Vacuum transport simulation method, device, equipment and medium for integrated circuit manufacturing process

Abstract

The application discloses an integrated circuit manufacturing process vacuum transport simulation method, device, equipment and medium, relates to the field of integrated circuit manufacturing process simulation, and the integrated circuit manufacturing process vacuum transport simulation method takes the initial position of the transport particle, the motion direction vector of the simulation particle, and the sub-node region of the simulation region as the input of the finite state machine, simulates the motion of the transport particle by combining the method of the two-dimensional line segment tree, converts the process of moving the transport particle in the prior art and analyzing the motion of the transport particle into dividing the simulation region by the two-dimensional line segment tree, and simultaneously combines the process of updating the state of the transport particle by the finite state machine, so that the time complexity in the simulation process is reduced, and the running efficiency of the simulation is improved.

Description

Technical Field

[0001] This invention relates to the field of integrated circuit manufacturing process simulation, and in particular to a method, apparatus, equipment and medium for simulating vacuum transport in integrated circuit manufacturing processes. Background Technology

[0002] Integrated circuit manufacturing technology is one of the core technologies of the modern electronic information industry, including a series of complex process steps such as photolithography, etching, ion implantation, chemical vapor deposition, physical vapor deposition, metallization, packaging and testing.

[0003] With continuous technological advancements, integrated circuit manufacturing is evolving towards smaller size, higher integration, and lower power consumption. Thin-film deposition processes, represented by chemical vapor deposition (CVD) and physical vapor deposition (PVD), are key processes in large-scale integrated circuit manufacturing. Both front-end and back-end processes require the deposition of numerous thin films for patterned growth. Examples include high-k dielectric materials like hafnium oxide (HfO2) and sidewall spacers like silicon dioxide (SiO2) and silicon nitride (SiNx) in front-end processes; and interconnecting metals like copper (Cu) and diffusion barrier layers like tantalum nitride (TaN) in back-end processes.

[0004] For manufacturing processes such as thin film deposition and etching, simulation involves macroscopic fluid process simulation at the equipment scale, surface formation process simulation at the microscopic reaction scale, and growth morphology simulation at the feature size scale. One mainstream simulation approach is the Monte Carlo (MC) method. This method divides the particle motion process into two parts: vacuum phase transport and motion in the solid phase. In the vacuum phase, it is typically assumed that the simulated feature size is much smaller than the particle's mean free path. Therefore, the particle can be considered to be moving in a uniform linear motion in this part. However, existing simulation methods usually move the particle grid by grid according to a certain logic to maintain its linear motion until it encounters the solid phase.

[0005] However, this method has high time complexity, and as the simulation area expands, it will severely reduce the running efficiency of the simulation program, and the computational cost is high. Summary of the Invention

[0006] In view of the above-mentioned technological status, this application provides a method, apparatus, equipment and medium for simulating vacuum transport in integrated circuit manufacturing processes, so as to reduce the time complexity of simulation and improve the running efficiency of simulation programs.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for simulating vacuum transport in integrated circuit manufacturing processes includes:

[0009] Using a two-dimensional segment tree method, the simulation region corresponding to the substrate is used as the root node to divide the region, and the sub-node regions corresponding to multiple child nodes of the root node are obtained.

[0010] Each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle are input into a finite state machine. The initial position and the motion direction vector of the transport particle are used as the first state of the transport particle through the finite state machine. Based on the first state, the motion of the transport particle is simulated to determine the motion position of the transport particle and the sub-node region where the motion position is located.

[0011] When the particle density in the sub-node region where the transport particle's movement position is located is either vacuum or dense, the final state of the transport particle is determined based on the transport particle's movement position and adsorption information.

[0012] When the particle density in the sub-node region where the transport particle's motion position is located is sparse, the two-dimensional segment tree method is used to divide the sub-node region into regions with the parent node as the parent node, obtaining the sub-node regions corresponding to multiple child nodes of the parent node; the first state is updated according to the motion position of the transport particle; the motion of the transport particle is simulated according to the first state to determine the motion position of the transport particle and the sub-node region where the motion position is located.

[0013] In one optional embodiment of this application, it further includes:

[0014] Based on the crystal stacking method that makes up the substrate, the simulation region is divided into crystal lattice to obtain the crystal lattice network of the simulation region;

[0015] The spatial volume corresponding to the grid unit of the lattice network is larger than the unit cell volume of the substrate.

[0016] In one optional embodiment of this application, the method of using a two-dimensional segment tree to divide the simulation region corresponding to the substrate as the root node and obtain the child node regions corresponding to multiple child nodes of the root node includes:

[0017] Determine the vertex coordinates of each vertex in the simulation region;

[0018] Based on the vertex coordinates, the simulation region is divided into regions to obtain the child node regions corresponding to the multiple child nodes of the root node.

[0019] In one optional embodiment of this application, when the particle density in the sub-node region where the transport particle's movement position is located is either vacuum or dense, determining the final state of the transport particle based on its movement position and adsorption information includes:

[0020] If the particle density in the sub-node region where the transport particle is located is vacuum, the transport particle is located at the boundary of the sub-node region, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that the transport particle moves to the last position in the sub-node region and is adsorbed.

[0021] If the particle density in the sub-node region where the transport particle is located is vacuum and the adsorption information of the transport particle is unadsorbed, then the final state of the transport particle is determined to be that the transport particle moves to other sub-node regions outside the sub-node region.

[0022] If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that it moves to the sub-node region and is adsorbed.

[0023] If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle indicates that it has not been adsorbed, then the final state of the transport particle is determined to be that it has not been adsorbed.

[0024] In one optional embodiment of this application, it further includes:

[0025] If the endpoint of the transport particle is not located in the sub-node region corresponding to multiple sub-nodes of the root node, the final state of the transport particle is determined to be that the transport particle exceeds the simulation boundary.

[0026] In one optional embodiment of this application, it further includes:

[0027] Obtain a substrate image of the substrate;

[0028] Based on the contour recognition of the substrate image, the simulation area corresponding to the substrate is determined.

[0029] Compared with existing technologies, the vacuum transport simulation method for integrated circuit manufacturing processes provided by this invention uses the initial position of the transport particle, the motion direction vector of the simulated particle, and the sub-node regions of the simulation area as inputs to a finite state machine. By combining a two-dimensional segment tree method, the motion of the transport particle is simulated. The process of moving the transport particle grid by grid and then analyzing the motion of the transport particle in the existing technology is transformed into a process of dividing the simulation area by a two-dimensional segment tree and updating the state of the transport particle by a finite state machine. This helps to reduce the time complexity of the simulation process and improve the simulation efficiency.

[0030] The present invention also provides a vacuum transport simulation device for integrated circuit manufacturing processes, comprising:

[0031] The region processing unit is used to divide the simulation region corresponding to the substrate into regions by using a two-dimensional segment tree method, taking the simulation region as the root node, and obtaining the sub-node regions corresponding to multiple child nodes of the root node.

[0032] The state machine processing unit is used to input each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle into a finite state machine. The finite state machine uses the initial position and motion direction vector of the transport particle as its first state. Based on the first state, the motion of the transport particle is simulated to determine the position of the transport particle and the sub-node region where the position is located. If the particle density in the sub-node region where the position is located is either vacuum or dense, the final state of the transport particle is determined based on its position and adsorption information. If the particle density in the sub-node region where the position is located is sparse, the two-dimensional segment tree method is used to divide the sub-node region into regions using the parent node, obtaining multiple sub-node regions corresponding to the parent node's child nodes. The first state is updated based on the position of the transport particle. The simulation of the motion of the transport particle is then performed again based on the first state to determine its position and the sub-node region where the position is located.

[0033] Compared with the prior art, the beneficial effects of the vacuum transport simulation device for integrated circuit manufacturing process provided by the present invention are the same as those of the vacuum transport simulation method for integrated circuit manufacturing process described in the above technical solution, and will not be repeated here.

[0034] The present invention also provides an electronic device, comprising:

[0035] processor;

[0036] Memory used to store the processor's executable instructions;

[0037] The processor is used to execute the aforementioned vacuum transport simulation method for integrated circuit manufacturing processes by running instructions in the memory.

[0038] Compared with the prior art, the beneficial effects of the electronic device provided by the present invention are the same as those of the vacuum transport simulation method for integrated circuit manufacturing process described in the above technical solution, and will not be repeated here.

[0039] The present invention also provides a computer storage medium storing instructions, which, when executed, implement the above-described vacuum transport simulation method for integrated circuit manufacturing process.

[0040] Compared with the prior art, the beneficial effects of the computer storage medium provided by the present invention are the same as those of the vacuum transport simulation method for integrated circuit manufacturing process described in the above technical solution, and will not be repeated here. Attached Figure Description

[0041] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0042] Figure 1 A flowchart of a vacuum transport simulation method for integrated circuit manufacturing processes provided in this application embodiment;

[0043] Figure 2 A schematic diagram of the root node partitioning provided in an embodiment of this application;

[0044] Figure 3 A directed graph of a finite state machine provided in an embodiment of this application;

[0045] Figure 4 A structural diagram of the vacuum transport simulation device for integrated circuit manufacturing process provided in this application embodiment;

[0046] Figure 5 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0047] To facilitate a clear description of the technical solutions in the embodiments of the present invention, the terms "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect. For example, the first threshold and the second threshold are merely used to distinguish different thresholds and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" are not necessarily different.

[0048] It should be noted that in this invention, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0049] In this invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, a combination of a and b, a combination of a and c, a combination of b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0050] Integrated circuit manufacturing technology is one of the core technologies of the modern electronic information industry, encompassing a series of complex processes including photolithography, etching, ion implantation, chemical vapor deposition (CVD), physical vapor deposition (PVD), metallization, packaging, and testing. With continuous technological advancements, integrated circuit manufacturing is moving towards smaller size, higher integration, and lower power consumption. Among these processes, thin-film deposition (TFT) and PVD are key technologies in large-scale integrated circuit manufacturing. Both front-end and back-end processes require the deposition of numerous thin films for patterned growth. Examples include high-k dielectric materials like hafnium oxide (HfO2) and sidewall spacers like silicon dioxide (SiO2) and silicon nitride (SiNx) in front-end processes; and interconnecting metals like copper (Cu) and diffusion barrier layers like tantalum nitride (TaN) in back-end processes.

[0051] Taking thin film fabrication as an example, substrate surface defects, internal pore defects generated during deposition, and inappropriate process conditions can lead to thin film functional failure, affecting the execution of subsequent processes. Currently, the process technology industry mainly uses experimental design methods to optimize existing processes and develop new ones. However, this requires designing a large number of experiments to find the key factors affecting the process and their degree of influence, which is very time-consuming and costly.

[0052] For manufacturing processes such as thin film deposition and etching, simulation involves macroscopic fluid process simulation at the equipment scale, surface formation process simulation at the microscopic reaction scale, and growth morphology simulation at the feature size scale. One mainstream simulation approach is the Monte Carlo (MC) method. This method divides the particle motion process into two parts: vacuum phase transport and motion in the solid phase. The vacuum phase is typically assumed to have feature sizes much smaller than the particle's mean free path. Therefore, the particles can be considered to move in uniform linear motion in this part. However, existing simulation methods usually move the particles grid-by-grid according to a certain logic to maintain their linear motion until they encounter the solid phase.

[0053] However, this method has high time complexity, and as the simulation area expands, it will severely reduce the running efficiency of the simulation program, and the computational cost is high.

[0054] In view of the above-mentioned technical status, this application provides a method, apparatus, equipment and medium for simulating vacuum transport in integrated circuit manufacturing processes, which will be described in detail in the following embodiments.

[0055] This application first provides a vacuum transport simulation method for integrated circuit manufacturing processes. Please refer to [link / reference]. Figure 1 , Figure 1 A flowchart of the vacuum transport simulation method for integrated circuit manufacturing process provided in this application embodiment.

[0056] like Figure 1 As shown, the vacuum transport simulation method for integrated circuit manufacturing process includes the following steps S101 to S104:

[0057] S101, using a two-dimensional segment tree method, the simulation area corresponding to the substrate is used as the root node to divide the region, and the child node regions corresponding to multiple child nodes of the root node are obtained.

[0058] A segment tree is a binary tree based on the divide-and-conquer approach, used for information statistics over intervals. Each node corresponds to an interval [1, r), and each leaf node represents a unit interval. The left leaf node of each non-leaf node [1, r) represents an interval [1, (1+r) / 2), and the right leaf node represents an interval [(1+r) / 2, r). There are two main ways to write a two-dimensional segment tree: one is a nested segment tree approach, where each node represents the horizontal column information of a matrix, and a segment tree stores the vertical column information of that horizontal column interval. The other approach is a quadtree approach, where each node corresponds to a matrix region [1, r) × [b, t), and each leaf node represents a unit-sized region (e.g., a grid with 1 grid). Each non-leaf node [1, r) × [b, t) has four child nodes representing the four quadrant sub-regions of the region it represents: [(l+r) / 2, r) × [(t+b) / 2, t), [l, (l+r) / 2) × [(t+b) / 2, t), [l, (l+r) / 2) × [b, (t+b) / 2), [(l+r) / 2, r) × [b, (t+b) / 2).] While the time complexity of this method for querying rectangular regions may be greater than that of nested segment trees in certain situations, such extreme cases leading to time complexity degradation are almost non-existent in real-world manufacturing processes. Its computational constant is excellent, and it can be extended to three-dimensional scenarios simply by converting it to an octree.

[0059] Furthermore, the simulation area corresponding to the substrate can be obtained based on a substrate image. The substrate image refers to a micro / nano structure pattern of the substrate, including but not limited to micro / nano image structures generated during a specific process step in the manufacturing of integrated circuit microelectronic devices, optoelectronic devices, microelectromechanical systems (MEMS) devices, and organic light-emitting materials. Specifically, it can be a non-planar substrate structure generated through processes such as etching, photolithography, and deposition, including right-angle steps, inclined steps, right-angle trenches, inclined trenches, T-structures, cantilever beam structures, or more complex single or periodic patterns. In this embodiment, the minimum size of the substrate structure can be a few nanometers, and the maximum size can be tens of micrometers.

[0060] The substrate image can be a scanning electron microscope image or a custom non-planar substrate structure image.

[0061] Furthermore, in order to improve the quality of the substrate image and the accuracy of subsequent processing of the simulation area, the substrate image can be preprocessed. The preprocessing includes, but is not limited to, image cropping, noise reduction, contrast adjustment, contour recognition, edge extraction, and smoothing.

[0062] Furthermore, the method of using a two-dimensional segment tree, which divides the simulation region corresponding to the substrate into regions using the root node, obtains the child node regions corresponding to multiple child nodes of the root node, including:

[0063] Determine the vertex coordinates of each vertex in the simulation region;

[0064] Based on the vertex coordinates, the simulation region is divided into regions to obtain the child node regions corresponding to the multiple child nodes of the root node.

[0065] Please refer to Figure 2 , Figure 2 This is a schematic diagram illustrating the division of the parent node of a two-dimensional segment tree provided in an embodiment of this application.

[0066] like Figure 2 As shown, the coordinates of the four vertices of the simulation region corresponding to the parent node are respectively , , , That is, the horizontal axis range of the child node region corresponding to the parent node is The vertical axis range is Based on this, the child node region is divided, specifically, the division rule is as follows: insert a horizontal axis. Insert vertical axis Furthermore, the sub-node region is further divided into 4 sub-node regions.

[0067] In this embodiment, the region division of the region (including the simulation region) is carried out concurrently with the transport of transport particles. That is, the region is further divided based on the movement position of the transport particles and the region where those positions are located. In other words, the simulation region will ultimately be divided into multiple sub-node regions of different levels. The size of the sub-node region represented by the lowest-level node should be larger than the volume of a unit cell to ensure computational efficiency.

[0068] Therefore, embodiments of this application also include:

[0069] Based on the crystal stacking method that makes up the substrate, the simulation region is divided into crystal lattice to obtain the crystal lattice network of the simulation region;

[0070] The spatial volume corresponding to the grid unit of the lattice network is larger than the unit cell volume of the substrate.

[0071] That is, based on the actual crystal stacking method, such as cubic or hexagonal lattices in two-dimensional cases, or simple cubic or hexagonal close-packing in three-dimensional cases, the vacuum region and the substrate solid region are divided into grids to form basic sites that particles can occupy. According to experimental results, using the correct lattice can significantly reduce the overall solid surface roughness in Monte Carlo simulations without affecting vacuum transport itself.

[0072] S102, input each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle into a finite state machine, so that the initial position of the transport particle and the motion direction vector are used as the first state of the transport particle through the finite state machine, and the motion of the transport particle is simulated according to the first state to determine the motion position of the transport particle and the sub-node region where the motion position is located.

[0073] A Finite State Machine (FSM) is a mathematical model used to describe the behavior of a system with a finite number of states. An FSM can be represented as a quintuple (Q, Σ, δ, q, F), where Q is the finite set of states, Σ is the set of input events (alphabet), δ is the transition function, q is the start state, and F is the set of accept states. It can be represented as a directed graph.

[0074] Please refer to Figure 3 , Figure 3 A directed graph of a finite state machine provided in an embodiment of this application. For example... Figure 3 As shown, q1, q2, and q3 represent three possible states, with q1 being the initial state, q2 being the intermediate state, and q3 being the final state. 0 and 1 represent the possible input values ​​of the finite state machine.

[0075] After inputting each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle into the finite state machine, the finite state machine will take the initial position of the transport particle and the motion direction vector of the transport particle as the first state of the transport particle, and simulate the motion of the transport particle according to the state to obtain the motion position of the transport particle and the sub-node region where the motion position is located.

[0076] In this embodiment, the input of the finite state machine includes the sub-node region of the simulation region corresponding to the substrate, the initial position of the transport particle, and the motion direction vector of the transport particle. The finite state machine simulates the motion of the transport particle in the simulation region based on the initial position and motion direction vector of the transport particle. During this process, the motion position of the transport particle input by the finite state machine changes as the simulation progresses until the transport particle is adsorbed by the substrate or the transport particle moves beyond the boundary of the simulation region.

[0077] Meanwhile, in order to accelerate the vacuum transport of particles during the simulation, the particle density of the sub-node region where the transport particle is located will be combined to further divide the state of the transport particle in the sub-node region represented by the current node, so as to accurately determine whether the final state of the transport particle in the sub-node region is adsorption or transported away from the sub-node and into other sub-node regions.

[0078] It should be noted that the movement of the transport particle between the sub-node regions is determined by the direction vector of the transport particle's movement. In practical applications, the sub-node regions at each level can be sorted based on the direction vector of the transport particle's movement, thereby obtaining an ordered set of sub-node regions at each level. This facilitates the simulation of the movement of the transport particle between sub-node regions at different levels using a finite state machine.

[0079] S103, when the particle density in the sub-node region where the transport particle's movement position is located is vacuum or dense, the final state of the transport particle is determined based on the transport particle's movement position and adsorption information.

[0080] After determining the sub-node region where the transport particle's movement position is located through the above S102, the particle density and adsorption information of the sub-node region where the movement position is located are further determined.

[0081] When the particle density in the sub-node region is a vacuum, the movement position of the transport particle is the boundary of the sub-node region, and the transport particle is adsorbed, the final state of the transport particle is determined to be: the transport particle moves to the last position in the sub-node region and is adsorbed.

[0082] If the particle density in the sub-node region where the transport particle is located is vacuum and the adsorption information of the transport particle is unadsorbed, then the final state of the transport particle is determined to be that it moves to another sub-node region outside the sub-node region.

[0083] If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that it moves to the sub-node region and is adsorbed.

[0084] If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle indicates that it has not been adsorbed, then the final state of the transport particle is determined to be that it has not been adsorbed.

[0085] If the particle density in the sub-node region where the transport particle's movement position is located is sparse, then the following S104 is further executed.

[0086] S104, when the particle density in the sub-node region where the transport particle's motion position is located is sparse, the two-dimensional segment tree method is used to divide the sub-node region into regions with the parent node as the parent node, obtaining the sub-node regions corresponding to multiple child nodes of the parent node; the first state is updated according to the motion position of the transport particle; the simulation of the motion of the transport particle is performed according to the first state to determine the motion position of the transport particle and the sub-node region where the motion position is located.

[0087] When the particle density in the child node region where the transport particle's movement position is located is sparse, the two-dimensional segment tree method is continued to be used to divide the region into regions by taking the child node region where the transport particle's movement position is located as the parent node, thereby obtaining the child node region corresponding to the parent node.

[0088] Then, based on the motion position of the transport particle, the first state of the transport particle is updated, that is, the initial position of the input finite state machine is updated to the motion state, the motion of the transport particle is simulated again, and the next motion position of the transport particle and the corresponding sub-node region are determined when the input of the finite state machine is the motion position. That is, the process returns to the steps in S102 above, which involve simulating the motion of the transport particle based on the first state and determining the motion position of the transport particle and the sub-node region where the motion position is located.

[0089] Furthermore, if the endpoint of the transport particle is not located in the child node region corresponding to multiple child nodes of the root node (i.e., the endpoint of the transport particle is not located in the simulation region), the final state of the transport particle is determined to be that the transport particle exceeds the simulation boundary.

[0090] Specifically, the process of determining the final state of the transport particle using a finite state machine can be implemented using a vacuum transport function.

[0091] The vacuum transport function can be implemented using the following code, where each node in the code corresponding to the vacuum transport function (including nodes at each level defined as t, with the attribute t.filt.size, the child nodes of the node located at t.chi, where i=0, 1, 2, 3, and the root node defined as root) is:

[0092] Vacuum transport:

[0093] VT(t, P1, P2): t represents the sub-node region where the transport particle is located, P1 represents the initial position of the transport particle, and P2 represents the direction vector of the transport particle's motion.

[0094] ins_ret_code=0; / / Initialize return code

[0095] state = cautch(t, P1, P2); / / state is the input value of the state machine, obtained by the cautch function.

[0096] switch(state):

[0097] case 0: return 0; / / State 0: The transport particle moves to a sub-node region outside the sub-node region corresponding to its movement position.

[0098] Case 1: Return 1; / / State 1: The transport particle is adsorbed at the last position in the sub-node region.

[0099] case 2: / / State 2

[0100] D = passdomain(t, P1); / / Calculate the child nodes t that the transport particle passes through during its motion and return them in order, storing them in array D.

[0101] foreach t in D:

[0102] ins_ret_code=VT(t, P1, P2);

[0103] if(ins_ret_code≠0):break;

[0104] return ins_ret_code;

[0105] Case 3: Return 1; / / State 3: Transport particles are adsorbed.

[0106] Case 4: Return 0; / / State 4: Transport particles have not been adsorbed.

[0107] case 5: return 2; / / Status 5: The transported particle exceeds the simulation boundary

[0108] In the code corresponding to the above "vacuum transportation", cautch(t, P1, P2) refers to the input information of the finite state machine. In the actual application process, P1 input by the finite state machine changes with the movement of the transported particle, and VT(t, P1, P2) is the first input of the finite state machine. Here, P1 is the initial position of the input particle.

[0109] Furthermore, cautch(t, P1, P2) is obtained through the following code:

[0110] cautch(t, P1, P2):

[0111] if(t.filt == 0): / / Empty area

[0112] if (the transported particle is adsorbed when moving to the area boundary):

[0113] P2 = P1;

[0114] return 1; / / The transported particle is adsorbed at the last position of the sub-node area

[0115] else:

[0116] if (the transported particle has moved outside the simulation area):

[0117] return 5; / / The transported particle exceeds the simulation boundary

[0118] else: return 0; / / The transported particle moves to other sub-node areas outside the sub-node area corresponding to the movement position

[0119] if (0 < t.filt / t.size < 0.8): return 2; / / Sparse area, the sub-node area should be divided

[0120] if (0.8 ≤ t.filt / t.size ≤ 1): / / Dense area, the existing method moves and detects whether it is adsorbed;

[0121] if (adsorbed):[[ID=,43]]

[0122] P2 = P1;

[0123] return 3; / / The transported particle is adsorbed

[0124] else:

[0125] if (the particle has moved outside the simulation area):

[0126] return 5; / / Outside the simulation region boundary

[0127] else: return 4; / / The transport particles were not adsorbed.

[0128] In practical applications, simulation experiments were conducted on the vacuum transport simulation method for integrated circuit manufacturing processes provided in this application embodiment. The experimental results show that, taking the vacuum transport of one million random particles as an example, depositing a U-shaped groove with a depth-to-width ratio of 1:1 on a two-dimensional region of size 4096*4096, using existing methods with single-threaded C language coding and a single-core CPU, can achieve the desired results. The simulation took approximately one hour to run, while under the same equipment conditions, this method only required about 11 seconds, significantly improving overall computational efficiency. In terms of theoretically expected time complexity, for an n*n simulation region, the integrated circuit manufacturing process vacuum transport simulation method provided in this embodiment has lower time complexity than existing simulation methods. Furthermore, during the experiment, the simulations of the vacuum phase and the solid phase are performed in parallel, making it easier to utilize parallelization techniques to improve overall simulation efficiency. The computational efficiency advantage of this scheme becomes even more pronounced as the simulation region expands.

[0129] In summary, the vacuum transport simulation method for integrated circuit manufacturing processes provided in this application uses the initial position of the transport particle, the motion direction vector of the simulated particle, and the sub-node regions of the simulation area as inputs to a finite state machine. By combining a two-dimensional segment tree method, the motion of the transport particle is simulated. The process of moving the transport particle grid by grid and then analyzing the motion of the transport particle in the prior art is transformed into a process of dividing the simulation area by a two-dimensional segment tree and updating the state of the transport particle by a finite state machine. This helps to reduce the time complexity of the simulation process and improve the running efficiency of the simulation.

[0130] This application also provides a vacuum transport simulation device for integrated circuit manufacturing processes; please refer to [reference needed]. Figure 3 , Figure 3 This is a structural diagram of the vacuum transport simulation device for integrated circuit manufacturing process provided in an embodiment of this application.

[0131] like Figure 4 As shown, the vacuum transport simulation device for integrated circuit manufacturing process includes:

[0132] The region processing unit 401 is used to divide the simulation region corresponding to the substrate into regions by using a two-dimensional segment tree method, taking the simulation region corresponding to the substrate as the root node, and obtaining the sub-node regions corresponding to multiple sub-nodes of the root node.

[0133] The state machine processing unit 402 is used to input each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle into a finite state machine. The finite state machine uses the initial position and motion direction vector of the transport particle as the first state of the transport particle. Based on the first state, the motion of the transport particle is simulated to determine the motion position of the transport particle and the sub-node region where the motion position is located. If the particle density in the sub-node region where the motion position of the transport particle is located is vacuum or dense, the final state of the transport particle is determined based on the motion position and adsorption information of the transport particle. If the particle density in the sub-node region where the motion position of the transport particle is located is sparse, the two-dimensional segment tree method is used to divide the sub-node region into regions using the parent node, obtaining multiple sub-node regions corresponding to the child nodes of the parent node. The first state is updated based on the motion position of the transport particle. The simulation of the motion of the transport particle is then performed again based on the first state to determine the motion position of the transport particle and the sub-node region where the motion position is located.

[0134] In one optional embodiment of this application, the device is further configured to:

[0135] Based on the crystal stacking method that makes up the substrate, the simulation region is divided into crystal lattice to obtain the crystal lattice network of the simulation region;

[0136] The spatial volume corresponding to the grid unit of the lattice network is larger than the unit cell volume of the substrate.

[0137] In one optional embodiment of this application, the method of using a two-dimensional segment tree to divide the simulation region corresponding to the substrate as the root node and obtain the child node regions corresponding to multiple child nodes of the root node includes:

[0138] Determine the vertex coordinates of each vertex in the simulation region;

[0139] Based on the vertex coordinates, the simulation region is divided into regions to obtain the child node regions corresponding to the multiple child nodes of the root node.

[0140] In one optional embodiment of this application, when the particle density in the sub-node region where the transport particle's movement position is located is either vacuum or dense, determining the final state of the transport particle based on its movement position and adsorption information includes:

[0141] If the particle density in the sub-node region where the transport particle is located is vacuum, the transport particle is located at the boundary of the sub-node region, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that the transport particle moves to the last position in the sub-node region and is adsorbed.

[0142] If the particle density in the sub-node region where the transport particle is located is vacuum and the adsorption information of the transport particle is unadsorbed, then the final state of the transport particle is determined to be that the transport particle moves to other sub-node regions outside the sub-node region.

[0143] If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that it moves to the sub-node region and is adsorbed.

[0144] If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle indicates that it has not been adsorbed, then the final state of the transport particle is determined to be that it has not been adsorbed.

[0145] In one optional embodiment of this application, the device is further configured to:

[0146] If the endpoint of the transport particle is not located in the sub-node region corresponding to multiple sub-nodes of the root node, the final state of the transport particle is determined to be that the transport particle exceeds the simulation boundary.

[0147] In one optional embodiment of this application, the device is further configured to:

[0148] Obtain a substrate image of the substrate;

[0149] Based on the contour recognition of the substrate image, the simulation area corresponding to the substrate is determined.

[0150] The device embodiments provided in this embodiment and the method embodiments of this application belong to the same application concept. For technical details not described in detail in this embodiment, please refer to the specific processing content of the vacuum transport simulation method for integrated circuit manufacturing process provided in the above embodiments of this application, which will not be repeated here.

[0151] This application also provides an electronic device, such as... Figure 5 As shown, Figure 5 This is a schematic diagram of an electronic device structure provided in an embodiment of this application.

[0152] like Figure 5 As shown, the electronic device includes:

[0153] Processor 210;

[0154] Memory 200 for storing executable instructions of the processor 210;

[0155] The processor 210 is configured to execute the vacuum transport simulation method for integrated circuit manufacturing process disclosed in any of the above embodiments by running instructions in the memory 200.

[0156] The processor 210, memory 200, communication interface 220, input device 230, and output device 240 are interconnected via a bus. Among them:

[0157] A bus can include a pathway for transmitting information between various components of a computer system.

[0158] Processor 210 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0159] Processor 210 may include a main processor, as well as a baseband chip, modem, etc.

[0160] The memory 200 stores a program that executes the technical solution of this invention, and may also store an operating system and other key business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory 200 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0161] Input device 230 may include a device for receiving user input data and information, such as a keyboard, mouse, camera, scanner, touch screen, etc.

[0162] Output device 240 may include devices that allow information to be output to a user, such as a display screen, printer, speaker, etc.

[0163] The communication interface 220 may include a device that uses any transceiver to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0164] The processor 210 executes the program stored in the memory 200 and calls other devices, and can be used to implement each step of any of the vacuum transport simulation methods for integrated circuit manufacturing processes provided in the above embodiments of this application.

[0165] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the integrated circuit manufacturing process vacuum transport simulation method of various embodiments of this application.

[0166] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0167] Furthermore, embodiments of this application may also be storage media storing computer programs, which are executed by a processor using the steps of the integrated circuit manufacturing process vacuum transport simulation method of various embodiments of this application.

[0168] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0169] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0170] The steps in the methods of the various embodiments of this application can be adjusted, merged, or deleted in order according to actual needs, and the technical features described in each embodiment can be replaced or combined.

[0171] The modules and sub-modules in the apparatus and terminal in the various embodiments of this application can be merged, divided, and deleted according to actual needs.

[0172] It should be understood that the disclosed terminals, devices, and methods can be implemented in other ways, given the several embodiments provided in this application. For example, the terminal embodiments described above are merely illustrative. For instance, the division of modules or sub-modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple sub-modules or modules may be combined or integrated into another module, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0173] The modules or submodules described as separate components may or may not be physically separate. The components that constitute a module or submodule may or may not be physical modules or submodules; that is, they may be located in one place or distributed across multiple network modules or submodules. Some or all of the modules or submodules can be selected to achieve the purpose of this embodiment's solution, depending on actual needs.

[0174] Furthermore, the functional modules or sub-modules in the various embodiments of this application can be integrated into one processing module, or each module or sub-module can exist physically separately, or two or more modules or sub-modules can be integrated into one module. The integrated modules or sub-modules described above can be implemented in hardware or in the form of software functional modules or sub-modules.

[0175] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0176] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software unit executed by a processor, or a combination of both. The software unit can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0177] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0178] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for simulating vacuum transport in integrated circuit manufacturing processes, characterized in that, include: Using a two-dimensional segment tree method, the simulation region corresponding to the substrate is used as the root node to divide the region, and the sub-node regions corresponding to multiple child nodes of the root node are obtained. Each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle are input into a finite state machine. The initial position and the motion direction vector of the transport particle are used as the first state of the transport particle through the finite state machine. Based on the first state, the motion of the transport particle is simulated to determine the motion position of the transport particle and the sub-node region where the motion position is located. When the particle density in the sub-node region where the transport particle's movement position is located is either vacuum or dense, the final state of the transport particle is determined based on the transport particle's movement position and adsorption information. When the particle density in the sub-node region where the transport particle's motion position is located is sparse, the two-dimensional segment tree method is used to divide the sub-node region into regions with the parent node as the parent node, obtaining the sub-node regions corresponding to multiple child nodes of the parent node; the first state is updated according to the motion position of the transport particle; the motion of the transport particle is simulated according to the first state to determine the motion position of the transport particle and the sub-node region where the motion position is located.

2. The method according to claim 1, characterized in that, Also includes: Based on the crystal stacking method that makes up the substrate, the simulation region is divided into crystal lattice to obtain the crystal lattice network of the simulation region; The spatial volume corresponding to the grid unit of the lattice network is larger than the unit cell volume of the substrate.

3. The method according to claim 1, characterized in that, The method employing a two-dimensional segment tree divides the simulation region corresponding to the substrate into regions using the root node, thereby obtaining multiple child node regions corresponding to the child nodes of the root node, including: Determine the vertex coordinates of each vertex in the simulation region; Based on the vertex coordinates, the simulation region is divided into regions to obtain the child node regions corresponding to the multiple child nodes of the root node.

4. The method according to claim 1, characterized in that, When the particle density in the sub-node region where the transport particle's movement position is located is either vacuum or dense, the final state of the transport particle is determined based on its movement position and adsorption information, including: If the particle density in the sub-node region where the transport particle is located is vacuum, the transport particle is located at the boundary of the sub-node region, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that the transport particle moves to the last position in the sub-node region and is adsorbed. If the particle density in the sub-node region where the transport particle is located is vacuum and the adsorption information of the transport particle is unadsorbed, then the final state of the transport particle is determined to be that the transport particle moves to other sub-node regions outside the sub-node region. If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle is adsorption, then the final state of the transport particle is determined to be that it moves to the sub-node region and is adsorbed. If the particle density in the sub-node region where the transport particle is located is dense, and the adsorption information of the transport particle indicates that it has not been adsorbed, then the final state of the transport particle is determined to be that it has not been adsorbed.

5. The method according to claim 1, characterized in that, Also includes: If the endpoint of the transport particle is not located in the sub-node region corresponding to multiple sub-nodes of the root node, the final state of the transport particle is determined to be that the transport particle exceeds the simulation boundary.

6. The method according to claim 1, characterized in that, Also includes: Obtain a substrate image of the substrate; Based on the contour recognition of the substrate image, the simulation area corresponding to the substrate is determined.

7. A vacuum transport simulation device for integrated circuit manufacturing processes, characterized in that, include: The region processing unit is used to divide the simulation region corresponding to the substrate into regions by using a two-dimensional segment tree method, taking the simulation region as the root node, and obtaining the sub-node regions corresponding to multiple child nodes of the root node. The state machine processing unit is used to input each of the sub-node regions, the initial position of the transport particle, and the motion direction vector of the transport particle into a finite state machine. The finite state machine uses the initial position and motion direction vector of the transport particle as its first state. Based on the first state, the motion of the transport particle is simulated to determine the position of the transport particle and the sub-node region where the position is located. If the particle density in the sub-node region where the position is located is either vacuum or dense, the final state of the transport particle is determined based on its position and adsorption information. If the particle density in the sub-node region where the position is located is sparse, the two-dimensional segment tree method is used to divide the sub-node region into regions using the parent node, obtaining multiple sub-node regions corresponding to the parent node's child nodes. The first state is updated based on the position of the transport particle. The simulation of the motion of the transport particle is then performed again based on the first state to determine its position and the sub-node region where the position is located.

8. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the vacuum transport simulation method for integrated circuit manufacturing process according to any one of claims 1 to 6 by running instructions in the memory.

9. A computer storage medium, characterized in that, The computer storage medium stores instructions that, when executed, perform the vacuum transport simulation method for integrated circuit manufacturing process according to any one of claims 1 to 6.

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