 400 proceeds to step 420. If not, subprocess 400 ends. Output indicating that no spectral peak corresponding to the corresponding analyte wavelength has been located is provided as input to step 304 of process 300.

[0181] In step 420, a constrained search is performed on the local background measurements near the peak vertex location. Interpolation of the background points allows the determination of the net peak intensity at the peak vertex location. The standard deviation (SD) of the local background measurements for the peak is calculated. The local background with the largest SD is selected.

[0182] At step 422, using the effective background SD, a confidence factor based on the signal-to-noise ratio is assigned to the spectral peak and is calculated as follows:

[0183]

[0184] where BG threshold is a scalar typically in the range 1 to 10.

[0185] If the confidence factor passes the threshold test, the peak corresponding to the wavelength of the corresponding analyte is considered to be detected, for example:

[0186] Confidence factor > C threshold

[0187] where Cthreshold is a scalar typically in the range 1 to 10.

[0188] If there is no valid background SD, the interpolated background value at the peak apex position is substituted and the signal-to-background ratio is calculated instead of the signal-to-noise ratio.

[0189] Although the above sub-process 400 is described with reference to an example method of spectral peak detection, it should be understood that any suitable peak detection algorithm may be implemented. Some suitable example peak detection algorithms may include, but are not limited to, window threshold methods, derivative analysis, and wavelet transforms.

[0190] Upon completion of step 422 , an output indicating that the spectral peak corresponding to the respective analyte wavelength has been located is provided as input to step 304 of process 300 .

[0191] Figure 5a and Figure 5b The information displayed in provides an example of a flat-top peak associated with the analyte wavelength of lithium (Li). Figure 5a As shown, the intensity of element Li in sample 1 is 2.4E+0 mg / L (424). Figure 5b The analyte wavelength of Li, 670.783 nm, is shown to be given a 1 star rating (reflecting a low confidence factor) due to the identification of a flat-topped spectral peak 426 at 670.774 nm near the analyte wavelength of 670.783 nm.

[0192] Figure 5c and 5d The information displayed in provides examples of typical spectral peaks associated with the analyte wavelength of lithium (Li). Figure 5c As shown, the intensity 428 of element Li in sample 7 is 6.78 mg / L Figure 5d It is shown that the analyte wavelength of Li, 670.783 nm, was given a 5-star rating (reflecting a high confidence factor) due to the identification of a common spectral peak 430 at 670.774 nm near the analyte wavelength of 670.783 nm.

[0193] Now refer to Figure 6A sub-process 500 is described for identifying a spectral peak for each potentially interfering emission wavelength identified in the query step 306 of the element search process 300 .

[0194] At query step 502, a determination is made as to whether subprocess 500 has evaluated all potentially interfering emission wavelengths identified in query step 306. If so, subprocess 500 is complete. If not, subprocess 500 obtains the next potentially interfering emission wavelength for evaluation and proceeds to step 504.

[0195] In step 504, based on the list of standard emission wavelengths and interfering emission wavelengths 222, subprocess 500 selects a clean interfering emission wavelength to determine the presence of the relevant interfering element corresponding to the corresponding interfering emission wavelength. Typically, subprocess 500 attempts to locate the most appropriate interfering emission wavelength from the list of emission wavelengths associated with the corresponding interfering element based on list 222, which may produce a result with an acceptable confidence level. For example, subprocess 500 can select an interfering emission wavelength on the spectrum that is sufficiently separated from nearby emission wavelengths that may cause spectral interference with the interfering emission wavelength. In addition, the selected clean interfering emission wavelength is not associated with the saturation intensity result in the sample spectral data. Therefore, subprocess 500 attempts to locate a clean interfering emission wavelength that is itself least likely to be subject to spectral interference and may be able to produce an acceptable result.

[0196] In sub-process step 400, using the previous reference Figure 4 The same peak identification method described above is used to determine whether the selected clean interfering emission wavelength corresponds to a peak in the sample spectral data.

[0197] At query step 506, if subprocess 400 determines that no spectral peak corresponds to a clean interfering emission wavelength, then subprocess 500 determines that no interfering element corresponding to the clean interfering emission wavelength is present in the sample and returns to query step 502 to obtain the next interfering emission wavelength for analysis. If subprocess 400 determines that a spectral peak corresponds to a clean interfering emission wavelength, then subprocess 500 determines that an interfering element corresponding to the clean interfering emission wavelength is present in the sample and subprocess 500 proceeds to query step 508.

[0198] At query step 508, subprocess 500 determines whether the detected interfering element is significant based on the confidence factor calculated in subprocess 400. Typically, if the identified interfering element is associated with a confidence factor greater than a predetermined threshold in the range of 1 to 50, subprocess 500 determines that the interfering element is significant and proceeds to step 510. If not, subprocess 500 determines that the interfering element is not significant and returns to query step 502 to retrieve the next available interfering emission wavelength.

[0199] In step 510, the distance between the peaks of the analyte wavelength and its associated interfering emission wavelength is determined. The measured intensities and relative intensities of the detected interfering elements and their associated analyte elements are also determined. The measured intensities are used to calculate the interference to analyte ratio (IAR or ), and the relative intensities are used to calculate the relative intensity interference to analyte ratio (RIR or ).

[0200] At query step 512, sub-process 500 determines whether a potentially interfering emission wavelength should be determined as a possible interfering wavelength and added to a possible interfering emission wavelength list 516 based on the following three threshold tests:

[0201] Peak separation < S threshold (1)

[0202]

[0203]

[0204] in

[0205] hh is the maximum separation (typically in the range of 1.0 to 20.0) between the apexes of the spectral peaks corresponding to the analyte wavelength (analyte peak) and the associated interfering emission wavelength (interference peak), respectively,

[0206] hh is the minimum value of the ratio of the measured interference peak signal to the measured analyte peak signal (usually in the range of 0.1 to 10.0),

[0207] hh is the minimum value of the ratio of the relative intensity of the interference to the relative intensity of the analyte (usually in the range of 1.0 to 20.0).

[0208] Threshold test (1) determines if the distance between the interfering peak and the analyte peak is less than a threshold value in the range of 1 to 20. Threshold test (2) determines if the IAR is above a threshold value in the range of 0.1 to 10.0. Threshold test (3) determines if the RIR is above a threshold value in the range of 1.0 to 20.0.

[0209] If any of the above threshold tests are true, the subprocess proceeds to step 514 and the potentially interfering emission wavelength is determined to be a possible interfering wavelength and added to list 516. If not, subprocess 512 returns to query step 502 to retrieve the next available interfering emission wavelength.

[0210] For example, Figure 7a and Figure 7b The method 106 implemented by the computer is shown to analyze the sample 5 (518, Figure 7a), it has been identified that the confidence in detecting the analyte element bismuth (Bi) at the emission wavelength of 222.821 nm is very low, because the confidence in detecting the interfering element chromium (Cr) at the nearby emission wavelength of 222.823 nm is very high (520, Figure 7b 7B , region 522 also shows at least two adjacent spectrum peaks around a wavelength of 222.821 nm.

[0211] Similarly, Figure 7c and Figure 7d The method 106 implemented by the computer is shown to analyze the sample 10 (524, Figure 7c ), it has been identified that the confidence in detecting the analyte element phosphorus (P) at the emission wavelength of 213.618 nm is very low, because the confidence in detecting the interfering element copper (Cu) at the nearby emission wavelength of 213.598 nm is very high (526, Figure 7d ).exist Figure 7d In the spectrum shown, a saturation result is also shown in region 528 near a wavelength of 223.619 nm.

[0212] Now refer to Figure 8 A subprocess 600 is described for determining with a certain level of confidence that one or more analyte elements are identified in a sample. The subprocess 600 is iteratively performed for each element in the element list to determine whether the element can be considered to be found in the sample based on the analyte wavelength identified in the revised list 312 based on a set of predetermined criteria.

[0213] At query step 602, subprocess 600 determines whether a minimum number of analyte wavelengths among the top 10 primary emission wavelengths are identified in the revised analyte wavelength list 312 for each element in the element list. In one embodiment, subprocess 600 determines whether a minimum number of two analyte wavelengths exists for elements with more than two emission wavelengths, and a minimum number of one analyte wavelength exists for elements with fewer than two emission wavelengths. Typically, analyte wavelengths are ranked according to their associated confidence factors. If so, subprocess 600 proceeds to query step 604. If not, subprocess 600 proceeds to query step 622.

[0214] At query step 604, subprocess 600 determines whether a minimum number of analyte wavelengths among the top three primary emission wavelengths are identified in the revised analyte wavelength list 312 for each element in the element list. In one embodiment, subprocess 600 determines whether a minimum number of two analyte wavelengths exists for elements with more than two emission wavelengths, and a minimum number of one analyte wavelength exists for elements with fewer than two emission wavelengths. Typically, analyte wavelengths are ranked according to their associated confidence factors. If so, subprocess 600 proceeds to query step 606. If not, subprocess 600 proceeds to query step 612.

[0215] At query step 606, if the minimum number of analyte wavelengths found are unlikely to be associated with any spectral interferences, subprocess 600 proceeds to step 608. Otherwise, subprocess 600 terminates for the currently evaluated analyte element and is iteratively executed for the next element in the element list.

[0216] The analyte element currently being evaluated is deemed present at step 608 . The identified element and its associated analyte wavelength are added to the identified element and analyte wavelength list 110 .

[0217] At query step 612, subprocess 600 determines whether at least one analyte wavelength for the current analyte element is a strong dominant wavelength that is not affected by spectral interference (e.g., a confidence factor greater than 10), and whether at least one analyte wavelength for the current analyte element is a lower-order analyte wavelength that is not affected by spectral interference from the first 10 dominant wavelengths (e.g., a confidence factor between 1 and 3). In essence, at query step 612, subprocess 600 determines whether there is at least one strong dominant analyte wavelength and supporting weaker analyte wavelengths for each element. If so, subprocess 600 proceeds to step 608, and the current analyte element is considered discovered and is added to list 110 along with the associated analyte wavelength. If not, subprocess 600 proceeds to query step 614.

[0218] At step 614, subprocess 600 checks whether a lower-order analyte wavelength from the top 10 principal wavelengths has been found for the evaluation element in revised list 312. If so, subprocess 600 proceeds to query step 616. If not, subprocess 600 terminates for the currently evaluated analyte element and subprocess 600 is iteratively executed for the next element in the element list.

[0219] At query step 616 , if all low-order analyte wavelengths found are subject to spectral interference, then sub-process 600 proceeds to step 620 . If not, then sub-process 600 proceeds to step 618 .

[0220] At step 618, subprocess 600 checks whether some lower-order analyte wavelengths are found to have no spectral interference or relatively weak spectral interference. If so, subprocess 600 proceeds to step 608, and the corresponding analyte element is considered to be found at the lower-order analyte wavelength. The element and the associated analyte wavelength are then added to list 110. If not, subprocess 600 terminates for the currently evaluated analyte element and is iteratively executed for the next element in the element list.

[0221] At step 620, subprocess 600 determines whether each found primary analyte wavelength has a strong signal. If so, subprocess 600 proceeds to step 608, and the corresponding analyte element is considered to be found at a lower-order analyte wavelength. The element and the associated analyte wavelength are then added to list 110. If not, subprocess 600 terminates for the currently evaluated analyte element and is iteratively executed for the next element in the element list.

[0222] At query step 622, subprocess 600 determines whether any strong analyte wavelengths (e.g., confidence factor greater than 10) have been found among the top 10 dominant wavelengths for the current analyte element. If so, subprocess 600 proceeds to query step 624. If not, subprocess 600 terminates for the currently evaluated analyte element and subprocess 600 is iteratively executed for the next element in the element list.

[0223] At step 624, subprocess 600 determines whether any weaker analyte wavelengths (e.g., with a confidence factor between 1 and 3) have been found among the top 10 dominant wavelengths for the current analyte element. If so, subprocess 600 proceeds to query step 626. If not, subprocess 600 proceeds to step 608, and the element is considered to be found at the strong dominant wavelength identified in query step 622. The element and associated analyte wavelength are then added to list 110.

[0224] The weaker analyte wavelength (and the stronger primary analyte wavelength from step 622) is deemed to be found for the analyte element at step 626. The element and associated analyte wavelength are then added to the list 110.

[0225] A process 700 is provided for re-evaluating and verifying whether any analyte wavelength associated with each element in the list 110 is still subject to spectral interference. Thus, the process 700 is a fine-tuning step to re-evaluate each analyte wavelength for the elements in the list 110 to remove any elements from the list 110 that may be subject to spectral interference.

[0226] At query step 702, for each element in list 110, process 700 determines whether there are any further corresponding analyte wavelengths for re-evaluation through process steps 704 through 714. If so, process 700 proceeds to step 704. If not, process 700 proceeds to sub-process 600.

[0227] At query step 704, process 700 iterates through all potential interfering emission wavelengths corresponding to the current analyte wavelength and selects the next available potential interfering emission wavelength for consideration at query step 706. If no more available interfering emission wavelengths remain, process 700 returns to query step 702. If there are still available interfering emission wavelengths remaining, process 700 proceeds to query step 706 for the next available interfering emission wavelength.

[0228] At query step 706, process 700 determines whether the current interfering emission wavelength has a corresponding element in list 110. If so, process 700 proceeds to 708. If not, process 700 returns to query step 704 to retrieve the next available interfering wavelength.

[0229] At query step 708, if an interfering emission wavelength has been previously identified as being associated with a corresponding analyte wavelength, process 700 returns to query step 702 to retrieve the next analyte wavelength associated with the current element in list 110. If an interfering emission wavelength has not been previously identified as being associated with a corresponding analyte wavelength, process 700 proceeds to step 710 to determine the impact of the interference.

[0230] At step 710, a proximity scalar is calculated to determine the significance of the interference. Typically, the following calculation can be used: 1.0 minus the wavelength difference (in nm) between the analyte and interfering wavelengths. Other suitable calculations based on the distance between the analyte wavelength and the corresponding interfering emission wavelength can also be used. In addition, the relative intensity ratio of the analyte wavelength peak intensity to the peak intensity of the highest confidence element interfering wavelength is calculated.

[0231] At query step 712, process 700 determines whether the neighboring scalar exceeds a threshold value (typically in the range of 0.2 to 1.0), and whether the scaled intensity and relative intensity are above a given threshold value (typically in the range of 0.05 to 0.9). If so, process 700 proceeds to step 714. If not, process 700 returns to query step 702 to retrieve the next available analyte wavelength.

[0232] At query step 714 , process 700 updates the possible interfering emission wavelength list 516 with the interfering wavelength evaluated in step 712 .

[0233] At sub-process 600 , for each element in list 110 , once all corresponding analyte wavelengths for the identified element have been processed through steps 704 through 714 , sub-process 600 is re-executed based on the updated list of possible interfering emission wavelengths 516 .

[0234] At query step 718, re-execution of subprocess 600 determines whether each element in current list 110 is present in the sample with an acceptable confidence level. If the current element is determined to be not present in the sample with an acceptable confidence level, process 700 ends. Otherwise, process 700 proceeds to step 720. Generally, subprocess 600 determines whether the analyte wavelength associated with the element is present with an acceptable confidence level. Based on the confidence level determined for the analyte wavelength, it can then be inferred whether the associated element is present in the sample.

[0235] At step 720 , process 700 removes the current element and associated analyte wavelength from list 110 .

[0236] Now refer to Figure 10 A process 800 is described for evaluating analyte wavelengths from the list 110 to generate a list of acceptable analyte wavelengths for ultimate display by the display device 104. Typically, the selection is made based on predetermined criteria, such as any one or more of the following:

[0237] Whether the analyte wavelength is associated with a saturation result

[0238] Whether the analyte wavelength is associated with spectral interferences

[0239] Maximum number of analyte wavelengths displayed for each corresponding element

[0240] Whether the analyte wavelength is associated with the user selection

[0241] At query step 802, process 800 determines whether all elements in list 110 have been evaluated based on steps 804 through 812. If so, process 800 terminates. If not, process 800 proceeds to query step 804.

[0242] At query step 804, process 800 determines, for each element in list 110, whether the element is associated with at least one saturated intensity measurement at the analyte wavelength without spectral interference. If so, process 800 proceeds to step 806. If not, process 800 proceeds to step 808.

[0243] At step 806, process 800 selectively includes up to two saturated analyte wavelength measurements having the highest confidence factors in the list of acceptable analyte wavelengths.

[0244] At step 808 , process 800 selectively includes the unsaturated analyte wavelength associated with the element in list 110 into the list of acceptable analyte wavelengths.

[0245] At query step 810, process 800 determines whether any user-selected wavelength is already included in the list of acceptable analyte wavelengths. If so, process 800 returns to query step 802 and retrieves the next element from list 110 for processing. If not, process 800 selectively includes the user-selected analyte wavelength in the list of acceptable analyte wavelengths. Typically, in this case, the user-selected analyte wavelength has not been determined to be a relevant analyte element found in a previously executed process. However, the results associated with the user-selected analyte wavelength will still be displayed in the list of acceptable analyte wavelengths.

[0246] Now refer to Figure 11 A process 900 is described for reviewing the list of acceptable analyte wavelengths for any abnormal results to identify any gross outliers that are typically the result of unrecorded interferences (ie, emission wavelengths that are not in the list of standard emission wavelengths and interfering emission wavelengths 222).

[0247] At step 902, the analyte wavelengths in the list of acceptable analyte wavelengths are ranked based on the measured concentrations of the relevant analyte elements in the sample. The concentration of each analyte element is determined based on the intensity concentration curve.

[0248] At query step 904 , if there are more than two analyte wavelength results per element, process 900 proceeds to step 906 . If not, process 900 proceeds to step 910 .

[0249] An interquartile range calculation is applied to the analyte wavelengths at step 906. In other examples, one or more different calculations may be applied, such as a Z score, a modified Z score, a lognormal distribution, etc.

[0250] For each analyte wavelength corresponding to an outlier result, the confidence factor associated with the analyte wavelength is lowered at step 908. The analyte wavelength is also considered an outlier.

[0251] At step 910, all analyte wavelengths are selected to remain in the accepted analyte wavelength list.

[0252] Now refer to Figure 12A process 1000 is described for selecting and ranking optimal analyte wavelengths for display on the display device 104. In the process 1000, a threshold test is applied to the accepted analyte wavelength results from the outlier checking process 900. To meet the threshold test, the analyte wavelength result must not correspond to a saturated result and must have an acceptable calibration curve.

[0253] The metrics used to determine an acceptable calibration curve may include, but are not limited to, the least squares goodness of fit correlation coefficient and the percentage relative standard error (RSE). The calibration curve metrics will be tested against an appropriate predetermined threshold. If no analyte wavelength result meets the test, a more relaxed test is used to include calibrated analyte wavelength results. If no analyte wavelength result is calibrated, all accepted analyte wavelength results are used. Finally, those analyte wavelength results that pass the given threshold test are ranked based on appropriate weights.

[0254] Examples of weighting factor calculations may include, but are not limited to:

[0255] Confidence factor multiplied by the square root of the relative intensity of the analyte at the wavelength

[0256] Confidence factor for the analyte wavelength

[0257] Confidence factor divided by the square root of the principal order of the analyte wavelength

[0258] The analyte wavelength result with the highest weight is selected to report the semi-quantitative concentration of the element.

[0259] The threshold test discussed above is applied at step 1002. Specifically, process 1000 determines whether the analyte wavelength result corresponds to a saturated result and whether the analyte wavelength has an acceptable calibration curve (eg, relative standard error less than 30%).

[0260] At query step 1004 , if the analyte wavelength meets the threshold test (eg, is not associated with a saturated result and has an acceptable calibration curve), process 1000 proceeds to step 1006 . If not, process 1000 proceeds to step 1008 .

[0261] At step 1006, the analyte wavelengths are ranked based on the weighting factor calculations described above. The analyte wavelength with the highest weight is selected and displayed on the display device 104 along with the associated concentration results of the corresponding analyte element.

[0262] At step 1008, a calibrated analyte wavelength test is applied (e.g., a lower threshold test than in step 1002). For example, a Boolean check is performed on the calibration curve to check whether a minimum number of standards is met. The calibration curve may also include an acceptable correlation coefficient.

[0263] At query step 1010, if a calibrated analyte result exists based on the testing in step 1008, then process 1000 proceeds to step 1006. If not, then process 1000 proceeds to step 1012.

[0264] At step 1012 , all analyte wavelengths in the acceptable analyte wavelength list are selected for use in the weighting factor calculation at step 1006 .

[0265] Figure 13 A graphical representation of the results 1014 from the list of acceptable analyte wavelengths is shown for display by the display device 104. In particular, Figure 13 Sample spectral data 1016 is shown for Sample 4. Also shown is the system 100's ability to select a portion 1018 of the spectrum for a detailed view in spectrum 1020, which provides a label of one or more analyte wavelengths and associated analyte elements from a list of acceptable analyte wavelengths at corresponding locations on spectrum 1012.

[0266] In practice, ICP-OES technology can be used to quantify up to 70 different elements in any given sample solution, and different samples may contain different combinations and concentrations of these elements. The automatic element identification feature in embodiments of the present invention allows users who have no knowledge of the solution's contents to quickly identify the essential components present in that solution. This can identify unusual or unexpected sample components that might otherwise be overlooked using manual element identification methods.

[0267] In addition, the ICP-OES emission lines of an element are often subject to spectral interferences, which occur when the analytical wavelength is partially or completely overlapped by the emission of another element or molecule, or is affected by unstructured background radiation. The presence and magnitude of spectral interferences are highly sample-dependent, even within the same method, and the appearance of analyte wavelengths affected by spectral interferences may be only subtly different from that of the analyte without interference; when the emission from the interferent is only slightly separated from the emission of the analyte wavelength, the presence of the interference may not be visually recognized.

[0268] The interference avoidance functionality of embodiments of the present invention cross-references multiple components of the spectral data for each measured solution with the known wavelength positions of all elements that can be quantified by ICP-OES. This allows for rapid and automatic identification of interferences at a given analyte wavelength, even in the presence of complete spectral overlap between these interferents and the analyte wavelength. This allows the operator to identify interferences without requiring knowledge of the potential spectral overlap or the contents of the solution.

[0269] Example applications of systems and methods according to example embodiments of the present invention will now be described below.

[0270] Example 1: Rapid Sample Evaluation and Assisted Method Development with ICP-OES

[0271] Spectral interferences and improper sample preparation are two of the most common causes of erroneous results in ICP-OES analysis. Spectral interferences can vary significantly between samples, particularly in samples containing high concentrations of spectrally abundant elements such as iron (Fe) or titanium (Ti). These interferences can go unnoticed, especially by inexperienced operators, and often appear in reported results as abnormally high concentrations of the affected element. Sample preparation errors can also be difficult to detect and can affect results, depending on the specific error and the preparation method used.

[0272] The system and method for ICP-OES according to embodiments of the present invention collects and interprets full spectral data for each sample, adding only a few seconds to each analysis. The algorithm behind the interpretation will automatically identify the elemental composition of each sample, as well as the presence of spectral interferences at common analyte wavelengths, without any input from the user. The following experimental results demonstrate the effectiveness of the method and system in identifying significant spectral interferences affecting several measurements in solid waste samples prepared according to standard method HJ 781-2016 (see Figure 14 ), including interferences from lanthanum (La) on arsenic (As), iron (Fe) on manganese (Mn), and titanium (Ti) on vanadium (V). In each case, the interference and suspected cause are clearly and automatically labeled in the software user interface, and a clear rating system is used to indicate the quality of the analyte peak at each wavelength of the analyte element. These experiments, performed in challenging sample matrices, successfully demonstrated the robustness of the spectral interference identification technique, even in the noisiest spectra.

[0273] The interference information provided by embodiments of the present invention can be quickly and easily obtained without requiring any method development or element selection on the part of the user. In some embodiments, method 106 will automatically report the results for each element it detects in each sample on a per-sample basis. Not only is there no need to develop methods to obtain this information, but the information itself can alert the user to possible interferences in the sample and make clear recommendations on the quality of other wavelengths for each detected element, thus providing a valuable first step in subsequent method development. The interference information can even be used to assist in the selection of interference correction techniques, helping to ensure that these corrections are applied correctly and compensate for interferences that are actually present in the sample being tested.

[0274] In some embodiments, identification of a common sample preparation error (insufficient HCl added to the acid digest) is demonstrated to be possible, in addition to the core functionality for high-throughput screening applications. Semi-quantification of chloride (Cl) in samples and convenient, real-time conditional formatting and filtering tools can immediately identify samples with abnormally low HCl levels (see Figure 15 ). Advantageously, the user interface can ensure that even inexperienced instrument operators can quickly and easily obtain such sample observations.

[0275] The user interface can provide a set of convenient graphical tools to display the contents of each measured solution. In some embodiments, the user interface allows the user to use a built-in color-coded periodic table heat map graphic (see Figure 16a and 16b ) to obtain an immediate assessment of the contents of their sample. Typically, the color coding of each element is customizable and correlates to the concentration of that element detected in each sample, allowing the user to make simple qualitative comparisons of elemental content between samples (also as Figure 15 In some embodiments, the visualization can be exported or included in a sample report after analysis.

[0276] Advantageously, the computer-implemented method 106 can be modular and compatible with other software modules to interface with the instrument 102. Embodiments of the present invention provide users with a high level of insight into the contents of their samples while requiring no knowledge of spectroscopy and minimal setup. In fact, the elemental composition of a sample and all the information described in the previous paragraph (including appropriate sample absorption and rise delay) can be obtained in 15 seconds; screening of a full rack of 60 samples can be completed in just 15 minutes.

[0277] Example 2: Simplified Method Development for DTPA Extraction of Soil Samples

[0278] Soil samples were prepared for analysis according to the Chinese HJ-804 method. Eight bioavailable elements were determined in DTPA-extracted soil samples using an Agilent 5800VDV ICP-OES equipped with an AVS 6-valve system and an SPS4 autosampler.

[0279] Sample screening according to embodiments of the present invention is performed and used to assist method development, thereby producing high-quality results without sample re-measurement. A reporting tool provided by embodiments of the present invention generates quantitative worksheets to facilitate semi-quantitative analysis and provides sample insights to supplement quantitative data.

[0280] Method development can be tedious and time-consuming. An imperfect method can lead to inaccurate data being reported and expensive re-measurements. Method development according to an exemplary embodiment of the present invention can include the following three steps.

[0281] Step 1: Run the sample

[0282] Sample screening according to Method 106 is fast and easy to set up. There is no need to select any elements or wavelengths. The screen captures data across the entire wavelength range in approximately 15 seconds, and an automated element discovery algorithm selects the elements and wavelengths for the operator.

[0283] Step 2: Add the recommended wavelength to the quantitation method

[0284] The screening produced a list of recommended wavelengths for each element detected in each sample.

[0285] For this application, all wavelengths selected by the screening process are also proposed in the HJ-804 prescribed method, indicating the reliability of the Method 106 algorithm.

[0286] Take Mn as an example (see Figure 17 ), screening according to Method 106 identified several wavelengths with a five-star confidence rating, indicating that these wavelengths may be suitable for quantitative methods.

[0287] Figure 17 The output shown in suggests Mn 257.610 as the highest rated analyte wavelength based on the quality of the analyte peak and its absence of interferences. The HJ 804 method recommends Mn 257.610 and Mn 293.305, corresponding to the output analyte wavelengths associated with a high confidence rating.

[0288] Question marks next to low-star-rated wavelengths indicate issues with two primary Mn lines. A pop-up box for the Mn 259.372 line indicates very low confidence in the result due to strong Fe interference. The Mn 294.921 line is also affected by Fe interference, as shown in Method 106. Based on our knowledge of these samples, both wavelengths were excluded from the quantification method.

[0289] Step 3: Run the quantitation method

[0290] Perform quantitative analysis using the wavelengths recommended for screening above and collect semi-quantitative data. This approach allows you to run a prescribed method while also collecting semi-quantitative data for up to 70 elements in the sample, such as Figure 18 shown.

[0291] The same automated element discovery algorithm used for screening evaluates the semi-quantitative data collected for each sample. The software calculates the approximate concentrations of all other elements in the sample and automatically identifies the presence of spectral interferences.

[0292] To have a higher confidence in the results, the output data from method 106 can be used to verify the full quantitative results. As shown in the table below, the semi-quantitative concentrations are within 25% of the full quantitative results, indicating that the results produced according to embodiments of the present invention have satisfactory confidence.

[0293]

[0294] explain

[0295] This specification, including the claims, is intended to be interpreted as follows:

[0296] The embodiments or examples described in the specification are intended to illustrate the present invention, rather than to limit its scope. As readily apparent to those skilled in the art, the present invention can be implemented by various modifications and additions. Therefore, it should be understood that the scope of the present invention is not limited to the exact construction and operation described or illustrated, but is limited only by the appended claims.

[0297] The mere disclosure of a method step or product element in the specification should not be construed as essential to the invention claimed herein unless explicitly stated or explicitly recited in the claims.

[0298] The terms in the claims are to be given the broadest meanings persons of ordinary skill in the art have given them as of the relevant date.

[0299] Unless expressly stated otherwise, the terms "a", "an" or "an" mean "one or more".

[0300] Neither the title nor the abstract of this application should be construed as limiting the scope of the claimed invention in any way.

[0301] When the preamble of a claim recites an object, benefit, or possible use of the claimed invention, it does not limit the claimed invention to having only that object, benefit, or possible use.

[0302] In the specification (including the claims), the term "comprise" and variations of the term (such as "include" or "which include") are used to mean "including but not limited to" unless expressly stated otherwise or unless context or usage requires an exclusive interpretation of the term.

[0303] The disclosures of any documents cited herein are incorporated by reference into this patent application as part of this disclosure, but only for the purpose of written description and implementation, and should in no way be used to limit, define or otherwise interpret any term of this application, which would not be unable to provide a definable meaning without incorporation by reference. The incorporation of any document by reference does not in itself constitute an endorsement or approval of any statement, view or argument contained in any incorporated document.

[0304] The reference to any background art or prior art in this specification does not constitute an admission that such background art or prior art constitutes common general knowledge in the relevant field, or is acceptable prior art relevant to the validity of the claims.

Claims

1. A computer-implemented method for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy, the method comprising the steps of: obtaining sample spectral data from the sample, obtaining, for each element of the periodic table quantifiable by optical emission spectroscopy, a list of one or more predetermined emission wavelengths, each predetermined emission wavelength being associated with a list of one or more potentially interfering emission wavelengths, determining a list of one or more analyte wavelengths corresponding to spectral peaks in the sample spectral data based on the emission wavelength list, determining, based on the list of one or more potential interfering emission wavelengths corresponding to the analyte wavelength, for each analyte wavelength, whether the corresponding spectral peak has a possibility of being affected by an interfering emission wavelength causing spectral interference, determining a revised list of one or more analyte wavelengths by removing from the list of analyte wavelengths analyte wavelengths corresponding to spectral peaks having a likelihood of being affected by interfering emission wavelengths, and A confidence level that one or more elements are present in the sample is determined based on a set of criteria applied to the revised analyte wavelength list.

2. The computer-implemented method of claim 1 , wherein The sample spectral data includes data representing emission intensities corresponding to wavelengths within the sample spectral range, and The step of determining the analyte wavelength list includes analyzing a region of interest of the sample spectral range corresponding to each predetermined emission wavelength of each element, determining whether the saturated result is within the region of interest, When it is determined that the saturation result is not located within the region of interest, it is determined whether a peak in the emission intensity is located within the region of interest. 3 . The computer-implemented method of claim 2 , wherein the step of determining the analyte wavelength list further comprises determining whether the saturation result represents a peak in emission intensity having a flat top.

4. The computer-implemented method of claim 2 or 3, wherein the step of determining the analyte wavelength list further comprises A confidence level that the peak in the emission intensity has been identified in the region of interest is determined based on a threshold test. 5 . The computer-implemented method of claim 4 , wherein determining a confidence level that a peak in the emission intensities has been identified in the region of interest comprises calculating a standard deviation of emission intensities about the peak to determine a confidence factor. 6 . The computer-implemented method of claim 5 , wherein the element associated with the peak is considered identified if the confidence factor is greater than a predetermined threshold.

7. The computer-implemented method of any preceding claim, wherein the step of determining whether the corresponding spectral peak for each analyte wavelength has a likelihood of being affected by an interfering emission wavelength comprises: Determine the clean interfering emission wavelength associated with each analyte wavelength, and Determine whether the clean interfering emission wavelength corresponds to a spectral peak in the sample spectral data.

8. The computer-implemented method of claim 7, wherein the step of determining a clean interfering emission wavelength comprises determining an interfering emission wavelength least likely to be affected by spectral interference.

9. The computer-implemented method of claim 7 or 8, further comprising: For each analyte wavelength corresponding to a spectral peak affected by a spectral interference, the significance of the spectral interference is determined based on any one or more of the following: The distance between the spectral peak corresponding to the clean interfering emission wavelength and the spectral peak corresponding to the associated analyte wavelength; • the ratio of the spectral peak corresponding to the clean interfering emission wavelength to the spectral peak corresponding to the associated analyte wavelength; and • The ratio of the emission intensity corresponding to the clean interfering emission wavelength and the emission intensity corresponding to the associated analyte wavelength.

10. The computer-implemented method of any one of the preceding claims, wherein the set of criteria for determining a confidence level that one or more elements are present in the sample comprises any one or more of the following: whether the number of detected primary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a first threshold; and whether the number of detected primary and secondary analyte wavelengths corresponding to each element in the revised analyte wavelength list is above a second threshold, wherein the primary analyte wavelength of the element corresponds to an emission wavelength having a high peak spectral intensity, and the secondary analyte wavelength of the element corresponds to an emission wavelength having a peak spectral intensity lower than that of the primary analyte wavelength.

11. The computer-implemented method of claim 10, wherein For elements having at least three primary analyte wavelengths, the first threshold is two, and for elements having two or fewer primary analyte wavelengths, the first threshold is one, and The second threshold is at least one primary analyte wavelength and one secondary analyte wavelength.

12. The computer-implemented method of any preceding claim, further comprising Based on the determined confidence level, one or more elements are added to the list of identified elements.

13. The computer-implemented method of claim 12, further comprising verifying each element in the identified element list to determine whether a peak in the sample spectral data associated with an analyte wavelength may be affected by an interfering emission wavelength causing spectral interference, and Upon determining that an analyte wavelength having a corresponding element in the identified element list may be affected by an interfering emission wavelength causing spectral interference, the corresponding element is removed from the identified element list.

14. The computer-implemented method of claim 12 or 13, further comprising Selectively displaying the analyte wavelength corresponding to each element in the list of identified elements based on selection criteria, wherein the selection criteria include any one or more of the following: whether the analyte wavelength is associated with a saturation result, the maximum number of analyte wavelengths displayed for each corresponding element, and Whether the analyte wavelength is associated with the user selection.

15. The computer-implemented method of any one of claims 12 to 14, further comprising Calculate the concentration of each element in the list of identified elements, The step of calculating the concentration of each element comprises measuring the emission intensity of the spectral peak associated with the corresponding element and correcting for background emission.

16. The computer-implemented method of any preceding claim, further comprising: Identify unusual analyte wavelengths, and Based on the measurements associated with the anomalous analyte wavelength, the confidence level that the corresponding element is present in the sample is lowered.

17. A system for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy, the system comprising: an optical emission spectrometer for obtaining sample spectral data from the sample; and A processor for performing a computer-implemented method according to any one of the preceding claims.

18. One or more tangible, non-transitory computer-readable media having computer-executable instructions for performing the computer-implemented method of any preceding claim.

19. A computer system for automatically identifying the presence of one or more elements in a sample via optical emission spectroscopy, the system comprising a sample data retrieval module, which is used to obtain sample spectrum data from the sample; a wavelength data retrieval module for obtaining, for each element of the periodic table quantifiable by optical emission spectroscopy, a list of one or more predetermined emission wavelengths, each predetermined emission wavelength being associated with a list of one or more potentially interfering emission wavelengths; a peak search module for determining a list of one or more analyte wavelengths corresponding to spectral peaks in the sample spectral data based on the emission wavelength list; an interference search module for determining, for each analyte wavelength, whether the corresponding spectral peak has a possibility of being affected by an interfering emission wavelength that causes spectral interference based on the list of one or more potential interfering emission wavelengths corresponding to the analyte wavelength; a wavelength processing module that determines a revised list of one or more analyte wavelengths by removing analyte wavelengths from the list of analyte wavelengths corresponding to spectral peaks having a likelihood of being affected by interfering emission wavelengths; and An element identification module is configured to determine a confidence level that one or more elements are present in the sample based on a set of criteria applied to the revised analyte wavelength list.

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