Design method, device, computer equipment and storage medium of three-dimensional integrated device

Abstract

The application relates to the technical field of integrated circuits, in particular to a design method and device of a three-dimensional integrated device, computer equipment and a storage medium. The method comprises the following steps: obtaining theoretical parameters of a target device, inputting the theoretical parameters into a simulation model, and obtaining theoretical characteristics output by the simulation model; obtaining defect parameters of a sample device prepared according to the theoretical parameters, inputting the defect parameters and the theoretical parameters into the simulation model, and obtaining production characteristics output by the simulation model; and determining an optimization dimension according to the theoretical characteristics and the production characteristics. The application can improve the research and development effectiveness of the three-dimensional integrated device.

Description

Technical Field

[0001] This application relates to the field of integrated circuit technology, and in particular to a design method, apparatus, computer equipment, and storage medium for a three-dimensional integrated device. Background Technology

[0002] To further improve the integration, miniaturization, and speed of chips, researchers are integrating chips into heterogeneous systems in three dimensions, with the aim of increasing the functional density of the chips.

[0003] In the process of three-dimensional heterogeneous system integration, the size of each component significantly affects the overall system size, especially for some microwave / millimeter-wave passive components, including capacitors, inductors, filters, duplexers, and low-noise amplifiers. The size of these components is a major bottleneck limiting the miniaturization of integrated circuits. Furthermore, due to limitations in process technology, integrated circuits based on three-dimensional integration processes may have structural defects, leading to reduced product functionality and performance.

[0004] Therefore, in order to improve product performance, it is urgent to optimize the R&D process of 3D integrated devices. Summary of the Invention

[0005] Therefore, it is necessary to provide a design method, apparatus, computer equipment, and storage medium for three-dimensional integrated devices that can improve the effectiveness of three-dimensional integrated device research and development, in response to the above-mentioned technical problems.

[0006] In a first aspect, this application provides a design method for a three-dimensional integrated device, the method comprising:

[0007] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0008] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0009] Based on the theoretical and production characteristics, the optimization dimensions are determined.

[0010] In one embodiment, the method further includes:

[0011] Based on the optimization dimension, an optimization strategy is determined; wherein, if the optimization dimension characterizes a design dimension defect, the optimization strategy is used to adjust the theoretical parameters so that the difference between the adjusted theoretical characteristics and the production characteristics is less than a preset error value; if the optimization dimension characterizes a production dimension defect, the optimization strategy is used to adjust the sample device fabrication method so that the difference between the production characteristics and the theoretical characteristics of the device fabricated based on the adjusted fabrication method is less than a preset error value.

[0012] In one embodiment, the step of preparing a sample device based on the theoretical parameters of the target device and obtaining the defect parameters of the sample device includes:

[0013] Obtain multiple sample devices fabricated based on the theoretical parameters of the target device;

[0014] Obtain the individual defect parameters of each of the sample devices;

[0015] The defect parameters of each sample device are determined based on the average value of the individual defect parameters of each sample device.

[0016] In one embodiment, obtaining the individual defect parameters of each of the sample devices includes:

[0017] For any given sample device, acquire an image of the sample device; the sample device includes at least one type of defect;

[0018] Based on the defect model corresponding to each defect, the image of the sample device is used to identify defects, and the individual defect parameters are obtained.

[0019] In one embodiment, the defect model includes a defect identification model and a defect calculation model corresponding to the defect identification model;

[0020] The step of identifying defects in the image of the sample device based on the defect model corresponding to each defect to obtain the individual defect parameters includes:

[0021] Based on the defect identification models described above, defects are identified in the images of the sample devices to determine at least one defect region.

[0022] Based on the defect calculation model corresponding to each defect region, the individual defect parameters of each defect region are determined.

[0023] In one embodiment, determining the individual defect parameters for each defect region based on the defect calculation model corresponding to each defect region includes:

[0024] For any defective region, the defective region is fitted into a regular region according to the defect calculation model corresponding to the defective region, and the regular region completely covers the defective region.

[0025] The size parameters of the regular region are calculated using the defect calculation model, and the individual defect parameters of the defect region are determined based on the size parameters of the regular region.

[0026] In one embodiment, fitting the defect region into a regular region based on the defect calculation model corresponding to the defect region includes:

[0027] If the defect type of the defect region is a metal line erosion defect, then the regular region is a three-dimensional column.

[0028] If the defect type of the defect region is a metal through-hole pit defect, then the regular region is a three-dimensional circular pit.

[0029] If the defect type of the defect region is a through-hole offset defect, then the regular region is a two-dimensional circular region marked with a center.

[0030] In one embodiment, the step of calculating the size parameters of the regular region using the defect calculation model, and determining the individual defect parameters of the defect region based on the size parameters of the regular region, includes:

[0031] If the regular region is a three-dimensional column, then the volume of the three-dimensional column is determined as the individual defect parameter of the defect region;

[0032] If the regular region is a three-dimensional circular pit, then the cavity volume of the circular pit is determined as the individual defect parameter of the defect region;

[0033] If the regular region is a two-dimensional circular region marked with a center, then the offset parameter between the center of the circular region and the center of the through hole corresponding to the theoretical parameter is determined as the individual defect parameter of the defect region.

[0034] In one embodiment, the sample device is fabricated based on glass through-hole technology and the theoretical parameters of the target device, wherein the sample device includes front metal lines, through-hole metal, glass substrate and back metal lines.

[0035] Secondly, this application also provides a design apparatus for a three-dimensional integrated device, the apparatus comprising:

[0036] The simulation module is used to obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model.

[0037] The correction module is used to obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0038] The comparison module is used to determine the optimization dimensions based on the theoretical characteristics and the production characteristics.

[0039] Thirdly, this application also provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0040] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0041] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0042] Based on the theoretical characteristics and the production characteristics, the optimization dimensions are determined. Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0043] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0044] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0045] Based on the theoretical and production characteristics, the optimization dimensions are determined.

[0046] Fifthly, this application also provides a computer program product comprising a computer program that, when executed by a processor, performs the following steps:

[0047] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0048] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0049] Based on the theoretical and production characteristics, the optimization dimensions are determined.

[0050] The aforementioned design method, apparatus, computer equipment, and storage medium for 3D integrated devices simulate the target device corresponding to theoretical parameters, determining whether the theoretical parameters require further optimization based on theoretical characteristics. Actual sample device fabrication and acquisition of defect parameters from the sample device enable more accurate identification of defects occurring during actual production. Both defect parameters and theoretical parameters are input into the simulation model, and production characteristics are acquired in the simulation environment to simulate the actual impact of defect parameters on the performance of the target device and determine optimization dimensions. Based on these optimization dimensions, the design team is guided to investigate the causes of defects in both design and production dimensions, ensuring the comprehensiveness and accuracy of defect analysis. The design process fully considers the impact of defects on product performance, thereby improving the effectiveness of 3D integrated device R&D and ultimately optimizing the performance of the 3D integrated device. Furthermore, this method provides a general workflow. For different types of devices, only corresponding defect parameter detection methods need to be designed for each type of device, and then the corresponding optimization dimensions can be generated according to this general workflow, without needing to design a separate defect detection process for each type of device, thus improving the versatility of the 3D integrated device design method. Attached Figure Description

[0051] Figure 1 This is an application environment diagram of a design method for three-dimensional integrated devices in one embodiment;

[0052] Figure 2 This is a flowchart illustrating a design method for a three-dimensional integrated device in one embodiment;

[0053] Figure 3 This is a three-dimensional schematic diagram of a three-dimensional integrated inductor structure in one embodiment;

[0054] Figure 4 This is a flowchart illustrating the process of obtaining defect parameters of a sample device in another embodiment;

[0055] Figure 5 This is a schematic diagram of a process for determining individual defect parameters based on images of sample devices in one embodiment;

[0056] Figure 6 This is a schematic diagram of RDL side etch defects in one embodiment;

[0057] Figure 7 This is a schematic diagram of a through-hole metal pit defect in one embodiment;

[0058] Figure 8 This is a schematic diagram of a through-hole offset defect in one embodiment;

[0059] Figure 9 This is a schematic diagram of a defect corresponding to a three-dimensional integrated inductor structure in one embodiment;

[0060] Figure 10 This is a flowchart illustrating the process of determining defect parameters based on an image of a sample device in one embodiment.

[0061] Figure 11 This is a flowchart illustrating the process of determining defect parameters based on a defect calculation model in one embodiment.

[0062] Figure 12 This is a schematic diagram of the process of fitting a defective region into a regular region in one embodiment;

[0063] Figure 13 This is a schematic diagram of fitting the defect region of the RDL into a three-dimensional column in one embodiment;

[0064] Figure 14 This is a schematic diagram of fitting the defect area of ​​a metal through-hole pit into a circular pit in one embodiment.

[0065] Figure 15 This is a schematic diagram of fitting a defective region of via offset into a circular region in one embodiment;

[0066] Figure 16 This is a flowchart illustrating a design method for a three-dimensional integrated device in another embodiment;

[0067] Figure 17 This is a structural block diagram of the defective device in one embodiment;

[0068] Figure 18 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0070] The design method for three-dimensional integrated devices provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. The design method for the three-dimensional integrated device of this application can be applied to... Figure 1In the server 104 shown, for example, the server 104 can acquire the theoretical parameters of the target device collected by the terminal 102, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model; acquire the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model; and determine the optimization dimensions based on the theoretical characteristics and production characteristics. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0071] Three-dimensional integrated circuits (3D integrated circuits) are a rapidly growing new technology with significant potential performance and functional advantages. 3D integration can enhance internal interconnects, provide high device integration density, effectively reduce the length and number of global interconnects, and promises to enable heterogeneous chip integration, achieving more complex and higher-performance on-chip systems. In recent years, as the feature size of semiconductor devices has gradually decreased, the integration density of integrated circuits has also gradually increased. However, with the increasing integration density, various defects may exist in the fabrication of semiconductor devices (especially 3D integrated passive devices based on through-silicon via (TSV) technology) due to process technology limitations, leading to reduced product functionality and performance. Therefore, accurately detecting structural defects in 3D integrated circuit products has become an urgent technical problem to be solved.

[0072] In one embodiment, such as Figure 2 As shown, a design method for three-dimensional integrated devices is provided, which can be applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0073] S202: Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model.

[0074] The target device is any device designed by the designer for integration onto a three-dimensional integrated circuit. The target device includes, but is not limited to, any one of capacitors, inductors, filters, duplexers, or couplers.

[0075] The theoretical parameters of the target device can include its design parameters and process parameters. Taking an inductor as an example, for instance... Figure 3As shown, this is a three-dimensional integrated inductor structure based on through-glass vias (TGVs) and redistribution layers (RDLs). Compared with traditional planar spiral inductor structures, this inductor structure is closer to a solenoid. The design parameters of the three-dimensional integrated inductor structure include the number of inductor turns, the spacing between TGVs on the same side, the spacing between TGVs on opposite sides, and the width of the RDL metal. The process parameters include the height of the through-glass via, the radius of the through-glass via, the thickness of the RDL metal, the conductivity of the silicon substrate, and the thickness of the TGV oxide layer.

[0076] The simulation model can be either pre-built simulation software or a model for calculating the equivalent circuit. Taking a three-dimensional integrated inductor structure as an example, the simulation software extracts the characteristic parameters of the target device using pre-built formulas. These characteristic parameters include scattering parameters (S-parameters), Y-parameters, quality factor (Q-value), inductance value, or capacitance value. For example, in a two-port network based on an inductor, the inductor parameter extraction formula is (where Y11 is the Y-parameter):

[0077]

[0078]

[0079] Theoretical characteristics refer to the simulation results obtained by inputting theoretical parameters into the simulation model. The simulation result parameters include, but are not limited to, at least one of the following: scattering parameters (S-parameters), response waveform, cutoff frequency, ripple amplitude, phase difference, quality factor (Q), characteristic impedance, capacitance value, and inductance value.

[0080] In this embodiment, the purpose of obtaining the theoretical characteristics output by the simulation model is to preliminarily verify the theoretical performance of the target device and determine whether the theoretical parameters of the target device are reasonable.

[0081] S204: Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model.

[0082] Among them, the sample device is a device fabricated based on theoretical parameters and actual production equipment. The defect parameters of the sample device refer to the various defect values ​​obtained from actual testing of the sample device. Different devices have different defect types, and the same device may also correspond to multiple different defect types. The types of defects in three-dimensional passive devices include, but are not limited to, metal pillar bulging in glass / through-silicon vias, metal pillar voids, incomplete connection with horizontal metal interconnects, voids or cracks in horizontal metal interconnects, etc. Specifically, different defect dimensions, such as different shapes and sizes of voids, will also lead to different device failure problems. There is a mapping relationship between the type of defect and the problems existing in the device. The device problems that defects may cause include, but are not limited to, signal integrity problems, electrical characteristic degradation problems, or overall functional loss problems.

[0083] Specifically, there is at least one sample device. When there is only one sample device, the defect value of that sample device is used as the defect parameter of the sample device. When there are multiple sample devices, the individual defect parameters corresponding to each sample device are collected, and the average value of multiple individual defect parameters can be used as the defect parameter of the sample device. Alternatively, the maximum defect value among the defect sample parameters can be used as the defect parameter of the sample device.

[0084] After obtaining the defect parameters, they can be inserted into the theoretical parameters to adjust them, and then the adjusted theoretical parameters can be input into the simulation model. Alternatively, both the theoretical parameters and the defect parameters can be input into the simulation model simultaneously, and the theoretical parameters can be adjusted within the simulation model. In this embodiment, the production characteristics output by the simulation model are obtained to simulate the performance of the target device under actual production conditions, in order to verify the extent to which the defect parameters affect the performance of the target device.

[0085] S206. Based on theoretical and production characteristics, determine the optimization dimensions.

[0086] In this embodiment, firstly, it is determined whether the device performance characterized by theoretical characteristics meets the preset performance indicators. If it does, it indicates that the theoretical parameters of the target device meet the design conditions. If it does not meet the preset performance indicators, it indicates that the theoretical parameters of the target device need further optimization. In this case, the optimization dimension indicates that there are design-dimensional defects in the theoretical parameters. Secondly, the theoretical characteristics are compared with the production characteristics to obtain the difference value. Based on the difference value, the impact of defective parameters on the performance of the target device can be determined. If the difference value exceeds the preset error range, it is determined that the sample device has a large error and is a defective product. At this time, if the theoretical characteristics meet the preset performance indicators and the difference value exceeds the preset error range, the optimization dimension indicates that there are production-dimensional defects in the production equipment, that is, abnormal operating conditions occur in the production environment, causing abnormal defects in the sample device prepared by the production equipment according to the preset theoretical parameters.

[0087] In the aforementioned design method for 3D integrated devices, the target device corresponding to the theoretical parameters is simulated, and the theoretical parameters are judged based on the theoretical characteristics to determine whether further optimization is needed. Sample devices are actually fabricated, and their defect parameters are obtained to more accurately identify defects occurring in the actual production process. Both defect parameters and theoretical parameters are input into the simulation model, and production characteristics are acquired in the simulation environment to simulate the actual impact of defect parameters on the performance of the target device and determine the optimization dimensions. Based on the optimization dimensions, the designer is guided to investigate the causes of defects in both the design and production dimensions, ensuring the comprehensiveness and accuracy of defect analysis. The impact of defects on product performance is fully considered during the design process to improve the effectiveness of 3D integrated device R&D and ultimately optimize the performance of the 3D integrated device. Furthermore, this method provides a general process. For different types of devices, only corresponding defect parameter detection methods need to be designed for each type of device, and then the corresponding optimization dimensions can be generated according to this general process, without needing to design a separate defect detection process for each type of device, thus improving the versatility of the 3D integrated device design method.

[0088] In one embodiment, the design method for the three-dimensional integrated device further includes: determining an optimization strategy based on the optimization dimension. Wherein, if the optimization dimension characterizes a design dimension defect, the optimization strategy is used to adjust theoretical parameters so that the difference between the adjusted theoretical characteristics and the production characteristics is less than a preset error value; if the optimization dimension characterizes a production dimension defect, the optimization strategy is used to adjust the sample device fabrication method so that the difference between the production characteristics and the theoretical characteristics of the device fabricated based on the adjusted fabrication method is less than a preset error value.

[0089] For example, when adjusting the design and / or manufacturing process of a three-dimensional integrated inductor structure based on an optimization strategy, a corresponding value range is first preset for each parameter of the three-dimensional integrated inductor structure. Table 1 below shows the theoretical parameters corresponding to the three-dimensional integrated inductor structure:

[0090] Table 1

[0091]

[0092]

[0093] Secondly, after determining the optimization dimension, the corresponding optimization strategy is retrieved based on the correlation between the optimization dimension and the preset optimization strategy. Specifically, if the optimization dimension characterizes a design dimension defect, the corresponding optimization strategy is as follows: using the controlled variable method, only the value of a certain dimension parameter in the theoretical parameters is changed each time, while the values ​​of other parameters remain unchanged; the influence of the operating frequency on the inductance value and quality factor of the three-dimensional integrated inductor structure is simulated, and the parameters corresponding to the simulation results that meet the preset design conditions are taken as candidate theoretical parameters. Sample devices corresponding to the candidate theoretical parameters are prepared, and the corresponding production characteristics are obtained. Candidate theoretical parameters whose difference between theoretical characteristics and production characteristics is less than the preset error value are selected as adjusted theoretical parameters.

[0094] If the optimization dimension characterizes the defects in the production dimension, then the corresponding optimization strategy is to obtain the various operating parameters of the production equipment in the working state, verify whether there are any abnormalities in the production equipment, so that the difference between the production characteristics and the theoretical characteristics of the device prepared based on the adjusted preparation method is less than the preset error value.

[0095] In this embodiment, corresponding optimization strategies are matched according to different optimization dimensions, and the theoretical parameters or sample device fabrication process is adjusted based on the optimization strategies to continuously iterate the device design and reduce the probability of defects in actual production.

[0096] If there are multiple sample devices, multiple sample devices are selected based on the same process parameters but different production lines. Furthermore, when determining the defect parameters of the sample devices, to reduce random errors, in one embodiment, such as... Figure 4 As shown, this embodiment provides an optional method for obtaining defect parameters of a sample device prepared according to theoretical parameters, that is, a method for refining S204. The specific implementation process may include:

[0097] S401, Obtain multiple sample devices fabricated based on the theoretical parameters of the target device.

[0098] In this process, multiple production lines are configured with the same process parameters, and each different production line is controlled to prepare a sample device based on the same theoretical parameters. Then, at least one device is obtained from each production line to obtain multiple sample devices. The actual production error of each production line is verified by using multiple sample devices from different production lines.

[0099] In one embodiment, each sample device is fabricated based on glass via technology and the theoretical parameters of the target device. The sample device includes a front-side RDL metal line, a TGV via metal, a glass substrate, and a back-side RDL metal line. Specifically, the front-side RDL metal line, TGV via metal, glass substrate, and back-side RDL metal line are arranged sequentially from top to bottom. The materials of the front-side and back-side RDL metal lines are gold, copper, or silver; the TGV via metal can be cylindrical, and the via metal material is copper; the glass substrate material can be quartz glass or borosilicate glass, such as Schott AF32.

[0100] S402, obtain the individual defect parameters of each sample device.

[0101] For any given sample device, when detecting the defect parameters of the sample device, different testing devices can be used to detect the defects of the sample device in various dimensions respectively; alternatively, the individual defect parameters of the sample device can be obtained by acquiring an image of the sample device and analyzing the image of the sample based on a deep learning model.

[0102] S403, determine the defect parameters of the sample devices based on the average value of the individual defect parameters of each sample device.

[0103] The defects of a device can be in multiple dimensions, such as dimension a, dimension b, dimension c, and dimension d. For any dimension of defect parameters, the average value of the individual defect parameters is obtained as the defect parameters of the sample device. For example, if individual defect parameter 1 is {a1, b1, c1, d1}, individual defect parameter 2 is {a2, b2, c2, d2}, and individual defect parameter 3 is {a3, b3, c3, d3}, then the defect parameters of the sample device are {(a1+a2+a3) / 3, (b1+b2+b3) / 3, (c1+c2+c3) / 3, (d1+d2+d3) / 3}.

[0104] When obtaining the individual defect parameters of any sample device, such as Figure 5 As shown, this embodiment provides an optional method for determining individual defect parameters based on images of sample devices, that is, a method for refining S402. The specific implementation process may include:

[0105] S501: For any given sample device, acquire an image of the sample device.

[0106] The sample device includes at least one type of defect. Multiple images of the sample device are acquired based on multiple preset shooting angles. The defect type and defect location of the sample device are analyzed more comprehensively and accurately through multiple sample images from different angles.

[0107] S502, based on the defect model corresponding to each defect, performs defect identification on the image of the sample device to obtain individual defect parameters.

[0108] Each defect type corresponds one-to-one with each defect model. Taking the above three-dimensional integrated inductor structure as an example, the defect types include, but are not limited to, metal line side etching defects (RDL side etching defects), through-hole offset defects, and through-hole metal pit defects.

[0109] Specifically, such as Figure 6 As shown, Figure 6 -(a) RDL metal wires prepared under ideal (standard) conditions; Figure 6 -(b) and Figure 6 -(c) all represent cases where corrosion occurs on the RDL metal wire, i.e., RDL lateral corrosion defects. For example... Figure 7 As shown, Figure 7 -(a) shows the cylindrical TGV structure prepared under ideal conditions (standard conditions). Figure 7 -(b) indicates incomplete filling of the TGV's metal conductor, such as pits on the top or bottom surface of the metal conductor, i.e., through-hole metal pit defects. Figure 8 As shown, Figure 8 -(a) shows the positional relationship between the RDL metal wire and the through-hole metal under ideal (standard) preparation conditions. Figure 8 -(b) indicates a shift in the position of the TGV through-hole metal compared to the position corresponding to the theoretical parameters, i.e., a through-hole offset defect. For example... Figure 9 As shown, this is a top view or bottom view of the three-dimensional integrated inductor structure, and the image shows the three types of defects mentioned above.

[0110] To accurately analyze each defect type, in this example, there is an RDL side erosion defect model for RDL side erosion defects, a through-hole offset defect model for through-hole offset defects, and a through-hole metal pit defect model for through-hole metal pit defects. Specifically, each defect model can be a neural network model trained based on training samples corresponding to each defect type, or it can be a computational model built specifically for each defect type; this embodiment does not impose any limitations on this.

[0111] In this embodiment, a defect model is provided for each defect type, which improves the targeting and accuracy of the identification of different defect types; and the sample image is used as the input of each defect model, and multiple defect models can analyze the sample image simultaneously, which improves the efficiency of defect identification.

[0112] Since convolutional neural networks can use multiple convolutional kernels to extract different image information, the defect model in this embodiment includes a defect recognition model and a defect calculation model corresponding to the defect recognition model; for example... Figure 10 As shown, this embodiment provides an optional method for identifying defects in the image of a sample device based on the defect model corresponding to each defect, thereby obtaining defect parameters. In other words, it provides a way to refine S502. The specific implementation process may include:

[0113] S1001, perform defect identification on the image of the sample device according to each defect identification model, and determine at least one defect area.

[0114] Each defect type corresponds one-to-one with a defect identification model. Each defect identification model can be a convolutional neural network model trained based on training samples corresponding to each defect type. The training samples are images of the original device and defect labels corresponding to the images of the original device. The defect labels can include defect type and defect region.

[0115] Specifically, for any image of any sample device, the image is identified according to each trained defect identification model to obtain at least one defect region. For example, the defect regions identified in the image are a1, a2, a3, b1, b2, c1, and c2. Among them, defect regions a1, a2, and a3 are identified based on defect identification model A, defect regions b1 and b2 are identified based on defect identification model B, and defect regions c1 and c2 are identified based on defect identification model C.

[0116] Furthermore, when defective regions at the same location are identified in different sample images corresponding to the same sample device, and the size or shape of the defective regions are different, a prompt message can be generated to prompt the designer to filter the repeatedly identified regions. In another possible implementation, the images corresponding to the same sample device can be made different from each other according to the preset shooting angle. Taking the three-dimensional integrated inductor structure as an example, since the main defect types identified by the three-dimensional integrated inductor structure are metal line side etching defects, via offset defects, and via metal pit defects, the shooting angle can be configured only as the top and bottom angles of the three-dimensional integrated inductor structure. For other target devices, this embodiment does not limit this.

[0117] S1002, based on the defect calculation model corresponding to each defect region, determine the individual defect parameters of each defect region.

[0118] After identifying each defect region, the defect parameters for each region are obtained by analyzing the corresponding defect calculation model. Based on these parameters, the individual defect parameters of the sample device are determined. Continuing the previous example, defect regions a1, a2, and a3 correspond to defect calculation model A, defect regions b1 and b2 correspond to defect calculation model B, and defect regions c1 and c2 correspond to defect calculation model C. Different algorithms may be used in defect calculation models A, B, and C depending on the different defect types.

[0119] Specifically, when determining the defect parameters of a sample device based on the average value of its individual defect parameters, for example, sample device 1 corresponds to defect region a (individual defect parameter value x1), defect region b (individual defect parameter value y1), and defect region c (individual defect parameter value z1); sample device 2 has defect regions a (individual defect parameter value x2), defect region b (individual defect parameter value y2), and defect region c (individual defect parameter value z2); and sample device 3 has defect regions a (individual defect parameter value x3) and defect region b (individual defect parameter value y1). Here, defect regions a and b refer to defect regions of the same type and location within the same sample device. Therefore, when calculating the defect parameters of the sample device, the defect parameters are: {defect region a (defect parameter value (x1+x2+x3) / 3), defect region b (defect parameter value (y1+y2+y3) / 3), and defect region c (defect parameter value (z1+z2) / 2)}.

[0120] In this embodiment, when analyzing any sample device, multiple images of the sample device are first acquired. Based on each defect identification model, defects are identified in each image to determine the defect area. After the defect area is determined, each defect area is analyzed based on each defect calculation model to obtain defect parameters. Each image is then input into each defect identification model and defect calculation model for analysis, which improves the efficiency of defect analysis.

[0121] Since the edges of defect regions are usually irregularly shaped, fitting irregular defect regions increases the computational load of the defect calculation model. Therefore, in order to achieve rapid analysis of defect regions, such as... Figure 11 As shown, this embodiment provides an optional method for determining defect parameters based on the defect calculation model corresponding to each defect region, that is, a method for refining S1002. The specific implementation process may include:

[0122] S1101: For any defect region, fit the defect region into a regular region according to the defect calculation model corresponding to the defect region.

[0123] Each defect calculation model corresponds to a regular graphic. After determining the regular graphic corresponding to the defect area, the defect area is fitted into a regular area based on the regular graphic, and the regular area completely covers the regular area.

[0124] Specifically, the above-mentioned method for generating regular regions is at least one of the following two methods: Method 1) After determining the regular shape, multiple candidate regions are generated by adjusting the position and size of the regular shape, and each candidate region completely covers the regular region. The region corresponding to the smallest parameter value (parameter value includes area or volume, etc.) among the candidate regions is selected as the regular region. Therefore, the regular region obtained at this time can completely cover the defect region, and the difference between the parameter of the regular region and the parameter of the defect region is within the allowable error range; Method 2) A preset parameter difference range is obtained. After determining the regular shape, the position and size of the regular shape are changed within the preset parameter difference range to generate the regular region. At this time, the difference between the parameter of the regular region obtained at this time and the parameter of the regular region is within the allowable error range.

[0125] Furthermore, the regular shape can be a two-dimensional planar shape or a three-dimensional solid shape. Therefore, the regular region can be a two-dimensional planar region or a three-dimensional spatial region. Optionally, referring to the example in S502 above, the regular region corresponding to the RDL side etching defect is a three-dimensional corrosion region; the regular region corresponding to the through-hole offset defect is a two-dimensional circular region with a center marked; and the regular region corresponding to the through-hole metal pit defect is a three-dimensional pit region. In this case, this embodiment provides an optional way to fit the defect region into a regular region, that is, to provide a way to refine S1101. The specific implementation process may include: if the defect type of the defect region is a through-hole metal pit defect, then the regular region is a three-dimensional circular pit; if the defect type of the defect region is a through-hole offset defect, then the regular region is a two-dimensional through-hole marked with a center; and if the defect type of the defect region is a metal line side etching defect, then the regular region is a three-dimensional column.

[0126] Continue to refer to Figure 11 S1102, calculate the size parameters of the regular region through the defect calculation model, and determine the individual defect parameters of the defect region based on the size parameters of the regular region.

[0127] Specifically, the calculation method differs for each regular region. After determining the dimensional parameters for each regular region, the defect parameters for that region are calculated based on the corresponding defect calculation model. For example, the defect parameter for RDL side erosion defects is the volume of the corroded column; the defect parameter for through-hole offset defects is the offset between the offset position of the through-hole and the position corresponding to the theoretical parameters; and the defect parameter for through-hole metal pit defects is the pit volume. Therefore, as... Figure 12 As shown, this embodiment provides an optional method for fitting a defect region into a regular region, that is, a method for refining S1102. The specific implementation process may include:

[0128] S1201, if the defect type of the defect area is a metal line side etching defect, then the regular area is a three-dimensional column.

[0129] In a target device, there may be multiple RDL metal lines. For any given RDL metal line, such as Figure 13 As shown, a sample image containing a corrosion region in the RDL metal wire is used as the target sample image. A rectangle is used as the regular shape to fit the corrosion region in the target sample image. In this embodiment, taking a three-dimensional integrated inductor structure as an example, when the target sample image is a top view of the three-dimensional integrated inductor structure, as shown... Figure 13 As shown in (a), the lateral erosion length and width of the rectangular region are measured using the lower left corner of the rectangular region as the zero point for dimensional determination. This is based on the formation of a 90-degree circular arc cylinder within the rectangular region, or as shown in (a). Figure 13 -(b) shows a 45-degree triangle (and) Figure 6 -(c) corresponds to).

[0130] Furthermore, in one embodiment, if the regular region is a three-dimensional cylinder, then the volume of the three-dimensional cylinder is determined as the individual defect parameter of the defect region. In another implementation, the volume and position of the cylinder or triangular prism can also be used as the individual defect parameter corresponding to the defect region.

[0131] Continue to refer to Figure 12 S1202, if the defect type of the defect area is a metal through-hole pit defect, then the regular area is a three-dimensional circular pit.

[0132] Among them, such as Figure 14 As shown, when calculating the defect parameters corresponding to the three-dimensional circular pit, it is first determined whether there is a pit on the top or bottom surface of the TGV in the sample image. If there is a pit, the top view of the pit is taken as the first sample image, and the inspection party obtains the cross-sectional view corresponding to the center section of the TGV by grinding the TGV, and takes the cross-sectional view as the second sample image.

[0133] like Figure 14As shown in (a), in the first sample image, a circle is used as a regular shape to fit the top surface of the pit, resulting in a circular region. The center of this circular region is taken as the test zero point, and the radius of the circular region is calculated as the diameter of the pit. Figure 14 As shown in (b), in the second sample image, a hollow cone with its vertex pointing downwards is used as a regular shape to fit the pit, such that the center of the cone's base coincides with the center of the aforementioned circular region. The cavity of the cone is then considered a regular region, and the height of the cone is determined as the pit depth. The volume of the conical cavity is calculated based on the pit diameter and pit depth.

[0134] Furthermore, in one embodiment, if the regular region is a three-dimensional circular pit, then the cavity volume of the circular pit is determined as the individual defect parameter of the defect region. In another implementation, the volume and position of the conical cavity can also be used as the individual defect parameters corresponding to the defect region.

[0135] Continue to refer to Figure 12 S1203, If the defect type of the defect area is a through-hole offset defect, then the regular area is a two-dimensional circular area marked with a center.

[0136] In a single target device, there may be multiple TGVs. For any given TGV, such as Figure 15 As shown, the theoretical center position A of the through-hole of the TGV is determined based on theoretical parameters. Then, if the corresponding through-hole position of the TGV is identified in the sample image, the through-hole position is fitted as a circular region marked with a center, and the center of this circular region is taken as the actual center position B. Points A and B are measured in the same spatial coordinate system. When calculating the offset distance Rα between the actual center position B and the theoretical through-hole center A, a line is established connecting points A and B, and the length of this line is calculated. When calculating the offset angle α between the actual center B and the theoretical through-hole center A, the angle between the aforementioned line and a preset baseline passing through point A is taken as the offset angle α.

[0137] Furthermore, in one embodiment, if the regular region is a two-dimensional circular region marked with a center, then the offset parameter between the center of the circular region and the center of the through hole corresponding to the theoretical parameter is determined as the individual defect parameter of the defect region. That is, the offset distance Rα and the offset angle α are used as the individual defect parameters of the defect region.

[0138] In this embodiment, each defect calculation model first fits each defect region into a regular region. Since the size parameters of the regular region are easy to collect and easy to calculate, the amount of computation in the process of obtaining defect parameters is reduced.

[0139] For example, based on the above embodiments, this embodiment provides an optional example of a design method for three-dimensional integrated devices. For instance... Figure 17 As shown, the specific implementation process includes:

[0140] S1701: Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0141] S1702, Obtain multiple sample devices fabricated based on the theoretical parameters of the target device;

[0142] S1703: For any given sample device, acquire an image of the sample device;

[0143] S1704, perform defect identification on the image of the sample device according to each defect identification model, and determine at least one defect area;

[0144] S1705, for any defect region, fit the defect region into a regular region according to the defect calculation model corresponding to the defect region;

[0145] S1706, calculates the size parameters of the regular region through the defect calculation model, and determines the individual defect parameters of the defect region based on the size parameters of the regular region;

[0146] Specifically, if the defect type of the defect area is a metal line erosion defect, then the regular area is a three-dimensional column, and the volume of the three-dimensional column is determined as the individual defect parameter of the defect area; if the defect type of the defect area is a metal through-hole pit defect, then the regular area is a three-dimensional circular pit, and the cavity volume of the circular pit is determined as the individual defect parameter of the defect area; if the defect type of the defect area is a through-hole offset defect, then the regular area is a two-dimensional circular area marked with a center, and the offset parameter between the center of the circular area and the center of the through-hole corresponding to the theoretical parameter is determined as the individual defect parameter of the defect area.

[0147] S1707, Determine the defect parameters of the sample devices based on the average value of the individual defect parameters of each sample device;

[0148] S1708: Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0149] S1709, determine the optimization dimensions based on theoretical and production characteristics.

[0150] S1710, Determine the optimization strategy based on the optimization dimensions.

[0151] If the optimization dimension characterizes the design dimension defect, the corresponding optimization strategy is as follows: adopt the control variable method, change the value of only one dimension parameter in the theoretical parameters each time, while keeping the other parameter values ​​unchanged; simulate the influence of the operating frequency on the inductance value and quality factor of the three-dimensional integrated inductor structure, take the parameters corresponding to the simulation results that meet the preset design conditions as candidate theoretical parameters, prepare sample devices corresponding to the candidate theoretical parameters, obtain the corresponding production characteristics, and select candidate theoretical parameters whose difference between theoretical characteristics and production characteristics is less than the preset error value as adjusted theoretical parameters.

[0152] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily 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 performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0153] Based on the same inventive concept, this application also provides a design apparatus for a three-dimensional integrated device to implement the design method of the three-dimensional integrated device described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method. Therefore, the specific limitations in one or more embodiments of the design apparatus for a three-dimensional integrated device provided below can be found in the limitations of the design method for the three-dimensional integrated device described above, and will not be repeated here.

[0154] In one embodiment, such as Figure 17 As shown, a design apparatus 1 for a three-dimensional integrated device is provided, including a simulation module 11, a correction module 12, and a comparison module 13, wherein:

[0155] Simulation module 11 is used to obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model.

[0156] The correction module 12 is used to obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0157] Comparison module 13 is used to determine the optimization dimensions based on theoretical and production characteristics.

[0158] In one embodiment, the design apparatus for the three-dimensional integrated device further includes a strategy generation module, which is used to determine an optimization strategy based on the optimization dimension; wherein, if the optimization dimension characterizes a design dimension defect, the optimization strategy is used to adjust the theoretical parameters so that the difference between the adjusted theoretical characteristics and the production characteristics is less than a preset error value; if the optimization dimension characterizes a production dimension defect, the optimization strategy is used to adjust the sample device fabrication method so that the difference between the production characteristics and the theoretical characteristics of the device fabricated based on the adjusted fabrication method is less than a preset error value.

[0159] In one embodiment, the design apparatus for the three-dimensional integrated device further includes a data acquisition module, which includes:

[0160] The fabrication submodule is used to obtain multiple sample devices fabricated based on the theoretical parameters of the target device;

[0161] The detection submodule is used to obtain the individual defect parameters of each sample device;

[0162] The mean submodule is used to determine the defect parameters of the sample devices based on the average value of the individual defect parameters of each sample device.

[0163] In one embodiment, the detection submodule includes:

[0164] The image acquisition module is used to acquire an image of any sample device; the sample device includes at least one type of defect;

[0165] The defect analysis module identifies defects in the images of sample devices based on the defect models corresponding to each defect, and obtains individual defect parameters.

[0166] In one embodiment, the defect model includes a defect identification model and a defect calculation model corresponding to the defect identification model; the defect analysis module includes:

[0167] The identification unit is used to identify defects in the image of the sample device according to each defect identification model, and determine at least one defect area.

[0168] The parsing unit is used to determine the individual defect parameters of each defect region based on the defect calculation model corresponding to each defect region.

[0169] In one embodiment, the parsing unit includes:

[0170] The fitting sub-unit is used to fit any defect region into a regular region based on the defect calculation model corresponding to the defect region. The regular region completely covers the defect region.

[0171] The calculation sub-unit is used to calculate the size parameters of the regular region through the defect calculation model, and to determine the individual defect parameters of the defect region based on the size parameters of the regular region.

[0172] In one embodiment, the fitting subunit is also used for:

[0173] If the defect type of the defect area is a metal line lateral etching defect, then the regular area is a three-dimensional column.

[0174] If the defect type of the defect area is a metal through-hole pit defect, then the regular area is a three-dimensional circular pit.

[0175] If the defect type of the defect area is a through-hole offset defect, then the regular area is a two-dimensional circular area marked with a center.

[0176] In one embodiment, the computing subunit is further configured to:

[0177] If the regular region is a three-dimensional column, then the volume of the three-dimensional column is determined as the defect parameter of the defect region;

[0178] If the regular region is a three-dimensional circular pit, then the cavity volume of the circular pit is determined as the defect parameter of the defect region.

[0179] If the regular region is a two-dimensional circular region marked with a center, then the offset parameter between the center of the circular region and the center of the through hole corresponding to the theoretical parameter is determined as the defect parameter of the defect region.

[0180] In one embodiment, the sample device is fabricated based on glass through-hole technology and the theoretical parameters of the target device, wherein the sample device includes front metal lines, through-hole metal, glass substrate and back metal lines.

[0181] Each module in the design apparatus for the aforementioned three-dimensional integrated device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware within or independently of the processor in a computer device, or stored in software within the memory of a computer device, so that the processor can call and execute the operations corresponding to each module.

[0182] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 18As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data related to the design methods of three-dimensional integrated devices. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a design method for a three-dimensional integrated device.

[0183] Those skilled in the art will understand that Figure 18 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0184] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0185] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0186] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0187] The optimization dimensions are determined based on theoretical and production characteristics.

[0188] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining an optimization strategy based on the optimization dimension; wherein, if the optimization dimension characterizes a design dimension defect, the optimization strategy is used to adjust the theoretical parameters so that the difference between the adjusted theoretical characteristics and the production characteristics is less than a preset error value; if the optimization dimension characterizes a production dimension defect, the optimization strategy is used to adjust the sample device fabrication method so that the difference between the production characteristics and the theoretical characteristics of the device fabricated based on the adjusted fabrication method is less than a preset error value.

[0189] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining multiple sample devices prepared according to the theoretical parameters of the target device; obtaining the individual defect parameters of each sample device; and determining the defect parameters of the sample devices based on the average value of the individual defect parameters of each sample device.

[0190] In one embodiment, when the processor executes the computer program, it further performs the following steps: for any sample device, acquire an image of the sample device; the sample device includes at least one type of defect; perform defect identification on the image of the sample device according to the defect model corresponding to each defect, and obtain individual defect parameters.

[0191] In one embodiment, the defect model includes a defect identification model and a defect calculation model corresponding to the defect identification model; when the processor executes the computer program, it also performs the following steps: performing defect identification on the image of the sample device according to each defect identification model to determine at least one defect region; and determining the individual defect parameters of each defect region according to the defect calculation model corresponding to each defect region.

[0192] In one embodiment, when the processor executes the computer program, it further performs the following steps: for any defect region, fits the defect region into a regular region according to the defect calculation model corresponding to the defect region, and the regular region completely covers the defect region; calculates the size parameters of the regular region through the defect calculation model, and determines the individual defect parameters of the defect region based on the size parameters of the regular region.

[0193] In one embodiment, when the processor executes the computer program, it further implements the following steps: if the defect type of the defect region is a metal line erosion defect, then the regular region is a three-dimensional column; if the defect type of the defect region is a metal through-hole pit defect, then the regular region is a three-dimensional circular pit; if the defect type of the defect region is a through-hole offset defect, then the regular region is a two-dimensional circular region marked with a center.

[0194] In one embodiment, when the processor executes the computer program, it further implements the following steps: if the regular region is a three-dimensional column, then the volume of the three-dimensional column is determined as the defect parameter of the defect region; if the regular region is a three-dimensional circular pit, then the cavity volume of the circular pit is determined as the defect parameter of the defect region; if the regular region is a two-dimensional circular region marked with a center, then the offset parameter between the center of the circular region and the center of the through hole corresponding to the theoretical parameter is determined as the defect parameter of the defect region.

[0195] In one embodiment, the sample device is fabricated based on glass through-hole technology and the theoretical parameters of the target device, wherein the sample device includes front metal lines, through-hole metal, glass substrate and back metal lines.

[0196] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0197] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0198] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0199] The optimization dimensions are determined based on theoretical and production characteristics.

[0200] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining an optimization strategy based on the optimization dimension; wherein, if the optimization dimension characterizes a design dimension defect, the optimization strategy is used to adjust the theoretical parameters so that the difference between the adjusted theoretical characteristics and the production characteristics is less than a preset error value; if the optimization dimension characterizes a production dimension defect, the optimization strategy is used to adjust the sample device fabrication method so that the difference between the production characteristics and the theoretical characteristics of the device fabricated based on the adjusted fabrication method is less than a preset error value.

[0201] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining multiple sample devices prepared according to the theoretical parameters of the target device; obtaining the individual defect parameters of each sample device; and determining the defect parameters of the sample devices based on the average value of the individual defect parameters of each sample device.

[0202] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: for any sample device, acquiring an image of the sample device; the sample device includes at least one type of defect; and performing defect identification on the image of the sample device according to the defect model corresponding to each defect to obtain individual defect parameters.

[0203] In one embodiment, the defect model includes a defect identification model and a defect calculation model corresponding to the defect identification model; when the computer program is executed by the processor, it also performs the following steps: performing defect identification on the image of the sample device according to each defect identification model to determine at least one defect region; and determining the individual defect parameters of each defect region according to the defect calculation model corresponding to each defect region.

[0204] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: for any defect region, fitting the defect region into a regular region according to the defect calculation model corresponding to the defect region, wherein the regular region completely covers the defect region; calculating the size parameters of the regular region through the defect calculation model, and determining the individual defect parameters of the defect region based on the size parameters of the regular region.

[0205] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: if the defect type of the defect region is a metal line erosion defect, then the regular region is a three-dimensional column; if the defect type of the defect region is a metal through-hole pit defect, then the regular region is a three-dimensional circular pit; if the defect type of the defect region is a through-hole offset defect, then the regular region is a two-dimensional circular region marked with a center.

[0206] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: if the regular region is a three-dimensional column, then the volume of the three-dimensional column is determined as the defect parameter of the defect region; if the regular region is a three-dimensional circular pit, then the cavity volume of the circular pit is determined as the defect parameter of the defect region; if the regular region is a two-dimensional circular region marked with a center, then the offset parameter between the center of the circular region and the center of the through hole corresponding to the theoretical parameter is determined as the defect parameter of the defect region.

[0207] In one embodiment, the sample device is fabricated based on glass through-hole technology and the theoretical parameters of the target device, wherein the sample device includes front metal lines, through-hole metal, glass substrate and back metal lines.

[0208] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0209] Obtain the theoretical parameters of the target device, input the theoretical parameters into the simulation model, and obtain the theoretical characteristics output by the simulation model;

[0210] Obtain the defect parameters of the sample device prepared according to the theoretical parameters, and input both the defect parameters and the theoretical parameters into the simulation model to obtain the production characteristics output by the simulation model;

[0211] The optimization dimensions are determined based on theoretical and production characteristics.

[0212] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining an optimization strategy based on the optimization dimension; wherein, if the optimization dimension characterizes a design dimension defect, the optimization strategy is used to adjust the theoretical parameters so that the difference between the adjusted theoretical characteristics and the production characteristics is less than a preset error value; if the optimization dimension characterizes a production dimension defect, the optimization strategy is used to adjust the sample device fabrication method so that the difference between the production characteristics and the theoretical characteristics of the device fabricated based on the adjusted fabrication method is less than a preset error value.

[0213] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining multiple sample devices prepared according to the theoretical parameters of the target device; obtaining the individual defect parameters of each sample device; and determining the defect parameters of the sample devices based on the average value of the individual defect parameters of each sample device.

[0214] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: for any sample device, acquiring an image of the sample device; the sample device includes at least one type of defect; and performing defect identification on the image of the sample device according to the defect model corresponding to each defect to obtain individual defect parameters.

[0215] In one embodiment, the defect model includes a defect identification model and a defect calculation model corresponding to the defect identification model; when the computer program is executed by the processor, it also performs the following steps: performing defect identification on the image of the sample device according to each defect identification model to determine at least one defect region; and determining the individual defect parameters of each defect region according to the defect calculation model corresponding to each defect region.

[0216] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: for any defect region, fitting the defect region into a regular region according to the defect calculation model corresponding to the defect region, wherein the regular region completely covers the defect region; calculating the size parameters of the regular region through the defect calculation model, and determining the individual defect parameters of the defect region based on the size parameters of the regular region.

[0217] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: if the defect type of the defect region is a metal line erosion defect, then the regular region is a three-dimensional column; if the defect type of the defect region is a metal through-hole pit defect, then the regular region is a three-dimensional circular pit; if the defect type of the defect region is a through-hole offset defect, then the regular region is a two-dimensional circular region marked with a center.

[0218] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: if the regular region is a three-dimensional column, then the volume of the three-dimensional column is determined as the defect parameter of the defect region; if the regular region is a three-dimensional circular pit, then the cavity volume of the circular pit is determined as the defect parameter of the defect region; if the regular region is a two-dimensional circular region marked with a center, then the offset parameter between the center of the circular region and the center of the through hole corresponding to the theoretical parameter is determined as the defect parameter of the defect region.

[0219] In one embodiment, the sample device is fabricated based on glass through-hole technology and the theoretical parameters of the target device, wherein the sample device includes front metal lines, through-hole metal, glass substrate and back metal lines.

[0220] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0221] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0222] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0223] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of designing a three-dimensional integrated device, comprising: The method comprises: acquiring a theoretical parameter of a target device, inputting the theoretical parameter into a simulation model, and acquiring a theoretical characteristic output by the simulation model; acquiring a plurality of sample devices prepared according to the theoretical parameter of the target device; for any sample device, acquiring an image of the sample device; the sample device comprises at least one type of defect; performing defect identification on the image of the sample device according to a defect model corresponding to each defect, to obtain an individual defect parameter; determining a defect parameter of the sample device according to an average value of the individual defect parameters of each sample device, and inputting the defect parameter and the theoretical parameter into the simulation model to acquire a production characteristic output by the simulation model; determining an optimization dimension according to the theoretical characteristic and the production characteristic; determining an optimization strategy according to the optimization dimension; if the optimization dimension represents a design dimension defect, the optimization strategy is used to adjust the theoretical parameter, so that the difference between the adjusted theoretical characteristic and the production characteristic is less than a preset error value; if the optimization dimension represents a production dimension defect, the optimization strategy is used to adjust the sample device preparation method, so that the difference between the production characteristic of the device prepared based on the adjusted preparation method and the theoretical characteristic is less than a preset error value.

2. The method of claim 1, wherein, The defect model comprises a defect identification model and a defect calculation model corresponding to the defect identification model; The defect identification on the image of the sample device according to the defect model corresponding to each defect to obtain the individual defect parameter comprises: performing defect identification on the image of the sample device according to each defect identification model to determine at least one defect region; determining the individual defect parameter of each defect region according to the defect calculation model corresponding to each defect region.

3. The method of claim 2, wherein, The determination of the individual defect parameter of each defect region according to the defect calculation model corresponding to each defect region comprises: for any defect region, fitting the defect region into a regular region according to the defect calculation model corresponding to the defect region, the regular region completely covering the defect region; calculating the size parameter of the regular region through the defect calculation model, and determining the individual defect parameter of the defect region based on the size parameter of the regular region.

4. The method of claim 3, wherein, The fitting of the defect region into a regular region according to the defect calculation model corresponding to the defect region comprises: if the defect type of the defect region is a metal line side etching defect, the regular region is a three-dimensional cylindrical body; if the defect type of the defect region is a metal via hole pit defect, the regular region is a three-dimensional circular pit; if the defect type of the defect region is a via hole offset defect, the regular region is a two-dimensional circular region marked with a center.

5. The method of claim 4, wherein, The calculation of the size parameter of the regular region through the defect calculation model, and the determination of the individual defect parameter of the defect region based on the size parameter of the regular region, comprise: if the regular region is a three-dimensional cylindrical body, the volume of the three-dimensional cylindrical body is determined as the individual defect parameter of the defect region; If the regular area is a three-dimensional circular pit, a cavity volume of the circular pit is determined as the individual defect parameter of the defect area; If the regular area is a two-dimensional circular area marked with a circle center, an offset parameter between the circle center of the circular area and a via center corresponding to the theoretical parameter is determined as the individual defect parameter of the defect area.

6. The method according to any one of claims 1 to 5, characterized in that, The sample device is prepared based on a glass via process and the theoretical parameter of the target device, and the sample device includes a front metal line, a via metal, a glass substrate, and a back metal line.

7. A design apparatus of a three-dimensional integrated device, characterized by comprising: The device comprises: An emulation module configured to acquire a theoretical parameter of a target device, input the theoretical parameter into an emulation model, and acquire a theoretical characteristic output by the emulation model; A collection module configured to acquire a plurality of sample devices prepared based on the theoretical parameter of the target device, acquire an image of each sample device, include at least one type of defect in the sample device, perform defect identification on the image of the sample device according to a defect model corresponding to each defect to obtain an individual defect parameter, and determine a defect parameter of the sample device according to an average value of the individual defect parameters of each sample device; A correction module configured to input the defect parameter and the theoretical parameter into the emulation model and acquire a production characteristic output by the emulation model; A comparison module configured to determine an optimization dimension according to the theoretical characteristic and the production characteristic; A strategy generation module configured to determine an optimization strategy according to the optimization dimension, wherein if the optimization dimension represents a design dimension defect, the optimization strategy is used to adjust the theoretical parameter so that a difference between an adjusted theoretical characteristic and the production characteristic is less than a preset error value, and if the optimization dimension represents a production dimension defect, the optimization strategy is used to adjust a sample device preparation method so that a difference between a production characteristic of a device prepared based on the adjusted preparation method and the theoretical characteristic is less than a preset error value. 8.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-7. The processor executes the computer program to implement the steps of the method in any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

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