GB2538232A

GB2538232A - Mixture identification

Info

Publication number: GB2538232A
Application number: GB1507841.3A
Authority: GB
Inventors: Andrew Sudnik Michael
Original assignee: ISOPRIME Ltd
Current assignee: ISOPRIME Ltd
Priority date: 2015-05-07
Filing date: 2015-05-07
Publication date: 2016-11-16
Also published as: EP3292402A1; WO2016178033A1; GB201507841D0

Abstract

Methods, systems and computer-readable media for identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixture by correlating a plurality of delta values for a sample mixture with a plurality of delta values for one of more reference mixtures, wherein the delta values are indicative of a relative isotope composition for a compound in the plurality of compounds in the respective mixtures. In this manner, the plurality of delta values for the components of the sample mixture and the reference mixture serves as respective delta values signatures for the purpose of identification. The compounds in the sample mixture 102 may be separated by a gas chromatograph 104 and oxidised or reduced at step 106 for introduction to the isotope ratio mass spectrometer IRMS 108 which determines delta values for each compound. Data 110 sent to the analysis engine 112 is analysed to provide correlation data 116

Description

MIXTURE IDENTIFICATION

Technical Field

100011 The present invention relates to an apparatus and method for identifying mixtures of compounds and/or compounds within a mixture. In particular, but not exclusively, the present invention relates to an apparatus and method for processing isotope ratio mass spectrometry data resulting from chemical analysis of a sample and identifying mixtures of compounds and/or compounds within a mixture for said sample.

Background

[0002] In many technical fields, it is useful to be able to identify mixtures of compounds. In some cases, it is useful to be able to identify compounds within a mixture. It is also useful to be able to identify the source of a mixture; this may involve differentiating between a synthetic mixture and a naturally occurring mixture or between two synthetic mixtures. For example, such techniques can be useful in detecting blood doping and the like.

[0003] Known methods, such as chromatography and thermogravimetric analysis, allow compounds within a mixture to be separated and analyzed. In some cases, the relative output of the analysis allows the overall mixture to be identified without specific identification of the compounds per se. In other cases, the compounds are identified.

[0004] One such known method is gas chromatography mass spectrometry (GC-MS). The output chromatograms can be used to analyze compound retention time in the gas chromatography apparatus; each mixture should have a unique chromatogram profile and therefore, by comparison with reference spectra, the mixture is identifiable. However, retention time is highly susceptible to environmental variations and so very careful control over the conditions during GC-MS is required.

Summary

[0005] According to a first aspect of the present invention, there is provided a computer-implemented method of identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixture, the method comprising: receiving, at a computing device, first data indicative of a first plurality of delta values associated with a sample mixture comprising a plurality of unknown compounds, wherein each delta value in the first plurality of delta values is indicative of a relative isotope composition for a respective unknown compound in the plurality of unknown compounds; receiving, at the computing device, second data indicative of a second plurality of delta values associated with a first reference mixture comprising a plurality of known compounds, wherein each delta value in the second plurality of delta values is indicative of a relative isotope composition for a respective known compound in the plurality of known compounds; determining, at the computing device, a correlation measure indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and the second plurality of delta values associated with the first reference mixture, based on the first data and the second data; and generating, at the computing device, data associating the sample mixture with a mixture identifier associated with the reference mixture, when the correlation measure satisfies a mapping condition.

[0006] According to some embodiments, each known compound in the plurality of known compounds is associated with a respective compound identifier in a plurality of compound identifiers, and the method further comprises generating, at the computing device, data associating at least one compound identifier in the plurality of compound identifiers with at least one unknown compound in the plurality of unknown compounds in the sample mixture, when the correlation measure satisfies the mapping condition.

[0007] According to some embodiments, the method further comprises, at the computing device, associating data representing a peak in a chromatograph for the sample mixture with the at least one compound identifier in the plurality of compound identifiers, wherein the peak corresponds to the at least one unknown compound in the plurality of unknown compounds. [0008] According to some embodiments, the first data is generated by application of isotope ratio spectrometry, isotope ratio mass spectrometry, cavity ring-down spectroscopy, infrared isotope spectroscopy, integrated cavity output spectroscopy, and/or quantum cascade laser spectroscopy to one or more analytes separated from the sample mixture.

[0009] According to some embodiments, the one or more analytes are separated from the sample mixture by application of gas chromatography, liquid chromatography, ion chromatography, and/or supercritical fluid chromatography to the sample mixture.

[0010] According to some embodiments, the correlation measure is determined based on a regression analysis performed on the first plurality of delta values and the second plurality of delta values.

100111 According to some embodiments, the correlation measure is an R-squared measure determined based on the regression analysis.

[0012] According to some embodiments, the mapping condition specifies a threshold correlation measure.

[0013] According to some embodiments, the threshold correlation measure is indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and a third plurality of delta values associated with a second reference mixture.

[0014] According to some embodiments, each delta value of the first plurality of delta values indicates a measure of isotope composition for a corresponding unknown compound in the plurality of unknown compounds in the sample mixture, relative to a standard isotope composition.

[0015] According to some embodiments, each delta value in the second plurality of delta values indicates a measure of isotope composition for a corresponding known compound in the plurality of known compounds in the first reference mixture, relative to the standard isotope composition.

[0016] According to a second aspect of the present invention, there is provided a non-transitory computer-readable medium comprising computer-executable instructions that, when executed by a processor in a computing device, cause the computing device to perform a method of identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixtures, the method comprising: receiving, at the computing apparatus, first data indicative of a first plurality of delta values associated with a sample mixture comprising a plurality of unknown compounds, wherein each delta value in the first plurality of delta values is indicative of a relative isotope composition for a respective unknown compound in the plurality of unknown compounds; receiving, at the computing device, second data indicative of a second plurality of delta values associated with a first reference mixture comprising a plurality of known compounds, wherein each delta value in the second plurality of delta values is indicative of a relative isotope composition for a respective known compound in the plurality of known compounds; determining, at the computing device, a correlation measure indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and the second plurality of delta values associated with the first reference mixture, based on the first data and the second data; and generating, at the computing device, data associating the sample mixture with a mixture identifier associated with the reference mixture, when the correlation measure satisfies a mapping condition.

[0017] According to a third aspect of the present invention, there is provided a system for identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixture, comprising at least one memory including computer program code and at least one processor in data communication with the at least one memory, wherein the at least one processor is configured to execute the computer program code and cause the system to: receive first data indicative of a first plurality of delta values associated with a sample mixture comprising a plurality of unknown compounds, wherein each delta value in the first plurality of delta values is indicative of a relative isotope composition for a respective unknown compound in the plurality of unknown compounds; receive second data indicative of a second plurality of delta values associated with a first reference mixture comprising a plurality of known compounds, wherein each delta value in the second plurality of delta values is indicative of a relative isotope composition for a respective known compound in the plurality of known compounds; determine a correlation measure indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and the second plurality of delta values associated with the first reference mixture, based on the first data and the second data; and generate data associating the sample mixture with a mixture identifier associated with the reference mixture, when the correlation measure satisfies a mapping condition.

Brief Description of the Drawings

[0018] Further features and advantages of the invention will become apparent from the following description of preferred embodiments of the invention, given by way of example only, which is made with reference to the accompanying drawings, of which: [0019] Figure 1 is a schematic diagram showing a system for analyzing an unidentified mixture in accordance with an embodiment.

[0020] Figure 2 is a flow chart showing a method for analyzing the unidentified mixture of compounds in accordance with an embodiment.

[0021] Figure 3 is a flow chart showing a method for dentifying compounds in the unidentified mixture in accordance with an embodiment.

[0022] Figure 4 is a chart showing a chromatogram for the unidentified mixture in accordance with an embodiment.

[0023] Figure 5 is a chart showing a scatter plot of reference delta values plotted against delta values for compounds in the unidentified mixture in accordance with an embodiment.

[0024] Figure 6 is a chart showing the chromatogram for the unidentified mixture with peaks labelled according to an embodiment.

[0025] Figure 7 is a schematic diagram showing a computer system for analyzing an unidentified mixture in accordance with an embodiment.

Detailed Description

[0026] The isotope ratio of a given compound is affected by the route by which the compound is made, and in some cases, by the environmental conditions under which the compound is made. However, for stable isotopes such as 13C and deuterium, the isotope ratio will not normally change once the compound has been made. Thus, in a mixture of compounds, each compound will have a specific and typically invariable isotope ratio.

[0027] The isotope ratio of a given compound may be quantified using a "delta value" or 5, as is known in the art. The delta value provide a measure of an isotope ratio for the given compound, relative to a standard isotope ratio. The delta value for a given compound is calculated according to the following formula: [0028] = ([compound isotope ratio] 1) x 1000 [standard isotope ratio] [0029] The standard isotope ratio featuring in the above formula is based on a standard material and is selected depending on the element in question. Examples of standard isotope ratios used for calculation of delta values are the standard isotope ratios defined by the International Atomic Energy Agency (IAEA) and the National Institute of Standards and Technology (KIST).

[0030] The isotope ratio of a compound may be measured using an isotope ratio spectrometer, such as an isotope ratio mass spectrometer. In this case, the compound of interest is converted (e.g., through catalytic combustion) to obtain one or more products, which are provided to the isotope ratio spectrometer as "analytes" for isotope ratio analysis. In this context, the analytes are quantitative conversion products of the compound of interest (whose isotopic compositions cannot be determined through spectroscopic means). Examples of typical analytes include CO? (where the i sotope ratio measured is31 (712--,), SO2 (where the isotope ratio measured is 34S/32S), N2 (where the isotope ratio measured is 25N/14,-is), CO (where the isotope ratio measured is 180/160) H2 (where the isotope ratio measured i.e. D/H) and ILO (where the isotope ratio measured is 2H/'H, i.e. D/H, and 180/160). The corresponding delta values for these example analytes are 513C, [0031] Embodiments of the present invention utilize the specific and invariable characteristics of isotope ratios and their corresponding delta values to facilitate identification of unknown or unidentified mixtures by correlation with isotope ratio data for one or more reference mixtures. In other words, embodiments of the invention utilize the plurality of isotope ratios measured for a given mixture of compounds as a "delta value signature" which is compared or correlated against the delta value signature of one or more reference mixtures, thereby facilitating identification of the given mixture. This approach is advantageous in that it is less susceptible to environmental variations when compared to prior art techniques for mixture identification.

[0032] Figure 1 shows a system 100 for analyzing a sample mixture 102 comprising a plurality of compounds in accordance with an embodiment. In this example, the identity of the sample mixture 102 and its constituent compounds are initially unknown or unidentified. The system 100 comprises a gas chromatograph 104, an isotope ratio mass spectrometer 108 and an analysis engine 112, which are configured to analyze and identify the sample mixture 102 based on the particular delta value signature of its constituent compounds.

[0033] The gas chromatograph 104 separates the constituent compounds of the sample mixture 102 using gas chromatography, as is known in the art. The separated compounds exit the gas chromatograph 104 temporally spaced according to their respective retention times. The temporal spacing between the separated compounds introduced by the gas chromatography is maintained throughout the subsequent isotope ratio analysis to allow the isotope ratios for each separated compound to be determined individually, as discussed below.

[0034] The separated compounds output by the gas chromatograph 104 are converted (i.e. oxidized or reduced) to form one of more respective analytes 106, which are in turn delivered to the isotope ratio mass spectrometer 108 for analysis. According some embodiments, only a subset of the analytes 106 obtained from the combustion process is provided to the isotope ratio mass spectrometer 108 for analysis, depending on the particular isotope ratios to be measured. According to alternative embodiments, all analytes 106 are provided to the isotope ratio mass 6345, 615N, 5180 and SD respectively.

spectrometer 108 but only a subset of the analytes 106 are measured. In a typical example, the subset of analytes 106 provided to or measured by the isotope ratio mass spectrometer 108 may comprise CO2, FI2 and/or ILO, thereby enabling the measurement of the I3C/I2C, and/or D/H isotope ratios, and calculation of the respective 5HC and SD delta values for each separated compound of the sample mixture.

100351 The isotope ratio mass spectrometer 108 is arranged to measure to the isotope ratios of the received analytes 106 and to calculate the corresponding delta values for the respective compounds of the sample mixture 102. The isotope ratio mass spectrometer 108 outputs data 110 indicative of the determined delta values for each compound of the sample mixture, and transmits data 110 to the analysis engine 112 for further processing and identification of the sample mixture 102. In some embodiments, the isotope ratio mass spectrometer 108 may output and transmit data 110 on a per-compound basis to account for the temporal spacing between compounds and their respective analytes introduced by the gas chromatograph 104. In an alternative embodiment, the isotope ratio mass spectrometer 108 may delay output and transmission of data 110 until the analytes for a predetermined number of separated compounds have been analyzed.

100361 According to some embodiments, the analysis engine 112 is a computing device provided with appropriate software for processing of the data 110 received from the isotope ratio mass spectrometer 108 in accordance with the embodiments described below. In some embodiments, the analysis engine 112 may be integrated with the isotope ratio mass spectrometer 108 in a single physical unit. In alternative embodiments, the analysis engine may be a standalone computing device which is configured to receive data 110 over a communications network or via a data storage medium, such as a CD-ROM or a USB storage device.

[0037] The analysis engine 112 is configured to perform a correlation process based on the calculated delta values for the sample mixture, represented by data 110, and delta values for one or more reference mixtures of known identity and composition. Data 114 indicative of delta values for the one or more reference mixtures is received and/or stored by the analysis engine 112. For example, in some embodiments, the delta values for the one or more reference mixtures may be provided to the analysis engine 112 by a user via a graphical user interface of the analysis engine 112. Alternatively, data 114 may be received by the analysis engine 112 via a communications network or a data storage medium, such as a CD-ROM or a USB storage device. In a typical example, the reference delta values represented by data 114 are those published by the Biogeochemical Laboratories, Indiana University, United States of America, for one or more "Hydrogen and Carbon Stable Isotope Reference Materials". A specific example of such a reference material is the "Fatty Acid Ester Mixture F8-. In an alternative example, the reference delta values may be obtained from a sample mixture analyzed using system 100 and stored for comparison with subsequent sample mixtures.

[0038] As discussed above, the analysis engine 112 is configured to perform a correlation process on the basis of data 110 and data 114 to determine the identity of the sample mixture 102. The analysis engine 112 is configured to output the result of the correlation process as data 116, which is indicative of an association between the sample mixture 102 and the determined identity of the sample mixture 102. Further details of the correlation process performed by the analysis engine 112 and the nature of data 116 resulting from the correlation process are discussed below with reference to Figures 2 to 6.

[0039] Further details of the steps involved in identification of the sample mixture 102 using the analysis system 100 are illustrated by Figure 2, which shows a method 200 for identifying a sample mixture in accordance with an embodiment. In a first step, the sample mixture 102 is received by the analysis system 100 for identification (step S202). Next, the sample mixture 102 is separated into its constituent compounds by gas chromatography performed by the gas chromatograph 112 (step S204). Each separated compound is separately evolved by combustion to produce one or more respective analytes 106 (step S206). For example, where the compounds are organic in nature (i.e. hydrocarbons) the analytes 106 resulting from step S206 will comprise H2, H2O and/or CO). Next, the analytes 106 resulting from step 5206 (or a subset thereof) are fed to the isotope ratio mass spectrometer 108 on a per-compound basis, and the isotope abundance is measured relative to a corresponding standard [step S208]. Once the relative isotope ratios for a given compound of the sample mixture has been measured, the corresponding delta value(s) for the given compound are calculated, relative to the appropriate standard isotope ratio [step S210]. Finally, data 110 indicative of the calculated delta values for compounds in the sample mixture 102 is sent to the analysis engine 112 and a correlation process is performed based on data 110 and data 114 to identify the sample mixture 102 [step S212].

[0040] Figure 3 shows a correlation process 300 performed by the analysis engine 112 to identify the sample mixture 110 in accordance with an embodiment. In a first step, the analysis engine 112 receives data 110 indicative of the delta values calculated for a plurality of compounds in the sample mixture 102 [step S302]. Next, the analysis engine 112 receives or retrieves data 114 indicative of the delta values for a plurality of known compounds in a reference mixture [step S304]. Once the data 110 for the sample mixture 102 and the data 114 for the reference mixture is available at the analysis engine 112, a correlation measure for the respective delta values is calculated [step S306]. The calculated correlation quantifies the statistical relationship between the delta values for the sample mixture 102 and the delta values for the reference mixture, and thus indicates the likelihood that the sample mixture 102 corresponds to the reference mixture. In a typical example, the correlation measure may correspond to the well-known R-squared value calculated as part of a regression analysis performed on the respective delta values. Next, the analysis engine 112 determines whether the calculated correlation measure satisfies one or more criteria defined by a mapping condition [step S308]. In this context, when the calculated correlation measure satisfies the mapping condition, it indicates that there is a reasonable likelihood that the sample mixture is a match to the reference material and can therefore be identified as such. For example, the mapping condition may specify that the calculated correlation measure must satisfy a predetermined threshold correlation measure for the reference material. In the present embodiment, upon determining that the calculated correlation measure satisfies the mapping condition, the analysis engine 112 generates data associating the sample mixture 102 with the identity of the reference mixture [step S310]. For example, the analysis engine 112 may generate data indicating the association between the sample mixture and the identity of the reference mixture, and optionally the calculated correlation measure to provide an indication of "certainty" for the association. According to some embodiments, once the identity of the sample mixture 102 has been determined, the analysis engine 112 may optionally utilize the determined correlation between the delta values of the sample mixture 102 and the delta values of the reference mixture to identify one or more peaks in a chromatogram for the sample mixture [step S312]. This latter step is explained further below with reference to Figures 4 to 6.

[0041] According to some embodiments, the method 300 of Figure 3 may be repeated for a plurality of reference mixtures to determine a plurality of respective correlation measures. According to this approach, the sample mixture 102 may be identified as this reference mixture which is associated with the "best" correlation as indicated by the respective correlation measure.

[0042] With regard to the regression analysis discussed above with reference to step S306 of Figure 3, it will be appreciated that when a R-squared measure is employed, a minimum of three delta values will be required to calculated the R-squared correlation measure (i.e. the R-squared value for two points is always equal to 1).

[0043] According to some embodiments, the correlation measure may by calculated on a subset of the delta values for the sample mixture and/or may be recalculated as additional delta value data becomes available as a result of the temporal spacing between the separated compounds introduced by the gas chromatography. Moreover, according to some embodiments, a plurality of correlation measures may be calculated for different respective subsets of the delta value data to enable identification of anomalous delta values (e.g. due to noise) and to ensure that such anomalous delta values are disregarded for the purpose of identifying the sample mixture.

[0044] Figure 4 show an example of a chromatogram 400 generated by the gas chromatograph 104 for the sample mixture 102. The chromatogram 400 is a plot of retention time 402 against intensity 404 and comprises a set of six peaks 406 which occur at different respective retention times. Each peak 406 in the chromatogram 400 corresponds to a respective compound separated from the sample mixture 110, but the identity of the respective compounds is initially unknown.

[0045] Figure 5 is a scatter chart 500 illustrating a technique for identifying compounds in the sample mixture 102 in accordance with an embodiment. In the present embodiment, the scatter chart 500 is a plot of delta values 502 (Srd) for a given reference mixture against delta values 504 (5,,,m) for the sample mixture. In this respect, the scatter chart 500 shows six data points 506 corresponding to the six unidentified peaks appearing in the corresponding chromatogram 400 of Figure 4, and a line of best fit 508 determined using a linear regression analysis during the correlation process of Figure 3. In the present example, the calculated correlation measure is the R-squared value with respect to the line of best fit 508, and it is assumed that the correlation measure satisfies the mapping condition specified in step S308 of Figure 3. Thus, based on the premise that the sample mixture 102 corresponds to the reference mixture, it is possible to map the unidentified peaks in the chromatogram 400 of Figure 4 to known compounds in the reference mixture shown in Figure 5. To provide an example, from Figure 5 it is known that the data point 506-3 corresponds to the delta value determined for a compound corresponding to the fourth peak 406-4 in the chromatogram 400 of Figure 4 and also to "compound A" of the reference mixture. On this basis, the compound corresponding to the fourth peak in chromatogram 400 may be identified as "compound A" and the analysis engine 112 may generate data indicating an association between the fourth peak 406-4 in chromatogram 400 and "compound A". In this respect, it will be noted that there is no correlation between the order of the peaks 406 in the chromatogram 400 and the magnitude of the associated delta values.

[0046] The result of the mapping described above with Figure 5 is illustrated by the chromatogram 600 of Figure 6, which has been updated to identify or "label" the fourth peak 406-4 as "compound A". Although only one peak has been identified in the present example, it will be appreciated that the technique described above with reference to Figure 5 can be employed to identity any number of peaks in the chromatogram 400 of Figure 4. Thus, the present embodiment enables identification of individual peaks in a chromatogram for the sample mixture 102, in addition to identification of the sample mixture 102 itself This identification is based solely on the particular delta value signature of the sample mixture 102 and is therefore independent of any potential variation caused by compound retention time or other systematic variations.

[0047] Advantageously, application of the R-squared technique in the embodiments described above with reference Figures 2-6 ensures that the correlation measure is essentially independent of any variation in delta value magnitude and scaling between the sample delta values and the reference delta values. Thus, in an example where mixture identification is performed on a set of sample delta values of 1, 2, 3, 4 & 5 with respect of a reference mixture with delta values 20, 30, 40, 50 & 60, an R-squared value of 1 would result irrespective of the translation and scaling between the sample and reference delta values.

[0048] According to some embodiments, the analysis engine 112 may be embedded as an embedded computer device in the isotope ratio mass spectrometer 108 of Figure L In such embodiments, the combined analysis engine 112 and isotope ratio mass spectrometer 108 function as a standalone apparatus for identification of unidentified sample mixtures. For example, the standalone apparatus may be provided with a display means (e.g. an LCD display panel), and input means (e.g. a keyboard and mouse) which enables a user of the apparatus to control the analysis of the sample mixture and view results of the identification and correlation process described above.

[0049] At least parts of the methods discussed above with reference to Figures 1 to 6 may be implemented using software instructions stored on a computer useable storage medium for execution by a computing device. As an example, an embodiment of a computer program product includes a computer useable storage medium to store a computer readable program that, when executed on a computing device, causes the computing device to perform operations, as described hereinbefore. Furthermore, embodiments of the invention can be embodied in the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computing device or any instruction execution system. For the purposes of this description, a computer-usable or computer-readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The apparatus may be a transitory or a non-transitory computer-readable medium. For example, the computer-useable or computer-readable medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device), or a propagation medium. Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk, and an optical disk. Current examples of optical disks include a compact disk with read only memory (CD-ROM), a compact disk with read/write (CD-R/W), and a digital versatile disk (DVD).

[0050] Embodiments of the analysis engine 112 described above with reference to Figures 1 to 6 are typically performed by a computer that executes computer readable instructions. Figure 7 depicts schematically an example of a suitable computer 700 that includes a processor 702, a memory 704, a storage device 706 and a network interface 708. The processor 702 may include a multifunction processor and/or an application-specific processor, examples of which include the PowerPCTM family of processors by IBMTM and the x86 and x86-64 family of processors by INTELTm. The memory 704 within the computer is typically RAM and storage device 706 is typically a large capacity permanent storage device such as a magnetic hard disk drive or solid state memory device. The network interface 708 enables communications with other computers in a network using as suitable protocol, such as the Internet Protocol (IP) and the processor 702 executes computer readable instructions stored in storage 706 to implement embodiments of the invention as described hereinbefore with reference to Figures 1 to 6.

[0051] Although the embodiments described above have employed a gas chromatography isotope ratio mass spectrometer to determine the isotope ratios of the analytes 106, it will be appreciated that other techniques may be employed. For example the separation may be carried out using a thermogravimetric analyzer, gas chromatography, liquid chromatography, ion chromatography, supercritical fluid chromatography, based apparatus and the like. In addition, the isotope ratio may be measured using a spectroscopy-based system, such as cavity ring-down spectroscopy (CRDS), infrared isotope spectroscopy, integrated cavity output spectroscopy, quantum cascade laser spectroscopy, based apparatus and the like. Similarly, the technique used to obtain the isotope ratios for the sample material is not limited to be the same technique as used to obtain the isotope ratios for the reference material.

[0052] As discussed above, according to some embodiments the delta values for more than one analytes may be determined for each separated compound. In particularly convenient cases, the analytes 106 can be formed for a given separated compound by the same processing step. Measurement of two or more sets of delta values allows two or more corresponding comparisons to be made with reference data values, further enhancing the reliability of the mixture identification.

[0053] In some embodiments, the sample induced into the isotope ratio mass spectrometer 108 is substantially all analyte for each separated compound. The analyte per se may be present in the compounds prior to separation by the gas chromatograph 104, but at least some of the mixed compounds will be processed to form the analyte. In some embodiments, the mixture compounds may be processed into the analyte using an oxidation or reduction reaction. In some embodiments, the mixture compounds may be processed into the analyte using combustion.

[0054] According to the embodiments described above, the compounds of the sample mixture are separated in time by the gas chromatograph 104. In other embodiments, the compounds may physically be separated into separate containers (e.g. fractional collection). In some embodiments, separation may be effected by chromatography, suitably gas chromatography, or by other methods such as thermogravimetric separation.

[0055] The above embodiments are to be understood as illustrative examples of the invention. Further embodiments of the invention are envisaged. It is to be understood that any feature described in relation to any one embodiment may be used alone, or in combination with other features described, and may also be used in combination with one or more features of any other of the embodiments, or any combination of any other of the embodiments. Furthermore, equivalents and modifications not described above may also be employed without departing from the scope of the invention, which is defined in the accompanying claims.

Claims

CLAIMSWhat is claimed is: 1. A computer-implemented method of identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixture, the method comprising: receiving, at a computing device, first data indicative of a first plurality of delta values associated with a sample mixture comprising a plurality of unknown compounds, wherein each delta value in the first plurality of delta values is indicative of a relative isotope composition for a respective unknown compound in the plurality of unknown compounds; receiving, at the computing device, second data indicative of a second plurality of delta values associated with a first reference mixture comprising a plurality of known compounds, wherein each delta value in the second plurality of delta values is indicative of a relative isotope composition for a respective known compound in the plurality of known compounds; determining, at the computing device, a correlation measure indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and the second plurality of delta values associated with the first reference mixture, based on the first data and the second data; and generating, at the computing device, data associating the sample mixture with a mixture identifier associated with the reference mixture, when the correlation measure satisfies a mapping condition.
2. A computer-implemented method according to claim 1, wherein each known compound in the plurality of known compounds is associated with a respective compound identifier in a plurality of compound identifiers, and the method further comprises generating, at the computing device, data associating at least one compound identifier in the plurality of compound identifiers with at least one unknown compound in the plurality of unknown compounds in the sample mixture, when the correlation measure satisfies the mapping condition.
3. A computer-implemented method according to claim 1, further comprising, at the computing device, associating data representing a peak in a chromatograph for the sample mixture with the at least one compound identifier in the plurality of compound identifiers, wherein the peak corresponds to the at least one unknown compound in the plurality of unknown compounds.
4. A computer-implemented method according to any one of the preceding claims, wherein the first data is generated by application of isotope ratio spectrometry, isotope ratio mass spectrometry, cavity ring-down spectroscopy, infrared isotope spectroscopy, integrated cavity output spectroscopy, and/or quantum cascade laser spectroscopy to one or more analytes separated from the sample mixture.
5. A computer-implemented method according to claim 4, wherein the one or more analytes are separated from the sample mixture by application of gas chromatography, liquid chromatography, ion chromatography, and/or supercritical fluid chromatography to the sample mixture.
6. A computer-implemented method according to any one of the preceding claims, wherein the correlation measure is determined based on a regression analysis performed on the first plurality of delta values and the second plurality of delta values.
7. A computer-implemented method according to claim 6, wherein the correlation measure is an R-squared measure determined based on the regression analysis.
8. A computer-implemented method according to any one of the preceding claims, wherein the mapping condition specifies a threshold correlation measure.
9. A computer-implemented method according to claim 8, wherein the threshold correlation measure is indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and a third plurality of delta values associated with a second reference mixture.
10. A computer-implemented method according to any one of the preceding claims, wherein each delta value of the first plurality of delta values indicates a measure of isotope composition for a corresponding unknown compound in the plurality of unknown compounds in the sample mixture, relative to a standard isotope composition.
11. A computer-implemented method according to any one of the preceding claims, wherein each delta value in the second plurality of delta values indicates a measure of isotope composition for a corresponding known compound in the plurality of known compounds in the first reference mixture, relative to the standard isotope composition.
12. A non-transitory computer-readable medium comprising computer-executable instructions that, when executed by a processor in a computing device, cause the computing device to perform a method of identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixtures, the method comprising: receiving, at the computing apparatus, first data indicative of a first plurality of delta values associated with a sample mixture comprising a plurality of unknown compounds, wherein each delta value in the first plurality of delta values is indicative of a relative isotope composition for a respective unknown compound in the plurality of unknown compounds; receiving, at the computing device, second data indicative of a second plurality of delta values associated with a first reference mixture comprising a plurality of known compounds, wherein each delta value in the second plurality of delta values is indicative of a relative isotope composition for a respective known compound in the plurality of known compounds; determining, at the computing device, a correlation measure indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and the second plurality of delta values associated with the first reference mixture, based on the first data and the second data; and generating, at the computing device, data associating the sample mixture with a mixture identifier associated with the reference mixture, when the correlation measure satisfies a mapping condition.
13. A system for identifying a sample mixture based on relative isotope composition for a plurality of compounds in the sample mixture, comprising at least one memory including computer program code and at least one processor in data communication with the at least one memory, wherein the at least one processor is configured to execute the computer program code and cause the system to: receive first data indicative of a first plurality of delta values associated with a sample mixture comprising a plurality of unknown compounds, wherein each delta value in the first plurality of delta values is indicative of a relative isotope composition for a respective unknown compound in the plurality of unknown compounds; receive second data indicative of a second plurality of delta values associated with a first reference mixture comprising a plurality of known compounds, wherein each delta value in the second plurality of delta values is indicative of a relative isotope composition for a respective known compound in the plurality of known compounds; determine a correlation measure indicative of a degree of correlation between the first plurality of delta values associated with the sample mixture and the second plurality of delta values associated with the first reference mixture, based on the first data and the second data; and generate data associating the sample mixture with a mixture identifier associated with the reference mixture, when the correlation measure satisfies a mapping condition.
14. An apparatus substantially as described herein with reference to, and as illustrated in, the accompany drawings.
15. A method substantially as described herein with reference to, and as illustrated in, the accompany drawings.