Mask defect detection method, device and machine table

Abstract

The invention relates to the technical field of integrated circuits, in particular to a mask defect detection method and device and a machine table. The method comprises the following steps: acquiring first to-be-detected defect information of a to-be-detected defect of a target mask; obtaining a preset defect list, wherein the preset defect list comprises multiple pieces of preset defect information; searching the first to-be-detected defect information in a preset defect list; and when the first to-be-detected defect information of the to-be-detected defect is recorded in the preset defect list, filtering the first to-be-detected defect information. A defect white list is obtained by setting a preset defect list. Afterwards, by determining whether the first to-be-detected defect information of the to-be-detected defect is located in the preset defect list, whether the to-be-detected defect affects the normal process of the target mask can be rapidly determined. Furthermore, under the condition that the first to-be-detected defect information of the to-be-detected defect is recorded in the preset defect list, it is considered that the to-be-detected defect does not affect normal use of the mask, the first to-be-detected defect information can be filtered, and the detection machine does not give an alarm.

Description

Technical Field

[0001] The present application relates to the technical field of integrated circuits, and in particular to a method, apparatus and machine for detecting mask defects. Background Art

[0002] In the actual production of semiconductor devices, masks are frequently used. This makes it inevitable that defects (Particles) will fall on the film surface of the mask. This will affect the normal lithography process. Therefore, it is often necessary to detect the mask.

[0003] Sometimes, the defect is located in a non-working area, and this defect does not affect the normal process. In order not to affect production capacity, the mask where the defect is located can be used normally. However, since the defect still exists, when detecting the mask, the detection machine will trigger an alarm for such masks, affecting the semiconductor manufacturing efficiency. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, apparatus and machine for detecting mask defects for the problem of low semiconductor manufacturing efficiency in the prior art.

[0005] To achieve the above object, on the one hand, a method for detecting mask defects is provided, including:

[0006] Obtaining first defect information to be detected of a defect to be detected on a target mask;

[0007] Obtaining a preset defect list, where the preset defect list includes at least one piece of preset defect information;

[0008] Searching for the first defect information to be detected in the preset defect list;

[0009] In the case where the first defect information to be detected of the defect to be detected is recorded in the preset defect list, filtering the first defect information to be detected.

[0010] In one embodiment, after searching for the first defect information to be detected in the preset defect list, it includes:

[0011] In the case where the first defect information to be detected of the defect to be detected is not recorded in the preset defect list, marking the first defect information to be detected as a new defect;

[0012] Performing a repeatability defect test on the new defect;

[0013] In the case where no repeatability defect appears, adding the first defect information to be detected of the new defect to the preset defect list.

[0014] In one embodiment, after performing the repetitive defect test on the new defect, it includes:

[0015] In the case of a repetitive defect occurring, it is determined that the target mask needs to be cleaned.

[0016] In one embodiment, the defect information includes size information and / or position information.

[0017] In one embodiment, the defect information includes size information;

[0018] After obtaining the first defect information to be measured of the target mask, it includes:

[0019] In the case where the size in the first defect information to be measured is greater than the defect control specification size, replace the inspection machine for mask defects, and use the replaced inspection machine to detect the second defect information to be measured of the defect to be measured;

[0020] In the case where the size in the second defect information to be measured is not greater than the defect control specification size, based on the preset defect list, the preset error value, and the second defect information to be measured of the defect to be measured, determine whether the defect to be measured has moved.

[0021] In one embodiment, in the case where the size in the second defect information to be measured is not greater than the defect control specification size, based on the preset error range and the second defect information to be measured of the defect to be measured, determining whether the defect to be measured has moved includes:

[0022] Based on the preset defect list and the preset error value, calculate the error range of the defect to be measured;

[0023] Based on whether the second defect information to be measured is within the error range, determine whether the defect to be measured has moved.

[0024] In one embodiment, the preset error value includes a position error value and a size error value, the position error value is ±0.5 μm, and the size error value is ±5 nm.

[0025] In one embodiment, in the case where the size of the first defect information to be measured is greater than the defect control specification size, after replacing the inspection machine for mask defects and using the replaced inspection machine to detect the second defect information to be measured of the defect to be measured, it includes:

[0026] In the case where the size in the second defect information to be measured is greater than the defect control specification size, it is determined that the target mask needs to be cleaned.

[0027] On the one hand, a mask defect detection device is provided, and the mask defect detection device includes:

[0028] A first acquisition module, configured to acquire first to-be-detected defect information of a to-be-detected defect of a target mask;

[0029] A second acquisition module, configured to acquire a preset defect list, where the preset defect list includes at least one piece of preset defect information;

[0030] A search module, configured to search for the first to-be-detected defect information in the preset defect list;

[0031] A filtering module, configured to filter the first to-be-detected defect information when the first to-be-detected defect information of the to-be-detected defect is recorded in the preset defect list.

[0032] On the one hand, a mask defect detection machine is provided, and a controller of the mask defect detection machine executes the mask defect detection method described in any one of the foregoing.

[0033] The mask defect detection method, device, and machine of the present application have the following beneficial effects: By setting a preset defect list, a defect whitelist can be obtained. Then, by determining whether the first to-be-detected defect information of the to-be-detected defect is in the preset defect list, it can be quickly determined whether the to-be-detected defect affects the normal process of the target mask. Further, when the first to-be-detected defect information of the to-be-detected defect is recorded in the preset defect list, it can be considered that the to-be-detected defect does not affect the normal use of the mask. Therefore, the first to-be-detected defect information can be filtered, and further, the detection machine does not issue an alarm, so that the semiconductor manufacturing process can proceed smoothly. Description of the Drawings

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0035] Figure 1 It is a flowchart of the mask defect detection method provided in the first embodiment;

[0036] Figure 2 It is a flowchart of the mask defect detection method provided in the second embodiment;

[0037] Figure 3 It is a flowchart of the mask defect detection method provided in the third embodiment;

[0038] Figure 4 Schematic diagram of a mask defect detection device provided in an embodiment.

[0039] To better describe and illustrate the embodiments and / or examples of the inventions disclosed herein, reference may be made to one or more of the accompanying drawings. Additional details or examples used to describe the drawings should not be construed as limiting the scope of any of the disclosed inventions, the presently described embodiments and / or examples, and the presently understood best mode of these inventions. Detailed implementation manners

[0040] To facilitate understanding of the present application, the present application will be described more comprehensively below with reference to the relevant drawings. Preferred embodiments of the present application are shown in the drawings. However, the present application may be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present application more thorough and comprehensive.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs. The terms used in the description of this application herein are for the purpose of describing specific embodiments only and are not intended to limit this application.

[0042] As used herein, the singular forms "a", "an" and "the" may also include the plural forms unless the context clearly dictates otherwise. It should also be understood that when the terms "comprise" and / or "include" are used in this specification, the presence of the stated features, integers, steps, operations, elements and / or components can be determined, but one or more other features, integers, steps, operations, elements, components and / or groups are not excluded from the presence or addition. At the same time, as used herein, the term "and / or" includes any and all combinations of the related listed items.

[0043] In one embodiment, refer to Figure 1 , and a mask defect detection method is provided, including the following steps:

[0044] Step S100: Obtain first measured defect information of a defect to be measured of a target mask.

[0045] Step S200: Obtain a preset defect list, and the preset defect list includes at least one piece of preset defect information.

[0046] Step S300: Search for the first measured defect information in the preset defect list.

[0047] Step S400: Filter the first measured defect information when the first measured defect information of the defect to be measured is recorded in the preset defect list.

[0048] In step S100, the target mask has a defect to be measured. When using a detection machine to detect the target mask, the position and size of the defect to be measured can be obtained. As an example, the first defect information to be measured of the defect to be measured may include the specific position and specific size of the defect to be measured. Further, a coordinate system can be established based on the target mask, and the specific position of the defect to be measured can be the position of the center of the defect to be measured in the coordinate system. This specific position can be represented by the X-axis coordinate (Location X) and the Y-axis coordinate (Location Y). The specific size of the defect to be measured can be the length or width of the defect to be measured. The above first defect information to be measured of the defect to be measured is only an example. In actual embodiments, the first defect information to be measured of the defect to be measured is not limited to position and size.

[0049] In step S200, the preset defect list can be a defect whitelist. As an example, the preset defect list can be statistically obtained from the historical database. The preset defect list includes multiple preset defect information, and the defects corresponding to these preset defect information do not affect the normal use of the corresponding mask. As an example, the preset defect information may include mask label, machine type for detecting the mask, specific position and specific size of the defect, etc.

[0050] In step S300, it can be checked whether there is first defect information to be measured in the preset defect list. As an example, the mask label and machine type for detecting the target mask can be determined first, and the specific position and specific size of the corresponding defect can be screened out in the preset defect list. Then, the position of the defect to be measured is compared with the position of the defect in the preset defect list one by one, and the size of the defect to be measured is compared with the size of the defect in the preset defect list one by one. Of course, in this step, the first defect information to be measured can be compared with the specific values in the preset defect list, or the first defect information to be measured can be compared with the range values of the position and size calculated based on the preset defect list. This embodiment does not limit the specific method of checking the first defect information to be measured in the preset defect list.

[0051] In step S400, when the first defect information to be measured of the defect to be measured is recorded in the preset defect list, it can be considered that the defect to be measured belongs to the defect whitelist. At this time, the defect to be measured does not affect the normal use of the mask. Therefore, the first defect information to be measured can be filtered, so that the detection machine does not give an alarm.

[0052] In addition, after step S300, please refer to Figure 2 and it may further include:

[0053] Step S410: When the first defect information to be measured of the defect to be measured is not recorded in the preset defect list, mark the first defect information as a new defect.

[0054] Step S420: Conduct a repeatability defect test on the new defect.

[0055] Step S430: When no repeatability defect occurs, add the first defect information to be measured of the new defect to the preset defect list.

[0056] Step S431: When a repeatability defect occurs, determine that the target mask needs to be cleaned.

[0057] In step S410, when the first defect information to be measured of the defect to be measured is not recorded in the preset defect list, it is necessary to determine whether the new defect will affect the normal process of the target mask.

[0058] In step S420, at this time, the method of repeatability defect test can be used to verify whether the new defect will affect the normal process of the target mask. Exemplarily, a wafer can be obtained, and after applying photoresist on the wafer, the target mask is used for exposure. Then, the wafer can be sent to a wafer inspection station for defect detection and analysis. If a repeatability defect occurs, it is considered that the new defect affects the normal process of the target mask. If no repeatability defect occurs, it is considered that the new defect does not affect the normal process of the target mask. It can be understood that the above repeatability defect test is only for exemplary illustration.

[0059] In step S430, when no repeatability defect occurs, it can be considered that the new defect does not affect the normal process of the target mask. At this time, the first defect information to be measured (position and size) of the new defect can be added to the preset defect list.

[0060] In step S431, when a repeatability defect occurs, it can be considered that the new defect affects the normal process of the target mask. At this time, it can be determined that the target mask needs to be sent for cleaning.

[0061] In this embodiment, by setting a preset defect list, a defect whitelist is obtained. Then, by determining whether the first defect information to be measured of the defect to be measured is in the preset defect list, it can be quickly determined whether the defect to be measured affects the normal process of the target mask. Further, when the first defect information to be measured of the defect to be measured is recorded in the preset defect list, it can be considered that the defect to be measured does not affect the normal use of the mask. Therefore, the first defect information can be filtered, so that the inspection station does not give an alarm, and thus the semiconductor manufacturing process can proceed smoothly.

[0062] In one embodiment, the first defect information to be measured includes the size of the defect to be measured. The preset defect list includes the defect control specification size of the target mask. It can be understood that the defect control specification size can be used to represent the maximum size of the defect acceptable for the target mask.

[0063] Correspondingly, after step S100, please refer to Figure 3 , including:

[0064] Step S500: When the size of the first defect information to be measured is greater than the defect control specification size, replace the inspection machine for mask defects, and use the replaced inspection machine to detect the second defect information to be measured of the defect to be measured.

[0065] Step S510: When the size in the second defect information to be measured is not greater than the defect control specification size, determine whether the defect to be measured has moved based on the preset defect list, the preset error value, and the second defect information to be measured of the defect to be measured.

[0066] In step S500, when the size of the first defect information to be measured is greater than the defect control specification size, it can be considered that the data is unreliable due to the aging of the inspection machine or the lack of regular calibration. At this time, the target mask can be detected again by replacing the inspection machine, and the second defect information to be measured of the same defect to be measured can be obtained. The second defect information to be measured may include the new position and new size of the defect to be measured.

[0067] In step S510, when the size in the second defect information to be measured is not greater than the defect control specification size, it may indicate that the defect to be measured has shifted, resulting in its failure to be detected in the preset defect list. Therefore, this embodiment provides a preset error value, which can be manually set or statistically obtained from historical data.

[0068] In one example, step S510 includes:

[0069] Step S511: Calculate the error range of the defect to be measured based on the preset defect list and the preset error value.

[0070] Step S512: Determine whether the defect to be measured has moved based on whether the second defect information to be measured is within the error range.

[0071] In step S511, as an example, the preset error value includes a position error value and a size error value. The position error value includes ±0.5 μm, and the size error value includes ±5 nm. It can be understood that the above position error value and size error value are only for illustrative purposes, and in actual embodiments, the error value and size error value are not limited to the above values.

[0072] In step S512, specifically, in a possible example, the sum or difference of the position in the second defect information to be measured and the position error value can be calculated to obtain the position error range. Also, the sum or difference of the size in the second defect information to be measured and the size error value can be calculated to obtain the size error range. Then, by comparing the preset defect list with the error range, it is determined whether the defect to be measured has moved. In another possible example, the sum or difference of the positions of the defects on the same wafer in the preset defect list and the position error value can be calculated to obtain the position error range. Also, the sum or difference of the sizes of the defects on the same wafer in the preset defect list and the size error value can be calculated to obtain the size error range. Then, by comparing with the error range in the second defect information to be measured, it is determined whether the defect to be measured has moved.

[0073] In addition, when the defect to be measured has a large movement, that is, when the defect to be measured exceeds the error range, the target mask can be repeatedly tested to determine whether the target mask needs to be cleaned. When the defect to be measured does not have a large movement, that is, when the defect to be measured does not exceed the error range, the first defect information to be measured and the second defect information to be measured are filtered.

[0074] In addition, please refer to Figure 3 , after step S500, it may further include:

[0075] Step S520: When the size in the second defect information to be measured is greater than the defect control specification size, it is determined that the target mask needs to be cleaned.

[0076] When it is determined by two different inspection machines that the size of the defect to be measured is greater than the defect control specification size, it can be confirmed that the size of the defect to be measured is large. At this time, it can be determined that the target mask needs to be cleaned. Then, the target mask should be cleaned in time.

[0077] Please refer to Table 1, which exemplarily shows the defect information.

[0078] Mask ID Grada Type Location X Location Y Size Spec Mask 1 G11 KRF 576.31 281.3 57nm 45nm Mask 2 G11 KRF 1561.1 98.7 61nm 45nm Mask 3 G11 KRF 1281.3 76.31 48nm 45nm Mask 4 G11 KRF 798.7 381.3 49nm 45nm

[0079] It should be understood that although Figure 1 , Figure 2 and Figure 3 in the flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, Figure 1 , Figure 2 and Figure 3At least some of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily executed and completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least some of the steps or stages in other steps or other steps.

[0080] In one embodiment, as Figure 4 shown, a reticle defect detection device is provided, including: a first acquisition module, a second acquisition module, a search module, and a filtering module, where:

[0081] The first acquisition module is used to acquire first defect information to be measured of a target reticle for a defect to be measured.

[0082] The second acquisition module is used to acquire a preset defect list, and the preset defect list includes at least one piece of preset defect information.

[0083] The search module is used to search for the first defect information to be measured in the preset defect list.

[0084] The filtering module is used to filter the first defect information to be measured when the first defect information to be measured of the defect to be measured is recorded in the preset defect list.

[0085] In one embodiment, the reticle defect detection device further includes a marking module. The marking module is used to mark the first defect information to be measured as a new defect when the first defect information to be measured of the defect to be measured is not recorded in the preset defect list; perform a repeatability defect test on the new defect; and add the first defect information to be measured of the new defect to the preset defect list when no repeatability defect occurs.

[0086] In one embodiment, the marking module is used to determine that the target reticle needs to be cleaned when a repeatability defect occurs.

[0087] In one embodiment, the reticle defect detection device further includes a replacement module. The replacement module is used to replace the detection machine for the reticle defect when the size of the first defect information to be measured is greater than the defect control specification size, and use the replaced detection machine to detect the second defect information to be measured of the defect to be measured; and determine whether the defect to be measured has moved based on the preset error value and the second defect information to be measured of the defect to be measured when the size in the second defect information to be measured is not greater than the defect control specification size.

[0088] In one embodiment, the replacement module is used to calculate the error range of the defect to be measured based on the preset defect list and the preset error value; and determine whether the defect to be measured has moved based on whether the second defect information to be measured is within the error range.

[0089] In one embodiment, the replacement module is configured to determine that the target mask needs to be cleaned when the size in the second defect information to be measured is greater than the defect control specification size.

[0090] For the specific limitations of the mask defect detection device, reference can be made to the limitations of the mask defect detection method in the foregoing text, which will not be elaborated here. Each module in the above mask defect detection device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in hardware form or independent of the processor, or stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0091] Based on the same inventive concept, in one embodiment, a mask defect detection machine is provided. The controller of the mask defect detection machine executes the mask defect detection method formed by any one or more of the embodiments of the present application and their combinations.

[0092] In one embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0093] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0094] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0095] In the description of the present application, the descriptions referring to terms such as "some embodiments", "other embodiments", "ideal embodiments", etc. mean that the specific features, structures, materials, or features described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In the present application, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. In addition, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that the "present embodiment" or "one embodiment" mentioned throughout the specification means that the specific features, structures, or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the appearances of "in one embodiment" or "in an embodiment" throughout the specification do not necessarily refer to the same embodiment.

[0096] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features of the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this application.

[0097] The above-described embodiments only represent several implementation manners of this application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent application. It should be noted that for those of ordinary skill in the art, without departing from the concept of this application, several modifications and improvements can be made, and these all belong to the protection scope of this application. Therefore, the protection scope of the patent of this application shall be subject to the appended claims. The above is only the preferred implementation manner of this application, and does not limit the patent scope of this application. Any equivalent structural transformation made by using the content of the specification and drawings of this application under the inventive concept of this application, or direct / indirect application in other related technical fields is included in the patent protection scope of this application.

Claims

1. A method for detecting mask defects, characterized in that: include: Acquire first defect information of a defect to be tested of a target mask; Obtaining a preset defect list, wherein the preset defect list includes at least one preset defect information; Searching for the first defect information to be tested in the preset defect list; When first defect information to be detected of the defect to be detected is recorded in the preset defect list, the first defect information to be detected is filtered.

2. The method for detecting mask defects according to claim 1, characterized in that: After searching the preset defect list for the first defect information to be tested, the method includes: If the first defect information to be tested of the defect to be tested is not recorded in the preset defect list, marking the first defect information to be tested as a new defect; performing a repetitive defect test on the new defect; In the case that no repetitive defects occur, the first defect information to be tested of the new defect is added to the preset defect list.

3. The method for detecting mask defects according to claim 2, characterized in that: After the new defect is subjected to a repeatable defect test, the method further comprises: In the event of a repetitive defect, it is determined that the target reticle requires cleaning.

4. The method for detecting mask defects according to claim 1, characterized in that: The defect information includes size information and / or position information.

5. The method for detecting mask defects according to claim 1, characterized in that: The defect information includes size information; After obtaining the first defect information to be tested of the target mask, the method includes: When the size in the first defect information to be tested is larger than the defect control specification size, replacing the inspection machine for the mask defect, and using the replaced inspection machine to detect the second defect information to be tested of the defect to be tested; When the size in the second defect information to be detected is not greater than the defect control specification size, it is determined whether the defect to be detected has moved based on the preset defect list, the preset error value and the second defect information to be detected of the defect to be detected.

6. The method for detecting mask defects according to claim 5, characterized in that: When the size in the second defect information to be detected is not greater than the defect control specification size, determining whether the defect to be detected moves based on a preset error range and the second defect information to be detected of the defect to be detected includes: Calculating the error range of the defect to be tested based on the preset defect list and the preset error value; Based on whether the second defect information to be detected is within the error range, it is determined whether the defect to be detected moves.

7. The method for detecting mask defects according to claim 5, characterized in that: The preset error value includes a position error value and a size error value, the position error value is ±0.5 μm, and the size error value is ±5 nm.

8. The method for detecting mask defects according to claim 5, characterized in that: When the size of the first defect information to be detected is larger than the defect control specification size, replacing the detection machine for the mask defect, and using the replaced detection machine to detect the second defect information to be detected of the defect to be detected, the method includes: When the size in the second defect information to be tested is larger than the defect control specification size, it is determined that the target mask needs to be cleaned.

9. A mask defect detection device, characterized in that: The mask defect detection device comprises: A first acquisition module, used for acquiring first defect information to be tested of a defect to be tested of a target mask; A second acquisition module is used to acquire a preset defect list, wherein the preset defect list includes at least one preset defect information; A search module, used for searching the first defect information to be tested in the preset defect list; The filtering module is used to filter the first defect information to be tested when the first defect information to be tested is recorded in the preset defect list.

10. A mask defect detection machine, characterized in that: The controller of the mask defect inspection machine executes the mask defect inspection method according to any one of claims 1 to 8.

Images