JPH02248848A - X-ray analysis of two-element compound for microscopic part - Google Patents

Abstract

PURPOSE:To learn the number of compounds containing two elements and an element content ratio accurately based on the number and positions of information groups appearing in a correlation chart which is produced by converting the results in the measurement of characteristic X rays of two elements of two-element compounds into a brightness value of respective image information. CONSTITUTION:A microscopic range of a sample is scanned by an electron beam to determine an intensity of energy of characteristic X rays in terms of elements from a matrix detection point and the intensity of energy is stored into a memory corresponding to the detection point according to address. The results in the measurement of the intensity of energy are converted into a brightness value of image information to prepare a histogram of a brightness value for respective elements. When a correlation chart of image brightness values of characteristic X rays of Ca and Mg is generated, for example, on a matrix screen of a CRT, information groups G1, G2 and G3 appear at a location where a ratio is almost equal between image brightness values of two elements. Thus, three types, not two, of compounds of the Ca and Mg are found to exist from three in the number of groups and an element content ratio is learned accurately from position coordinates of the groups.

Description

DETAILED DESCRIPTION OF THE INVENTION <Industrial Application Field> The present invention relates to an innovative method for analyzing two-element compounds in microscopic X-ray analysis.

<Prior art> For example, electron microscopes and so-called E P MA (Electro
Microscopic X-ray analysis using a ronProbe In the field of micro X-ray analysis, in which each characteristic X-ray emitted from a specimen is measured and the sample is analyzed based on the measurement results of those characteristic X-rays, image processing technology has recently been applied to the analysis results by EPMA. Several attempts have been made to apply this, but so far, the image processing functions provided by them are
It is limited to simply imaging the results of peak separation, line analysis, and one-plane analysis performed in conventional EPMA analysis.

Therefore, in the image processing method for microscopic X-ray analysis according to the above-mentioned conventional technology, although the image processing technology is applied to the analysis results by EPMA, the types of elements constituting the sample and their concentrations (content ratios) are ) [element identification], which was the traditional EPMA analysis.

Therefore, as a result of intensive research, the present inventors applied a completely new image processing method to the analysis results by EPMA, thereby creating a new field of analysis that was previously impossible. Images used in microscopic X-ray analysis are the basis for not only analyzing the types and concentrations (content ratios) of substances (element identification), but also analyzing the types and distribution states of compounds that make up the sample (substance identification). Processing method (which is prior art to the present invention)
As a result, we have developed the
A date has already been proposed through a patent application.

In other words, the image processing method in micro X-ray analysis according to the prior art is as follows: scanning and irradiating an electron beam within a minute predetermined range of a sample, and thereby detecting a matrix of detection points within the predetermined range. A memory corresponding to a matrix-shaped detection point area within a predetermined range of the sample in microscopic X-ray analysis in which each emitted characteristic X-ray is measured and the sample is analyzed based on the measurement results of the characteristic X-rays. Each measurement result of the characteristic X-rays is stored by address in a memory having areas and addresses, and each measurement result of the characteristic X-rays stored in the memory is converted into a brightness value of image information, and then the image is stored. A brightness value histogram is created, each peak in the image brightness value histogram of the characteristic X-rays is multivalued so that the base portions of adjacent peaks do not interfere with each other, and each peak in the image brightness value histogram of the characteristic X-rays is An image processing means that displays only the multivalued part in mutually different colors or symbols on a matrix screen having the number of pixels and addresses corresponding to the matrix-like detection point areas within a predetermined range of the sample. It is.

Figures 5 and 6 show dolomite ore as a sample.
A specific example of the analysis results using the image processing method in the above-mentioned microscopic X-ray analysis is shown. Note that the dolomite ore sample is composed of three types of compounds, namely, kukaite (C
a Mg (C0sL).

Houkaite (CaCO3), limestone (CaCO.

・M　g　COs　).

First, as in the conventional method, an electron microscope and EPMA are used to scan and irradiate an electron beam within a small predetermined range of the sample, and each of the matrix-shaped detection point areas within the predetermined range of the sample is The energy intensity of characteristic X-rays (X-rays unique to each element) emitted from each detection point is measured.

Next, the energy intensity measurement results of the characteristic X-rays for each element obtained by the EPMA are measured in a matrix detection point area (for example,
Memory area (65536 pixels) corresponding to
(memory) and addresses in a memory that has addresses.

Here, if the energy intensity measurement results of the characteristic xvA stored in each memory are analyzed according to the same method as before, the types of elements contained in the sample (in this example,
a, Mg, C, O) and concentration (content ratio), respectively, and the elements of the sample can be identified.

Furthermore, after converting the energy intensity measurement results of the characteristic X-rays stored in each of the memories into image information brightness values (image density values) (for example, normalizing them to 0 to 255), Its image brightness value histogram (
The relationship between the image brightness value and the count number of pixels with the same image brightness value is created. Figure 5 is an example of the image brightness value histogram, which shows the characteristic X-rays of Ca, which was selected as an element contained in all three types of compounds constituting the sample (dolomite ore). The image brightness value histogram H is shown, and there are three peaks A corresponding to those three types of compounds.

It can be seen that it has B and C.

Here, each peak A in the image brightness value histogram H of characteristic X-rays of Ca obtained as described above.

The data in all areas B and C (65536 image brightness value data) are divided into the number of pixels (256 x 25
If we simply display the brightness as it is on one matrix screen with 6 pixels) and addresses, the image brightness of all the pixels on that screen will only change in a continuous two-dimensional (analog) manner. , the boundaries of each of the peaks A, B, and C cannot be determined.

Therefore, as shown in FIG. 5, the peaks A, B, and C in the image brightness value histogram H of the Ca characteristic
) is multivalued (divided into a, b, and c parts) so that the base parts of peaks A, B, and C do not interfere with each other, and the multivalued parts of each peak A, B, and C (a.

b, c), as shown in FIG. 6, a single matrix screen P (for example, a CRT ), each of the peaks A is displayed (mapped) with a different color (for example, red, blue, yellow) or symbol (for example, O1×, Δ).

The regions occupied by B and C and their respective boundaries, that is, the phases of the three types of compounds constituting the sample (dolomite ore) can be clearly distinguished and captured.

In this way, according to the image processing method in microscopic X-ray analysis, an image brightness value histogram of characteristic X-rays of elements constituting the sample is created, and each peak in the image brightness value histogram is divided into adjacent peaks. The bases of the peaks are multivalued so that they do not interfere with each other, and only the multivalued parts of each peak in the image brightness value histogram are
By adopting a unique image processing means that displays different colors or symbols on a matrix screen having the number of pixels and addresses corresponding to the matrix detection point areas within a predetermined range of the sample, each of the above It is now possible to clearly distinguish and capture the regions occupied by each peak and each boundary, that is, the phase (distribution state) of the compounds that make up the sample, allowing new analysis that was previously impossible. In other words, it has great potential for analyzing not only the types and concentrations (content ratios) of elements that make up a sample (element identification), but also the types and distribution states of compounds that make up a sample (substance identification). It has now been opened.

<Problems to be solved by the invention> However, even in the prior art (image processing method in microscopic X-ray analysis) which is expected to have very excellent advantages as described above, the following problems still remain. .

In other words, when using the image processing method in micro X-ray analysis according to the prior art, (a) Although it is possible to analyze the number and distribution state of compounds that make up the sample, The only information that can be obtained through analysis is that the compound contains one selected element; it is not possible to determine what other types of elements the compound contains. Not only is there a fundamental limit that it is impossible to There is no problem because the number of peaks A, B, and C in the value histogram H (3) is the same as the number of compounds (3) that make up the sample (Kukaite, Houkaite 1 Limestone). ,always,
In this way, the number of peaks in the image brightness value histogram of characteristic X-rays of one selected element does not necessarily match the number of compounds constituting the sample. In a brightness value histogram, even if the peak appears to be one, it may actually be made up of multiple overlapping peaks.
In such a case, there is a problem that multiple compounds may be mistakenly regarded as one compound, making it impossible to perform correct analysis.

The present invention was made as a result of further research in view of the above circumstances, and its main purpose is to increase the number of compounds constituting the sample by focusing on the two elements contained in the sample. We need to develop an analysis method for two-element compounds using microscopic X-ray analysis that can easily and accurately analyze compounds and obtain more detailed information about these compounds (identifying two types of contained elements). It's about doing.

<Means for Solving the Problems> In order to achieve the above object, the present invention scans and irradiates an electron beam within a minute predetermined range on a sample, and accordingly creates a matrix of detection points within the predetermined range. Measure the characteristic X-rays related to the two elements respectively emitted from the N region, and store the characteristic The measurement results of characteristic X-rays are stored for each address, and the measurement results of characteristic X-rays of both elements stored in both memories are converted into brightness values of image information, and then the image brightness of both elements is converted. Create a value correlation diagram, and based on the number and each position of data groups appearing in the image brightness value correlation diagram of both elements,
The present invention provides a method for analyzing two-element compounds in microscopic X-ray analysis, which employs a unique method of determining the number of compounds containing both of the above-mentioned elements and the content ratio of both elements in each compound.

<Effects> The effects achieved by employing such distinctive means are as follows.

That is, in the method for analyzing two-element compounds in microscopic X-ray analysis according to the present invention, the microscopic region X according to the prior art is
Rather than focusing on only one element contained in a sample, as is the case with image processing methods in radiation analysis, two elements are selected and the measurement results of characteristic X-rays of both elements are used as image information. After converting to brightness values, an image brightness value correlation diagram of both elements is created, and based on the number of data groups appearing in the image brightness value correlation diagram and each position, the number of compounds containing both elements and the number of compounds in each compound are calculated. By determining the content ratio of both elements, even if the peaks in the image brightness value histograms for each element slightly overlap, as will become clearer from the description of the examples described later, However, it is important to accurately analyze the number of compounds that make up the sample without making any mistakes.
It is very easy to determine the content ratio of these compounds, and moreover, it is possible to obtain more detailed and reliable information regarding the presence of the two types of elements mentioned above in a single analytical operation. Now you can get it.

<Example> Hereinafter, as a specific example of the image processing method in microscopic X-ray analysis according to the present invention, analysis results using a stone as a sample will be described.

First, as in the conventional method, an electron microscope and EPMA are used to scan and irradiate an electron beam within a minute predetermined range of the sample, and as a result, a matrix-like detection point area within the predetermined range of the sample is scanned. The energy intensity of characteristic X-rays (X-rays unique to each element) emitted from each detection point is measured.

Next, the energy intensity measurement results of the characteristic X-rays for each element obtained by the EPMA are measured in a matrix detection point area (for example,
Memory area (65536 pixels) corresponding to
(memory) and addresses by address in the memory where they exist.

Here, if we analyze the energy intensity measurement results of characteristic
, Mg, etc.) and concentration (content ratio), respectively, and the elemental identification of the sample can be performed.

Furthermore, the energy intensity measurement results of the characteristic X-rays stored in each of the memories are converted into brightness values (image density values) of image information (for example, normalized to 0 to 255), and then each element is An image brightness value histogram (relationship between the image brightness value and the count number of pixels having the same image brightness value) is created for each image brightness value. Figures 1 and 2 are
An example of the image brightness value histogram, which shows the image brightness of characteristic X-rays of the first element (Ca) and second element (Mg) selected from among the elements contained in the sample (Kumaite). Value histograms H1 and H2 are shown, respectively.

Among these, the image brightness value histogram H1 of the characteristic X-ray of Ca shown in FIG. 1 has two peaks Al and Bl in this example, and the image brightness value of the characteristic X-ray of Mg shown in FIG. The value histogram H2 also has two peaks A2 in this example.
．． It can be seen that it has B2.

As far as we can see from the image brightness 414 histograms H1 and H2 of both of these characteristic X-rays, this sample (Kumaite) has Ca
It is presumed that it is composed of two types of compounds containing Mg and Mg.

However, as shown in FIG. 3, a diagram showing the correlation between the image brightness values of the characteristic X-rays of Ca and the image brightness values of the characteristic X-rays of Mg is
56x256 pixels), the above estimation turns out to be incorrect.

That is, in the image brightness value correlation diagram shown in FIG. 3, the horizontal axis (X axis) is the image brightness value (0 to 255
), the vertical axis (y-axis) is the image brightness value of characteristic X-rays of Mg (0 to
255), and each point shown on this X-7 screen indicates the number of data for which the combination of (image brightness value of Ca, image brightness value of Mg) is the same, and the brightness of image information (image density:
For example, 256 tones from 0 to 255! 11).

For example, the number of data satisfying x=20 and y=40 is counted with reference to the original data, and the number is calculated as (x
, y) = (20, 40) are displayed with a brightness corresponding to the number of pixels. In this example, the operations described above are performed using X.

If one point is performed for each y in units of 256, the number of operations is 256'' = 65536.

Now, as is clear from the image brightness value correlation diagram above,
In this example, it can be seen that data groups (three data groups Gl, G2°G3 in this example) are formed at locations where the ratio of the image brightness values of the two elements Ca and Mg is approximately equal. Therefore, from this, that is, from the number (3) of the data group CI, G2,03 appearing in the image brightness value correlation diagram, the essential compound containing Ca and Mg is determined from the first
It can be seen from the figure and FIG. 2 that there are actually three types, not two as estimated. In addition, each data group C1, G2. From the position of G3 (X coordinate, y coordinate), the content -' ratio of Ca and Mg in each compound can also be read.

By the way, in the image brightness value histogram H1 of characteristic X-rays of Ca shown in FIG. 1, there are two data groups Gl.
, G2 as one peak A1, and in the Mg characteristic X-ray image brightness value histogram H2 shown in FIG. 2, two data groups G2. G3 is one peak B
2 can be understood from the image brightness value correlation diagram.

Furthermore, as shown by square window marks a'b',c' in FIG. 3, each data group Gl, G2 . A representative part of G3 is extracted (that is, multivalued), and these data groups Gl.

G2. The data corresponding to the multivalued parts a', b', and c' of G3 are extracted from the energy intensity measurement results of the characteristic X-rays stored in the Ca or Mg memory, and are converted into image brightness values. Although not shown here, the number of pixels (256 x 256 pixels) corresponding to the matrix detection point area within a predetermined range of the sample is converted into (image density value) (for example, normalized to 0 to 255). and addresses on one matrix screen (e.g. CRT) with different colors (e.g. red, blue, yellow) or symbols (e.g. O2
, Δ), the areas occupied by the three types of compounds constituting the sample (limit stone) and their respective boundaries, in other words, the three types of compounds constituting the sample (limit stone) can be displayed (mapped) as shown in FIG. 6 above. It is possible to clearly distinguish and capture the phases of different types of compounds, and therefore it is also possible to read the content ratios of these three types of compounds. Note that each data group G1. G2. G3 multilevel part (ab', c')
If the method of selecting is too narrow, there will be too many background parts on the matrix screen, and the boundaries of each area will become unclear. Therefore, these multivalued parts (a', b'c+) Each data group Gl, G2. G
It is desirable to set the value as wide as possible within a range that does not deviate from 3.

By the way, in the above embodiment, when creating the image brightness value correlation diagram, the image brightness value of the characteristic X-ray of the first element and the image brightness value of the characteristic X-ray of the second element are plotted on the horizontal axis (X axis).
and on the vertical axis (y axis), on this x-7 screen, (the first
We have shown an example of a so-called brightness display method in which the number of data with the same combination of image brightness values of an element and image brightness values of a second element is expressed by the brightness of image information. As shown in , the image brightness value of the characteristic X-ray of the first element and the image brightness value of the characteristic X-ray of the second element are plotted on the horizontal axis (X-axis) and the vertical axis (y-axis). A so-called three-dimensional coordinate system may be adopted in which the number of data having the same combination of image brightness values of an element and image brightness values of a second element is taken on the vertical axis (two axes).

In addition, in the above embodiment, an electron microscope and an EPMA
We have shown an example in which the energy intensity of characteristic X-rays of each element measured by Convert the energy intensity of the line to weight concentration (or atomic %) and then convert it to a brightness value (image density value) of image information (for example, normalize to 0 ~ 100)
You may also do so.

<Effects of the Invention> As is clear from the detailed description above, according to the method for analyzing two-element compounds in microscopic XNIA analysis according to the present invention, in particular, unlike in the case of the prior art, Rather than focusing on only one element, we select two elements, convert the characteristic X-ray measurement results of both elements into image information brightness values, and then create an image brightness value correlation diagram for both elements. By calculating the number of compounds containing both elements and the content ratio of both elements in each compound based on the number of data groups appearing in the image brightness value correlation diagram and each position, even if each element Even in cases where peaks slightly overlap in the image brightness value histogram, the number of compounds making up the sample and their content ratios can be analyzed very easily and accurately. Furthermore, it is now possible to obtain more detailed and reliable information regarding the presence of the two types of elements mentioned above in a single analytical operation, and this makes it possible to obtain more detailed and reliable information regarding the presence of these two types of elements in a single analytical operation. This has the excellent effect of solving problems (a) and (b).

[Brief explanation of drawings]

Figures 1 to 4 are for explaining a specific example of the method for analyzing two-element compounds in microscopic X-ray analysis according to the present invention. The image brightness value histogram of the characteristic X-ray of Ca in the case of the same <Fig. 2 is the image brightness value histogram of the characteristic X-ray of Mg, and the third figure
The figure shows a (Ca-Mg) image brightness value correlation diagram expressed using a brightness display method, and FIG. 4 shows a (Ca-Mg) image brightness value correlation diagram expressed using a three-dimensional coordinate system. Further, FIGS. 5 and 6 are for explaining the technical background of the present invention and problems in the prior art, and FIG. 5 shows image processing in minute X-ray analysis according to the prior art. In the method, a brightness histogram of characteristic X-rays of Ca and its multi-value method are shown when dolomite ore is used as a sample, and Fig. 6 is a schematic illustration of a matrix screen displaying the distribution state of Ca. It shows.

Claims (1)

[Claims] Scanning and irradiating an electron beam within a minute predetermined range of a sample, and measuring characteristic X-rays related to two elements emitted from matrix-like detection point regions within the predetermined range. and storing the measurement results of characteristic X-rays regarding the two elements in two memories each having a memory area and an address corresponding to a matrix-like detection point area within a predetermined range of the sample, each address separately; After converting the characteristic X-ray measurement results of both elements stored in both memories into brightness values of image information, an image brightness value correlation diagram of both elements is created, and an image brightness value correlation diagram of both elements is created. Based on the number of data groups appearing in and each position,
A method for analyzing two-element compounds in micro X-ray analysis, characterized in that the number of compounds containing both of the elements and the content ratio of both elements in each compound are determined.