Methods, devices, storage media and equipment for tracking micro / nano fabricated sample processes

Abstract

This invention provides a method, apparatus, storage medium, and device for tracking the micro / nano fabrication sample process, comprising: step S101, acquiring an initial set of defect features on the sample surface before micro / nano fabrication; step S102, selecting defect features of any region from the initial set of defect features as a first set of defect features; step S103, acquiring a second set of defect features of the selected region of the sample after performing any step of micro / nano fabrication; step S104, sending a sample confirmation prompt if the matching degree between the second set of defect features and the first set of defect features is less than a first threshold; and step S105, updating the initial set of defect features in conjunction with the second set of defect features and returning to execute steps S102-S105 until the micro / nano fabrication process ends.

Description

Technical Field

[0001] This invention relates to the field of sample tracking, and more specifically to methods, apparatus, storage media, and devices for tracking the process of micro- and nano-fabricated samples. Background Technology

[0002] Micro-nano fabrication processes encompass multiple steps, including wafer cleaning, resist coating, baking, exposure, development, etching, thin film deposition, and chemical mechanical polishing. In traditional research settings, recording the parameters for these complex processes relies heavily on manual recording by researchers. For example, during wafer cleaning, researchers must meticulously record the cleaning solution ratio, real-time temperature, and cleaning time; during resist coating, the resist layer thickness must be frequently measured, and the spin coater's rotation speed and acceleration data recorded; and during exposure, researchers must closely monitor the lithography machine screen, recording parameters such as exposure time and light source intensity. Researchers often experience data errors and omissions due to the dual pressures of equipment operation and data recording. Worse still, data from different processes is scattered across different notebooks or electronic files, forcing researchers to spend time searching through records when reviewing or tracing an experiment, hindering rapid data retrieval and effective integration. Micro-nano fabrication places extremely stringent requirements on precision and efficiency, and full-process traceability is crucial to ensuring the accuracy and repeatability of scientific research results. Manual recording methods obviously cannot meet these needs, becoming a bottleneck that restricts scientific research progress and seriously hindering the innovation and development of micro-nano fabrication technology in the scientific research field.

[0003] In contrast, mature wafer fabs have already established comprehensive production management systems. Wafer marking technology, through methods such as laser etching and inkjet printing, imbues the surface of wafers with unique identifiers, much like issuing a personal "ID card" to each wafer. From raw material warehousing to finished product delivery, this identifier runs through the entire production process, enabling precise tracking of wafer production information. Meanwhile, the MES (Manufacturing Execution System) monitors every step of the production line in real time, collecting massive amounts of information such as equipment operation data, process parameters, and quality inspection results. Through big data analysis and algorithm optimization, it achieves refined management and data traceability throughout the entire process, including production scheduling, material management, and quality control. However, system deployment not only requires the purchase of expensive hardware such as servers and sensors and high software costs, but also requires significant investment in customized development to adapt to the specific needs of scientific research experiments. Furthermore, the daily operation and maintenance of the system demands a highly specialized team, requiring personnel with expertise in both information technology and micro-nano fabrication processes. The characteristics of scientific research scenarios, namely "small batches, multiple batches, and high-frequency process adjustments," are completely different from the large-scale, standardized production mode of wafer fabs. This makes it difficult for this system to respond flexibly to the rapid changes in scientific research experiments. The high cost and complex operation and maintenance also deter many research institutions from using it effectively in their scientific research work. Summary of the Invention

[0004] Based on this, the present invention provides a method, apparatus, storage medium and equipment for tracking the process of micro-nano fabrication samples. It utilizes the characteristic that image feature acquisition of samples is required before each process step of micro-nano fabrication, combines the unique defect features of the sample itself to identify the sample, and introduces a sample consistency confirmation step to update the defect features of the sample during the micro-nano fabrication process, so as to realize the whole process tracking of micro-nano fabricated samples without introducing other equipment or laser marking the sample.

[0005] In a first aspect, the present invention provides a method for tracking the flow of micro / nano fabricated samples, comprising:

[0006] Step S101: Before the sample undergoes micro / nano processing, an initial set of defect features on the sample surface is obtained;

[0007] Step S102: Select the defect features of any region from the initial defect feature set as the first set of defect features;

[0008] Step S103: After the sample has undergone any step of micro-nano fabrication, obtain the second set of defect features of the selected area of ​​the sample.

[0009] Step S104: If the matching degree between the second set of defect features and the first set of defect features is less than the first threshold, send a sample confirmation prompt message;

[0010] Step S105: If a confirmation message confirming sample consistency is received, update the initial defect feature set in conjunction with the second set of defect features, and return to execute steps S102-S105 until the micro-nano fabrication process ends.

[0011] Furthermore, the acquisition of the initial defect feature set of the sample surface specifically involves:

[0012] Initial image information of the sample surface is acquired using an image acquisition device;

[0013] Based on the initial image information, the defect features of the sample surface edge region are obtained, and the defect features of all edge regions are recorded as the initial defect feature set.

[0014] Furthermore, the step of obtaining the defect features of the sample surface edge region based on the initial image information specifically involves:

[0015] The initial image information is input into the feature extraction model to obtain the defect features of the sample surface edge region.

[0016] Furthermore, the step of selecting defect features from any region in the initial defect feature set as the first set of defect features specifically involves:

[0017] Select any corner region and the defect features on the adjacent edges of that corner region from the initial defect feature set as the first set of defect features.

[0018] Furthermore, if the matching degree between the second set of defect features and the first set of defect features is less than a first threshold, a sample confirmation prompt message is sent, specifically:

[0019] If the difference in the number of features between the second set of defect features and the first set of defect features is higher than the first ratio compared to the number of features in the first set of defect features;

[0020] Or the area difference between the second area of ​​any defect feature in the second set of defect features and the first area of ​​the defect feature in the first set of defect features is higher than the second ratio compared with the first area, and the number of area differences higher than the second ratio exceeds the area number threshold.

[0021] Or the second area of ​​any one of the defect features in the second set of defect features exceeds a preset area threshold;

[0022] Send a sample confirmation message.

[0023] Furthermore, if confirmation information indicating sample consistency is received, updating the initial defect feature set in conjunction with the second set of defect features specifically involves:

[0024] If a confirmation message indicating sample consistency is received, the second set of defect features is merged into the initial set of defect features in conjunction with the sample micro-nano fabrication steps.

[0025] The second set, which combines the defect characteristics of the sample micro-nano fabrication steps, includes the process parameters and processing time of the sample micro-nano fabrication steps.

[0026] Secondly, the present invention also provides a micro / nano fabrication sample flow tracking device, comprising:

[0027] The initial defect feature acquisition module is used to acquire the initial defect feature set on the sample surface before the sample undergoes micro-nano processing.

[0028] The region selection module is used to select the defect features of any region from the initial defect feature set as the first set of defect features;

[0029] The defect feature reacquisition module is used to acquire a second set of defect features of a selected area of ​​the sample after any step of the micro-nano fabrication process is performed on the sample.

[0030] The defect feature matching module is used to send a sample confirmation prompt message if the matching degree between the second set of defect features and the first set of defect features is less than a first threshold.

[0031] The defect feature update module is used to update the initial defect feature set in combination with the second set of defect features if a confirmation information of sample consistency is received, and then return to the execution area selection module, defect feature reacquisition module, defect feature matching module and defect feature update module until the micro-nano fabrication process ends.

[0032] Furthermore, if the matching degree between the second set of defect features and the first set of defect features is less than a first threshold, a sample confirmation prompt message is sent, specifically:

[0033] If the difference in the number of features between the second set of defect features and the first set of defect features is higher than the first ratio compared to the number of features in the first set of defect features;

[0034] Or the area difference between the second area of ​​any defect feature in the second set of defect features and the first area of ​​the defect feature in the first set of defect features is higher than the second ratio compared with the first area, and the number of area differences higher than the second ratio exceeds the area number threshold.

[0035] Or the second area of ​​any one of the defect features in the second set of defect features exceeds a preset area threshold;

[0036] Send a sample confirmation message.

[0037] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the micro / nano fabrication sample flow tracking methods in the first aspect.

[0038] Fourthly, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform any of the micro / nano fabrication sample flow tracking methods in the first aspect.

[0039] The beneficial effects of adopting the above technical solution are as follows: This embodiment utilizes the characteristic that image feature acquisition of samples is required before each process step of micro-nano processing. Combined with the unique defect features of the sample itself, sample identification is performed. Furthermore, a sample consistency verification step is introduced to update the defect features of the sample during the micro-nano processing. This enables full-process tracking of micro-nano processed samples without introducing additional equipment or laser marking. This reduces the need for laser-printed mark identification and eliminates the need for excessive equipment, improving the efficiency of sample tracking during micro-nano processing. Compared with traditional laser marking tracking methods, this technology does not leave permanent marks on the sample surface, avoiding surface damage and material property changes that may be caused by laser marking. It is particularly suitable for micro-nano device processing where surface integrity requirements are extremely high. Simultaneously, it eliminates the need for dedicated equipment for laser marking identification and the complex image recognition algorithm debugging process, significantly reducing equipment costs and manpower investment. In actual production, operators only need to use existing image acquisition equipment to complete sample tracking, significantly improving sample tracking efficiency, shortening the processing cycle, and providing strong support for the intelligent and efficient development of the micro-nano processing industry. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0041] Figure 1 This is a schematic diagram of a micro / nano fabrication sample process tracking method in one embodiment of this application;

[0042] Figure 2(a) is a schematic diagram of local defect features of a sample in one embodiment of this application;

[0043] Figure 2(b) is a schematic diagram of another local defect feature of a sample in one embodiment of this application;

[0044] Figure 3(a) is a schematic diagram of sample defect characteristics in a laboratory operation step in one embodiment of this application;

[0045] Figure 3(b) is a diagram of the defect features of the sample before processing and a magnified view of the upper left corner in one embodiment of this application;

[0046] Figure 3(c) is a diagram showing the defect features of the sample after the glue application operation in one embodiment of this application, and a magnified view of the upper left corner.

[0047] Figure 3(d) is a defect feature diagram and a magnified view of the upper left corner of the sample after photolithography and development operation in one embodiment of this application;

[0048] Figure 3(e) is a diagram showing the defect features of a sample after coating operation and a magnified view of the upper left corner in one embodiment of this application;

[0049] Figure 3(f) is a diagram showing the defect features of a sample after wet processing in one embodiment of this application, and a magnified view of the upper left corner.

[0050] Figure 3(g) is a defect feature diagram and a magnified view of the upper left corner of a sample after dry etching operation in one embodiment of this application;

[0051] Figure 4 This is a schematic diagram of a micro / nano fabrication sample flow tracking device in one embodiment of this application. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. To describe the present invention in more detail, the micro-nano fabrication sample flow tracking method, apparatus, storage medium, and device provided by the present invention will be specifically described below with reference to the accompanying drawings.

[0053] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an," "a," or "the" do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms "comprising" or "including" mean that the preceding element or object encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. The terms "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0054] Wafer marking technology uses laser etching, inkjet printing, and other methods to give each wafer a unique identifier, much like issuing a personal "ID card." This identifier is present throughout the entire production process, from raw material warehousing to finished product delivery, enabling precise tracking of wafer production information. Meanwhile, the MES (Manufacturing Execution System) monitors every step of the production line in real time, collecting massive amounts of information such as equipment operation data, process parameters, and quality inspection results. Through big data analysis and algorithm optimization, it achieves refined management and data traceability across the entire process, including production scheduling, material management, and quality control. However, system deployment requires not only the purchase of expensive hardware such as servers and sensors and high software costs, but also significant investment in customized development to adapt to the specific needs of scientific research experiments. Furthermore, the daily operation and maintenance of the system demands a highly specialized team, requiring personnel with expertise in both information technology and micro / nano fabrication processes. The characteristics of scientific research scenarios, namely "small batches, multiple batches, and high-frequency process adjustments," are completely different from the large-scale, standardized production mode of wafer fabs. This makes it difficult for this system to respond flexibly to the rapid changes in scientific research experiments. The high cost and complex operation and maintenance also deter many research institutions from using it effectively in their scientific research work.

[0055] This invention provides an application scenario for a micro / nano fabrication sample process tracking method. This application scenario includes the terminal device provided in the embodiment. The terminal device includes, but is not limited to, smartphones and computer devices. The computer device can be at least one of desktop computers, portable computers, laptop computers, mainframe computers, tablet computers, etc. The terminal device receives a set of defect features of the sample before and after the micro / nano fabrication steps, compares the matching degree between the defect features, and updates the set of sample defect features. (See attached...) Figure 1 The diagram shows a method for tracking the flow of micro / nano fabricated samples. For details, please refer to the embodiments of the method for tracking the flow of micro / nano fabricated samples.

[0056] The micro-nano fabrication sample process tracking method provided in this embodiment is applied to a micro-nano fabrication laboratory. The laboratory includes process equipment for each micro-nano fabrication stage, and each process equipment is equipped with a high-resolution process camera to acquire sample image information. Each high-resolution process camera is communicatively connected to the laboratory processing device, and the acquired sample image information is combined with the corresponding process equipment tags and uploaded to the laboratory processing device for identifying defect features of the sample image information.

[0057] Step S101: Before the sample undergoes micro / nano processing, an initial set of defect features on the sample surface is obtained.

[0058] During wafer dicing or wafer fabrication, one or more defects may be introduced at the sample edges. Because the number, shape, and area of ​​these edge defects are random, most samples exhibit inconsistent edge defects. It is precisely this randomness that creates the natural identification characteristics of the sample edges. Each sample's set of defect features acts as its unique ID, used for tracking the sample during micro / nano fabrication.

[0059] Specifically, obtaining the initial set of defect features on the sample surface includes:

[0060] Step S202: Acquire initial image information of the sample surface using an image acquisition device;

[0061] Step S203: Obtain the defect features of the sample surface edge region based on the initial image information, and record the defect features of all edge regions as the initial defect feature set.

[0062] The method of obtaining the defect features of the sample surface edge region based on the initial image information specifically involves inputting the initial image information into a feature extraction model to obtain the defect features of the sample surface edge region.

[0063] As shown in Figures 2(a) and 2(b), the sample has local defect features. For example, in Figure 2(a), the sample has a concave defect at the location marked by lines 1 and 2, and point 3 is the vertex mark of the sample. In Figure 2(b), the sample has a concave defect at the location marked by line 4, and the surface has micro-texture defects at the location marked by line 5, and point 6 is the vertex mark of the sample. By analyzing the unique features of the sample surface micro-texture and defect distribution, the feature extraction models in computer vision (such as SIFT model and SURF model) are used to extract the defect features of all edge regions of the sample.

[0064] Step S102: Select the defect features of any region from the initial defect feature set as the first set of defect features.

[0065] Specifically, the defect features of any region are selected from the initial defect feature set as the first set of defect features, as follows:

[0066] Select any corner region and the defect features on the adjacent edges of that corner region from the initial defect feature set as the first set of defect features.

[0067] Considering that comparing all the defect features on the sample one by one would require a lot of time and computing resources, and that the defect features on the edge and corner areas of the sample are more obvious, this embodiment can select any corner area and the defect features on the adjacent edge of the sample as obvious features representing the identity information of the sample.

[0068] Furthermore, to improve the efficiency of subsequent defect feature comparison, this embodiment can also acquire the global image features and defect features of the surface edge region of the sample, based on the above scheme. When a significant difference is found in the global image features of the sample before and after the micro-nano processing step, such as the global image feature shape of the sample before micro-nano processing being circular and the global image feature shape of the sample after micro-nano processing being rectangular, or the global image feature size of the sample before micro-nano processing being 8 inches and the global image feature size of the sample after micro-nano processing being 6 inches, it clearly indicates that the acquired image information before and after micro-nano processing does not belong to the same sample. Therefore, it is unnecessary to further compare the defect features of the edge of the micro-nano processed sample, reducing unnecessary waste of computational resources. The global image features of the sample include the shape, size, and special internal structures of the sample.

[0069] Furthermore, considering that the impact of each stage of micro-nano processing on the defect features of different regions varies, this embodiment can also select any one or more corner regions and the defect features on multiple adjacent edges of the corner region from the initial defect feature set as the first set of defect features, increase the defect feature region representing the sample identity feature, reserve a spare defect feature recognition region, and improve the accuracy of defect feature marking of the sample.

[0070] Step S103: After the sample has undergone any step of micro-nano fabrication, obtain the second set of defect features of the selected area of ​​the sample.

[0071] After a sample undergoes any step of micro / nano fabrication, the defect characteristics of the sample may change. Therefore, it is necessary to re-acquire the defect characteristics of the selected region in the first set of defect characteristics and obtain the second set of defect characteristics.

[0072] Step S104: If the matching degree between the second set of defect features and the first set of defect features is less than the first threshold, send a sample confirmation prompt message.

[0073] Specifically, if the matching degree between the second set of defect features and the first set of defect features is less than the first threshold, it includes the following situations:

[0074] (1) The difference in the number of features between the second set of defect features and the first set of defect features is higher than the first proportion compared with the number of features in the first set of defect features.

[0075] Because micro / nano fabrication processes can affect the defect characteristics of samples, such as adding new edge defects or causing some edge defects to disappear, and considering the large number of edge defects on the samples, to avoid requiring users or staff to re-verify the samples even for minor changes in defect characteristics, a sample confirmation prompt is only sent to users or staff when the number of defect characteristics in a selected area of ​​the sample changes significantly. This situation can be represented as follows: , The number of features in the first set of defect features. The number of features in the second set of defect features. The first proportion.

[0076] (2) The difference between the second area of ​​any defect feature in the second set of defect features and the first area of ​​the defect feature in the first set of defect features is higher than the second ratio compared with the first area, and the number of areas with the difference higher than the second ratio exceeds the area number threshold.

[0077] Because micro- and nano-fabrication processes can affect the defect characteristics of samples, such as increasing or decreasing the area of ​​some edge defects, and considering the large number of edge defects in the samples, to avoid requiring users or staff to re-verify the samples even for minor changes in defect characteristics, a sample confirmation prompt is only sent to users or staff when the area of ​​the same defect feature within a selected area of ​​the sample changes significantly, and the number of features with area changes is large. This situation can be represented as... ,and , Let be the first area of ​​any defect feature. The second area is the defect feature corresponding to the first area, measured after micro / nano fabrication. The second proportion, This refers to the number of defect features whose area difference exceeds the second proportion. This is the threshold for the area quantity.

[0078] (3) The second area of ​​any defect feature in the second set of defect features exceeds the preset area threshold.

[0079] Considering that samples need to be transferred to different processing equipment by clamping during micro-nano fabrication, improper operation during sample clamping can easily cause large edge defects to the sample. Therefore, a preset area threshold is set. When the second area of ​​any defect feature exceeds the preset area threshold, it indicates that the sample may have large edge defects due to improper operation. At this time, a sample confirmation prompt message needs to be sent to the user or staff.

[0080] It should be noted that the sample confirmation prompt information in this embodiment is used to remind users or staff whether the sample has changed before and after the micro-nano processing, and to verify the characteristics of the sample after the change.

[0081] Step S105: If a confirmation message confirming sample consistency is received, update the initial defect feature set in conjunction with the second set of defect features, and return to execute steps S102-S105 until the micro-nano fabrication process ends.

[0082] Since changes in sample defect characteristics may be related to the micro / nano fabrication steps the sample has undergone, to preserve the operational space for researchers to explore the regularity of sample defects and further analyze them to improve the yield of micro / nano fabricated samples, this embodiment does not cover the changed defect characteristics. Instead, it saves them together with the parameters of the micro / nano fabrication steps the sample has undergone, providing a data foundation for subsequent exploration of sample defect regularity and improvement of sample yield. Specifically:

[0083] If a confirmation message confirming sample consistency is received, the second set of defect features, combined with the sample micro / nano fabrication steps, is merged into the initial set of defect features. The second set of defect features, combined with the sample micro / nano fabrication steps, includes the process parameters and processing time of the sample micro / nano fabrication steps. It should be noted that, in this embodiment, the sample defect features include not only the defects located at the sample edge mentioned above, but also the micro / nano fabricated patterns on the sample.

[0084] Referring to the schematic diagram of sample defect characteristics in the laboratory operation process shown in Figure 3(a), the changes in the above-mentioned defect characteristics are explained. Figure 3(b) is a defect characteristic diagram of the sample before processing, with the three defect characteristic points in the upper left corner (specifically, the three characteristic points circled in the enlarged view) marking the sample. After the adhesive coating operation, Figure 3(c) is a defect characteristic diagram of the sample after the adhesive coating operation. It can be seen that the three defect characteristic points in the upper left corner (specifically, the three characteristic points circled in the enlarged view) still exist, but an additional dirt characteristic point appears in the upper right corner. Subsequently, the sample is subjected to photolithography and development operation. Figure 3(d) is a defect characteristic diagram of the sample after the photolithography and development operation. It can be seen that the three defect characteristic points in the upper left corner (specifically, the three characteristic points circled in the enlarged view) still exist, but an additional dirt characteristic point appears in the upper right corner. The additional etching pattern in the upper right corner can also serve as a sample identification feature. Figure 3(e) shows the defect feature map of the sample after coating operation. The three defect feature points in the upper left corner (specifically, the three feature points circled in the magnified view) are still retained. Subsequently, a wet etching operation is performed on the sample. Figure 3(f) shows the defect feature map of the sample after wet etching operation. The three defect feature points in the upper left corner (specifically, the three feature points circled in the magnified view) are still retained. Similarly, the etching pattern in the upper right corner is also retained, and defect feature points are added to the two side edges. Figure 3(g) shows the defect feature map of the sample after dry etching operation. After dry etching, the three defect feature points in the upper left corner of the sample (specifically, the three feature points circled in the magnified view) are still retained, as are the etching pattern in the upper right corner and the defect feature points on the two side edges. Taking this as an example, after the size or area of ​​the three defect feature points in the upper left corner of the sample changes, an etching pattern can also be introduced as a sample identification feature.

[0085] Furthermore, to improve convenience for users or staff, voice input technology can be used to confirm sample consistency. For example, users can input "This defect feature corresponds to a sample that is consistent with the sample from the previous stage." Using a natural language processing model, the speech can be quickly converted into accurate text, enabling timely marking of sample defect features. Additionally, users or staff can also annotate sample feature defects via voice input. For example, they can input "The newly appearing defect feature is due to improper sample clamping operation" or "The disappearance of the defect feature is related to step A of micro / nano fabrication," annotating the specific scenario and cause of the defect feature change, thus forming a complete process file.

[0086] Furthermore, this embodiment can also statistically analyze the defect characteristics of multiple historical samples in the micro-nano fabrication process to form a defect characteristic profile of the specific micro-nano fabrication process, and dynamically adjust the acceptability of a certain defect characteristic for the specific micro-nano fabrication process, specifically as follows:

[0087] Obtain a set of defect features from several historical samples at various micro / nano fabrication stages;

[0088] Clustering the defect feature set of all historical samples in each micro-nano fabrication step yields a defect feature profile for each micro-nano fabrication step.

[0089] The first threshold corresponding to the matching degree between the second set of defect features and the first set of defect features in the micro-nano fabrication process is adjusted based on the defect feature profile of the micro-nano fabrication process.

[0090] For example, using 50 historical samples processed by a micro-nano fabrication platform as reference data, the defect characteristics of these 50 historical samples during the etching process are statistically analyzed, and the defect characteristics during the etching process are clustered. It is found that the defect characteristics during the etching process are mainly concentrated on the expansion of the defect area. In response, the threshold values ​​of the defect area portion of the second set and the first set of defect characteristics during the etching process can be adjusted to relax the verification conditions for the change of defect area during the etching process and reduce the triggering of unnecessary verifications.

[0091] In addition, since the defect characteristics of the sample may also be related to personnel operation, this embodiment can also combine laboratory personnel information to statistically analyze the historical sample defect characteristics of specific laboratory personnel. When the frequency of a certain type of defect characteristic in the historical operation of a laboratory personnel exceeds the alarm threshold, an alarm message is generated for the laboratory personnel to remind them to avoid the occurrence of this type of defect characteristic in subsequent micro-nano processing, thereby improving the standardization of sample operation by different experimental personnel in micro-nano processing.

[0092] Regarding the sample defect characteristics related to human operation mentioned above, and in conjunction with the specific operational procedures in the laboratory, the following is a further description of the situations in which sample defects may occur: The following summarizes the situations in which improper operation by laboratory personnel leads to sample defects:

[0093] (a) Mechanical damage

[0094] Mechanical damage includes physical scratches and impacts, as well as sample drops and collisions. Physical scratches and impacts mainly occur when using tools such as tweezers and clamps, where excessive force or rough handling can cause defects in the sample. For example, the tip of the tweezers may accidentally scratch the sample surface, or the clamp may shift its position while holding the sample, causing uneven force on the sample edges and resulting in scratches or indentations on the sample surface. Sample drops and collisions refer to changes in the sample's defect characteristics caused by slipping, unstable handling, or collisions with other objects during manual sample transfer.

[0095] (ii) Pollution introduction category

[0096] Specifically, contamination introduction includes grease and stain contamination, as well as particulate contamination. Grease and stain contamination refers to the transfer of grease, sweat, and surface dirt from the hands to the sample surface when the operator is not wearing gloves or the gloves are damaged, resulting in direct skin contact. Additionally, using uncleaned tools (such as tweezers or clamps contaminated with oil) can also contaminate the sample. Particulate contamination refers to the adhesion of airborne dust, fibers, and other particulate impurities to the sample surface when cleanroom procedures are not strictly followed (such as opening sample packaging in a non-cleanroom environment or not wearing protective clothing during operation), which can then obstruct the photolithography process.

[0097] (iii) Errors in operational procedures

[0098] Specifically, operational errors include situations involving solution residue and drying, as well as incorrect parameter settings. Solution residue and drying refer to situations where, during the cleaning process, the prescribed cleaning time, cleaning solution ratio, and rinsing sequence are not followed, resulting in cleaning solution residue remaining on the sample surface. Once the residual cleaning solution dries, it will form water stains or crystals on the sample surface, affecting the quality of subsequent photolithography and coating, leading to problems such as uneven patterns and localized peeling. Incorrect parameter settings refer to situations where, when using equipment that requires manual operation (such as during spin coating of photoresist), the operator fails to correctly set the specific equipment parameters (such as spin coating speed and time), resulting in uneven photoresist thickness and causing defects in the sample compared to the preset microscope pattern.

[0099] It should be understood that, although attached Figure 1 The steps in the flowchart are shown sequentially according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders. Furthermore, [the following is a list of steps]. Figure 1 At least some of the steps in the process may include multiple sub-steps or sub-stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0100] The above-described embodiments of the present invention describe in detail a method for tracking the flow of micro / nano fabricated samples. Since the above-described method can be implemented using various types of devices, the present invention also discloses a device for tracking the flow of micro / nano fabricated samples, in conjunction with the appendix. Figure 4 The following are specific embodiments for detailed explanation.

[0101] The initial defect feature acquisition module 301 is used to acquire the initial defect feature set of the sample surface before the sample is micro- or nano-processed.

[0102] The region selection module 302 is used to select the defect features of any region from the initial defect feature set as the first set of defect features;

[0103] The defect feature reacquisition module 303 is used to acquire a second set of defect features of a selected area of ​​the sample after any step of micro-nano processing is performed on the sample.

[0104] The defect feature matching module 304 is used to send a sample confirmation prompt message if the matching degree between the second set of defect features and the first set of defect features is less than a first threshold.

[0105] The defect feature update module 305 is used to update the initial defect feature set in combination with the second set of defect features if a confirmation information of sample consistency is received, and then return to the execution area selection module, defect feature reacquisition module, defect feature matching module and defect feature update module until the micro-nano fabrication process ends.

[0106] For details regarding the micro / nano fabrication sample flow tracking device, please refer to the method specifications above; they will not be repeated here. Each module in the aforementioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the terminal device in hardware form or independent of it, or stored in the memory of the terminal device in software form, so that the processor can call and execute the corresponding operations of each module.

[0107] In one embodiment, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described micro / nano fabrication sample flow tracking method.

[0108] The computer-readable storage medium may be an electronic storage device such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), hard disk, or ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium has storage space for program code that performs any of the method steps described above. This program code can be read from or written to one or more computer program products, and the program code may be compressed in an appropriate form.

[0109] In one embodiment, the present invention provides a computer device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the above-described micro / nano fabrication sample flow tracking method.

[0110] The computer device includes a memory, a processor, and one or more computer programs, wherein the one or more computer programs can be stored in the memory and configured to be executed by one or more processors, and the one or more application programs are configured to perform the above-described micro / nano fabrication sample flow tracking method.

[0111] A processor may include one or more processing cores. The processor connects to various parts of the computer device using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory, and by calling data stored in memory. Optionally, the processor may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also be implemented separately as a communication chip, without being integrated into the processor.

[0112] The memory may include random access memory (RAM) or read-only memory (ROM). The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), and instructions for implementing the various method embodiments described above. The data storage area may also store data created by the terminal device during use.

[0113] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for tracking the flow of micro / nano fabricated samples, characterized in that, include: Step S101: Before the sample undergoes micro / nano processing, an initial set of defect features on the sample surface is obtained; Step S102: Select the defect features of any region from the initial defect feature set as the first set of defect features; Step S103: After the sample has undergone any step of micro-nano fabrication, obtain the second set of defect features of the selected area of ​​the sample. Step S104: If the difference in the number of features between the second set of defect features and the first set of defect features is higher than a first ratio compared to the number of features in the first set of defect features; or the difference in the area between the second area of ​​any defect feature in the second set of defect features and the first area of ​​that defect feature in the first set of defect features is higher than a second ratio compared to the first area, and the number of area differences higher than the second ratio exceeds an area number threshold; or the second area of ​​any defect feature in the second set of defect features exceeds a preset area threshold, a sample confirmation prompt message is sent. Step S105: If a confirmation message confirming sample consistency is received, update the initial defect feature set in conjunction with the second set of defect features, and return to execute steps S102-S105 until the micro-nano fabrication process ends. The step of selecting defect features from any region in the initial defect feature set as the first set of defect features specifically involves: Select any corner region and the defect features on the adjacent edges of that corner region from the initial defect feature set as the first set of defect features; The sample confirmation prompt information is used to remind users or staff whether the sample has changed before and after the micro-nano processing, and to verify the characteristics of the sample after the change.

2. The micro / nano fabrication sample flow tracking method as described in claim 1, characterized in that, The acquisition of the initial defect feature set of the sample surface specifically includes: Initial image information of the sample surface is acquired using an image acquisition device; Based on the initial image information, the defect features of the sample surface edge region are obtained, and the defect features of all edge regions are recorded as the initial defect feature set.

3. The micro / nano fabrication sample flow tracking method as described in claim 2, characterized in that, The step of obtaining the defect features of the sample surface edge region based on the initial image information specifically involves: The initial image information is input into the feature extraction model to obtain the defect features of the sample surface edge region.

4. The micro / nano fabrication sample flow tracking method as described in claim 1, characterized in that, If a confirmation message indicating sample consistency is received, the initial defect feature set is updated in conjunction with the second set of defect features, specifically as follows: If a confirmation message indicating sample consistency is received, the second set of defect features is merged into the initial set of defect features in conjunction with the sample micro-nano fabrication steps. The second set, which combines the defect characteristics of the sample micro-nano fabrication steps, includes the process parameters and processing time of the sample micro-nano fabrication steps.

5. A micro / nano fabrication sample flow tracking device, characterized in that, include: The initial defect feature acquisition module is used to acquire the initial defect feature set of the sample surface before the sample is micro- or nano-fabricated. The region selection module is used to select the defect features of any region from the initial defect feature set as the first set of defect features; The defect feature reacquisition module is used to acquire a second set of defect features of a selected area of ​​the sample after any step of the micro-nano fabrication process is performed on the sample. The defect feature matching module is configured to send a sample confirmation prompt if: the difference in the number of features between the second set of defect features and the first set of defect features is higher than a first proportion compared to the number of features in the first set of defect features; or the difference in the area between the second area of ​​any defect feature in the second set of defect features and the first area of ​​that defect feature in the first set of defect features is higher than a second proportion compared to the first area, and the number of area differences higher than the second proportion exceeds an area number threshold; or the second area of ​​any defect feature in the second set of defect features exceeds a preset area threshold. The defect feature update module is used to update the initial defect feature set in combination with the second set of defect features if a confirmation information of sample consistency is received, and then return to the execution area selection module, defect feature reacquisition module, defect feature matching module and defect feature update module until the micro-nano fabrication process ends; The step of selecting defect features from any region in the initial defect feature set as the first set of defect features specifically involves: Select any corner region and the defect features on the adjacent edges of the corner region from the initial defect feature set as the first set of defect features; the sample confirmation prompt information is used to remind users or staff whether the sample has changed before and after the micro-nano processing, and to verify the features of the sample after the change.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of any one of the micro / nano fabrication sample flow tracking methods in claims 1-4.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it performs any one of the micro / nano fabrication sample flow tracking methods according to claims 1-4.

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