JP2018028636A - Mask inspection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a mask inspection method by which a defect of a mask can be accurately detected in a short time.SOLUTION: The mask inspection method in accordance with the embodiment of the present invention comprises: irradiating a mask to be inspected with light from a light source; acquiring a first image of the mask to be inspected by use of an optical system having a first numerical aperture; creating a reference image in a calculating part based on image drawing data used for drawing the mask to be inspected; comparing the first image to the reference image in a comparing part to detect a defect candidate portion of the mask to be inspected; acquiring a second image of the defect candidate portion by use of an optical system having a second numerical aperture larger than the first numerical aperture; and comparing the second image to the reference image in the comparing part to identify a defect portion of the mask to be inspected.SELECTED DRAWING: Figure 2

Description

  Embodiments according to the present invention relate to a mask inspection method.

  2. Description of the Related Art Conventionally, a mask inspection apparatus images a mask drawing pattern using an optical system having a relatively high resolution, and performs a mask defect inspection using a high-resolution image obtained thereby. Further, after correcting the detected defect, the mask inspection apparatus similarly obtains a high-resolution image and re-inspects the mask. Such a high resolution inspection makes it possible to detect relatively small defects.

  On the other hand, the number of pixels of the photodiode array of the mask inspection apparatus is determined to be a predetermined value, and the number of pixels of an image that can be acquired at one time is equal regardless of the resolution of the optical system. For this reason, the high resolution optical system can only capture an area in a smaller range than the low resolution optical system.

JP-A-4-321047

  As described above, the high-resolution image becomes an image of a small area as compared with the low-resolution image. Therefore, in the conventional high resolution inspection, it is difficult to detect a defect over a relatively large area or a large size defect. For example, a defect (transmittance abnormal defect) whose transmittance gradually changes in the plane of the mask may have a change in transmittance that is too small in a narrow imaging region by high-resolution inspection. In this case, the change in transmittance is less than the defect determination threshold, and the mask inspection apparatus cannot detect an abnormality in the high-resolution inspection.

  In addition, since the imaging area that can be acquired at a time is small in the high-resolution inspection, it takes a long time to image the entire mask. Therefore, the conventional inspection method has a problem that the inspection takes a long time.

  SUMMARY OF THE INVENTION An object of the present invention is to provide a mask inspection method capable of accurately detecting a mask defect in a short time.

  The mask inspection method according to the present embodiment is used for drawing a mask to be inspected by irradiating the mask to be inspected with light from a light source, obtaining a first image of the mask to be inspected using an optical system having a first numerical aperture. A reference image is created by the calculation unit based on the drawing data, the first image and the reference image are compared by the comparison unit to detect a defect candidate portion of the mask to be inspected, and a second numerical aperture larger than the first numerical aperture A second image of a defect candidate location is obtained using an optical system having the above, and the defect location of the mask to be inspected is specified by comparing the second image with a reference image by a comparison unit.

  In creating the reference image, the calculation unit may create the reference image by processing the drawing data so that the pattern of the reference image approaches the pattern of the first image.

  In creating the reference image, the calculation unit generates difference data between the drawing data and the transfer pattern data estimated from the exposure conditions when transferring the pattern of the mask to be inspected, and corresponds to the difference data among the drawing data. The reference image may be created by determining the filter coefficient so that the degree of processing of the part is larger than that of the other parts, and processing the drawing data using the filter coefficient.

  In creating the reference image, the calculation unit generates difference data between the drawing data and the design data before the optical proximity effect correction, and the portion corresponding to the difference data in the drawing data is processed with a higher degree of processing than the other portions. The reference coefficient may be created by determining the filter coefficient so as to increase and processing the drawing data using the filter coefficient.

  The second image includes a transmission image and a reflection image of the mask to be inspected, and the defect portion is specified by both comparing the transmission image of the mask to be inspected with the reference image and comparing the reflection image of the mask to be inspected with the reference image. The method may include estimating the defect detected in step 5 as a pseudo defect.

Schematic which shows an example of the mask inspection apparatus of 1st Embodiment. The flowchart which shows an example of the mask inspection method by 1st Embodiment. The flowchart which shows an example of the creation process of the reference image by 1st Embodiment. The conceptual diagram which shows an example of the creation process of the reference image by 1st Embodiment. The graph which shows an example of a low-resolution image, and the change of the transmittance | permeability. The graph which shows an example of a high-resolution image, and the change of the transmittance | permeability. The flowchart which shows an example of the mask inspection method by 2nd Embodiment. The flowchart which shows an example of the mask inspection method by 4th Embodiment.

  Embodiments according to the present invention will be described below with reference to the drawings. This embodiment does not limit the present invention.

(First embodiment)
FIG. 1 is a schematic diagram illustrating an example of a mask inspection apparatus according to the first embodiment. The mask inspection apparatus 100 can be used, for example, to inspect a pattern defect of an optical mask (hereinafter also simply referred to as a mask).

(Configuration of mask inspection system)
The mask inspection apparatus 100 includes an XYθ table 2, a light source 3, a polarization beam splitter 4, a transmission optical system 5, a reflection optical system 6, a photodiode array 8, an autoloader 9, an X-axis motor 10A, and a Y-axis. A motor 10B, a θ-axis motor 10C, a laser length measurement system 12, and an objective lens switching mechanism 13 are provided.

  The XYθ table 2 can place a mask 1 as a mask to be inspected thereon, and can move in, for example, an X direction, a Y direction, and a θ direction in a horizontal plane. The mask 1 is a photomask used in a photolithography process of a semiconductor manufacturing process, and has a pattern to be transferred to a wafer or a layer thereon. The drawing pattern drawn on the mask 1 is a pattern including optical proximity correction (OPC), and may be different from the transfer pattern transferred to the wafer or the like.

  The light source 3 emits laser light toward the polarization beam splitter 4. Note that light used for pattern defect inspection, that is, inspection light may be laser light. The polarization beam splitter 4 reflects the light from the light source 3 toward the transmission optical system 5 and the reflection optical system 6.

  The transmission optical system 5 includes a mirror 5a and objective lenses 5b_1, 5b_2, 5c_1, and 5c_2. The mirror 5a reflects the light transmitted through the polarization beam splitter 4 to the objective lens 5b_1 or 5b_2. The reflected light from the mirror 5a is irradiated toward the XYθ table 2 through the objective lens 5b_1 or 5b_2. The mask 1 placed on the XYθ table 2 transmits light from the objective lens 5b_1 or 5b_2. The light transmitted through the mask 1 enters the photodiode array 8 via the objective lens 5c_1 or 5c_2. The objective lens 5c_1 or 5c_2 forms the incident transmitted light of the mask 1 on the photodiode array 8 as an image of the mask 1 (hereinafter also referred to as a transmitted image). The photodiode array 8 photoelectrically converts the optical image of the mask 1. Based on the optical image of the mask 1 subjected to photoelectric conversion, the defect of the mask 1 is inspected.

  Here, the first transmission optical system using the objective lenses 5b_1 and 5c_1 has a first numerical aperture NA1, and the second transmission optical system using the objective lenses 5b_2 and 5c_2 has a second numerical aperture NA2. The objective lens switching mechanism 13 performs switching between the objective lenses 5b_1 and 5b_2 and switching between the objective lenses 5c_1 and 5c_2. For example, when the first numerical aperture NA1 is smaller than the second numerical aperture NA2, the image acquired using the first transmission optical system is a low resolution image, and the image acquired using the second transmission optical system is high. It becomes a resolution image. As described above, the mask inspection apparatus 100 includes a plurality of objective lens sets (5b_1, 5c_1) and (5b_2, 5c_2) having different numerical apertures. By switching the objective lens sets, transmission images having different resolutions can be obtained. Can be acquired.

  The reflective optical system 6 includes a mirror 6a, a polarizing beam splitter 6b, and objective lenses 6c and 6d. The mirror 6a reflects the light reflected by the polarization beam splitter 4 to the polarization beam splitter 6b. The polarization beam splitter 6b irradiates the reflected light from the mirror 6a toward the XYθ table 2 through the objective lens 6c. The mask 1 placed on the XYθ table 2 reflects the light from the polarization beam splitter 6b. The reflected light of the mask 1 passes through the polarization beam splitter 6b and enters the photodiode array 8 through the objective lens 6d. The objective lens 6 d forms the incident reflected light of the mask 1 on the photodiode array 8 as an image of the mask 1 (hereinafter also referred to as a reflected image). The photodiode array 8 photoelectrically converts the optical image of the mask 1. Based on the optical image of the mask 1 subjected to photoelectric conversion, the defect of the mask 1 is inspected.

  The reflection optical system 6 using the objective lens 6c is an optical system that can acquire a high-resolution image, and has a relatively large numerical aperture (second numerical aperture NA2). Thus, the mask inspection apparatus 100 further includes one objective lens pair (6c, 6d), and can acquire a high-resolution reflection image. The mask inspection apparatus 100 may further include a reflection optical system (not shown) having a small numerical aperture so that a low-resolution reflection image can be acquired.

  As described above, the objective lens switching mechanism 13 receives instructions from the objective lens control circuit 16 in order to change the numerical apertures NA1 and NA2, and sets the objective lenses (5b_1, 5c_1), (5b_2) of the transmission optical system 5. 5c_2). In the mask inspection method according to the present embodiment, a defect inspection (first inspection) of the mask 1 is executed using a low resolution image acquired by a first transmission optical system (for example, 5b_1, 5c_1) having a low numerical aperture. Next, the objective lens switching mechanism 13 switches to a second transmission optical system (for example, 5b_2, 5c_2) having a high numerical aperture, and uses the high-resolution image acquired by the second transmission optical system to perform defect inspection ( The second inspection) is further performed. The defect inspection using the reflection image acquired by the reflection optical system 6 is executed as necessary. Details of the mask inspection method will be described later (see the fourth embodiment).

  The autoloader 9 automatically transports the mask 1 on the XYθ table 2 or automatically collects the mask 1 on the XYθ table 2 in accordance with a command from the autoloader control circuit 15. The X-axis motor 10A, the Y-axis motor 10B, and the θ-axis motor 10C move the XYθ table 2 in the X direction, the Y direction, and the θ direction (the rotation direction in the XY plane (substantially horizontal plane)), respectively. Thereby, the light of the light source 3 is scanned with respect to the mask 1 on the XYθ table 2. The laser length measurement system 12 detects the positions of the XYθ table 2 in the X direction and the Y direction.

  The mask inspection apparatus 100 includes a control computer 30, an emulation circuit 14, an autoloader control circuit 15, an objective lens control circuit 16, a table control circuit 17, an autofocus control circuit 18, a sensor circuit 19, A position circuit 22 and a comparison circuit 25 are provided.

  The control computer 30 is connected to the circuit via the bus 20 and executes various controls related to the defect inspection of the mask 1.

  The autoloader control circuit 15 controls the autoloader 9. The table control circuit 17 controls driving of the motors 10A to 10C. The motors 10A to 10C move the XYθ table 2 so that the light from the light source 3 scans the mask 1.

  The autofocus control circuit 18 controls the XYθ table 2 so as to perform focusing. For example, the autofocus control circuit 18 moves the XYθ table 2 in the Z direction based on a focus signal corresponding to the height of the sensor surface detected by a Z sensor (not shown).

  The sensor circuit 19 captures the optical image photoelectrically converted by the photodiode array 8 and A / D converts the captured optical image. Then, the sensor circuit 19 outputs the A / D converted optical image to the comparison circuit 25. The sensor circuit 19 may be, for example, a TDI (Time Delay Integration) sensor circuit. By using the TDI sensor, the pattern of the mask 1 can be imaged with high accuracy.

  The laser length measurement system 12 detects the movement position of the XYθ table 2 and outputs the detected movement position to the position circuit 22. The position circuit 22 detects the position of the mask 1 on the XYθ table 2 based on the movement position input from the laser length measurement system 12. The position circuit 22 outputs the detected position of the mask 1 to the comparison circuit 25.

    The emulation circuit 14 serving as a calculation unit reads drawing data used for drawing the mask 1 and creates a reference image based on the drawing data. The drawing data may be information such as the coordinates of the figure representing the mask 1, the length of the side, and the type, and is design data including optical proximity effect correction (OPC) in consideration of the optical proximity effect. The drawing data may be read from a magnetic disk device 31 described later. The reference image is image data obtained by simulating the transfer pattern on the wafer from the drawing data using the exposure conditions for transferring the pattern of the mask 1 onto the wafer. That is, the reference image is an image obtained by emulating an exposure process from drawing data of a transfer pattern. Details of the emulation processing will be described later. Note that the emulation circuit 14 may be configured to be able to execute a developing process for converting drawing data into binary or multi-valued image data and a filter process other than the above emulation.

  The comparison circuit 25 measures the line width of each position of the optical image obtained from the sensor circuit 19 while using the position information input from the position circuit 22. The comparison circuit 25 compares the line width and gradation value (brightness) of both the measured optical image and the reference image input from the emulation circuit 14. For example, the comparison circuit 25 detects an error between the pattern of the optical image and the pattern of the reference image as a defect of the mask 1.

  The mask inspection apparatus 100 further includes a control computer 30, a magnetic disk device 31, a magnetic tape device 32, a floppy (registered trademark) disk device 33, a CRT 34, a pattern monitor 35, and a printer 36. These components 30 to 36 are all connected to the bus 20. The control computer 30 executes various types of control and processing related to the defect inspection of the mask 1 for each component connected to the bus 20. The magnetic disk device 31, the magnetic tape device 32, and the floppy disk 33 store various types of information related to defect inspection. The CRT 34 and the pattern monitor 35 display various images related to defect inspection. The printer 36 prints various information related to defect inspection.

(Mask inspection method)
Next, a mask inspection method using the mask inspection apparatus 100 will be described.

  FIG. 2 is a flowchart showing an example of the mask inspection method according to the first embodiment. In this embodiment, the mask inspection apparatus 100 performs a D-DB (Dieto DataBase) inspection that inspects a defect of the mask 1 by comparing a transmission image with a reference image.

(First inspection)
First, the autoloader 9 loads the mask 1 onto the XYθ table 2, and the XYθ table 2 performs alignment of the mask 1 (S10).

  Next, in order to perform a 1st test | inspection, the setting of an optical system and the setting of imaging conditions are performed (S20). In the first inspection, a defect inspection is performed using a low-resolution image close to the transfer pattern. The imaging conditions are, for example, the conditions of the light that irradiates the mask 1 such as the light amount, the numerical aperture, and the aperture shape of the transmission optical system 5. In the present embodiment, the objective lens switching mechanism 13 selects an objective lens (5b_1, 5c_1) having a relatively small numerical aperture among the objective lenses of the transmission optical system 5. Thereby, the mask 1 is imaged by the first transmission optical system having the relatively small first numerical aperture NA1. For example, the imaging conditions of the first transmission optical system are conditions that follow (equal to) the exposure conditions (for example, light quantity, numerical aperture, aperture shape, etc.) when the pattern of the mask 1 is transferred to a resist or the like on the wafer. May be.

  Next, an optical image of the mask 1 is taken (S30). For example, the mask inspection apparatus 100 virtually divides the inspection area of the mask 1 into stripes, and scans light from the optical system along the stripes. The transmitted light from the mask 1 is photoelectrically converted by the photodiode array 8, and the transmitted image of the mask 1 is acquired by the sensor circuit 19. A transmission image (first image) captured by the first transmission optical system is an image having a relatively low resolution (low resolution image). The low resolution image is an image close to the transfer pattern transferred to the wafer by the exposure process. That is, the low-resolution image is an image close to the actual transfer pattern, with the outer edge of the drawing pattern somewhat blurred and the corners rounded.

  On the other hand, in parallel with or before and after steps S20 and S30, the emulation circuit 14 receives the drawing data of the mask 1 from the database such as the magnetic disk device 31 and creates a reference image emulating the exposure conditions (S40). . Note that the emulator circuit 14 may create a reference image of the portion in real time while the photodiode array 8 is imaging a certain stripe on the mask 1.

  Here, the drawing data is design data including OPC, and is data of a pattern (drawing pattern) to be actually drawn on the mask 1. That is, the drawing data is not design data that does not include OPC (pre-OPC data) but design data that includes OPC (post-OPC data). Since the pattern according to the pre-OPC data (pre-OPC pattern) does not include OPC, it is almost equal to the transfer pattern to be transferred to the wafer in the exposure process. On the other hand, a pattern according to post-OPC data (post-OPC pattern) is a drawing pattern drawn on the mask 1 in consideration of the optical proximity effect in the exposure process. For this reason, the drawing pattern of the mask 1 is different from the transfer pattern to the wafer and the low resolution image.

  Therefore, the emulation circuit 14 as a calculation unit generates a reference image by filtering the drawing data in order to emulate (simulate) the exposure conditions in the wafer exposure process. This filtering process is also referred to as a reference image learning process. In this way, by emulating exposure conditions by the reference image learning step, a reference image close to the transfer pattern (pre-OPC pattern) can be obtained.

  However, on the other hand, the low-resolution image is close to the transfer pattern (that is, the pre-OPC pattern), but is somewhat different from the pre-OPC pattern. Therefore, when a defect inspection is performed using a reference image obtained by simply emulating exposure conditions as it is, a large number of pseudo defects may occur. The pseudo defect is a pseudo defect that is detected due to a difference between the reference image and the optical image even though it is not a defect of the mask 1. In order to reduce such pseudo defects, a reference image with high accuracy (that is, closer to a low resolution image) is required.

  Therefore, the emulator circuit 14 according to the present embodiment processes the drawing data to create a reference image in order to further approximate the drawing pattern to the low resolution image. The reference image creation process (reference image learning step) according to the present embodiment will be described in more detail with reference to FIG.

  FIG. 3 is a flowchart showing an example of a reference image creation process (step S40) according to the first embodiment. 4A to 4D are conceptual diagrams illustrating an example of reference image creation processing according to the first embodiment.

  First, the emulation circuit 14 acquires or creates drawing data and transfer data (S41). FIG. 4A shows a drawing pattern (post-OPC pattern) according to drawing data including OPC. Of the drawing patterns 110 and 120, 110 is an OPC pattern, and 120 excluding the OPC pattern is a transfer pattern. The drawing data is stored in advance in the magnetic disk device 31 or the like, and the emulator circuit 14 may acquire the drawing data from the magnetic disk device 31 or the like.

  FIG. 4B shows a transfer pattern (pre-OPC pattern) according to the transfer data. Since the transfer pattern does not include the OPC pattern, only the transfer pattern 120 is shown in FIG. 4B, and the OPC pattern 110 is not shown. When pre-OPC data is not available, the transfer data may be image data obtained by simply emulating exposure conditions by the reference image learning step. In this case, the emulation circuit 14 may generate transfer data from the drawing data by emulating the drawing data in advance according to the exposure conditions. The filter coefficient used for the emulation at this time does not include the weighting described later. When pre-OPC data is available, the pre-OPC data may be used as transfer data as in the third embodiment.

  Next, the emulation circuit 14 generates difference data between the drawing data shown in FIG. 4A and the transfer data shown in FIG. 4B (S43). For example, the emulation circuit 14 can obtain difference data by performing a logical operation (for example, exclusive OR XOR) on the drawing data and the transfer data. FIG. 4C shows a difference pattern according to the difference data. This difference pattern results in the OPC pattern 110. Therefore, hereinafter, the OPC pattern 110 is also referred to as a difference pattern 110.

  Next, the emulation circuit 14 performs weighting so as to increase the filter coefficient of the part corresponding to the difference data among the filter coefficients used in the reference image learning step (S45). The filter coefficient is a coefficient indicating the degree of processing applied to the drawing pattern such as blurring processing, rounding processing, line width adjustment, and the like. The blurring process is a process of blurring the outer edge of the drawing pattern, and the rounding process is a process of rounding a corner portion of the drawing pattern with a certain curvature. The weighting is to change the filter coefficient corresponding to the predetermined area in order to increase the degree of processing of the predetermined area in the drawing pattern. The emulation circuit 14 according to the present embodiment weights the difference data and changes (for example, increases) the filter coefficient corresponding to the difference data. Thus, the emulation circuit 14 determines the filter coefficient so that the degree of processing of the portion corresponding to the difference data in the drawing data is larger than that of the other portions.

  Next, the emulation circuit 14 processes the drawing data using the filter coefficient determined in step S45 (reference image learning step). Thereby, a reference image is created (S47). At this time, the emulation circuit 14 may use a weighted filter coefficient for the portion corresponding to the difference data in the drawing data and use a weighted filter coefficient for the other portion. As a result, the reference image is largely processed in the portion corresponding to the difference data, and is substantially equal to the transfer pattern in the other portions. FIG. 4D is a conceptual diagram illustrating a reference image after the reference image learning process according to the present embodiment. As shown in FIG. 4D, the reference image according to the present embodiment is largely processed in the portion 115 corresponding to the difference pattern (that is, the OPC pattern), and is substantially equal to the transfer pattern in the other portion 120. The reference image created in this way can be brought closer to a low-resolution image than the transfer pattern itself shown in FIG. That is, the mask inspection apparatus 100 according to the present embodiment can perform reference image learning using a filter coefficient that weights a different portion of a low-resolution image that is slightly different from a transfer pattern (pre-OPC pattern). By performing the process, a reference image approximated by a low resolution image can be created. As a result, pseudo defects can be reduced in die-database (D-DB) inspection using low-resolution images.

  Note that the portion of the drawing data to be weighted may be arbitrarily changed so that the reference image matches the low resolution image. That is, in the above example, the difference data (OPC data) 110 is weighted, but in addition or alternatively, a specific location obtained empirically or statistically may be weighted. In this case, the specific part is stored in advance in the magnetic disk device 31 or the like, and the emulation circuit 14 executes the weighting (step S45) and the reference image learning step (step S47) by including the specific part in the difference data. do it.

  Further, the emulation circuit 14 may further convert the reference image into binary or multivalued image data so that the reference image and the low resolution image can be compared. Further, the emulation circuit 14 may further perform other filter processing on the reference image as necessary.

  Referring again to FIG. 2, the comparison circuit 25 receives the low resolution image and the reference image, and compares the low resolution image with the reference image (S50). At this time, the comparison circuit 25 receives the low resolution image from the sensor circuit 19 and receives the reference image from the emulation circuit 14. The comparison circuit 25 compares the low-resolution image with the reference image using the position information input from the position circuit 22 and detects the error as a defect candidate of the mask 1 (S60). The comparison circuit 25 performs comparison processing for each imaging region (frame) of the photodiode array 8. The frame is an image unit that can be captured by the photodiode array 8 at a time. The defect candidate image and the defect candidate location (coordinates) may be stored in the magnetic disk device 31 or the like or displayed on the CRT 34. As described above, since the reference image is an image approximated by a low-resolution image, pseudo defects included in the defect candidates can be reduced.

(Second inspection)
Next, in order to perform the second inspection, an optical system and imaging conditions are set (S70). In the second inspection, the mask inspection apparatus 100 uses the second transmission optical system having the second numerical aperture NA2 larger than the first numerical aperture NA1 of the first transmission optical system, and uses the second transmission optical system (second resolution). Image). In the second inspection, the objective lens switching mechanism 13 switches the objective lens of the transmission optical system 5 from the objective lens (5b_1, 5c_1) to the objective lens (5b_2, 5c_2). Thereby, the defect candidate of the mask 1 is imaged by the second transmission optical system having the relatively large second numerical aperture NA2.

  Next, an optical image of a defect candidate portion of the mask 1 is taken (S80). At this time, the mask inspection apparatus 100 only needs to capture an image of a defect candidate of the mask 1, and does not need to capture the entire drawing pattern of the mask 1. Therefore, although the image range of each frame is small, only the defect candidate portion needs to be imaged, so the time required for the second inspection can be shorter than that for acquiring a high-resolution image of the entire drawing pattern. The transmission image (second image) captured by the second transmission optical system is an image having a relatively high resolution (high resolution image), and is an image close to the drawing pattern drawn on the mask 1.

  Next, the comparison circuit 25 receives the high resolution image and the drawing data, and compares the high resolution image with the reference image (drawing pattern) (S90). At this time, the comparison circuit 25 receives a high-resolution image from the sensor circuit 19 and receives a drawing pattern as a reference image from the emulation circuit 14. The comparison circuit 25 compares the defect candidate image of the high-resolution image with the defect candidate image of the drawing pattern using the position information of the defect candidate location, and specifies the error as a defect of the mask 1 (S100). The detected defect image and defect location (coordinates) may be stored in the magnetic disk device 31 or the like, or displayed on the CRT 34. The second inspection can identify a high resolution image of the defect and the exact location of the defect. The high-resolution image of the identified defect and the position of the defect may be displayed on the CRT 34 or printed by the printer 36.

  After the operator confirms (reviews) the defect of the mask 1 and corrects the defect with a correction machine, the mask inspection apparatus 100 performs the first inspection (steps S10 to S60) again (S110). That is, the mask inspection apparatus 100 acquires again the low-resolution image of the mask 1 after correction, and compares the low-resolution image again with the reference image created by the reference image learning process in step S40. The mask inspection apparatus 100 detects again a defect candidate portion of the mask 1 after correction. Thereby, it can be confirmed that the defect of the mask 1 is corrected. As the reference image, the reference image created in step S40 of the first first inspection may be used as it is. If the defect candidate is a pseudo defect, the defect candidate portion is stored in advance in the magnetic disk device 31 or the like after step S100 or after review by the operator, and detected in step S110 of the reinspection. It may be set so that it is not. Thereby, in the re-inspection, a more accurate defect inspection excluding the pseudo defect portion can be performed.

  As described above, the mask inspection method according to the present embodiment performs the D-DB inspection using the low-resolution image in the first inspection, detects the defect candidate portion, and then detects the high resolution of the defect candidate portion in the second inspection. A D-DB inspection is performed using an image, and a defective portion is specified. The first numerical aperture NA1 of the first transmission optical system used for the first inspection is smaller than the second numerical aperture NA2 of the second transmission optical system used for the second inspection. However, the number of pixels (number of pixels) of the photodiode array 8 is constant (for example, 512 × 512 pixels) regardless of the numerical aperture. Therefore, as described above, the photodiode array 8 can capture a relatively wide region with one imaging when the first transmission optical system is used, but can perform one imaging with the second transmission optical system. Only a relatively narrow area can be imaged.

  For example, FIG. 5A and FIG. 5B are graphs showing an example of the imaging region R1 of the low-resolution image and the change in the transmittance, respectively. 6A and 6B are graphs showing an example of the imaging region R2 of the high-resolution image and the change in the transmittance, respectively. The high resolution image in FIG. 6A corresponds to the image of the broken line frame R2 in the low resolution image in FIG. That is, the high resolution image may be said to be an enlarged image of the broken line frame R2 of the low resolution image. 5B and 6B, the vertical axis represents the transmittance of the mask 1, and the horizontal axis represents the position of the image.

  As described above, the comparison process is executed for each imaging region of the photodiode array 8. Therefore, when the imaging region R1 is wide as in the low resolution image of FIG. 5A, the mask inspection apparatus 100 can easily detect the abnormal transmittance defect over a wide area. For example, in the low-resolution image, the change in transmittance from positions P1 to P2 in FIG. In this case, the change in transmittance tends to exceed the defect determination threshold, and the mask inspection apparatus 100 can detect the defect. On the other hand, when the imaging region R2 is narrow as in the high-resolution image of FIG. 6A, the mask inspection apparatus 100 cannot easily detect the abnormal transmittance defect. For example, in a high-resolution image, the change in transmittance from positions P11 to P12 in FIG. 6B is relatively small. In this case, it is difficult for the change in transmittance to exceed the defect determination threshold, and it becomes difficult for the mask inspection apparatus 100 to detect the defect.

  First, since the mask inspection apparatus 100 according to the present embodiment performs D-DB inspection using a low-resolution image in the first inspection, it easily detects a wide-area defect such as an abnormal transmittance defect or a large size defect. be able to.

  In addition, a low-resolution image can be acquired in a short time because the area that can be imaged at one time is wide, but a high-resolution image takes a long time to acquire because the area that can be imaged at a time is narrow. In the present embodiment, an image of the entire drawing pattern of the mask 1 is acquired in the first inspection, but the image is a low resolution image. Therefore, it takes less time than acquiring a high-resolution image of the drawing pattern in the first inspection. Moreover, although this embodiment acquires a high-resolution image in a 2nd test | inspection, the image of only the image of a defect candidate location is acquired. Therefore, in this embodiment, the inspection time of the second inspection is also short. Therefore, this embodiment can shorten the time of the entire mask inspection.

  In addition, a high-resolution image remains for a portion specified as a defect. Therefore, the defect location (coordinates) can be specified accurately, and the defect can be easily confirmed and corrected.

(Second Embodiment)
FIG. 7 is a flowchart showing an example of the mask inspection method according to the second embodiment. In the first embodiment, the mask inspection apparatus 100 captures an image of the entire drawing pattern of the mask 1 in the first inspection, and detects a defect candidate portion for the entire drawing pattern. On the other hand, in the second embodiment, the mask inspection apparatus 100 selectively inspects a portion that is easy to detect with a low resolution image and easily causes a defect in the first inspection. For example, a location where a defect is likely to occur in a region wider than a predetermined region (hereinafter also referred to as a defect estimated location) such as an abnormal transmittance defect, a T-shaped butting pattern, and a large size defect is empirically based on drawing data. Alternatively, it can be statistically estimated. The T-butting pattern is, for example, a pattern in which one end of another straight line faces the side surface of the straight line and has a T shape. The defect estimation part may be called a so-called high MEEF (Mask Error Enhancement Factor) part. In the second embodiment, such a defect estimation portion is stored in advance in the magnetic disk device 31 or the like. In the first inspection, the mask inspection apparatus 100 selectively images a defect estimation portion in the drawing pattern (S31).

  Thereafter, the comparison circuit 25 selectively compares the low-resolution image with the reference image for the estimated defect location (S51).

  Other steps of the mask inspection method according to the second embodiment may be the same as the corresponding steps of the first embodiment. Therefore, the reference image generation method and the second inspection according to the second embodiment may be the same as those of the first embodiment.

  According to the second embodiment, in the first inspection, the mask inspection apparatus 100 captures only a defect estimation portion estimated to be likely to cause a defect in the drawing pattern, and the low-resolution image and the reference image are detected at the defect estimation portion. Compare Therefore, the inspection time can be further shortened.

(Third embodiment)
In the first embodiment, the emulation circuit 14 uses image data obtained by simply emulating exposure conditions for drawing data as transfer data in the reference image learning step. On the other hand, in the third embodiment, the emulation circuit 14 may use pre-OPC data (design data before OPC that does not include OPC) as transfer data in the reference image learning step. In this case, the pre-OPC data is stored in advance in the magnetic disk device 31 and the like in the same manner as the drawing data, and the emulator circuit 14 acquires the pre-OPC data from the magnetic disk device 31 and the like. The other steps of the third embodiment may be the same as the corresponding steps of the first embodiment. The flow of the mask inspection method according to the third embodiment is the same as that shown in FIG.

  Thus, when pre-OPC data is available, the emulation circuit 14 may execute the reference image learning step using the pre-OPC data as transfer data. The third embodiment can obtain the same effects as those of the first embodiment.

(Fourth embodiment)
FIG. 8 is a flowchart showing an example of the mask inspection method according to the fourth embodiment. In the first embodiment, the high-resolution image in the second inspection is a transmission image acquired using the second transmission optical system. In the fourth embodiment, the high-resolution image in the second inspection includes not only the transmission image acquired using the second transmission optical system but also the reflection image acquired using the reflection optical system 6.

  For example, similarly to FIG. 2, after capturing a high-resolution transmission image using the second transmission optical system in steps S70 and S80, the objective lens switching mechanism 50 changes the optical system to the second transmission optical system (5a, 5a, 5b_2, 5c_2) is switched to the reflective optical system 6 (S81).

  Next, similarly to steps S70 and S80, the optical system and the imaging conditions are set (S83), and an optical image (high resolution image) of the defect candidate portion is captured (S85). Thereby, the mask inspection apparatus 100 acquires a high-resolution reflection image.

  Thereafter, steps S90 and S100 are performed for both the high-resolution transmission image and the reflection image. Thereby, for example, when a defect is detected in both the transmission image and the reflection image, it is considered that the quality of the reference image is not good. Therefore, the mask inspection apparatus 100 determines that it is a pseudo defect candidate. In this case, when the operator reviews the defect of the mask 1, it is only necessary to confirm whether or not the pseudo defect candidate is a defect of the mask 1. On the other hand, if a defect is detected in either the transmission image or the reflection image, the mask inspection apparatus 100 determines that the defect is a candidate defect location.

  The other steps of the fourth embodiment may be the same as the corresponding steps of the first embodiment. Therefore, the fourth embodiment can obtain the same effect as the first embodiment.

  In the first to fourth embodiments, the D-DB comparison inspection is performed. However, these embodiments can also be applied to die-to-die comparison inspection (DD inspection). In this case, the mask inspection apparatus performs a DD comparison inspection using the low resolution image to detect a defect candidate location, and then executes a DD comparison inspection using the high resolution image to identify the defect location. Identify. In this case, it is not necessary to create a reference image. Thus, even if this embodiment is applied to die-to-die comparison inspection (DD inspection), the effect of this embodiment is not lost. Moreover, you may combine the said 1st-4th embodiment arbitrarily.

  At least a part of the mask inspection method according to the present embodiment may be configured by hardware or software. When configured by software, a program for realizing at least a part of the functions of the mask inspection method may be stored in a recording medium such as a flexible disk or a CD-ROM, and read and executed by a computer. The recording medium is not limited to a removable medium such as a magnetic disk or an optical disk, but may be a fixed recording medium such as a hard disk device or a memory. Further, a program that realizes at least a part of the functions of the mask inspection method may be distributed via a communication line (including wireless communication) such as the Internet. Further, the program may be distributed in a state where the program is encrypted, modulated or compressed, and stored in a recording medium via a wired line such as the Internet or a wireless line.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 100 ... Mask inspection apparatus, 1 ... Mask, 2 ... XYtheta table, 3 ... Light source, 4 ... Polarization beam splitter, 5 ... Transmission optical system, 6 ... Reflection optical system 8 ... Photodiode array, 9 ... Autoloader, 10A ... X-axis motor, 10B ... Y-axis motor, 10C ... θ-axis motor, 12 ... Laser measurement system, 13. .. Objective lens switching mechanism, 14 ... Emulation circuit, 15 ... Autoloader control circuit, 16 ... Objective lens control circuit, 17 ... Table control circuit, 18 ... Autofocus control circuit, 19 ... Sensor circuit, 22 ... Position circuit, 25 ... Comparison circuit, 30 ... Control computer

Claims (5)

Irradiate the mask to be inspected with light from the light source,
Obtaining a first image of the mask to be inspected using an optical system having a first numerical aperture;
Based on the drawing data used for drawing the mask to be inspected, a reference image is created by the calculation unit,
The first image and the reference image are compared by a comparison unit to detect a defect candidate location of the inspection mask,
Obtaining a second image of the defect candidate location using an optical system having a second numerical aperture greater than the first numerical aperture;
A mask inspection method comprising: comparing the second image and the reference image with the comparison unit to identify a defective portion of the mask to be inspected.   2. The mask inspection according to claim 1, wherein in the creation of the reference image, the calculation unit creates the reference image by processing the drawing data so that the pattern of the reference image approaches the pattern of the first image. Method. In creating the reference image, the calculation unit includes:
Generate difference data between the drawing data and transfer pattern data estimated from exposure conditions when transferring the pattern of the mask to be inspected,
The filter coefficient is determined so that the degree of processing of the portion corresponding to the difference data in the drawing data is greater than that of the other portions,
The mask inspection method according to claim 1, wherein the reference image is created by processing the drawing data using the filter coefficient. In creating the reference image, the calculation unit includes:
Generate difference data between the drawing data and design data before optical proximity correction,
The filter coefficient is determined so that the degree of processing of the portion corresponding to the difference data in the drawing data is greater than that of the other portions,
The mask inspection method according to claim 1, wherein the reference image is created by processing the drawing data using the filter coefficient. The second image includes a transmission image and a reflection image of the inspection mask,
The defect location is specified by estimating a defect detected by both a comparison between the transmission image of the inspection mask and the reference image and a comparison between the reflection image of the inspection mask and the reference image as a pseudo defect. The mask inspection method according to claim 1, comprising:

Images