JP6827836B2 - Foreign matter removal processing evaluation method - Google Patents

Description

The present invention relates to a method for evaluating a foreign matter removing treatment applied to a main surface of a substrate. Substrates to be subject to foreign matter removal processing include, for example, semiconductor wafers, liquid crystal display device substrates, plasma display substrates, FED (Field Emission Display) substrates, optical disk substrates, magnetic disk substrates, and optomagnetic disk substrates. , Photomask substrates, ceramic substrates, solar cell substrates, etc. are included.

In the manufacturing process of the semiconductor device, a foreign matter removing process for removing foreign matter on the surface of the substrate (semiconductor wafer), that is, a cleaning process is executed. Conventionally used methods for evaluating the quality of this cleaning process are a step of applying a contaminant containing fine particles (particles) to the substrate, and then a first counting step of measuring the number of particles on the substrate. After that, a cleaning step of cleaning the substrate and a second counting step of measuring the number of particles on the substrate are included. The quality of the cleaning process, that is, the foreign matter removal rate can be calculated by using the number of particles measured in the first counting step and the second counting step. A particle counter, which is a laser scattering type surface inspection machine, is used for counting particles.

Japanese Unexamined Patent Publication No. 2013-153062

The evaluation of the foreign matter removing treatment that has been conventionally performed is performed on a bare substrate (bare wafer) in which an uneven pattern is not formed on the surface. However, the cleaning process performed in the manufacturing process of the semiconductor device or the like is executed not only on the bare substrate but also on the substrate in which the uneven pattern is formed on the surface. It is not always clear whether the result of evaluating the foreign matter removal treatment using the bare substrate is equivalently applicable to the substrate on which the uneven pattern is formed.

On the other hand, in the evaluation of the foreign matter removal process on the premise that particles are counted by the particle counter, for example, pollutants are attached to the main surface of the bare wafer so that 1000 to 50,000 particles adhere to the main surface of the bare wafer having a diameter of 30 cm. Is applied. In this case, the number of particles (particle density) per unit area is 14 to 70 particles / cm ² . However, with such a particle density, the number of particles entering between the fine patterns formed on the main surface of the substrate is insufficient, and the foreign matter removal performance cannot be appropriately evaluated. If particles are attached to the surface of the substrate at a density higher than the above, the particles cannot be counted accurately due to the limitation of the resolution of the particle counter.

On the other hand, it is conceivable to count the particles using a surface defect inspection device that inspects the defects of the pattern formed on the substrate surface. However, since this device is a device for measuring pattern defects, it is not suitable for counting a large number of particles on a substrate. Specifically, since the upper limit of the number of defects that can be measured on a wafer with a diameter of 30 cm is about 150,000, when trying to count the particles adhering to the wafer at high density, the measurement limit is easily reached and overflows. Resulting in.

Therefore, one object of the present invention is to provide a practical method capable of appropriately evaluating the foreign matter removing treatment on the main surface of the substrate on which the uneven pattern is formed.

One embodiment of the present invention provides a foreign matter removal treatment evaluation method for evaluating a foreign matter removal treatment on a substrate main surface on which an uneven pattern is formed. This method includes a first image acquisition step of photographing a first region on the main surface of the substrate on which the first uneven pattern is formed with an electron microscope to acquire a first image, and a second image acquisition step equivalent to the first uneven pattern. A substrate contamination step of adhering foreign matter to a substrate main surface including a second region in which an uneven pattern is formed and a substrate main surface including a third region in which a third uneven pattern equivalent to the first uneven pattern is formed. After the substrate contamination step, the second region is photographed with an electron microscope to acquire a second image, and after the substrate contamination step, the substrate main surface including the third region is subjected to. After the foreign matter removal treatment step of executing the foreign matter removal treatment for removing the foreign matter and the foreign matter removal treatment step, the third region is photographed with an electron microscope to acquire a third image. The acquisition step, the first area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the first unevenness pattern in the first image as the first area ratio, and the second unevenness in the second image. The second area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the pattern and the foreign matter as the second area ratio, and the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter in the third image. Foreign matter removal by the foreign matter removal process is calculated by using the third area ratio acquisition step of acquiring the above as the third area ratio, the first area ratio, the second area ratio, and the third area ratio. Including the rate calculation process.

According to this method, the first image, the second image, and the third image are the first, second, and third regions in which the first uneven pattern, the second uneven pattern, and the third uneven pattern that are equivalent to each other are formed, respectively. Is taken with an electron microscope and obtained. The first image is an image obtained by photographing the main surface of the substrate which has not been subjected to the substrate contamination step. The second image is an image obtained by photographing the main surface of the substrate on which the substrate contamination process has been performed. The third image is an image obtained by photographing the main surface of the substrate which has been subjected to the substrate contamination step and then the foreign matter removal treatment. Therefore, the difference between the first image and the second image corresponds to the result of foreign matter being attached by the substrate contamination step. The difference between the second image and the third image corresponds to the processing result in which the foreign matter is removed by the foreign matter removing treatment. The difference between the first image and the third image corresponds to the overall processing result after both the substrate contamination step and the foreign matter removing treatment step.

In order to evaluate the difference between these images, the ratio of the area of the image portion corresponding to the first uneven pattern in the first image (first region) is acquired as the first area ratio. Further, the second area ratio corresponding to the total area ratio of the image portion corresponding to the second uneven pattern in the second image (second region) and the image portion of the foreign matter is acquired. Then, the third area ratio corresponding to the total area ratio of the image portion corresponding to the third uneven pattern and the image portion of the foreign matter in the third image (third region) is acquired. The difference between the first area ratio and the second area ratio corresponds to the total amount (total number) of foreign substances adhered in the substrate contamination step. The difference between the second area ratio and the third area ratio corresponds to the total amount (total number) of foreign matters removed in the foreign matter removing treatment step. The difference between the first area ratio and the third area ratio corresponds to the difference in the total amount of foreign matter (total number) before and after the substrate contamination step and the foreign matter removal treatment step. Therefore, by using the first area ratio, the second area ratio, and the third area ratio, it is possible to calculate the foreign matter removal rate while eliminating the influence of the uneven pattern on the main surface of the substrate.

In this method, the state of adhesion of foreign matter on the main surface of the substrate is calculated by photographing the main surface of the substrate with an electron microscope and processing and analyzing the image obtained by the photographing. Therefore, there is no limitation on the number of adhered particles as in the case of using the particle counter, and there is no problem of the measurement limit as in the case of using the surface defect inspection device. Therefore, since the foreign matter removal treatment can be evaluated by adhering foreign matter to the main surface of the substrate at high density, it is possible to provide a practical method applicable to the evaluation of the foreign matter removal treatment on the substrate having the uneven pattern on the main surface. ..

In one embodiment of the present invention, the first image binarization step of binarizing the first image to acquire the first binarized image is further included, and the first area ratio acquisition step is the 12th. This is a step of acquiring the ratio of the area of the image portion corresponding to the first uneven pattern in the first image as the first area ratio based on the digitized image.
In this method, the first image is binarized and the first binarized image is acquired. Further, based on the first binarized image, an image portion corresponding to the first uneven pattern in the first image (first region) (in the electron microscope image of the first concave-convex pattern, when binarized, a foreign substance is formed. The ratio of the area of the image portion) binarized to the same value is acquired as the first area ratio.

The present invention is also a foreign matter removal processing evaluation method for evaluating a foreign matter removing treatment on a substrate main surface on which an unevenness pattern is formed, and represents a first region in which a first unevenness pattern is formed on the substrate main surface. The first area ratio acquisition step of acquiring the first area ratio representing the ratio of the area of the image portion corresponding to the first unevenness pattern in the first image and the second unevenness pattern equivalent to the first unevenness pattern are formed. A substrate contamination step of adhering foreign matter to the substrate main surface including the second region and the substrate main surface including the third region on which the third uneven pattern equivalent to the first uneven pattern is formed, and the substrate contamination step. After the second image acquisition step of photographing the second region with an electron microscope to acquire the second image and the substrate contamination step, the foreign matter is subjected to the foreign matter on the substrate main surface including the third region. A foreign matter removing treatment step of executing a foreign matter removing treatment for removing foreign matter, and a third image acquisition step of photographing the third region with an electron microscope to acquire a third image after the foreign matter removing treatment step. A second image binarization step of binarizing the second image to acquire a second binarized image, and a third image binarization step of binarizing the third image to acquire a third binarized image. Second area ratio acquisition that acquires the ratio of the area of the image portion corresponding to the second uneven pattern and the foreign matter in the second image as the second area ratio based on the conversion step and the second binarized image. A third area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter in the third image as the third area ratio based on the step and the third binarized image. A foreign matter removal treatment evaluation method including a foreign matter removal rate calculation step of calculating a foreign matter removal rate by the foreign matter removal treatment using the first area ratio, the second area ratio, and the third foreign matter removal treatment. provide.

This method can be applied if the information to be acquired from the first image corresponding to the first region, that is, the first area ratio is known.
In one embodiment of the present invention, there is a second image binarization step of binarizing the second image to obtain a second binarized image, and a binarization of the third image to obtain a third binarized image. further comprising a third image binarization step of acquiring, to the step of obtaining the second area ratio, based on the second binarized image, the second concavo-convex pattern in the second image and It is a step of acquiring the ratio of the area of the image portion corresponding to the foreign matter as the second area ratio, and the step of acquiring the third area ratio is in the third image based on the third binarized image. This is a step of acquiring the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter as the third area ratio.

In this method, the second image and the third image are binarized, respectively, and the second and third binarized images are acquired. Further, based on the second binarized image, an image portion corresponding to the second uneven pattern in the second image (second region) (in the electron microscope image of the second concave-convex pattern, when binarized, a foreign substance is formed. A second area ratio corresponding to the sum of the area ratios of the image portion (the image portion binarized to the same value) and the image portion of the foreign matter is acquired. Then, based on the third binarized image, an image portion corresponding to the third uneven pattern in the third image (third region) (among the electron microscope images of the third concave-convex pattern, when binarized, a foreign substance is formed. The third area ratio corresponding to the sum of the area ratios of the image portion) and the image portion of the foreign matter that are binarized to the same value is acquired.

In one embodiment of the present invention, the foreign matter removal rate calculation step includes a step of obtaining a value obtained by subtracting the first area ratio from the second area ratio. Since the value obtained by subtracting the first area ratio from the second area ratio corresponds to the area ratio obtained by subtracting the portion corresponding to the uneven pattern from the second area ratio, the amount of foreign matter after the substrate contamination step, that is, the initial amount of foreign matter. Corresponds to.
In one embodiment of the present invention, the foreign matter removal rate calculation step includes a step of obtaining a value obtained by subtracting the first area ratio from the third area ratio. Since the value obtained by subtracting the first area ratio from the third area ratio corresponds to the area ratio obtained by subtracting the portion corresponding to the uneven pattern from the third area ratio, it is on the main surface of the substrate that has undergone the substrate contamination step and the foreign matter removal treatment step. Corresponds to the amount of foreign matter, that is, the amount of foreign matter after processing.

In one embodiment of the present invention, the foreign matter removal rate calculation step includes a step of obtaining a value obtained by subtracting the third area ratio from the second area ratio. The second area ratio is the sum of the area ratio corresponding to the uneven pattern and the area ratio corresponding to the initial amount of foreign matter. On the other hand, the third area ratio is the sum of the area ratio corresponding to the uneven pattern and the area ratio corresponding to the amount of foreign matter after processing. Therefore, the value obtained by subtracting the third area ratio from the second area ratio corresponds to the difference between the initial foreign matter amount and the processed foreign matter amount. This is the amount of foreign matter removed by the foreign matter removing process, that is, the amount of foreign matter removed.

In one embodiment of the present invention, the foreign matter removal rate calculation step includes a step of calculating the foreign matter removal rate by the following formula A or B.
Foreign matter removal rate = 1-{(third area ratio-first area ratio) / (second area ratio-first area ratio)} ... A
Foreign matter removal rate = (second area ratio-third area ratio) / (second area ratio-first area ratio) ... B
Equations A and B are equivalent. When applying any of the formulas, a value obtained by subtracting the first area ratio from the second area ratio (corresponding to the initial amount of foreign matter) is obtained. Then, when the formula A is applied, a value obtained by subtracting the first area ratio from the third area ratio (corresponding to the amount of foreign matter after processing) is further obtained. On the other hand, when the formula B is applied, a value obtained by subtracting the third area ratio from the second area ratio (corresponding to the amount of foreign matter to be removed) is further obtained.

In one embodiment of the present invention, the main surface of the substrate including the first region is the main surface of the first substrate, and the main surface of the substrate including the second region is the main surface of the second substrate different from the first substrate. It is a face.
In imaging with an electron microscope, the main surface of the substrate is exposed to the electron beam, so that the pattern on the surface of the substrate is damaged by the electron beam. Therefore, rather than setting the first region and the second region on the main surface of the same substrate, by setting the region on another substrate main surface on which the same pattern is formed, the error caused by the damage caused by the electron beam is eliminated. Therefore, the quality of the foreign matter removal treatment can be evaluated more appropriately.

For the same reason, in one embodiment of the present invention, the main surface of the substrate including the second region is the main surface of the second substrate, and the main surface of the substrate including the third region is different from the second substrate. This is the main surface of the third substrate.
In one embodiment of the present invention, the first image, the second image, and the third image are images obtained by photographing the first region, the second region, and the third region at the same magnification, respectively. is there. This makes the processing using the first image, the second image, and the third image more appropriate. Moreover, in this case, the areas of the first image, the second image, and the third image are equal. Therefore, the first area ratio can be replaced by the area of the image portion corresponding to the first uneven pattern in the first image, and the second unevenness pattern and the area of the image portion corresponding to the foreign matter in the second image can be used to replace the first area ratio. The area ratio can be replaced, and the third area ratio can be replaced by the area of the third uneven pattern in the third image and the image portion corresponding to the foreign matter. That is, the area itself can be treated as an area ratio, and the foreign matter removal rate can be calculated.

In one embodiment of the present invention, the second image acquisition step recognizes a region having the same shape and size as the first region as the second region by forming a concave-convex pattern equivalent to the first region. A third region recognition including a region recognition step, in which the third image acquisition step recognizes a region having the same shape and size as the first region as the third region by forming an uneven pattern equivalent to that of the first region. Including the process. This makes the processing using the first image, the second image, and the third image more appropriate.

In one embodiment of the present invention, a plurality of the first region, the second region, and the third region are set, and a plurality of the first images corresponding to the plurality of the first regions are acquired. A plurality of the second images corresponding to the plurality of second regions are acquired, a plurality of third images corresponding to the plurality of third regions are acquired, and the first unevenness in each of the plurality of first images is acquired. The average value of the ratio of the area of the image portion corresponding to the pattern is defined as the first area ratio, and the average value of the ratio of the area of the image portion corresponding to the second uneven pattern and the foreign matter in each of the plurality of the second images. Is defined as the second area ratio, and the average value of the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter in each of the plurality of third images is defined as the third area ratio.

As a result, a plurality of the first region, the second region, and the third region are set, respectively, and the first area ratio and the second area are calculated by averaging the first image, the second image, and the third image. The rate and the third area rate are calculated. As a result, the accuracy of evaluation of the foreign matter removing process can be improved.
In one embodiment of the present invention, a plurality of the first binarized images corresponding to the plurality of first images are acquired, and a plurality of the binarized images corresponding to the plurality of second images are obtained. Is acquired, and a plurality of third binarized images corresponding to the plurality of third images are acquired. Then, based on these, the first area ratio, the second area ratio, and the third area ratio are obtained.

In one embodiment of the present invention, the substrate contamination step includes a step of applying a contaminated liquid in which foreign substances are dispersed in a liquid to which an acid is added to the main surface of the substrate. By dispersing foreign matter in the acid-added liquid to create a contaminated liquid, the foreign matter having a controlled zeta potential can be applied to the main surface of the substrate. As a result, foreign matter can be uniformly adhered to the main surface of the substrate. In particular, the flow of the contaminated liquid is greatly affected by the uneven pattern on the main surface of the substrate on which the uneven pattern is formed, and as a result, when the foreign matter flows together with the contaminant liquid, the foreign matter tends to be unevenly distributed depending on the uneven pattern. Therefore, by controlling the zeta potential of the foreign matter using the liquid to which the acid is added and making it easy for the foreign matter to adhere to the main surface of the substrate, it is possible to realize a dispersion tendency that is less dependent on the uneven pattern.

In one embodiment of the invention, the acid is hydrochloric acid. The use of hydrochloric acid makes it easier to control the zeta potential of foreign substances.
In one embodiment of the present invention, the pH of the contaminant is 4 or less. As a result, the zeta potential of the foreign matter can be controlled to a value at which the foreign matter easily adheres to the main surface of the substrate.

FIG. 1 is a diagram for explaining a foreign matter removal processing evaluation method according to an embodiment of the present invention. FIG. 2 is a conceptual diagram showing an overall configuration example of a system for implementing the foreign matter removal processing evaluation method according to this embodiment. FIG. 3 is a block diagram for explaining a functional configuration of the foreign matter removal rate calculation device. 4A and 4B are schematic cross-sectional views for explaining the characteristics of the foreign matter adhesion treatment (board contamination step) on the main surface of the substrate. FIG. 5A is an electron micrograph of an evaluation sample substrate prepared using a contaminated solution in which particle particles are dispersed in pure water whose pH has not been adjusted. On the other hand, FIG. 5B is an electron micrograph of an evaluation sample substrate prepared by using a contaminated solution in which particles are dispersed in a solvent whose pH is adjusted to 4 or less (more specifically, 2 or less) with hydrochloric acid. .. 6A, 6B and 6C are diagrams for explaining a calculation example of the foreign matter removal rate. FIG. 7 is a diagram for explaining a foreign matter removal treatment evaluation method according to another embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
FIG. 1 is a diagram for explaining a foreign matter removal processing evaluation method according to an embodiment of the present invention. This foreign matter removal processing evaluation method uses three substrates, that is, the first substrate W1, the second substrate W2, and the third substrate W3. A common pattern is formed on the main surfaces of the first substrate W1, the second substrate W2, and the third substrate W3. That is, the first concavo-convex pattern P1 is formed in the first region R1 of the main surface of the first substrate W1, and the second concavo-convex pattern P2 is formed in the second region R2 of the main surface of the second substrate W2. A third concavo-convex pattern P3 is formed in the third region R3 on the main surface of the third substrate W3. The first, second and third uneven patterns P1 to P3 are substantially the same pattern.

The surface states of the first to third substrates W1 to W3 on which the first to third uneven patterns P1 to P3 are formed are initialized by the pre-cleaning steps (steps S11, S12, S13). .. After the pre-cleaning step, the main surface of the first substrate W1 is photographed with an electron microscope. More specifically, the first image is acquired by recognizing the first region R1 of the main surface of the first substrate W1 (step S41) and photographing the first region R1 with an electron microscope (step S51). (Step S61). That is, the image data of the first image generated by the electron microscope is stored.

On the other hand, for the second substrate W1 and the third substrate W3, after pre-cleaning (steps S12 and S13), a substrate contamination step (steps S22 and S23) of adhering foreign matter to their main surfaces is performed. As a result, foreign matter adheres to the main surfaces of the second and third substrates W2 and W3 in substantially the same state.
Next, the main surface of the second substrate W2 is photographed with an electron microscope. More specifically, the second region R2 on the main surface of the second substrate W2 is recognized (step S42), and the second region R2 is photographed with an electron microscope (step S52) to acquire a second image. (Step S62). That is, the image data of the second image generated by the electron microscope is saved.

For the third substrate W3, after the substrate contamination step (step S23), a foreign matter removing process for removing the foreign matter on the main surface, that is, a cleaning process is executed (step S33). This cleaning treatment is a foreign matter removal treatment to be evaluated by this method. After this cleaning process, the main surface of the third substrate W3 is photographed with an electron microscope. More specifically, the third region R3 on the main surface of the third substrate W3 is recognized (step S43), and the third region R3 is photographed with an electron microscope (step S53) to acquire a third image. (Step S63). That is, the image data of the third image generated by the electron microscope is saved.

When the first image, the second image, and the third image are acquired in this way, the foreign matter removal rate by the cleaning process is calculated by the arithmetic process using the data of these images. The image data representing the first image, the second image, and the third image is multi-valued data (multi-gradation data) in which the brightness of each pixel is represented by a large number of gradations. The multi-valued image data representing the first image, the second image, and the third image are binarized by applying an appropriate binarization threshold, and thereby the first binarized image and the second binary image, respectively. A digitized image and a third binarized image are acquired (steps S71, S72, S73). That is, binarized data in which the brightness of each pixel is binarized to 0 or 1 is generated.

In the first, second and third binarized images, for example, the pattern portion on the main surface of the substrate, specifically the convex pattern portion, appears in white (for example, represented by the binary data "1"). , The portion where the convex pattern does not exist, that is, the concave pattern portion appears in black (for example, it is represented by the binary data "0"). Of course, this is an example, and a binarized image in which the convex pattern appears in black and the concave pattern appears in white may be acquired.

Next, based on the first binarized image, the area of the image portion corresponding to the convex portion of the first uneven pattern P1 in the first region R1, specifically, the area of the white region in the first binarized image is the first. It is obtained as one area A1 (step S81). Similarly, the area of the white portion of the second binarized image is obtained as the second area A2 (step S82). Further, similarly, the area of the white portion in the third binarized image is obtained as the third area A3 (step S83). In the second binarized image, in addition to the white portion constituting the convex pattern portion of the second uneven pattern P2 in the second region R2, the foreign matter adhering to the main surface of the second substrate W1 is the white portion in the image. Consists of. Therefore, the second area A2 is the total area of the convex pattern portion and the image portion of the foreign matter in the second region R2. The same applies to the third area A3, and the convex pattern portion of the third uneven pattern P3 in the third area A3 and the foreign matter form a white image portion.

Next, the foreign matter removal rate is calculated using the first area A1, the second area A2, and the third area A3 thus obtained (step S9).
The specific formula for calculating the foreign matter removal rate is as shown in the following formula (1).
Foreign matter removal rate = 1-{(A3 / R-A1 / R) / (A2 / R-A1 / R)} ... (1)
In the formula (1), R is a common area of the first region R1, the second region R2, and the third region R3, that is, an area common to the first, second, and third images. The first region R1, the second region R2, and the third region R3 are regions of the same shape and size, and by photographing these regions with an electron microscope at the same magnification, in the first, second, and third images. The areas of the first, second and third regions R1, R2 and R3 are equal.

In the second term on the right side of the formula (1), A1 / R is a first area ratio representing the ratio of the area of the first uneven pattern P1 (more accurately, the area of the convex pattern portion) in the first image. Similarly, A2 / R is a second area ratio representing the ratio of the area of the second uneven pattern P2 (more accurately, the area of the convex pattern portion) in the second image, and A3 / R is the third image. It is a third area ratio representing the ratio of the area of the third uneven pattern (more accurately, the area of the convex pattern portion) in the inside.

The following equation (2) can be obtained by taking the denominator of the second term on the right side of the equation (1) and 1 / R, which is a common factor of the numerator.
Foreign matter removal rate = 1-{(A3-A1) / (A2-A1)} ... (2)
That is, by photographing the first region R1, the second region R2, and the third region R3 having the same area with the same magnification with an electron microscope, the first area ratio A1 / R, the second area ratio A2 / R, and the third area The rates A3 / R can be replaced by the first area A1, the second area A2, and the third area A3, respectively.

In the formula (2), the denominator of the second term is the area obtained by subtracting the first area A1 from the second area A2. Since this area difference (A2-A1) is a value obtained by subtracting the area of the convex pattern portion in the second region R2 from the second area A2, it corresponds to the amount of foreign matter after the substrate contamination step, that is, the initial amount of foreign matter. doing. On the other hand, in the formula (2), the molecule of the second term is the area obtained by subtracting the first area A1 from the third area A3, and the area of the convex pattern portion in the third region R3 is subtracted from the third area A3. The value. This value corresponds to the amount of foreign matter on the main surface of the substrate that has undergone the substrate contamination step and the foreign matter removal treatment step (cleaning step), that is, the amount of foreign matter after treatment.

Equation (1) can be transformed as in the following equation (3) and further as in equation (4).
Foreign matter removal rate = (A2 / R-A3 / R) / (A2 / R-A1 / R)} ... (3)
Foreign matter removal rate = (A2-A3) / (A2-A1) ... (4)
The molecule on the right side of the formula (4) is the area obtained by subtracting the third area A3 from the second area A2. The second area A2 is the sum of the area corresponding to the convex pattern portion of the second uneven pattern P2 and the area corresponding to the initial amount of foreign matter. On the other hand, the third area A3 is the sum of the area corresponding to the convex pattern portion of the third uneven pattern P3 and the area corresponding to the amount of foreign matter after processing. Therefore, the value obtained by subtracting the third area A3 from the second area A2 corresponds to the difference between the initial amount of foreign matter and the amount of foreign matter after processing. This is the amount of foreign matter removed by the foreign matter removing process, that is, the amount of foreign matter removed.

FIG. 2 is a conceptual diagram showing an overall configuration example of a system for implementing the foreign matter removal processing evaluation method according to this embodiment. This system includes a substrate cleaning apparatus 1 that executes a cleaning treatment of an evaluation target, an evaluation sample manufacturing apparatus 2 that executes a substrate contamination treatment to prepare a substrate W as an evaluation sample, and a scanning electron microscope 3. , The foreign matter removal rate calculation device 4. The foreign matter removal rate arithmetic unit 4 can be configured by, for example, a computer. The substrate cleaning device 1 may be a single-wafer type device that executes a cleaning process on each substrate W, or a batch type that collectively executes a cleaning process on a plurality of substrates W. It may be the device of. The scanning electron microscope 3 photographs the main surface of the substrate W by scanning the main surface of the substrate W with an electron beam, and outputs image data representing an electron micrograph obtained thereby. The output image data is input to the foreign matter removal rate calculation device 4.

The evaluation sample manufacturing apparatus 2 is a single-wafer type that manufactures one evaluation substrate W for evaluating the cleaning ability of the substrate cleaning apparatus 1 by applying a contaminated solution containing a contaminant on the surface of the substrate W. It is a device of. In this example, the evaluation sample manufacturing apparatus 2 includes a box-shaped chamber 10 for partitioning a processing space, a spin chuck 11 arranged in the chamber 10, a contaminated solution supply unit 12, and a rinse liquid supply unit 13. Including.

The spin chuck 11 is a substrate holding unit that holds one substrate W in a horizontal posture in the chamber 10 and rotates the substrate W around a vertical rotation axis (vertical axis) 15 passing through the center of the substrate W. ..
The contaminated solution supply unit 12 supplies the contaminated solution 16 in which the contaminants are dispersed in the liquid to the surface (main surface) of the substrate W held by the spin chuck 11. More specifically, the contaminated solution supply unit 12 includes a contaminated solution nozzle 21, a nozzle arm 22 to which the contaminated solution nozzle 21 is attached to the tip, and a contaminated solution pipe 23 having one end connected to the contaminated solution nozzle 21. The contaminated solution valve 24 interposed in the contaminated solution pipe 23 and the nozzle moving unit 25 coupled to the nozzle arm 22 are included. The nozzle moving unit 25 horizontally moves the contaminated solution nozzle 21 along the upper surface of the substrate W held by the spin chuck 11, thereby scanning the landing point of the contaminated solution on the main surface of the substrate W. The contaminated solution supply unit 12 further includes a tank 26 for storing the contaminated solution 16. The other end of the contaminated solution pipe 23 is connected to the tank 26. A liquid supply pipe 27 for supplying liquid (in this embodiment, deionized water (DIW)) as a medium for dispersing pollutants is connected to the tank 26. A valve is provided in the middle of the liquid supply pipe 27. 28 is interposed to control the supply of the liquid to the tank 26. While the liquid is supplied from the liquid supply pipe 27 into the tank 26, the pollutants are charged into the tank 26 and into the liquid. By dispersing the contaminants, the contaminant solution 16 is prepared. If necessary, a stirrer 29 is provided in the tank 26 to uniformly disperse the contaminants in the liquid.

The pollutant supplied to the tank 26 may be a powder of particles, a metal pollutant (for example, copper sulfate), or an organic pollutant. The powder particles can be exemplified the SiO ₂ powder, powder of silicon nitride _{(SiN, Si 3 N 4)} , powdered polystyrene latex, aluminum powder and the like. As the type of pollutant, the same kind of pollutant as the pollutant to be removed by the substrate cleaning device 1 is selected.

The rinse liquid supply unit 13 includes a rinse liquid nozzle 31. A rinse liquid pipe 32 is connected to the rinse liquid nozzle 31, and a rinse liquid valve 33 is interposed in the rinse liquid pipe 32. A rinse liquid such as DIW (deionized water) is supplied to the rinse liquid pipe 32. The rinse liquid nozzle 31 may be a fixed nozzle that supplies the rinse liquid toward the rotation center of the substrate W held by the spin chuck 11.

As described above, in order to execute the foreign matter removal processing evaluation method according to this embodiment, three substrates W1, W2, and W3 having a common uneven pattern formed on the main surface are prepared, and these three substrates are prepared. Pre-cleaning treatment is performed on W1, W2, and W3 as needed. The first region of the main surface of the first substrate W1 is photographed by the scanning electron microscope 3 without going through the substrate contamination step by the evaluation sample manufacturing apparatus 2 and the cleaning step by the substrate cleaning apparatus 1. On the other hand, the second and third substrates W2 and W3 become evaluation samples after undergoing a substrate contamination step by the evaluation sample manufacturing apparatus 2. Of the second and third substrates W2 and W3 that have undergone the substrate contamination step in this way, the second substrate W2 has a second region of its main surface formed by the scanning electron microscope 3 without undergoing the cleaning step by the substrate cleaning apparatus 1. Be photographed. Then, the third substrate W3 is subjected to a cleaning treatment by the substrate cleaning device 1 before being photographed by the scanning electron microscope 3. After the cleaning treatment, the third region of the main surface of the third substrate W3 is photographed by the scanning electron microscope 3.

The operation of the evaluation sample manufacturing apparatus 2 can be outlined as follows.
A substrate W (second substrate W2 or third substrate W3) is carried into the chamber 10 by a transfer robot (not shown) and passed to the spin chuck 11. The spin chuck 11 holds the substrate W and rotates it around the rotation axis 15. On the other hand, the contaminated solution nozzle 21 moves horizontally above the substrate W held by the spin chuck 11 by the nozzle moving unit 25. On the other hand, when the contaminated solution valve 24 is opened, the contaminated solution is supplied from the tank 26 to the contaminated solution nozzle 21. This contaminated solution is supplied from the contaminated solution nozzle 21 to the main surface of the substrate W. The liquid landing point is scanned on the substrate W by the horizontal movement of the contaminated solution nozzle 21 by the nozzle moving unit 25. Since the substrate W is rotated, the contaminated solution is supplied to the entire surface of the substrate W.

When the contaminated solution is supplied to the entire main surface of the substrate W, the contaminated solution valve 24 is closed, and the nozzle moving unit 25 retracts the contaminated solution nozzle 21 to the retracted position. Next, the spin chuck 11 rotates the substrate W at high speed, so that the main surface of the substrate W is dried. At this time, if necessary, an inert gas such as nitrogen gas may be supplied toward the main surface of the substrate W to promote drying of the main surface of the substrate W. By such a drying step, the liquid in the contaminated solution supplied to the main surface of the substrate W evaporates, and the contaminants adhere to the main surface of the substrate W. In this way, after the contaminants adhere to the main surface of the substrate W, the rinse liquid valve 33 is opened, the rinse liquid is supplied to the main surface of the substrate W, and the rinse treatment for the substrate W is executed. After the rinsing process, the rinsing solution valve 33 is closed, the supply of the rinsing solution is stopped, and the spin drying process is executed by the high-speed rotation of the substrate W by the spin chuck 11. By this rinsing treatment and spin drying treatment, the attached contaminants are not lost from the main surface of the substrate W.

In this way, the substrate W (W2, W3) as an evaluation sample is created, and the substrate W is discharged to the outside of the chamber 10 by the transfer robot.
FIG. 3 is a block diagram for explaining a functional configuration of the foreign matter removal rate calculation device. In this embodiment, the foreign matter removal rate calculation device 4 is composed of a computer, and includes a CPU (central processing unit) 41, a storage device 42, an input device 43, and a display 44. The storage device 42 includes a ROM and a RAM. The storage device 42 may be in any form such as a solid-state memory, an HDD (hard disk drive), an SSD (solid state drive), or a combination thereof. The input device 43 is an input man-machine interface for a keyboard, a pointing device, or the like. The display 44 is an example of an information output device, and is a man-machine interface for presenting information to a user. The information output device may include a communication device that outputs data to a printing device, another computer, or the like in place of the display 44 or in addition to the display 44.

The program 47 and the data 48 are stored in the storage device 42. Examples of the data stored in the storage device 42 include the first image data D1, the second image data D2 and the third image data D3 corresponding to the first image, the second image and the third image described above, and the above-mentioned third image data D3. Includes first binary image data BD1, second binary image data BD2, and third binary image data BD3 corresponding to the first binarized image, the second binarized image, and the third binarized image.

The CPU 41 executes the program 47 stored in the storage device 42. As a result, the computer constituting the foreign matter removal rate arithmetic unit 4 realizes the functions as a plurality of function processing units. The plurality of functional processing units include an image data input unit 51, an area recognition unit 52, a binarization processing unit 53, a white area calculation unit 54, and a removal rate calculation unit 56.
The image data input unit 51 takes in the image data output by the scanning electron microscope 3. The region recognition unit 52 recognizes the first region R1, the second region R2, and the third region R3 from the image data output by the scanning electron microscope 3. The image data input unit 51 takes in the image data of the region recognized by the region recognition unit 52 from the scanning electron microscope 3, and stores the image data as the first image data D1, the second image data D2, or the third image data D3. Store in.

The region recognition unit 52 sets and recognizes a predetermined region in the image output by the scanning electron microscope 3 as the first region R1 when the main surface of the first substrate W1 is imaged. The image data of the recognized area is extracted as the first image data D1 by the image data input unit 51. The region recognition unit 52 also recognizes the second region R2 corresponding to the first region R1 from the image data output by the scanning electron microscope 3 when the second substrate W2 is photographed. The image data of the recognized area is extracted as the second image data D2 by the image data input unit 51. The region recognition unit 52 further corresponds to the first region R1 and the second region R2 from the image data output by the scanning electron microscope 3 when the third substrate W3 is photographed by the scanning electron microscope 3. Recognize the image of region R3. The image data of the recognized area is extracted as the third image data D3 by the image data input unit 51.

The binarization processing unit 53 reads out the first image data D1, the second image data D2, and the third image data D3 from the storage device 42, and binarizes them using a predetermined binarization threshold value. Therefore, the first binary image data BD1, the second binary image data BD2, and the third binary image data BD3 are generated. These binary image data BD1, BD2, BD3 are stored in the storage device 42.

The white part area calculation unit 54 reads out the first, second and third binary image data BD1, BD2, BD3 from the storage device 42, and represents the first binarized image and the second binarized image. And the area of each white part of the third binarized image is obtained. The area of the white portion may be represented by the total number of pixels of the binary data "1". The area of the white portion in the first binarized image is stored in the storage device 42 as first area data representing the first area A1. The area of the white portion in the second binarized image is stored in the storage device 42 as the second area data representing the second area A2. The area of the white portion in the third binarized image is stored in the storage device 42 as the third area data representing the third area A3.

The removal rate calculation unit 56 reads out the first area data, the second area data, and the third area data from the storage device 42, applies them to any of the above equations (1) to (4), and removes foreign matter. Calculate the rate.
4A and 4B are schematic cross-sectional views for explaining the characteristics of the foreign matter adhesion treatment (board contamination step) on the main surface of the substrate. FIG. 4A shows a state in which particle powder is dispersed in pure water (deionized water) to prepare a contaminated solution 16 and the contaminated solution 16 is applied to the main surface of the substrate W. On the other hand, FIG. 4B shows a state when the contaminated solution 16 is prepared by dispersing the particle powder in a dilute aqueous hydrochloric acid solution and the contaminated solution 16 is applied to the main surface of the substrate W. That is, in the case of FIG. 4B, a small amount of hydrochloric acid is added to the contaminated solution 16 in the case of FIG. 4A.

Since the uneven pattern P is formed on the main surface of the substrate W, the particles 60 enter the groove between the patterns P. At this time, as shown graphically in FIG. 4A, when the particles 60 are unevenly distributed due to centrifugal force during the drying process after the contaminated solution 16 is applied, or when the liquid is accumulated in a portion which is difficult to dry and the particles 60 are concentrated. There is. As a result, the particles 60 are not uniformly dispersed in the uneven pattern P.

On the other hand, in the contaminated solution 16 in which the pH is adjusted by adding hydrochloric acid, the zeta potential of the particles 60 is controlled. More specifically, for example, when the substrate W is a silicon substrate, its zeta potential is negative, whereas when the particles 60 composed of SiO ₂ are dispersed in pure water having a pH of 4 or less, the particles 60 The zeta potential of the substrate W has a positive electrode property having a polarity opposite to the polarity of the zeta potential of the substrate W. As a result, the particles 60 are electrically attracted to the substrate W, so that the particles 60 are likely to adhere to the main surface of the substrate W. As a result, the particles 60 are less likely to move even during the drying process, and as shown graphically in FIG. 4B, uneven distribution of the particles 60 in the uneven pattern P can be avoided.

FIG. 5A is an electron micrograph of an evaluation sample substrate prepared using a contaminated solution in which particle particles are dispersed in pure water whose pH has not been adjusted. On the other hand, FIG. 5B is an electron micrograph of an evaluation sample substrate prepared by using a contaminated solution in which particles are dispersed in a solvent whose pH is adjusted to 4 or less (more specifically, 2 or less) with hydrochloric acid. .. As can be understood from these comparisons, the main surface of the substrate on which the uneven pattern P is formed is formed by adjusting the contaminated solution with a solvent whose pH is adjusted, preferably 4 or less (more preferably 2 or less). It is understood that the particles 60 can be uniformly dispersed and adhered to the solvent.

The width of the uneven pattern P is about 40 nm to 50 nm, and the interval is about 100 nm to 200 nm. In this case, if the adhesion density (area ratio) of the particles 60 on the substrate W is about 10% to 40%, it is possible to evaluate the foreign matter removing performance in the uneven pattern P.
6A, 6B and 6C are diagrams for explaining a calculation example of the foreign matter removal rate. The first image shown in FIG. 6A is an electron micrograph of the main surface of the first substrate W1 before the substrate contamination treatment, and the second image shown in FIG. 6B is the main surface of the second substrate W2 after the substrate contamination treatment. It is an electron micrograph, and the third image shown in FIG. 6C is an electron micrograph of the main surface of the third substrate W3 after the substrate cleaning treatment.

As can be understood from the first image of FIG. 6A, the convex pattern portion of the uneven pattern P (P1 to P3) formed on the main surface of the substrate W (W1, W2, W3) is a binarized first image. Appears as a white part in the binarized image. As can be seen from the second and third images of FIGS. 6B and 6C, the particles 60 attached to the main surface of the substrate W (W1, W2, W3) also appear as white parts in the binarized image. .. Therefore, in the binarized images obtained from the second image and the third image, the convex pattern portion of the concave-convex pattern P and the portion corresponding to the particles 60 appear as white portions.

In this example, the area ratio (A1 / R) of the white portion in the binarized image obtained from the first image of FIG. 6A is, for example, 32%. The area ratio (A2 / R) of the white portion in the binarized image obtained from the second image of FIG. 6B is, for example, 44%. Further, the area ratio (A3 / R) of the white portion in the binarized image obtained from the third image of FIG. 6C is, for example, 36%. By substituting these area ratios into the above equation (1) or equation (3), the white image portion caused by the uneven pattern P can be canceled, and the foreign matter removal performance before and after the cleaning process, that is, the foreign matter removal rate. Can be sought. The foreign matter removal rate in the above example is 67%.

As described above, in this embodiment, the first image (first image data D1), the second image (second image data D2), and the third image (third image data D3) have the same first uneven pattern. Scan the first, second and third regions R1, R2, R3 on the first, second and third substrates W1, W2, W3 on which P1, the second uneven pattern P2, and the third uneven pattern P3 are formed, respectively. Obtained by photographing with a scanning electron microscope 3. The first image (first image data D1) is an image obtained by photographing the main surface of the first substrate W1 which has not been subjected to the substrate contamination step. The second image (second image data D2) is an image obtained by photographing the main surface of the second substrate W2 subjected to the substrate contamination step. The third image (third image data D3) is an image obtained by photographing the main surface of the third substrate W3 which has been subjected to the substrate contamination step and then the foreign matter removal treatment. Therefore, the difference between the first image and the second image corresponds to the result of foreign matter being attached by the substrate contamination step. The difference between the second image and the third image corresponds to the processing result in which the foreign matter is removed by the foreign matter removing treatment. The difference between the first image and the third image corresponds to the overall processing result after both the substrate contamination step and the foreign matter removing treatment step.

To evaluate the differences between these images, the first, second and third images are binarized, respectively, and the first, second and third binarized images (first, second and third). 3 Binary image data BD1, BD2, BD3) is acquired. Further, based on the first binary image data BD1, the image portion corresponding to the first uneven pattern P1 in the first region R1 (when the scanning micrograph image is binarized, the value is equal to that of the foreign matter (particle)). The area of the image to be digitized) is acquired as the first area A1. Further, based on the second binary image data BD2, the second uneven pattern P2 in the second region R2 and the second area A2 corresponding to the total area of the image portion of the foreign matter (particle) are acquired. Then, based on the third binary image data BD3, the third uneven pattern P3 in the third region R3 and the third area A3 corresponding to the total area of the image portion of the foreign matter (particle) are acquired.

In this embodiment, the first image, the second image, and the third image are images obtained by photographing the main surfaces of the substrates W1, W2, and W3 at the same magnification. Therefore, the first area A1 can be treated as the ratio of the area of the image portion corresponding to the first uneven pattern P1 in the first region R1, that is, the first area ratio. Similarly, the second area A2 can be treated as the ratio of the total area of the second uneven pattern P2 in the second region R2 and the image portion corresponding to the foreign matter (particles), that is, the second area ratio. Furthermore, similarly, the third area A3 can be treated as the ratio of the total area of the third uneven pattern P3 in the third region R3 and the image portion corresponding to the foreign matter (particles), that is, the third area ratio.

The difference between the first area A1 (first area ratio) and the second area A2 (second area ratio) corresponds to the total amount (total number) of foreign substances adhered in the substrate contamination step. Further, the difference between the second area A2 (second area ratio) and the third area A3 (third area ratio) corresponds to the total amount (total number) of foreign substances removed in the foreign matter removing treatment step. The difference between the first area A1 (first area ratio) and the third area A3 (third area ratio) corresponds to the difference in the total amount of foreign matter, that is, the total number before and after the substrate contamination step and the foreign matter removal treatment step. Therefore, by using the first area A1 (first area ratio), the second area A2 (second area ratio), and the third area A3 (third area ratio), the uneven pattern P on the main surface of the substrate W The foreign matter removal rate can be calculated while eliminating the influence.

In this method, the state of adhesion of foreign matter on the main surface of the substrate W is calculated by photographing the main surface of the substrate W with the scanning electron microscope 3 and processing and analyzing the image data obtained by the photographing. Therefore, there is no limitation on the number of adhered particles as in the case of using the particle counter, and there is no problem of the measurement limit as in the case of using the surface defect inspection device. Therefore, since foreign matter can be evaluated by adhering foreign matter to the main surface of the substrate W at a high density, a practical method applicable to the evaluation of the foreign matter removing treatment on the substrate W having the uneven pattern P on the main surface is provided. can do.

Further, in this embodiment, the first region R1 for acquiring the first image, the second region R2 for acquiring the second image, and the third region R3 for acquiring the third image are different substrates. It is set on the main surface of W1, W2, and W3. In the photographing using the scanning electron microscope 3, since the main surface of the substrate W is exposed to the electron beam, the pattern of the main surface of the substrate W is damaged by the electron beam. Therefore, by setting the first, second and third regions R1, R2 and R3 as regions on the main surface of another substrate W1, W2 and W3 in which the same pattern is formed, the damage caused by the electron beam is caused. The error can be eliminated. Thereby, the quality of the foreign matter removing treatment can be appropriately evaluated.

FIG. 7 is a diagram for explaining a foreign matter removal treatment evaluation method according to another embodiment of the present invention. In FIG. 7, the steps corresponding to each step shown in FIG. 1 are indicated by the same reference numerals.
In this embodiment, a plurality of first regions R11 to R14 are set on the first substrate W1, and first concavo-convex patterns P11 to P14 are formed in each of these regions. On the second substrate W2, there are a plurality of second regions R21 to R24 corresponding to the plurality of first regions R11 to R14, and in these regions, a second region equivalent to the first uneven pattern P11 to P14, respectively. 2 Concavo-convex patterns P21 to P24 are formed. On the third substrate W3, there are a plurality of third regions R31 to R34 corresponding to the plurality of first regions R11 to R14, and in these regions, the first concavo-convex patterns P11 to P14 are equivalent to each other. 3 Concavo-convex patterns P31 to P34 are formed. It is preferable that the plurality of first regions R11 to R14, the plurality of second regions R21 to R24, and the plurality of third regions R31 to R34 correspond to each other in the same shape and size.

The plurality of first regions R11 to R14 are preferably regions of the same shape and size, but may be regions having different shapes and sizes, or both. The same applies to the plurality of second regions R21 to R24 and the plurality of third regions R31 to R34. The first uneven patterns P11 to P14 may be the same pattern or different patterns, but it is preferable that the process rules are the same. The same applies to the second uneven pattern P21 to P24 and the third uneven pattern P31 to P34.

In this embodiment, a plurality of first images corresponding to the plurality of first regions R11 to R14 are acquired (step S61), and a plurality of second images corresponding to the plurality of second regions R21 to R24 are acquired. (Step S62), a plurality of third images corresponding to the plurality of third regions R31 to R34 are acquired (step S63). Further, a plurality of first binary image data corresponding to the plurality of first images are generated (step S71), and a plurality of second binary image data corresponding to the plurality of second images are generated (step S72). ), A plurality of third binary image data corresponding to each of the plurality of third images are generated (step S73).

Then, based on the plurality of first-value image data, the area of the white region in the plurality of first-valued images is obtained (step S81), the average value thereof is obtained, and the average value is calculated. The first area is A1 (step S101). Similarly, based on the plurality of binary image data, the area of the white region in the plurality of binary images is obtained (step S82), the average value thereof is obtained, and the average value thereof is obtained. Is the second area A2 (step S102). Further, based on the plurality of third-valued image data, the area of the white region in the plurality of third-valued images is obtained (step S83), the average value thereof is obtained, and the average value is calculated. The third area is A3 (step S103).

Using the first, second and third areas A1, A2 and A3 thus obtained, the foreign matter removal rate can be obtained by any of the above formulas (1) to (4).
For the average value calculation, the CPU 41 (see FIG. 3) of the foreign matter removal rate calculation device 4 realizes the function as the average area calculation unit 55 by executing the program 47. The average value calculation may be replaced by a calculation for obtaining the sum of a plurality of areas to be calculated.

If the first substrate W1, the second substrate W2, and the third substrate W3 are photographed at the same magnification by the scanning electron microscope 3, the first area A1 is the first in each of the plurality of first regions R11 to R14. Corresponds (proportional) to the average value of the ratio of the area of the image portion corresponding to the uneven patterns P11 to P14, that is, the average value of the area ratio (first area ratio). Similarly, the second area A2 is the average value of the ratio of the areas of the second uneven patterns P21 to P24 and the image portion corresponding to the foreign matter in each of the plurality of second regions R21 to R24, that is, the average value of the area ratio ( Corresponds to (proportional) to the second area ratio). Similarly, the third area A3 is the average value of the ratio of the areas of the third uneven patterns P31 to P34 and the image portion corresponding to the foreign matter in each of the plurality of third regions R31 to R34, that is, the average value of the area ratio ( Corresponds to (proportional) to the third area ratio).

According to this embodiment, the plurality of first regions R11 to R14, the second regions R21 to R24, and the third regions R31 to R34 are set, and the corresponding plurality of first images, second images, and third images are set. The foreign matter removal rate is obtained based on the average value calculation based on. As a result, the accuracy of evaluation of the foreign matter removing process can be improved. More specifically, since the foreign matter removal performance can be comprehensively evaluated for a plurality of regions dispersed and arranged on the main surface of the substrate W, more appropriate evaluation becomes possible.

Although one embodiment of the present invention has been described above, the present invention can be implemented in still another embodiment.
For example, in the above-described embodiment, the main surfaces of the three substrates W1, W2, and W3 on which the same pattern is formed are photographed by the scanning electron microscope 3. However, when the foreign matter removing performance of the substrate cleaning device 1 is evaluated a plurality of times, it is possible to omit photographing the main surface of the first substrate W in the second and subsequent evaluations. This is because in the first evaluation, information such as the first image, the first binarized image, and the first area corresponding to the first substrate W1 has already been acquired, so that the information can be reused. As long as the evaluation is performed by the same method using the substrate on which the same pattern is formed, the information acquired corresponding to the first substrate W1 is reused for the evaluation of the foreign matter removal performance by another device. can do.

Further, in the above-described embodiment, the main surface of the first substrate W1 is photographed to acquire the first image, and the main surface of the second substrate W2 is photographed to acquire the second image. If the influence of pattern damage due to scanning of electron beams during imaging by the microscope 3 can be tolerated, the main surface of the same substrate may be photographed before and after the substrate contamination step to obtain a first image and a second image, respectively. .. Similarly, the main surface of the same substrate may be photographed before and after the cleaning process step to obtain a second image and a third image, respectively.

The equivalent uneven pattern formed in the first region, the second region, and the third region is preferably the same pattern, but may be different patterns having the same area ratio of the pattern portions. Further, the first region R1, the second region R2, and the third region R3 do not necessarily have to be regions having the same area. In this case, the following equation (1a) or (3a), which is a modification of the above equations (1) and (3), may be used. However, in the formulas (1a) and (3a), the areas of the first region R1, the second region R2, and the third region R3 are represented by their respective symbols.

Foreign matter removal rate = 1-{(A3 / R3-A1 / R1) / (A2 / R2-A1 / R1)} ... (1a)
Foreign matter removal rate = (A2 / R2-A3 / R3) / (A2 / R2-A1 / R1)} ... (3a)
The setting or recognition of the first region, the second region, and the third region may be performed at the time of photographing by the scanning electron microscope 3, but the image data output by the scanning electron microscope 3 is stored in the storage device 42. Even if a part of the image represented by the accumulated image data is set or recognized as a first region, a second region, or a third region, and the first image, the second image, and the third image are extracted. Good. The first region, the second region, and the third region may be set or recognized based on the image data after binarization.

Further, in the above-described embodiment, the binarized image obtained by binarizing the first image, the second image, and the third image is generated, but the first area (the first area (third) without generating the binarized image. 1 area ratio), a second area (second area ratio), and a third area (third area ratio) may be obtained. For example, in the first image data D1, the number of pixels having a brightness equal to or higher than a predetermined threshold value may be counted, and the counting result may correspond to the first area A1. Similarly, values corresponding to the second area A2 and the third area A3 can be obtained based on the second image data D2 and the third image data, respectively.

In addition, various design changes can be made within the scope of the matters described in the claims.

W substrate W1 1st substrate W2 2nd substrate W3 3rd substrate P Concavo-convex pattern P1 1st concavo-convex pattern P2 2nd concavo-convex pattern P3 3rd concavo-convex pattern R1 1st region R2 2nd region R3 3rd region R 1st to 3rd Area of area D1 1st image data D2 2nd image data D3 3rd image data BD1 1st binary image data BD2 2nd binary image data BD3 3rd binary image data 1 Substrate cleaning device 2 Evaluation sample manufacturing device 3 Scanning electron microscope 4 Foreign matter removal rate calculator 10 Chamber 11 Spin chuck 12 Contaminated solution supply unit 13 Rinse solution supply unit 15 Rotating axis 16 Contaminated solution 21 Contaminated solution nozzle 22 Nozzle arm 23 Contaminated solution piping 24 Contaminated solution valve 25 Nozzle moving unit 26 Tank 27 Liquid supply pipe 28 Valve 29 Stirrer 31 Rinse liquid nozzle 32 Rinse liquid pipe 33 Rinse liquid valve 41 CPU
42 Storage device 43 Input device 44 Display 47 Program 48 Data 51 Image data input section 52 Area recognition section 53 Binarization processing section 54 White section Area calculation section 55 Average area calculation section 56 Removal rate calculation section 60 Particles

Claims (16)

This is a foreign matter removal treatment evaluation method for evaluating the foreign matter removal treatment on the main surface of the substrate on which the uneven pattern is formed.
The first image acquisition step of photographing the first region where the first uneven pattern of the main surface of the substrate is formed with an electron microscope and acquiring the first image, and
A substrate main surface including a second region on which a second unevenness pattern equivalent to the first unevenness pattern is formed, and a substrate main surface including a third region on which a third unevenness pattern equivalent to the first unevenness pattern is formed. The substrate contamination process that attaches foreign matter to the
After the substrate contamination step, a second image acquisition step of photographing the second region with an electron microscope to acquire a second image,
After the substrate contamination step, a foreign matter removing treatment step of executing a foreign matter removing treatment for removing the foreign matter on the main surface of the substrate including the third region,
After the foreign matter removal processing step, a third image acquisition step of photographing the third region with an electron microscope to acquire a third image,
A first area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the first uneven pattern in the first image as the first area ratio.
A second area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the second uneven pattern and the foreign matter in the second image as the second area ratio.
A third area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter in the third image as the third area ratio.
A foreign matter removal rate calculation step of calculating the foreign matter removal rate by the foreign matter removal process using the first area ratio, the second area ratio, and the third area ratio.
Foreign matter removal treatment evaluation method including. It further includes a first image binarization step of binarizing the first image to obtain a first binarized image.
The step of acquiring the first area ratio as the first area ratio, based on the first binarized image, the ratio of the area of the image portion corresponding to the first uneven pattern in the first image. The foreign matter removal processing evaluation method according to claim 1. This is a foreign matter removal treatment evaluation method for evaluating the foreign matter removal treatment on the main surface of the substrate on which the uneven pattern is formed.
Acquiring the first area ratio to acquire the first area ratio representing the ratio of the area of the image portion corresponding to the first uneven pattern in the first image representing the first region in which the first uneven pattern of the main surface of the substrate is formed. Process and
A substrate main surface including a second region on which a second unevenness pattern equivalent to the first unevenness pattern is formed, and a substrate main surface including a third region on which a third unevenness pattern equivalent to the first unevenness pattern is formed. The substrate contamination process that attaches foreign matter to the
After the substrate contamination step, a second image acquisition step of photographing the second region with an electron microscope to acquire a second image,
After the substrate contamination step, a foreign matter removing treatment step of executing a foreign matter removing treatment for removing the foreign matter on the main surface of the substrate including the third region,
After the foreign matter removal processing step, a third image acquisition step of photographing the third region with an electron microscope to acquire a third image,
A second area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the second uneven pattern and the foreign matter in the second image as the second area ratio.
A third area ratio acquisition step of acquiring the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter in the third image as the third area ratio.
A foreign matter removal rate calculation step of calculating the foreign matter removal rate by the foreign matter removal process using the first area ratio, the second area ratio, and the third area ratio.
Foreign matter removal treatment evaluation method including. A second image binarization step of binarizing the second image to obtain a second binarized image, and
Further including a third image binarization step of binarizing the third image to obtain a third binarized image.
In the step of acquiring the second area ratio, the ratio of the area of the image portion corresponding to the second uneven pattern and the foreign matter in the second image is calculated based on the second binarized image. It is a process to acquire as
Based on the third binarized image, the step of acquiring the third area ratio is the ratio of the area of the image portion corresponding to the third uneven pattern and the foreign matter in the third image to the third area ratio. The foreign matter removal treatment evaluation method according to any one of claims 1 to 3, which is a step of acquiring the image. The foreign matter removal treatment evaluation method according to any one of claims 1 to 4, wherein the foreign matter removal rate calculation step includes a step of obtaining a value obtained by subtracting the first area ratio from the second area ratio. The foreign matter removal treatment evaluation method according to any one of claims 1 to 5, wherein the foreign matter removal rate calculation step includes a step of obtaining a value obtained by subtracting the first area ratio from the third area ratio. The foreign matter removal treatment evaluation method according to any one of claims 1 to 5, wherein the foreign matter removal rate calculation step includes a step of obtaining a value obtained by subtracting the third area ratio from the second area ratio. The foreign matter removal treatment evaluation method according to any one of claims 1 to 4, wherein the foreign matter removal rate calculation step includes a step of calculating the foreign matter removal rate by the following formula A or B.
Foreign matter removal rate = 1-{(third area ratio-first area ratio) / (second area ratio-first area ratio)} ... A
Foreign matter removal rate = (second area ratio-third area ratio) / (second area ratio-first area ratio) ... B Claims 1 to 1, wherein the main surface of the substrate including the first region is the main surface of the first substrate, and the main surface of the substrate including the second region is the main surface of the second substrate different from the first substrate. 8. The method for evaluating foreign matter removal treatment according to any one of items 8. Claims 1 to 1, wherein the main surface of the substrate including the second region is the main surface of the second substrate, and the main surface of the substrate including the third region is the main surface of the third substrate different from the second substrate. The foreign matter removal treatment evaluation method according to any one of 9. Claims 1 to 10, wherein the first image, the second image, and the third image are images obtained by photographing the first region, the second region, and the third region at the same magnification, respectively. The foreign matter removal treatment evaluation method according to any one item. The second image acquisition step includes a second region recognition step in which a concavo-convex pattern equivalent to that of the first region is formed and a region having the same shape and size as the first region is recognized as the second region.
The third image acquisition step includes a third region recognition step in which a concavo-convex pattern equivalent to the first region is formed and a region having the same shape and size as the first region is recognized as the third region. The foreign matter removal treatment evaluation method according to any one of 1 to 11. A plurality of the first region, the second region, and the third region are set, respectively.
A plurality of the first images corresponding to the plurality of the first regions are acquired, a plurality of the second images corresponding to the plurality of second regions are acquired, and a plurality of the plurality of images corresponding to the plurality of third regions are acquired. The third image is acquired,
The average value of the ratio of the area of the image portion corresponding to the first uneven pattern in each of the plurality of first images is defined as the first area ratio, and the second uneven pattern and the second uneven pattern in each of the plurality of second images. The average value of the area ratio of the image portion corresponding to the foreign matter is defined as the second area ratio, and the average value of the area ratio of the third uneven pattern and the image portion corresponding to the foreign matter in each of the plurality of the third images. The foreign matter removal treatment evaluation method according to any one of claims 1 to 12, wherein is the third area ratio. The foreign matter removal treatment evaluation method according to any one of claims 1 to 13, wherein the substrate contamination step includes a step of applying a contaminated liquid in which foreign matter is dispersed in a liquid to which acid is added to the main surface of the substrate. The method for evaluating a foreign matter removing treatment according to claim 14, wherein the acid is hydrochloric acid. The method for evaluating a foreign matter removing treatment according to claim 14 or 15, wherein the pH of the contaminated liquid is 4 or less.