JP3876070B2 - Method for identifying analytical elements using surface analysis equipment - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an element identification method when a sample surface is analyzed using a surface analysis instrument such as an electronic probe microanalyzer.
[0002]
[Prior art]
In general, in the case of analyzing an element distribution on a sample surface using a surface analyzer such as an electron probe microanalyzer (EPMA), an Auger electron spectrometer (AES), or a photoelectron spectrometer (ESCA), an element identification process is as follows: The transition line energy table that lists element names, spectrum peak transition line names, energy values, and the like is used to compare the actually measured spectrum data with the energy table.
[0003]
[Problems to be solved by the invention]
However, many elements have a plurality of spectral peaks instead of a single spectral peak, and a plurality of elements may have the same spectral peak. For example, FIG. 6 is a diagram showing a part of the energy spectrum of Cu and P, but both Cu and P have the spectrum peak indicated by the energy value E ₁ . In this way, when there are multiple elements with the same spectral peak, when the spectral peak is detected in the measured spectral data, there may be multiple elements actually, but in reality, due to the overlap of spectral peaks Frequently, elements that do not exist are judged as identification elements. As a result, the accuracy of the element identification process is reduced. In FIG. 6, E ₂ is the energy value of the main line of Cu.
[0004]
Moreover, the energy axis of a spectrum often shifts for some reason during measurement, and if the energy axis of the spectrum shifts, accurate element identification becomes almost impossible.
[0005]
The present invention has been made to solve the above problems in the element identification method of elemental analysis of a sample surface using surface analysis instruments, such as a conventional electron probe microanalyzer, the deviation of the energy axis of spectrum It is an object of the present invention to provide an analysis element identification method using a surface analysis instrument which is corrected so that element identification processing can be performed with high accuracy.
[0006]
[Means for Solving the Problems]
In order to solve the above-mentioned problems, the invention according to claim 1 detects a spectrum peak based on spectrum data obtained from a sample analysis point in a method for identifying an element by analyzing a sample surface using a surface analysis instrument. And detecting the position of the spectrum peak having the maximum intensity among the detected spectrum peaks, and a predetermined multiple (k) of the half-value width of the spectrum peak centered on the energy position corresponding to the intensity of the spectrum peak having the maximum intensity. Element identification by comparing the measured spectrum data with the specific energy spectrum data having the main peak of the element selected by the coarse detection by pattern matching processing. And the identification element identified in the element identification step. And is characterized in that it comprises a step of correcting the deviation of the combined maximum peak position energy axis in the measured spectrum data to the maximum peak position in the energy table.
[0009]
In this way , by the comparison by the pattern matching process between the measured spectrum data and the specific energy spectrum data having the main peak in the element selected by the rough detection, the maximum peak position in the energy table corresponding to the identified element is obtained. Since the deviation of the spectral energy axis is corrected by matching the maximum peak position in the measured spectral data, even if the deviation of the energy axis of the measured spectral data occurs for some reason, the deviation of the spectral energy axis is accurate. It is corrected, and the element identification process can be performed with high accuracy.
[0010]
DETAILED DESCRIPTION OF THE INVENTION
Next, embodiments will be described. FIG. 1 is a diagram showing a schematic configuration of an electron probe microanalyzer to which an analysis element identification method using a surface analysis instrument according to the present invention is applied. In FIG. 1, an electron beam 2 generated from a filament 1 is irradiated onto the surface of a sample 4 placed on a sample stage 3 via a focusing lens and an objective lens (not shown), and the irradiation point of the electron beam 2 on the sample 4 is irradiated. The characteristic X-rays 5 generated in step 1 are dispersed by the spectroscopic element 6 and detected by the detector 7. In the signal processing system 8, various signal processing is performed on the detection signal output from the detector 7, and element identification processing is performed.
[0011]
Next, a first embodiment of the analytical element identification method according to the present invention performed in the signal processing system 8 of the electronic probe microanalyzer will be described with reference to the flowchart of FIG. First, the spectrum data detected by the detector and the measurement conditions are written in the spectrum file (step 11). Next, spectrum data is read out from the spectrum file, and signal processing such as smoothing and secondary differentiation is performed to detect a spectrum peak (step 12). Next, the detected spectral peaks are compared with the transition line energy table (list showing element names, transition line names, energy values, etc.) with a predetermined constant energy width at the energy value corresponding to the spectral peak position. The identification element corresponding to the detected spectrum peak is roughly detected. Next, in the above rough detection, when a plurality of elements are identified with respect to the detected spectrum peak, it is confirmed whether or not a main line (main peak line) of the plurality of elements is present in the detected spectrum data. Are selected as identification element candidates, and elements having no main line are excluded from identification element candidates (step 13).
[0012]
Next, normalization processing of the measured spectrum data is performed, and a fingerprint region database corresponding to the element of the identified element candidate selected in the processing of step 13 is input and compared with it (pattern matching processing by the fingerprint region). (Step 14). Fingerprint region data refers to spectrum data of a region in which each element has a waveform energy spectrum indicating characteristics unique to the element, and the waveform and the main peak are added to those features. FIG. 3 is a diagram showing an example of a spectral fingerprint region, and a normalized fingerprint region database is created for measurable reference elements.
[0013]
Comparison with the fingerprint area database is performed as follows. That is, as shown by the following equation (1), the difference between the peak positions of the two spectral data to be compared is added to obtain the square root, and the square root d is defined as the coincidence parameter between the spectra.
d = SQR [SUM (i = 0 to n) {P1 (i) -P2 (i)}] (1)
Here, P1 (i) is each peak position of the measured spectrum data, and P2 (i) is each peak position of the fingerprint region database.
[0014]
The element having the smallest value of the coincidence parameter d is set as an element to be identified. The other elements are regarded as elements determined by overlapping spectral peaks, excluded from the identified elements (step 15), and the element identification processing result is displayed (step 16). Thus, by performing comparison with the fingerprint region database (pattern matching processing using the fingerprint region), the element identification processing can be performed quickly with high accuracy.
[0015]
Next, a second embodiment of the present invention will be described. When elemental analysis of a sample surface is performed using a surface analysis instrument such as an electronic probe microanalyzer, the energy axis of the spectrum often shifts for some reason during measurement. When such a shift in the energy axis of the spectrum occurs, accurate element identification becomes almost impossible. In this embodiment, the pattern matching processing step by the fingerprint region used in the first embodiment is used to correct the axis deviation of the energy axis of the spectrum generated at the time of measurement, and the element identification processing is performed with high accuracy. It is something that can be done.
[0016]
Next, a second embodiment will be described with reference to the flowchart of FIG. First, as in the first embodiment, the spectrum data detected by the detector and the measurement conditions are written into the spectrum file (step 21). Next, spectrum data is read from the spectrum file, subjected to signal processing such as smoothing and second-order differentiation processing, and spectrum peaks are detected. Subsequently, the spectrum peak P having the maximum intensity is selected from the detected spectrum peaks, and the energy position corresponding to the intensity of the spectrum peak P is obtained. Next, the measurement spectrum data is normalized, and normalized spectrum data D is generated. Next, as shown in FIG. 5, an element having an energy main line that falls within the range of k times the half-value width of the maximum spectrum peak P is selected, and the identification element is roughly detected. This rough detection is performed by comparison with the transition line energy table (step 22). However, the value of k is a value corresponding to the predicted maximum deviation width of the energy axis of the measured spectrum data.
[0017]
Next, a fingerprint region database corresponding to the element selected by the process of step 22 is input, compared with the measured spectrum data that has been normalized, and the matching degree parameter d similar to that of the first embodiment. Ask for. The element having the smallest value of the coincidence parameter d is set as an element to be identified (step 23).
[0018]
Next, the deviation between the spectrum peak position of the identified element and the position of the maximum spectrum peak P in the measured spectrum data is interpreted as the axis deviation value of the energy axis, and the energy axis is corrected (step 24). After such correction of the energy axis, element identification at the next analysis point is performed using the same element identification processing method as in the prior art by comparison with the transition line energy table (step 25). Thereby, since the axial deviation of the energy axis of the spectrum is accurately corrected, even when the element identification process similar to the conventional one is performed, the element identification with higher accuracy than the conventional one can be performed.
[0019]
【The invention's effect】
As has been described based on the embodiments, the invention according to claim 1, in the case where the deviation of the energy axis of measurement spectral data occurs also accurately correct the axial deviation, precision Element identification can be performed.
[Brief description of the drawings]
FIG. 1 is a diagram showing a schematic configuration of an electron probe microanalyzer to which an analysis element identification method using a surface analysis instrument according to the present invention is applied.
FIG. 2 is a flowchart for explaining a first embodiment of the present invention;
FIG. 3 is a diagram illustrating an example of a fingerprint region of a spectrum.
FIG. 4 is a flowchart for explaining a second embodiment of the present invention;
FIG. 5 is a diagram showing an example of normalized measurement spectrum data.
FIG. 6 is a diagram showing an example of spectrum peak overlap.
[Explanation of symbols]
1 Filament 2 Electron Beam 3 Sample Stage 4 Sample 5 Characteristic X-ray 6 Spectroscopic Element 7 Detector 8 Signal Processing System

Claims (1)

  In the method of identifying the elements by analyzing the sample surface using a surface analyzer, the spectrum peak is detected based on the spectrum data obtained from the sample analysis point, and the position of the spectrum peak with the maximum intensity among the detected spectrum peaks Detecting the identified element in a range of a predetermined multiple (k times) of the half-value width of the spectrum peak centered on the energy position corresponding to the intensity of the spectrum peak of the maximum intensity, and A step of performing element identification by comparing the measured spectrum data and unique energy spectrum data having the main peak of the element selected by the rough detection by pattern matching processing, and identifying elements identified in the element identification step To the maximum peak position in the corresponding energy table Method for identifying analytical element by surface analysis instruments, characterized in that the combined maximum peak position in the serial measured spectrum data and a step of correcting the deviation of the energy axis.

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