JP6601514B2 - Method for evaluating particle size distribution of precipitate and method for producing steel sheet - Google Patents

Description

  The present invention relates to a method for evaluating the particle size distribution of precipitates present in a metal material, and particularly to a method capable of evaluating the particle size distribution of fine precipitates having a particle size of 1 μm or less with high accuracy. Moreover, this invention relates to the manufacturing method of the steel plate using the evaluation method of the said particle size distribution.

  It is known that the structure and characteristics of a metal material are greatly affected by precipitates contained in the metal material. Therefore, controlling the structure of various metal materials using precipitates and improving properties such as strength are performed on an industrial scale. In particular, in the field of steel materials, research and development aiming at further higher quality and higher functionality by controlling the state of precipitates are actively conducted.

  In the research and development as described above, it is important to accurately grasp the state of the precipitate, and for that purpose, methods for measuring the particle size distribution of the precipitate with high accuracy have been studied.

  For example, Patent Document 1 proposes a method of evaluating inclusions and precipitate particles present in a metal material using an electron microscope. In the method, particles extracted by electrolyzing a metal material in an electrolytic solution are once dispersed and held in an organic solvent, and a sample whose number density is increased by dropping and drying it on a support film is obtained. Observe under a microscope.

  Patent Document 2 proposes a method for evaluating the particle size distribution of inclusions and precipitates in steel by a sequential classification method of a slurry using a field flow fractionation (FFF) method. According to the above method, since many electrolytically extracted particles are targeted for measurement, the particle size distribution can be evaluated accurately and quickly.

JP 2004-317203 A Japanese Patent No. 4572001

  However, the method described in Patent Document 1 has a problem that fine precipitate particles tend to aggregate while the extracted particles are dispersed and held in the solution. Since the cohesive force increases as the particle size decreases, it is difficult to avoid agglomeration of fine precipitates of 0.1 μm or less even if the dispersion medium is devised, and an accurate particle size distribution cannot be measured.

  The method described in Patent Document 2 also has the same problem as Patent Document 1 because the precipitate particles need to be dispersed and held in the solution. A further important problem is that this method directly determines the scattering intensity distribution, not the number distribution. In a dispersion system with a uniform particle size, the number distribution matches the scattering intensity distribution relatively well, but in a dispersion system in which particles of various particle sizes exist, the scattering intensity due to the large particle size The scattering intensity distribution does not reflect an accurate particle size distribution because it is emphasized against the scattering intensity by small particles.

  As described above, the conventional methods as described in Patent Documents 1 and 2 cannot determine the particle size distribution of fine precipitates having a particle size of 1 μm or less with sufficient accuracy.

  This invention is made | formed in view of the said situation, and provides the particle size distribution evaluation method of the precipitate which can evaluate the particle size distribution of the fine precipitate whose particle size is 1 micrometer or less with high precision. For the purpose. Furthermore, it aims at providing the manufacturing method of a steel plate using the said evaluation method.

  As a result of intensive studies to solve the above-described problems, the present inventors have extracted precipitates existing in a metal material by an extraction replica method (a one-stage replica method) or a two-stage replica method, and performed scanning transmission using an electron microscope. By observing under an acceleration voltage of 40 kV or less using an electron (Scanning Transmission Electron Microscope, STEM) image, it is possible to clearly identify even fine precipitates having a particle diameter of 1 μm or less. It was found that an accurate particle size distribution can be evaluated.

That is, the gist configuration of the present invention is as follows.
1. A method for evaluating the particle size distribution of precipitates having a particle size of 1 μm or less present in a metal material,
A polishing step of polishing the surface of the metal material;
An etching step of etching the surface of the metal material;
A replica sample preparation step of extracting a precipitate present on the surface of the metal material after the etching into a replica film formed by depositing a conductive substance to form a replica sample;
An observation step of observing the replica sample using an electron microscope under an acceleration voltage of 40 kV or less to obtain a scanning transmission electron image;
Analyzing the scanning transmission electron image based on a contrast level, a particle analysis step for discriminating particles to be evaluated,
A particle size distribution acquisition step for acquiring a particle size distribution of the particles to be evaluated in the particle analysis step
A method for evaluating the particle size distribution of precipitates.

2. 2. The particle size distribution evaluation method for precipitates according to 1 above, wherein, in the particle analysis step, particles to be evaluated are determined based on at least one of a particle size and an aspect ratio of the particles in the scanning transmission electron image.

3. further,
After the particle analysis step, a characteristic X-ray spectrum acquisition step of acquiring a characteristic X-ray spectrum generated by irradiating each of the particles to be evaluated with an electron beam;
A spectral analysis step of analyzing the characteristic X-ray spectrum;
The particle size distribution evaluation method of the deposit according to 1 or 2 above.

4). 4. The precipitation according to 3 above, wherein, in the spectrum analysis step, it is determined whether or not each particle is a precipitate based on the characteristic X-ray spectrum, and the particles determined not to be a precipitate are excluded from the evaluation target. Evaluation method of particle size distribution.

5). In the spectral analysis step, the particles are classified into a plurality of groups based on the characteristic X-ray spectrum,
5. The particle size distribution evaluation method for precipitates according to 3 or 4 above, wherein in the particle size distribution acquisition step, a particle size distribution is acquired for each group.

6). further,
Prior to the observation step, there is a preliminary irradiation step of irradiating the measurement region of the replica sample with a defocused electron beam for 600 seconds or more, and the particle size distribution evaluation method for precipitates according to any one of the above 1 to 5 .

7). The method for evaluating the particle size distribution of precipitates according to any one of 1 to 6 above, wherein the metal material is a steel material.

8). Using the particle size distribution evaluation method for precipitates according to any one of 1 to 7 above, the particle size distribution of precipitates in a steel plate during production is evaluated, and the steel plate is manufactured based on the obtained particle size distribution. The manufacturing method of the steel plate which determines the manufacturing conditions of the at least 1 process after the next process in.

9. Using the precipitate particle size distribution evaluation method according to any one of 1 to 7 above, the particle size distribution of the precipitate in the steel plate during production is evaluated, and based on the obtained particle size distribution, after the steel plate. A method for manufacturing a steel sheet, which determines manufacturing conditions for manufacturing the steel sheet.

10. Using the precipitate particle size distribution evaluation method according to any one of 1 to 7 above, the particle size distribution of the precipitate in the steel sheet in the process of production is evaluated, and the subsequent steps are manufactured based on the obtained particle size distribution. The manufacturing method of the steel plate which determines whether it performs.

  According to the present invention, the particle size distribution of fine precipitates having a particle size of 1 μm or less can be evaluated with high accuracy. Moreover, according to this invention, while using the said particle size distribution evaluation method in manufacture of a steel plate, while improving a yield, manufacturing cost can be reduced.

It is a flowchart which shows the process in 1st embodiment of this invention. It is the transmission electron image obtained by observing the deposit of a replica sample at the acceleration voltage of 30 kV. It is the transmission electron image obtained by observing the deposit of a replica sample at the acceleration voltage of 200 kV. It is a flowchart which shows the process in 2nd embodiment of this invention. It is a figure which shows an example of the characteristic X-ray spectrum of a deposit. 3 is a graph showing the particle size distribution obtained in Example 1 and Comparative Example 1. 10 is a graph showing measurement results in Comparative Example 2. 3 is a graph showing the particle size distribution obtained in Example 2. 6 is a graph showing the particle size distribution obtained in Example 6. 6 is a graph showing the particle size distribution obtained in Example 7.

  Next, a method for carrying out the present invention will be specifically described. In addition, the following description shows the suitable embodiment of this invention, and this invention is not limited at all by the following description.

(Evaluation method of particle size distribution of precipitates)
First, a method for evaluating the particle size distribution of precipitates according to an embodiment of the present invention will be described.

(First embodiment)
FIG. 1 is a flowchart showing processing in the first embodiment of the present invention. As shown in FIG. 1, the precipitate particle size distribution evaluation method according to an embodiment of the present invention includes the following steps as essential steps.
(1) Polishing step (2) Etching step (3) Replica sample preparation step (4) Observation step (5) Particle analysis step (6) Particle size distribution acquisition step

[Metal material]
As the metal material to be measured in the present invention, any metal material can be used as long as it is a metal material containing precipitates. Among these, from the viewpoint of industrial usefulness of information obtained by the evaluation method of the present invention, it is effective to apply to steel materials such as steel plates, and in particular, to be applied to thin steel plates, electromagnetic steel plates and the like. It is valid.

  In order to extract the precipitate in the metal material by the extraction replica method, it is necessary to make the precipitate float on the surface of the metal material in advance. Therefore, it is necessary to polish and then etch the surface of the metal material.

(1) Polishing Step The polishing method used in the polishing step is not particularly limited, and any method such as mechanical polishing can be used. Usually, polishing may be performed by a method according to the material, characteristics, etc. of the metal material according to a conventional method. In the polishing step, the surface of the metal material is preferably mirror-polished.

(2) Etching Step In the etching step, the deposit is exposed on the sample surface by etching the surface of the metal material. That is, only the base material (matrix) of the metal material is selectively corroded, and only the precipitates are lifted on the surface of the base material.

  As an etching method, any method such as chemical etching or electrolytic etching can be used. Various conditions in the etching process (such as an etching solution, an etching condition, an electrolytic solution, and an electrolytic condition) may be appropriately selected according to the metal material to be used.

  For example, when the metal material is a steel material, it is preferable to perform electrolytic etching by performing constant potential electrolysis in an electrolytic solution. Examples of the electrolyte include an alcohol solution containing 10% by mass acetylacetone (10% acetylacetone-1% tetramethylammonium chloride-methyl alcohol; 10% AA electrolyte), and perchloric acid-methanol-2-n. -Butoxyethanol electrolyte (A3 electrolyte) can be used.

In order to accurately evaluate the particle size distribution of the precipitate, it is desirable to measure the particle size of a certain number of precipitates. Specifically, as described later, 10 ³ or more precipitates are measured. It is preferable to measure the particle size. Therefore, it is desirable to perform etching so that a sufficient number of precipitate particles are extracted from the replica sample. On the other hand, if etching is performed excessively, the precipitates are extracted in an overlapped state, so that it is difficult to accurately evaluate the particle size of the individual precipitate particles. In consideration of the above points, it is preferable to determine a suitable etching amount. In the case of chemical etching, the etching amount can be adjusted by the composition of the etching solution and the etching time, and in the case of electrolytic etching, the amount of etching can be adjusted by the composition of the electrolytic solution and the energization amount (coulomb amount).

(3) Replica Sample Preparation Step Next, the precipitate particles that are exposed on the surface of the metal material by the etching are extracted into a replica sample formed by depositing a conductive material. The preparation of the replica sample may be performed according to a conventional method, and the method is not particularly limited, and can be performed by, for example, a one-step replica method or a two-step replica method.

-One-step replica method When replica samples are prepared by the one-step replica method, first, a conductive material is vapor-deposited on the surface of the metal material after the etching step, and then immersed in a corrosive solution to form the vapor-deposited film into a metal. Peel from material. In the replica sample thus obtained, precipitates are held on the surface on the side in contact with the metal material.

  The replica sample production by the one-step replica method can be performed, for example, as follows. First, a conductive substance is deposited on the surface of the metal material after the etching process. Next, an approximately 3 mm square grid cut is made in the deposited film using a cutter knife or the like, and the deposited film is extracted from the surface of the metal material by dipping in a corrosive solution such as hydrochloric acid + methanol solution. Remove. The peeled-deposited film is spread on a transmission electron microscope observation mesh and dried.

-Two-stage replica method When replica samples are prepared by the two-stage replica method, first, an organic film made of acetylcellulose or the like is fused to the surface of the metal material after the etching step, and then the organic film is peeled off. Thus, the precipitate particles are extracted on the surface of the organic coating. Next, a conductive substance is vapor-deposited on the surface of the organic film on which the precipitate is held, and then the organic film is dissolved and removed with an organic solvent. As a result, a replica sample in a state where precipitates are extracted from the deposited film of the conductive material is obtained.

  In either case of using the one-step replica method or the two-step replica method, any conductive material can be used. Examples of the conductive substance include metals such as aluminum, titanium, and nickel, and carbon. Among these, carbon is preferably used. Carbon is easy to transmit an electron beam and has a small X-ray absorption coefficient. Therefore, if carbon is used as the conductive material, the contrast difference in the scanning transmission electron image (STEM image) is increased, and the precipitate particles can be easily extracted (discriminated) in the particle analysis step described later. Moreover, when acquiring a characteristic X-ray spectrum so that it may mention later, it is easy to obtain the characteristic X-ray from a precipitate.

  A commercially available mesh can be used as the mesh for holding the replica sample. The mesh material is preferably different from the elements contained in the precipitate.

(4) Observation Step Next, the surface of the replica sample obtained in the replica sample preparation step is observed using an electron microscope to obtain a STEM image. In the present invention, in the above observation, it is important to use a scanning transmission electron microscope (STEM) as the electron microscope and to set the acceleration voltage to 40 kV or less.

Acceleration voltage: 40 kV or less FIG. 2 is an example of a STEM image obtained by observing a precipitate of a replica sample at an acceleration voltage of 30 kV using an electron microscope. As shown by the arrows in the figure, even a very fine precipitate having a particle size of about 5 nm can be clearly identified by using the STEM image and setting the acceleration voltage to 40 kV or less.

  On the other hand, FIG. 3 is an example of a transmission electron image obtained by observing the precipitate of the replica sample at an acceleration voltage of 200 kV. In this way, when the acceleration voltage exceeds 40 kV, electrons pass through the precipitate, so that the contrast difference of the image is remarkably reduced. As a result, it is difficult to discriminate fine particles and evaluate the particle size, such as precipitates having a particle size of 1 μm or less, which is the subject of the present invention. Therefore, in the present invention, the acceleration voltage is set to 40 kV or less. The acceleration voltage is more preferably 35 kV or less. On the other hand, the lower limit of the acceleration voltage is not particularly limited, and can be an arbitrary value as long as the acceleration voltage can pass through the precipitate. However, if the acceleration voltage is too low, the resolution of the STEM image is lowered, and sufficient measurement accuracy may not be obtained. Therefore, the acceleration voltage is preferably 20 kV or more, and more preferably 25 kV or more.

As described above, in order to evaluate the particle size distribution of the precipitates accurately, it is desirable to increase the number of particles to measure the particle diameter, according to the study of the present inventors, 10 ³ or more It is preferable to use particles as a measurement target.

Further, from the viewpoint of investigating the relationship between the material of the metal material and the precipitates in the steel, it is preferable to set not only the number of measurement particles but also the measurement region to some extent. For example, in order to examine the relationship between the grain growth property and the precipitate, it is desirable to observe an area of 1 × 10 ³ μm ² or more, more preferably 5 × 10 ³ μm ² or more with an electron microscope.

  The electron microscope is not particularly limited, and any device can be used. For example, a scanning transmission electron microscope equipped with a detector (semiconductor detector, scintillator, etc.) for acquiring transmission electrons in a normal scanning electron microscope can be used. Furthermore, it is preferable that the scanning transmission electron microscope has a mechanism that can scan the sample stage with a pulse motor or the like as necessary when moving the visual field.

  As the STEM image, either a bright-field image or a dark-field image can be used, but a contrast due to elements other than precipitates such as crystal grain boundaries and irregularities appears in the dark-field image compared to the bright-field image. Since it is difficult, it is preferable to use a dark field image.

(5) Particle Analysis Step Next, the STEM image obtained in the observation step is analyzed to determine the particles to be evaluated. The analysis can be performed based on the contrast level of the scanning transmission electron image, similarly to the analysis of a general electron microscope image. For example, the acquired STEM image can be analyzed by binarization processing based on the contrast. The threshold value in the binarization process may be set so that, for example, a representative visual field is selected and the shape of the precipitate particles in the visual field can be accurately extracted. In the replica sample, the contrast difference between the precipitate and the support film (deposited film of the conductive material) is relatively large and is not easily affected by fluctuations in the primary electron beam. Just keep it.

  The particulate region included in the STEM image analyzed as described above is considered to be a precipitate. Therefore, the size of each particulate region, that is, the size of the precipitate particles is evaluated next. Examples of the size include a ferret diameter and a circle-equivalent diameter, and it is preferable to determine one or both of these. Here, the ferret diameter refers to the length of one side of a rectangle circumscribing the particles in the STEM image. As the ferret diameter, it is preferable to obtain at least one of a minimum ferret diameter, a maximum ferret diameter, and an average ferret diameter (an average value of the minimum ferret diameter and the maximum ferret diameter) for each particle. Moreover, when performing the characteristic X-ray analysis of the precipitate as described later, it is preferable to obtain the position (for example, the position of the center of gravity of each particulate region) at which the analysis is performed.

  The particulate region analyzed as described above is set as an evaluation target in the next particle size distribution evaluation step. At this time, all the particulate regions included in the STEM image can be evaluated, but as described below, the particles to be evaluated are selected based on one or both of the particle size and the aspect ratio. You can also.

  That is, as described above, it is possible to discriminate the precipitate by analyzing the STEM image based on the contrast, but depending on the conditions, a non-precipitate or noise or the like is present in the image with the same degree of contrast as the precipitate. May be observed. For example, on the surface of the metal material after etching, there are crystal grain boundaries, surface irregularities, polishing wrinkles, and the like in addition to precipitates, which may be transferred to a replica sample. Since these are observed as contrasts in the STEM image, they cannot be removed by the binarization process and become noise.

  Therefore, the accuracy of the particle size distribution can be further improved by excluding the particulate region that is not considered to be a precipitate from the evaluation target based on the particle size and the aspect ratio. As will be described later, when evaluating the characteristic X-ray spectrum of each particle, it can be determined whether or not the particle is a precipitate based on the characteristic X-ray spectrum. In this case, the time required for measurement of the characteristic X-ray spectrum increases, and the measurement efficiency decreases. Therefore, by selecting the particles to be evaluated based on the particle diameter and aspect ratio in advance, the time required for evaluating the characteristic X-ray spectrum can be shortened.

[Sorting based on particle size]
When performing selection based on the particle size, among the particulate regions included in the STEM image, those having a particle size satisfying a predetermined condition are set as evaluation targets, and other regions are excluded from the evaluation targets. For example, out of the particulate regions in the STEM image, those having a particle size (for example, an average ferret diameter) equal to or larger than a predetermined threshold may be set as an evaluation target. The threshold is determined according to the material to be evaluated.

[Selection based on aspect ratio]
When sorting based on the aspect ratio is performed, the particulate regions included in the STEM image are set as evaluation targets when the aspect ratio satisfies a predetermined condition, and other regions are excluded from the evaluation targets. Specifically, it is preferable that an evaluation target is a particulate region in the STEM image whose aspect ratio is equal to or less than a predetermined threshold value. Since the threshold value depends on the properties of the metal material, the shape of the precipitates, and the like, it is necessary to appropriately set the threshold value based on the actual STEM image. For example, when most of the precipitates have a nearly spherical shape (when the aspect ratio is close to 1), by setting the threshold within a range of about 2 to 6, most of the precipitates can be distinguished from noise. Is possible. On the other hand, when it is necessary to detect precipitates close to a plate shape or an elliptical shape, the threshold value is set within a range of about 8-12. As the aspect ratio, a value of (maximum ferret diameter / minimum ferret diameter) can be used.

  In addition, when the support film supporting the precipitate of the replica sample is smooth and has little dust, dirt, etc., and the particulate region observed in the STEM image can be determined to be almost a precipitate, all of the particles included in the STEM image Particulate regions can be evaluated.

(6) Particle size distribution acquisition process Finally, a particle size distribution is calculated | required based on the measured size about the particle | grains made into evaluation object in the said particle | grain analysis process. For example, the size of each particle (for example, the average ferret diameter) is ranked, and the number of particles and the existing fraction for each rank are calculated.

(Second embodiment)
FIG. 4 is a flowchart showing processing in the second embodiment of the present invention. In the present embodiment, the following steps are performed in addition to the steps of the first embodiment described above.
(A) Pre-irradiation step (b) Characteristic X-ray spectrum acquisition step (c) Spectrum analysis step FIG. 4 shows the case where the above steps (a) to (c) are performed. It is also possible to perform only the preliminary irradiation step and not perform the (b) characteristic X-ray spectrum acquisition step and (c) the spectrum analysis step. Conversely, (a) the preliminary irradiation step is not performed, and (b) a characteristic X-ray spectrum acquisition step and (c) a spectrum analysis step can be performed. Hereinafter, each step will be described.

(A) Pre-irradiation process When observation is performed with an electron microscope, contamination of the sample (contamination) may occur when hydrocarbons derived from the atmosphere in the electron microscope are deposited on the electron beam irradiation position on the sample. When a sample is contaminated, the contamination may appear as a precipitate in the STEM image. In addition, when the contamination is severe, the precipitate is covered with a contamination film, and a sufficient contrast difference cannot be obtained, which may make analysis difficult. Further, in observation with an electron microscope, accuracy may be reduced due to sample drift. These adverse effects are particularly remarkable in the measurement of fine precipitates having a particle size of 1 μm or less, which is the subject of the present invention.

  Therefore, it is preferable to perform preliminary irradiation for 600 seconds or more to irradiate the primary electron beam defocused on the surface of the measurement region of the replica sample before the observation step of acquiring the scanning electron image. Thereby, the bad influence by the said contamination and drift can be suppressed, and the precision of a particle size distribution can further be improved. If the irradiation time in the preliminary irradiation step is less than 600 seconds, contamination and drift cannot be sufficiently suppressed. Although there is no particular upper limit on the irradiation time, it is preferably set to 3000 seconds or less from the viewpoint of work efficiency and effects. The acceleration voltage in the preliminary irradiation process is not particularly limited, but may be the same as the acceleration voltage in the observation process, for example.

(B) Characteristic X-ray spectrum acquisition process There are cases where a plurality of types of precipitates having different components exist in the metal material, and it is desired to evaluate the particle size distribution for each type of precipitate. In addition, dust and contaminants on the sample surface may be taken into the replica sample and may need to be distinguished from precipitates. In such a case, after the particle analysis step, a characteristic X-ray spectrum acquisition step for acquiring a characteristic X-ray spectrum generated by irradiating each particle to be evaluated with an electron beam, and the obtained characteristic X-ray It is desirable to further provide a spectrum analysis step for analyzing the spectrum.

  First, in the characteristic X-ray spectrum acquisition step, the particles observed in the STEM image are irradiated with a primary electron beam, and the generated characteristic X-ray spectrum is acquired using an X-ray spectroscopic device mounted on an electron microscope. Although the position which irradiates a primary electron beam will not be specifically limited if it is inside each particle | grain, For example, it can be set as the gravity center position of each particle | grain. As the X-ray spectrometer, a wavelength dispersive X-ray spectrometer (WDS) using a spectroscopic crystal, an energy dispersive spectrometer (EDS) that separates X-ray energy using a semiconductor, or the like can be used. In terms of measurement efficiency, it is preferable to use EDS with higher detection sensitivity. What is necessary is just to set the measurement conditions of a characteristic X-ray spectrum according to the deposit etc. which become a measuring object.

  FIG. 5 is a diagram showing an example of a characteristic X-ray spectrum of a precipitate, and specifically, is obtained by irradiating the precipitate surrounded by a broken line in FIG. 2 with an electron beam (Ni is a mesh). Material). Thus, even a fine precipitate having a particle size of about 5 nm can be measured for a characteristic X-ray spectrum, and an element contained in the precipitate can be identified from the obtained characteristic X-ray spectrum. it can.

(C) Spectrum analysis process Next, the obtained characteristic X-ray spectrum is analyzed. Information obtained from the characteristic X-ray spectrum can be used in any method, and specific examples are given below.

[Determination of precipitates]
Based on the characteristic X-ray spectrum, it can be determined whether or not each particle is a precipitate. That is, since the element contained in each particle is known from the characteristic X-ray spectrum, it can be determined whether or not the particle is a precipitate based on the information. By excluding particles determined not to be precipitates from the evaluation target when evaluating the particle size distribution, the particle size distribution can be obtained with higher accuracy.

[Classification of precipitates]
When multiple types of precipitates having different components exist, each particle can be classified into a plurality of groups for each component based on the characteristic X-ray spectrum. Therefore, in the particle size distribution acquisition step, if the particle size distribution is acquired for each group, the particle size distributions of the precipitates having different components can be independently evaluated.

  Only one or both of the determination of whether or not it is the precipitate and the classification of the precipitate may be performed.

  In any of the above cases, the intensity or quantitative value of the characteristic X-ray spectrum can be used for the discrimination and classification of the precipitate. For example, the characteristic X-ray spectrum of the precipitate is measured in advance under the same conditions as the measurement conditions in the characteristic X-ray spectrum acquisition step, elemental analysis is performed, and the threshold value used for the determination and classification of the precipitate is based on the result. It is preferable to decide. Based on the characteristic X-ray intensity and component content set as the threshold, whether or not each particle is a precipitate from the characteristic X-ray spectrum obtained in the characteristic X-ray spectrum acquisition step, or any component Can be analyzed. In addition, since the intensity | strength of the characteristic X-ray obtained also depends on a particle size, it is desirable to set a threshold value using the precipitate of the magnitude | size close | similar to the minimum diameter within an observation visual field. Specifically, about 10 to several tens of precipitates having a size near the minimum diameter are selected in the observation field, and the element composition is analyzed by EDS. ) Is calculated. This may be set as a threshold for particle analysis, but in automatic analysis, drift occurs with the movement of the stage. Therefore, the characteristic X-rays obtained from the precipitates are higher than in the case of manual analysis. Usually the amount is reduced. In consideration of this, it is preferable to set the threshold value by multiplying the representative value by a coefficient of about 0.3 to 0.8.

(Steel plate manufacturing method)
Next, the manufacturing method of the steel plate which is another embodiment of this invention is demonstrated.

  As described above, fine precipitates existing in the steel affect various properties of the steel sheet through the pinning force against the movement of the grain boundaries and dislocations. Since the precipitation state of the precipitate depends on the heat treatment conditions in the manufacturing process of the steel sheet, it is conceivable to determine the heat treatment conditions so that the properties of the finally obtained steel sheet are improved. However, since the actual characteristics of the steel sheet are affected not only by the precipitates but also by various other factors, it is difficult to determine the optimum heat pattern in the heat treatment process using only the characteristics of the final steel sheet as an index.

  Therefore, as a result of evaluating the formation state of fine precipitates in steel plates manufactured with various heat patterns using the above-mentioned precipitate particle size distribution evaluation method, the steel particles produced with the same heat pattern have a high reproduction particle size distribution. It was found that there was a match in gender. It was also confirmed that the median particle size of the precipitate obtained from the particle size distribution of the precipitate changes sensitively with respect to the heat treatment temperature. This result shows that by using the particle size distribution evaluation method, the heat pattern can be effectively optimized in the production of the steel sheet using the obtained particle size distribution as a direct index. Therefore, the manufacturing method of the said steel plate is very effective when manufacturing the various steel plates which utilize precipitates, such as a grain-oriented electrical steel plate.

  For example, in the manufacturing process of a certain steel sheet, when the particle size distribution was evaluated using the particle size distribution of the precipitate, by increasing the heat treatment temperature by 10 ° C., an increase in the average particle size of about 3 nm and the distribution width of the particle size Expansion was confirmed. By utilizing such measurement results, the relationship between the heat treatment temperature, the precipitate generation state, and the material of the steel sheet can be clarified, so that the manufacturing conditions in the actual steel sheet manufacturing process can be determined with higher accuracy. .

  Therefore, in one embodiment of the present invention, (A) using the precipitate particle size distribution evaluation method described above, the particle size distribution of precipitates in the steel sheet during production is evaluated, and based on the obtained particle size distribution, A manufacturing condition of at least one step after the next step in manufacturing the steel sheet is determined.

  In another embodiment of the present invention, (B) the particle size distribution evaluation method for precipitates described above is used to evaluate the particle size distribution of precipitates in the steel sheet during production, and based on the obtained particle size distribution. The manufacturing conditions for manufacturing the steel plate after the steel plate are determined.

  In any of the above embodiments (A) and (B), the production conditions can be determined based on the evaluation result of the particle size distribution. Among them, it is preferable to determine manufacturing conditions (also referred to as heat treatment conditions or heat patterns) in the heat treatment step based on the evaluation result of the particle size distribution.

  In the determination of the production conditions, any information can be used as long as it is information on the particle size distribution obtained by the particle size distribution evaluation method. Among these, it is preferable to use the median diameter or the width of the particle size distribution. . In particular, since the size of the precipitate affects the growth of crystal grains, the median diameter is extremely effective as an index for determining subsequent manufacturing conditions.

  For example, in the embodiment of the above (A), the particle size distribution of precipitates in the steel sheet in the middle stage of the manufacturing process is measured, and the subsequent manufacturing conditions are determined based on the result. That is, the production conditions in the subsequent steps can be adjusted by feedforward control based on the result of evaluating the state of precipitates during production.

  In the embodiment (B), one or more steel plates are manufactured in advance, and the manufacturing conditions for manufacturing the steel plate after the steel plate based on the evaluation result of the particle size distribution performed during the manufacturing process. Can be determined.

  Specifically, for a precipitate existing in a steel plate previously prepared at several heat treatment temperatures, a median diameter is obtained by an inventive method in a certain step. For the subsequent steps, the final product is manufactured without changing the conditions, and the quality of the precipitate is determined by investigating the quality. The crystal grains may vary depending on various conditions, but as a result of the investigation, the formation state of the precipitates strongly depends on the heat treatment conditions, so based on the correlation between the median diameter of the precipitates obtained in advance and the quality, Appropriate manufacturing conditions (for example, heat treatment conditions / range, etc.) can be determined and actually applied as manufacturing conditions in a factory.

  In the particle size distribution measurement according to the present invention, the distribution width can also be evaluated. In particular, when the distribution width is wider than usual or the distribution shape is doubled, it is conceivable that the precipitate generation state is uneven depending on the location. In this case, since there is a possibility that the characteristics are adversely affected, for example, a measure for increasing the processing time in the heat treatment step may be considered in order to make the precipitate generation state uniform.

  In another embodiment of the present invention, the particle size distribution evaluation method for the precipitates is used to evaluate the particle size distribution of the precipitates in the steel sheet in the process of manufacture, and the subsequent steps are manufactured based on the obtained particle size distribution. Determine whether or not to do so.

  In the production of steel sheets, the particle size distribution of precipitates may fluctuate greatly due to disturbance factors or equipment abnormalities. Therefore, the particle size distribution of precipitates in the steel sheet in the middle of production is evaluated, and based on the result, it is determined whether or not to perform the subsequent process, in other words, whether or not the production of the steel sheet is interrupted. can do. For example, if the precipitate state has changed to such an extent that it is difficult to optimize the particle size distribution of the precipitate even if the manufacturing conditions in the process after that point are adjusted, The process is not performed. Thereby, generation | occurrence | production of an unnecessary cost can be prevented.

  As described above, according to the steel sheet manufacturing method of the present invention, it is possible to manufacture a steel sheet inexpensively and stably by optimizing the heat treatment temperature and improving the yield in the manufacturing process.

  EXAMPLES Hereinafter, although an Example demonstrates this invention further in detail, this invention is not limited to the following examples at all.

<Example 1>
A steel plate was manufactured according to the procedure described below, and the particle size distribution of the precipitate was evaluated by the method of the second embodiment described above.

(Manufacture of steel sheets)
% By mass
C: 0.06%,
Si: 3.0%,
Mn: 0.12%, and S: 0.015%,
A steel slab having a composition comprising a balance of Fe and inevitable impurities is melted in a vacuum melting furnace and manufactured according to a conventional method. Next, the steel slab was heated to 1400 ° C. and then hot-rolled to obtain a hot-rolled sheet having a thickness of 2.5 mm. The hot-rolled sheet was subjected to hot-rolled sheet annealing at 1000 ° C. for 60 seconds, then subjected to cold rolling to an intermediate sheet thickness of 1.5 mm, subjected to intermediate annealing at 1050 ° C. for 60 seconds, and then finish cooling Cold rolling was performed to obtain a cold-rolled sheet having a thickness of 0.23 mm. Next, recrystallization annealing was performed in a humid atmosphere of 55 vol% H ₂ -45 vol% N ₂ , which also served as decarburization at 850 ° C. for 150 seconds, to obtain a recrystallization annealed plate.

(Preparation of replica sample)
A 10 mm square steel piece was collected from the obtained recrystallized annealing plate, the thickness from one surface of the steel piece to the central layer was reduced by polishing, and mirror-polished, and further using a 10% AA-based electrolyte. Etching was performed. After the etching, a replica sample was produced from the center layer by a two-stage replica method. Acetylcellulose was used as the organic coating, and carbon was used as the conductive material constituting the support membrane. As a sample mesh, a commercially available Cu mesh (mesh size: 150 μm) was used.

(Observation)
The surface of the obtained replica sample was observed with an electron microscope to obtain a STEM image. The observation conditions were acceleration voltage: 30 kV, observation magnification: 50,000 times, and a STEM-bright field image was acquired. Prior to the observation, preliminary irradiation was performed on the entire measurement region of the replica sample by irradiating a defocused electron beam at an acceleration voltage of 30 kV for 1800 seconds. Further, in other examples, preliminary irradiation was performed under the same conditions as in Example 1 unless otherwise specified.

(analysis)
Subsequently, the obtained STEM image was subjected to particle analysis, and an average ferret diameter and an aspect ratio of an area darker than a preset threshold value were obtained for the STEM-bright field image acquired in each measurement field. In addition, because of the unevenness due to intergranular corrosion and pits in the grains, there was a lot of contrast other than precipitates, so out of each region, the region having an average ferret diameter of 10 nm or more and an aspect ratio of 10 or less was evaluated. did.

(Characteristic X-ray spectrum)
Further, each of the regions to be evaluated in the above process was analyzed by EDS for 2 seconds per region to obtain a characteristic X-ray spectrum. Next, based on the obtained characteristic X-ray spectrum, it was determined whether or not each region was a precipitate, and the region determined not to be a precipitate was excluded from the evaluation target.

  In addition, since the typical precipitate which exists in the steel plate used in a present Example is MnS, the characteristic X-ray intensity of S was used as a parameter | index for judgment whether it is the said precipitate. That is, a region where the characteristic X-ray intensity of S is equal to or greater than a predetermined threshold value is determined as a precipitate.

  The threshold value was determined by the following procedure. First, 20 precipitates having a small particle size (about 15 to 20 nm) among the precipitates confirmed in the observation field in advance were manually subjected to EDS analysis, and the characteristic X-ray intensity of S was measured. Next, an average value of the obtained characteristic X-ray intensities was calculated, and 50% thereof was set as a threshold value.

(Particle size distribution)
For the region finally evaluated, that is, the region determined to be a precipitate, the particle size distribution of the precipitate (number-based frequency distribution) using the information obtained by the analysis of the STEM image described above. Asked. The obtained result is shown in FIG. 6 (curve a). Note that the area of the measurement region was set to 5 × 10 ³ μm ² from the viewpoint of ensuring measurement reproducibility and representativeness.

<Comparative Example 1>
Next, for comparison, particle size distribution was evaluated by SEM according to the following procedure. First, a test piece is collected from the vicinity of a position where a steel piece for producing a replica sample in Example 1 is collected, and the surface scale and the like are removed by mechanical and chemical polishing, and then the same as in Example 1 above. By this method, the thickness from one surface of the test piece to the center layer was reduced by polishing and mirror-polished. Next, electrolytic etching was performed in an A3 electrolytic solution, and the etched steel sheet surface was used as an observation / measurement surface. The sample was observed with an SEM at an acceleration voltage of 30 kV, and the obtained secondary electron image was analyzed to evaluate the particle size distribution. The obtained result is shown in FIG. 6 (curve b). The area of the measurement region was 5 × 10 ³ μm ² as in Example 1.

  When the result shown in FIG. 6 is seen, in the particle size distribution (curve a) obtained in Example 1, the mode value is about 35 nm, and the distribution of precipitates is observed in the range of 10 nm to 60 nm. On the other hand, in the particle size distribution (curve b) of the comparative example obtained from the SEM-secondary electron image in Comparative Example 1, the mode value is about 50 nm, and the number of precipitates is in the region where the particle size is less than 50 nm. It is rapidly decreasing. From this result, it is understood that the evaluation based on the SEM-secondary electron image cannot evaluate the precipitate having a particle size of less than 50 nm. Further, in Example 1, particles having a particle size of 50 nm or more are hardly observed, whereas in Comparative Example 1, the distribution frequency in the range of the particle size of 50 nm to 100 nm is high, which is higher than that of the method of the present invention. Therefore, the particle size is highly evaluated. This is considered to be because, in the method using SEM, a depression is generated in the matrix around the precipitate due to etching, and the contrast caused by this depression affects the binarized image.

<Comparative Example 2>
For comparison, the particle size distribution was evaluated by the field flow fractionation (FFF) method. Specifically, the same steel plate as used in Example 1 was cut into a size of 30 mm × 40 mm, and then a precipitate slurry electrolytically extracted with a 10% -AA electrolyte was used, and the particle size distribution was determined by the FFF method. Evaluated. FIG. 7 shows the results of the measurement performed twice in total (first time: curve a, second time: curve b). The results of measurement under the same conditions using Au colloidal particles with a particle size of 100 nm and a particle size of 250 nm as markers are shown in FIG. 7 (curve c).

  In the FFF method, the precipitate particles in the slurry are sequentially discharged out of the column from the smaller particle size. When compared with the discharge time of the colloidal gold particles (curve c) introduced as a standard for the particle size, the size of the precipitates in the curves a and b is considered to be about 90 nm. However, as described above, the size of the precipitates present in the sample is mainly 20 to 40 nm, and it can be seen that the particle size is evaluated to be larger than the actual size by the measurement by the FFF method. This is considered to be because the precipitate introduced into the column as a slurry has aggregated in the column. We searched for appropriate measurement conditions using various solutions, but using a dispersion that retained the precipitates without agglomerating them caused the precipitates to be adsorbed by the membrane filter in the column for size separation. When a solution system having no adsorption was used, the precipitates aggregated, and no reliable results could be obtained.

<Example 2>
A steel plate was manufactured according to the procedure described below, and the particle size distribution of the precipitate was evaluated by the method of the second embodiment described above.

(Manufacture of steel sheets)
% By mass
C: 0.1%,
Si: 0.01%
Mn: 0.4 %%,
P: 0.01%
S: 0.001%%,
Ti: 0.12%,
Al: 0.04%, and N: 0.003%
A steel slab having a composition comprising a balance of Fe and inevitable impurities is melted in a vacuum melting furnace and manufactured according to a conventional method. Next, the steel slab was hot-rolled and further finished by cold rolling to a final thickness of 3 mm, and then annealed at a maximum temperature of 880 ° C. The surface scale of the obtained steel sheet was removed by mechanical / chemical polishing, and a two-stage replica sample was produced by a procedure usually performed by observation with an electron microscope. Acetylcellulose was used as the organic coating, and carbon was used as the conductive material constituting the support membrane. A commercially available Ni mesh (mesh size: 150 μm) was used as the sample mesh.

  The surface of the obtained replica sample was observed with an electron microscope to obtain a STEM image. The observation conditions were acceleration voltage: 30 kV, observation magnification: 50,000 times, and a STEM-bright field image was acquired.

  Next, the obtained STEM image was subjected to particle analysis, and an average ferret diameter and an aspect ratio of an area darker than a preset threshold value were obtained for the STEM-bright field image acquired in each measurement field. In addition, since contrasts other than precipitates due to unevenness due to intergranular corrosion or pits in the grains were also confirmed, among the regions, regions having an average ferret diameter of 10 nm or more were evaluated.

This was performed for the entire field of view of the preset measurement region, and 10 ³ or more precipitates were extracted to determine the particle size distribution of the precipitates in the sample. In addition, from the viewpoint of ensuring the reproducibility of measurement and representativeness in the sample, one measurement region was set to 5 × 10 ³ μm ² . FIG. 8 shows the results of the measurement repeated four times with the measurement field changed (curves a to d correspond to the first to fourth results, respectively). With respect to the precipitate having a size of 10 nm or more, almost the same particle size distribution was obtained by four measurements. As a result of calculating the average particle diameter in each measurement from the obtained particle size distribution, the average value of the average particle diameter in the four measurements is 18.8 nm, the standard deviation σ serving as an index of repeat measurement accuracy is 0.5 nm, Good repeatability measurement accuracy was obtained.

<Example 3>
In addition to the selection based on the average ferret diameter (threshold value: 10 nm), the particle size distribution was evaluated under the same conditions as in Example 2 except that the particles to be evaluated were selected with an aspect ratio of 5 as a threshold value.

<Example 4>
In addition to the selection based on the average ferret diameter (threshold value: 10 nm), in addition to the selection of particles to be evaluated using the characteristic X-ray generation amount of 20 cps of Ti as a threshold based on the characteristic X-ray spectrum measured by EDS Evaluated the particle size distribution under the same conditions as in Example 2. The main precipitate in the sample used in this example was TiC.

<Example 5>
After performing sorting based on the average ferret diameter and aspect ratio, the particle size distribution was evaluated under the same conditions as in Example 3 except that both sorting based on the characteristic X-ray spectrum measured by EDS was performed. As a result of selection based on the aspect ratio, the characteristic X-ray spectrum was not measured by the EDS for the region excluded from the evaluation target. Each selection condition was the same as in Examples 3 and 4.

  Table 1 shows the standard deviation in each of Examples 2 to 5 (variation in average particle diameter in four measurements) and the time required for the measurement. The repeatability was also good in the second embodiment in which the selection from noise based on the aspect ratio and the selection based on the characteristic X-ray spectrum were not performed. In the third embodiment in which the selection was performed based on the aspect ratio, the repeatability was further improved. Improved. Moreover, in Example 4 which performed the selection based on the characteristic X-ray spectrum, since it was determined whether or not it was a precipitate depending on the element, the measurement accuracy was excellent, and the standard deviation was further improved. In the fifth embodiment in which the selection by the characteristic X-ray spectrum is performed after the selection by the aspect ratio, it is not necessary to perform the EDS analysis in the region where the aspect ratio does not satisfy the condition, and accordingly, the method of the fourth embodiment. In contrast, the measurement time can be shortened. For this reason, the measurement repeatability was excellent, the measurement time was shorter than in Example 4, and the efficiency was excellent.

  Since the replica samples used in these examples had a relatively smooth surface and a small amount of dust, they had extremely high measurement accuracy even when they were not distinguished from noise by aspect ratio or EDS elemental analysis. Although no deterioration was observed, depending on the material to be evaluated and the type of precipitate, the presence or absence of these may greatly affect the analysis accuracy and measurement time.

  Although examples of particle size, aspect ratio, and EDS elemental analysis results are shown as selection criteria for particles to be evaluated, these selections and combinations are arbitrary. In addition to the above examples, one or more arbitrary parameters such as area, major axis, minor axis, and perimeter can be used in combination with the above parameters.

<Comparative Example 3>
For comparison, the same sample as Example 2 was filtered and collected on a filter paper with a precipitate extracted with a 10% -AA (10% acetylacetone-1% tetramethylammonium chloride-methyl alcohol) electrolyte. The sample was observed with a secondary electron image of SEM and particle analysis was attempted. However, since the size of the precipitate was small, it was difficult to evaluate the size of each precipitate on the filter paper. Further, most of the observed precipitates were agglomerated and accurate particle size measurement could not be performed.

<Example 6>
A two-stage replica sample was produced from another location of the central layer of the steel plate used in Example 1 under the same conditions as in Example 1.

(Observation)
The surface of the obtained replica sample was observed with an electron microscope to obtain a STEM image. The observation conditions were acceleration voltage: 20 kV, observation magnification: 50,000 times, and a STEM-dark field image was obtained. Prior to the observation, preliminary irradiation was performed on the entire measurement region of the replica sample by irradiating a defocused electron beam at an acceleration voltage of 30 kV for 1800 seconds.

(analysis)
Subsequently, the obtained STEM image was subjected to particle analysis, and an average ferret diameter and an aspect ratio of an area darker than a preset threshold value were obtained for the STEM-dark field image acquired in each measurement field. Of each region, a region having an average ferret diameter of 10 nm or more and an aspect ratio of 10 or less was evaluated.

(Particle size distribution)
The particle size distribution (number-based frequency distribution) of the precipitates was determined using the information obtained by the above-described STEM-dark field image analysis. Note that the area of the measurement region was set to 5 × 10 ³ μm ² from the viewpoint of ensuring measurement reproducibility and representativeness.

  The obtained particle size distribution is shown in FIG. In this example, a replica sample was produced from the same steel plate as that used in Example 1 as the sample, so that a result almost equal to Example 1 (curve a in FIG. 6) was obtained. In contrast to the bright-field image, the dark-field image has almost no contrast due to intergranular corrosion, pits in the grains, and other precipitates, so that only the precipitate can be extracted without performing EDS analysis. I knew it was possible.

<Example 7>
A steel plate was manufactured according to the procedure described below, and the particle size distribution of the precipitate was evaluated by the method of the second embodiment described above.

(Manufacture of steel sheets)
% By mass
C: 0.06%,
Si: 3.0%,
Mn: 0.12%,
Cu: 0.03%,
S: 0.015%,
A steel slab having a composition comprising a balance of Fe and inevitable impurities is melted in a vacuum melting furnace and manufactured according to a conventional method. Next, the steel slab was heated to 1400 ° C. and then hot-rolled to obtain a hot-rolled sheet having a thickness of 2.5 mm. The hot-rolled sheet was subjected to hot-rolled sheet annealing at 1000 ° C. for 60 seconds, then subjected to cold rolling to an intermediate sheet thickness of 1.5 mm, subjected to intermediate annealing at 1050 ° C. for 60 seconds, and then finish cooling Cold rolling was performed to obtain a cold-rolled sheet having a thickness of 0.23 mm. Then recrystallization annealed sheet is subjected to recrystallization annealing, which also serves as a 900 ° C. × 180 seconds decarburization in a wet atmosphere of _{55vol% H 2 -45vol% N 2} .

(Preparation of replica sample)
A 10 mm square steel piece was collected from the obtained recrystallized annealing plate, the thickness from one surface of the steel piece to the central layer was reduced by polishing, and mirror-polished, and further using a 10% AA-based electrolyte. Etching was performed. After the etching, a replica sample was produced from the center layer by a two-stage replica method. Acetylcellulose was used as the organic coating, and carbon was used as the conductive material constituting the support membrane. A commercially available Ni mesh (mesh size: 150 μm) was used as the sample mesh.

(Observation)
The surface of the obtained replica sample was observed with an electron microscope to obtain a STEM image. The observation conditions were acceleration voltage: 30 kV, observation magnification: 50,000 times, and a STEM-bright field image was acquired. From the viewpoint of ensuring measurement reproducibility and representativeness, the area of the measurement region was set to 5 × 10 ³ μm ² . Prior to the observation, preliminary irradiation was performed on the entire measurement region of the replica sample by irradiating a defocused electron beam at an acceleration voltage of 30 kV for 1800 seconds.

(analysis)
Subsequently, the obtained STEM image was subjected to particle analysis, and an average ferret diameter and an aspect ratio of an area darker than a preset threshold value were obtained for the STEM-bright field image acquired in each measurement field. In addition, because of the unevenness due to intergranular corrosion and pits in the grains, the contrast other than the precipitate was confirmed, and therefore, in each region, the region having an average ferret diameter of 10 nm or more and an aspect ratio of 10 or less was evaluated. It was.

(Characteristic X-ray spectrum)
Further, each of the regions to be evaluated in the above process was analyzed by EDS for 2 seconds per region to obtain a characteristic X-ray spectrum. Here, since the precipitate present in the steel sheet used in this example was a precipitate composed of CuS and MnS, a threshold value was set using characteristic X-rays of Cu and Mn as indices. Specifically, for Cu and Mn, determination based on the obtained characteristic X-ray dose is performed, and a region satisfying either Mn of 5 cps or more or Cu of 10 cps or more is determined to be a precipitate. Areas that are not are excluded from the assessment.

(Particle size distribution)
For the region finally evaluated, that is, the region determined to be a precipitate, the particle size distribution of the precipitate (number-based frequency distribution) using the information obtained by the analysis of the STEM image described above. Asked. Based on the obtained elemental analysis results, the precipitate is classified into a precipitate (Cu> Mn) having a Cu count greater than the Mn count and a precipitate (Mn> Cu) having a Mn count greater than the Cu count. Each particle size distribution was determined.

  The obtained particle size distribution is shown in FIG. From this result, the particle size of the precipitate with the Cu count number larger than the Mn count number is as small as about 1/2 of the particle size of the precipitate with the Mn count number larger than the Cu count number, and the particle size distribution width It was found to be small.

<Example 8>
Six cold-rolled sheets having an intermediate sheet thickness of 1.5 mm were produced under the same conditions as in Example 1. The median diameter obtained from the particle size distribution of the precipitates on the intermediate annealed plate by subjecting the six cold-rolled plates to an intermediate annealing temperature of 1000 to 1150 ° C. for 60 seconds. Further, intermediate annealed plates having a distribution spread of 34 nm (± 4 nm), 39 nm (± 8 nm), 46 nm (± 13 nm), 51 nm (± 17 nm), 54 nm (± 19 nm), and 60 nm (± 23 nm) were prepared. By the same method as in Example 1, the particle size distribution of the precipitates at the 1/4 depth position of the plate thickness from the steel plate surface was evaluated.

Next, finish cold rolling is performed to obtain a cold rolled sheet having a thickness of 0.23 mm, and primary recrystallization annealing is performed in a humid atmosphere of 55 vol% H ₂ -45 vol% N ₂ , which also serves as decarburization at 870 ° C. for 150 seconds. Thus, a primary recrystallization annealed plate was obtained.

  Next, an annealing separator mainly composed of MgO was applied to the primary recrystallization annealing plate, and secondary recrystallization annealing was performed in a laboratory tube furnace at 1200 ° C. for 10 hours in a hydrogen atmosphere. The sample after the secondary recrystallization annealing was taken out of the furnace, and after removing the oxide film on the surface by emery polishing, macro etching was performed with a nital solution, and the secondary recrystallization structure was observed. When the median diameter of the precipitate on the intermediate annealed plate was 46 nm (± 13 nm) or more, secondary recrystallization did not occur.

Therefore, a 0.23 mm cold-rolled sheet after finish cold rolling under the condition that the median diameter of the precipitates on the intermediate annealed sheet was 46 nm (± 13 nm) or more was placed in a humid atmosphere of 55 vol% H ₂ -45 vol% N _2. Was subjected to primary recrystallization annealing also serving as decarburization at 850 ° C. for 150 seconds and 830 ° C. for 150 seconds to obtain a primary recrystallization annealing plate. Next, an annealing separator mainly composed of MgO was applied to the primary recrystallization annealing plate, and secondary recrystallization annealing was performed in a laboratory tube furnace at 1200 ° C. for 10 hours in a hydrogen atmosphere. The sample after the secondary recrystallization annealing is taken out of the furnace, the oxide film on the surface is removed by emery polishing, macro etching is performed with a nital solution, and the secondary recrystallization structure is observed. When annealing is performed, when the median diameter of the precipitate on the intermediate annealed plate expresses secondary recrystallization under the condition of 46 nm (± 13 nm) to 54 nm (± 19 nm), and when primary recrystallization annealing is performed at 850 ° C., Secondary recrystallization was developed under the condition that the median diameter of the precipitate on the intermediate annealing plate was 46 nm (± 13 nm) to 51 nm (± 17 nm). When the median diameter of the precipitate on the intermediate annealing plate was 60 nm (± 23 nm), secondary recrystallization did not occur at any primary recrystallization annealing temperature.

  B8 (magnetic flux density when excited at 800 A / m) of the sample in which secondary recrystallization was confirmed by secondary recrystallization annealing before the oxide film removal was measured by the method described in JIS C2550. However, the higher the primary recrystallization annealing temperature, the better the B8.

As described above, based on the survey results for laboratory vacuum steel ingots, the primary recrystallization annealing temperature is set as the intermediate annealing plate precipitate as the manufacturing conditions for manufacturing the steel plate having the component system used in this example in the factory. Based on the median diameter, the following changes were made.
(1) When the median diameter of the precipitate on the intermediate annealing plate is less than 40 nm, the primary recrystallization annealing temperature is set to 870 ° C.
(2) Same as above, when it is 40 nm or more and less than 50 nm, the primary recrystallization annealing temperature is set to 850 ° C.
(3) Same as above, when it is 50 nm or more and less than 55 nm, the primary recrystallization annealing temperature is set to 830 ° C.
(4) In the case of 55 nm or more, since it can be predicted that secondary recrystallization will not occur in any way from the generation state of precipitates, the coil production was stopped.

  In actual operation, the slab components are not exactly the same for each steel output, so if the steel output timing is different, the size of the precipitates may be different even if the production conditions up to intermediate annealing are the same. By measuring the size of the precipitate after the intermediate annealing step by the method of this application and determining the manufacturing conditions for each slab of the same steel, the same manufacturing is performed for slabs of the same steel that will be manufactured later. It is possible to manufacture by applying conditions.

  As described above, according to the method of the present invention, the particle size distribution of precipitates having a particle size of 1 μm or less can be evaluated accurately and with good reproducibility. Therefore, it can be used very suitably for the design / development and quality control of metal materials, especially thin steel plates, and further optimization of manufacturing conditions in factories, and has high industrial value. Further, since the method of the present invention can automatically and continuously perform the steps from observation to particle analysis and particle size distribution acquisition, it is possible to perform automatic analysis, for example, by unattended operation overnight.

  In addition, by accurately evaluating the state of precipitates generated in steel, it is possible to determine the appropriate manufacturing conditions for creating an ideal precipitation state without being affected by other factors, It can be manufactured. Further, by measuring the particle size distribution of the precipitates in the steel in the midway process material, the production cost can be reduced by stopping the production for the situation where the characteristic improvement in the subsequent process cannot be expected.

Claims (6)

A method for evaluating the particle size distribution of precipitates having a particle size of 1 μm or less present in a metal material,
A polishing step of polishing the surface of the metal material;
An etching step of etching the surface of the metal material;
A replica sample preparation step of extracting a precipitate present on the surface of the metal material after the etching into a replica film formed by depositing a conductive substance to form a replica sample;
An observation step of observing the replica sample using an electron microscope under an acceleration voltage of 40 kV or less to obtain a scanning transmission electron image;
Analyzing the scanning transmission electron image based on a contrast level, a particle analysis step for discriminating particles to be evaluated,
A particle size distribution acquisition step for acquiring a particle size distribution of the particles to be evaluated in the particle analysis step;
It has a door,
In the particle analysis step, based on at least one of the particle size and aspect ratio of the particle in the scanning transmission electron image, determine the particle to be evaluated,
After the particle analysis step, a characteristic X-ray spectrum acquisition step of acquiring a characteristic X-ray spectrum generated by irradiating each of the particles to be evaluated with an electron beam;
A spectral analysis step of analyzing the characteristic X-ray spectrum,
In the spectral analysis step, it is determined whether or not each particle is a precipitate based on the characteristic X-ray spectrum, and the particles determined not to be a precipitate are excluded from the evaluation target.
Prior to the observation step, there is further provided a pre-irradiation step of irradiating an electron beam defocused on the measurement region of the replica sample at the same acceleration voltage as that in the observation step for 600 seconds or more . In the spectral analysis step, the particles are classified into a plurality of groups based on the characteristic X-ray spectrum,
In the particle size distribution acquiring step, to acquire a particle size distribution for each of the groups, the particle size distribution evaluation method of the precipitates according to claim 1. The particle size distribution evaluation method for precipitates according to claim 1 or 2 , wherein the metal material is a steel material. The particle size distribution evaluation method for precipitates according to any one of claims 1 to 3 is used to evaluate the particle size distribution of precipitates in a steel plate in the middle of production, and based on the obtained particle size distribution, The manufacturing method of the steel plate which determines the manufacturing conditions of the at least 1 process after the following process in manufacture. Using the particle size distribution evaluation method for precipitates according to any one of claims 1 to 3 , the particle size distribution of precipitates in a steel plate in the process of production is evaluated, and based on the obtained particle size distribution, from the steel plate A method for manufacturing a steel sheet, which determines manufacturing conditions for manufacturing the steel sheet later. The particle size distribution evaluation method for precipitates according to any one of claims 1 to 3 is used to evaluate the particle size distribution of precipitates in the steel sheet during production, and the subsequent steps are based on the obtained particle size distribution. A method for manufacturing a steel sheet, which determines whether or not to perform manufacturing.