PCB processing control device and system

Abstract

To process a crystal substrate using an appropriate processing method depending on the crystal substrate and a processing condition.SOLUTION: A substrate processing control device 10 includes a substrate processing machine learning unit 11 that includes a substrate processing learning unit 31 that generates a substrate processing model by learning training data, receives input of explanatory variables including parameters related to a crystal substrate 200 and parameters related to a processing condition, and outputs objective variables including parameters related to an optical system 120 and parameters related to driving a stage 112, and a control unit 12 that controls a substrate processing device 100 including the optical system 120 and a substrate support device 110 on the basis of the objective variables.SELECTED DRAWING: Figure 3

Description

Technical Field

[0005] , ,

[0001] This invention relates to a substrate processing control device and system for controlling a substrate processing apparatus. Specifically, it relates to a substrate processing control device and system that uses artificial intelligence to control a substrate processing apparatus so as to condense a laser beam inside a substrate to form a modifiable layer that can be peeled off.

Background Art

[0002] Conventionally, various single crystals have been used as materials for semiconductor substrates. Among these single crystals, silicon (Si), silicon carbide (SiC), gallium nitride (GaN), gallium phosphide (GaP), diamond (C), etc. are called difficult-to-machine materials, and it has been difficult to cut them out as substrates from a bulk such as an ingot or a block by conventional machining. For this reason, as a processing method alternative to machining, a processing technique has been studied in which a laser beam is irradiated toward the main surface of a substrate, condensed to a predetermined depth from the main surface to form a processing mark, thereby forming a modifiable layer that can be peeled off.

[0003] In addition, diamond substrates and gallium nitride substrates are used as bases for heteroepitaxial growth of diamond crystals on single crystal substrates of silicon or magnesium oxide (MgO), and gallium nitride on substrates such as silicon, silicon carbide, and sapphire (Al2O3), respectively. As a method for reusing these base substrates and processing a grown substrate into a thin wafer, the above-described processing technique using a laser beam has been studied.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Non-Patent Documents

[0005]

Non-Patent Document 1

[0006] However, because the single crystal materials mentioned above have various solid structures and types of chemical bonds, and therefore differ in their properties, in order to form a modified layer that can be peeled off by laser processing technology, it was necessary to individually consider a processing method suitable for the substrate to be processed, taking into account the material, crystal structure, bonding form, crystal plane orientation, crystal growth off-angle, and other parameters of the single crystal substrate to be processed, as well as processing conditions such as the characteristics of the laser light, focusing of the laser light into the substrate, laser light scanning method, and the depth and thickness of the modified layer to be formed.

[0007] This invention is proposed in view of the above-mentioned circumstances and aims to provide a substrate processing control device and system that controls a substrate processing apparatus to process a crystal substrate using an appropriate processing method according to the crystal substrate to be processed and the processing conditions. [Means for solving the problem]

[0008] To solve the above-mentioned problems, the substrate processing control device according to this application is a substrate processing control device that irradiates a laser beam toward the main surface of a crystal substrate placed on a stage and controls a substrate processing device to form a peelable modified layer by focusing the laser beam to a predetermined depth from the main surface, and includes a machine learning unit that receives explanatory variables including parameters relating to the crystal substrate to be processed and parameters relating to the processing conditions of the crystal substrate as input, and outputs an objective variable including parameters relating to the optical system for irradiating the crystal substrate with laser beam and parameters relating to the driving of the stage according to the explanatory variables, and a control unit that controls the substrate processing device based on the objective variable output from the machine learning unit.

[0009] The machine learning unit includes a board processing model generation unit that generates a board processing model by learning from multiple training data consisting of pairs of explanatory variables and corresponding target variables; a board processing model storage unit that stores the board processing model generated by the board processing model generation unit; and a board processing model application unit that applies the board processing model stored in the board processing model storage unit to infer the target variable from the explanatory variables. The input explanatory variables are processed in the board processing model application unit, and the target variable inferred by the board processing model application unit may be output.

[0010] The substrate processing model generation unit and the substrate processing model storage unit may constitute a substrate processing learning unit that learns training data to generate a substrate processing model and stores the generated substrate processing model. The substrate processing model application unit and the substrate processing model storage unit may constitute a substrate processing inference unit that stores the generated substrate processing model and applies the substrate processing model to infer the target variable from the input explanatory variables.

[0011] The explanatory variables may include, as parameters relating to the crystal substrate, at least one of the crystal material, crystal structure, crystal type, plane orientation, off-angle, cleavage plane, slip plane, Burgers vector, and dislocation plane. The explanatory variables may further include, as parameters relating to the crystal substrate, at least one of the wavelength dependence of transmittance, the coordinates of crystal defects, and the coordinates of surface foreign matter. The explanatory variables may include, as parameters relating to the processing conditions, at least one of the slicing thickness of the crystal substrate, the depth from the surface of the crystal substrate to the modified layer, and the thickness of the modified layer.

[0012] The objective variable may include at least one of the optical system parameters, such as the wavelength, pulse width, brightness, and repetition frequency of the laser light. The objective variable may also include at least one of the stage drive parameters, such as the scanning direction and scanning speed.

[0013] It may further include a console into which explanatory variables can be entered. It may further include sensors for detecting parameters of the crystal substrate.

[0014] The substrate processing system according to this application includes a substrate processing control device, a substrate processing apparatus comprising a substrate support device including a stage on which a crystal substrate is placed and a stage drive device for driving the stage, and an optical system for irradiating laser light toward the main surface of the crystal substrate placed on the stage of the substrate support device, wherein the substrate processing apparatus is controlled by the substrate processing control device. [Effects of the Invention]

[0015] According to this invention, artificial intelligence based on supervised machine learning can be used to control the processing of a crystal substrate appropriately according to the crystal substrate to be processed and the processing method. [Brief explanation of the drawing]

[0016] [Figure 1] This is a perspective view showing the general configuration of a substrate processing control system. [Figure 2]It is a block diagram showing a schematic configuration of a substrate processing control system. [Figure 3] It is a block diagram showing a schematic configuration of a substrate processing machine learning unit. [Figure 4] It is a diagram showing the configuration of a substrate processing model. [Figure 5] It is a diagram for explaining the operation of a substrate processing machine learning unit. [Figure 6] It is a perspective view showing the crystal structure of a sphalerite-type structure. [Figure 7] It is a perspective view showing the crystal structure of a diamond-type structure [Figure 8] It is a perspective view showing the crystal structure of a wurtzite-type structure. [Figure 9] It is a perspective view showing the crystal structure of hexagonal gallium nitride. [Figure 10] It is a schematic diagram for explaining the relationship between the basic structure of a regular tetrahedron constituting a crystal substrate and the laser scanning direction. [Figure 11] It is a schematic diagram showing the scanning direction of laser light with respect to a crystal substrate. [Figure 12] It is a diagram for explaining the formation of processing marks on a crystal substrate where the surface orientations of the main surface and the cleavage plane are the same. [Figure 13] It is a diagram for explaining the formation of processing marks on a crystal substrate where the surface orientations of the main surface and the cleavage plane are different. [Figure 14] It is a diagram for explaining the formation of processing marks on a crystal substrate where the surface orientations of the main surface and the cleavage plane are different. [Figure 15] It is a perspective view showing the crystal structure of a rock salt-type crystal.

Embodiments for Carrying Out the Invention

[0017] Embodiments of the substrate processing control device and system will be described in detail below with reference to the drawings. This embodiment assumes a substrate processing control device that controls a substrate processing device to form a peelable modified layer by placing a crystalline substrate on a stage, irradiating it with laser light toward its main surface, and focusing the laser light to a predetermined depth from the main surface, and a substrate processing control system having such a substrate processing device and substrate processing control device. Specifically, it is assumed that a peelable substrate is created by generating cleavage along the cleavage plane in the modified layer and controlling the modified layer to form this cleavage plane continuously in the plane direction of the crystalline substrate. Here, the plane direction of the crystalline substrate refers to the direction in which the main surface of the crystalline substrate extends, and a layer formed continuously in the plane direction refers to a layer formed so as to extend parallel to the main surface.

[0018] Figure 1 is a perspective view showing the schematic configuration of the substrate processing control system of this embodiment. Figure 2 is a block diagram showing the schematic configuration of the substrate processing system. The substrate processing system includes a substrate processing control device 10 and a substrate processing apparatus 100 controlled by the substrate processing control device 10.

[0019] The substrate processing apparatus 100 includes a substrate support device 110 that supports and drives the crystal substrate 200, and an optical system 120 that irradiates laser light B toward the main surface 200a of the crystal substrate 200. The substrate support device 110 includes a stage 112 on which the crystal substrate 200 is placed, a stage drive device 111 that supports the stage 112 so that it can be driven in the XY direction in the horizontal plane and in the vertical Z direction, and so that it can be rotated around the Z axis, and a fixing device 113 that fixes the crystal substrate 200 to the stage 112. The fixing device 113 can be an adhesive layer, a mechanical chuck, an electrostatic chuck, a vacuum chuck, etc.

[0020] The optical system 120 includes a laser light source 121 and a laser focusing unit 127 including an objective lens 125 and an aberration adjustment unit 126, so that the laser light B emitted from the laser light source 121 is irradiated toward the main surface 200a of the crystal substrate 200 via the laser focusing unit 127. The optical system 120 may further include other optical elements such as a diffractive optical element (DOE).

[0021] The substrate processing control device 10 includes a console 13 having a display, keyboard, etc., and a sensor 14 that can detect the material, size, crystal orientation, etc., of the crystal substrate 200 to be processed. The sensor 14 may be configured by combining, for example, a transmittance measuring device, a laser interference size measuring device, an X-ray diffractometer, etc.

[0022] As shown in Figure 2, in the substrate processing control device 10, parameters related to the crystal substrate 200, such as the material, size, and crystal orientation of the crystal substrate 200, which are input from the console 13 or sensor 14, and parameters related to processing conditions, such as the slicing thickness, which are input from the console 13, are input to the substrate processing machine learning unit 11 as explanatory variables. Based on the input explanatory variables, the substrate processing machine learning unit 11 outputs parameters related to the optical system 120, including the wavelength and pulse width of the laser light B, and parameters related to the driving of the stage 112 in the substrate support device 110, including the driving direction and driving speed of the stage 112, as objective variables, in accordance with the inference of the machine-learned artificial intelligence.

[0023] Furthermore, in the substrate processing control device 10, the target variable output from the substrate processing machine learning unit 11 is sent to the control unit 12, and the control unit 12 controls the substrate processing device 100 according to the target variable. Specifically, the control unit 12 controls the optical system 120 of the substrate processing device 100 by sending a control signal to the optical system 120 based on the parameters of the optical system 120 of the target variable, and controls the driving of the stage 112 of the substrate processing device 100 by sending a control signal to the substrate support device 110 of the substrate processing device 100 based on the parameters of the stage 112 of the target variable.

[0024] As shown in Figure 1, the machine learning unit 11 and control unit 12 of the board processing control device 10 may be configured using a personal computer as the main body 16 of the board processing control device 10. In this case, the machine learning unit 11 and control unit 12 may be implemented by executing an appropriate program on the personal computer in the main body 16.

[0025] Figure 3 is a block diagram showing the schematic configuration of the PCB processing machine learning unit 11. In the PCB processing machine learning unit 11, the PCB processing training data storage unit 21 stores training data used for supervised machine learning. Training data is a collection of many pairs of explanatory variables and the corresponding target variables. The PCB processing training data storage unit 21 has collected a large amount of training data in advance for use in machine learning. Training data may be created, for example, by computer simulation.

[0026] The substrate processing model generation unit 22 creates a substrate processing model by learning the training data supplied from the substrate processing training data storage unit 21. Figure 4 shows an example of the configuration of the substrate processing model. This substrate processing model is composed of a neural network. The neural network includes multiple layers composed of nodes and can be configured to optimize weights and biases through supervised learning, i.e., learning from training data. Note that the substrate processing model is not limited to a neural network and may be realized by other types of configurations.

[0027] The PCB processing model storage unit 23 stores the PCB processing model generated by the PCB processing model generation unit 22. If the PCB processing model is composed of a neural network, the PCB processing model storage unit 23 stores parameters of the PCB processing model, such as weights and biases set by training with training data. Even if the PCB processing model is implemented with a configuration other than a neural network, the PCB processing model storage unit 23 stores the parameters of the PCB processing model.

[0028] The PCB processing model application unit 24 reads the parameters of the PCB processing model from the PCB processing model storage unit 23 to reproduce the PCB processing model, applies the PCB processing model to the input explanatory variables, and outputs the target variable. If the PCB processing model is composed of a neural network, the weights and biases of the PCB processing model are read from the PCB processing model storage unit 23 to reproduce the PCB processing model.

[0029] In the PCB processing machine learning unit 11, the PCB processing model generation unit 22 and the PCB processing model storage unit 23 constitute a PCB processing learning unit 31 that generates a PCB processing model through supervised learning. Furthermore, the PCB processing model storage unit 23 and the PCB processing model application unit 24 constitute a PCB processing inference unit 32 that infers the target variable from the explanatory variables by applying the PCB processing model generated by supervised learning.

[0030] Figure 5 is a diagram illustrating the operation of the substrate processing machine learning unit 11. The substrate processing machine learning unit 11 receives parameters related to the crystal substrate 200 to be processed, such as the material, size, and crystal orientation of the crystal substrate 200, and parameters related to processing conditions, such as the slicing thickness and the thickness of the modified layer, as explanatory variables. The parameters related to the crystal substrate 200, such as the material, size, and crystal orientation of the crystal substrate 200, may be input from values ​​measured by the sensor 14, or the values ​​of these parameters may be input from the console 13. Measurement of the crystal substrate 200 by the sensor 14 is performed before the crystal substrate 200 is placed on the stage 112 and processing is carried out. Parameters related to processing conditions, such as the slicing thickness and the thickness of the modified layer, may be input from the console 13.

[0031] Table 1 shows examples of explanatory variables to be input to the substrate processing machine learning unit 11. The explanatory variables include parameters related to the crystal substrate 200. The parameters related to the crystal substrate 200 include parameters specific to each individual crystal substrate 200, such as the material, size, and crystal orientation of the crystal substrate 200. Parameters specific to the crystal substrate 200 also include the XYZ coordinates of crystal defects and the XY coordinates of surface foreign matter. These parameters specific to the crystal substrate 200 can be detected by measurement by the sensor 14, and are shown in the "Detected Data for Crystal Substrate" column in Table 1.

[0032] [Table 1]

[0033] Table 2 shows examples of materials for the crystal substrate 200. Examples of materials listed in Table 2 include single-crystal silicon, single-crystal diamond, 4H-SiC, 6H-SiC, single-crystal gallium nitride, single-crystal gallium arsenide, single-crystal gallium phosphide, single-crystal sapphire, and single-crystal magnesium oxide. The crystal structure and cleavage planes of each material are also described in Table 2. The substrate processing control device 10 is not limited to these types of materials and can accommodate other types of materials. For example, the material may be polycrystalline, such as polycrystalline silicon, or amorphous, such as glass.

[0034] [Table 2]

[0035] As shown in Table 1, the parameters relating to the crystalline substrate 200 include parameters determined by the material of the crystalline substrate 200, such as the crystal structure, chemical bonding, plane orientation, off-angle, cleavage plane orientation, slip plane orientation, slip direction, Burgers vector, and dislocation plane. Referring to Table 2, the crystal structure and cleavage plane are shown as parameters determined by the material. These parameters can be considered attributes of the material of the crystalline substrate 200, and are therefore shown in the "Attributes of Crystalline Substrate 200" column in Table 1.

[0036] Table 1 shows the slip plane orientation and slip direction in the material attributes column for the crystal substrate 200. Slip planes in crystalline materials occur when crystals above and below a crystal plane shift in a slip direction, which is a direction specified by the crystalline material. This shift is caused by introducing dislocations, which are line defects, into the crystalline material, and the slip plane is formed by the plastic deformation of the crystalline material. The Burgers vector is defined as a vector that represents this shift. In a slip system, the slip plane and slip direction are paired, and most of these planes and directions coincide with the closest-packed plane and closest-packed direction in the atomic arrangement of the crystalline material. On the other hand, cleavage is considered to be a brittle fracture and is said to occur near the starting point of deformation. In this embodiment, the processing mechanism involves focusing laser light B from the main surface 200a of the crystal substrate 200 to a predetermined depth to generate cleavage in the crystalline material, starting from a dislocation-induced shift.

[0037] The explanatory variables also include parameters related to processing conditions. These parameters include the thickness of the crystalline substrate 200 sliced ​​from the crystalline substrate 200, and the thickness of the modified layer formed inside the crystalline substrate 200. These parameters are shown in the "Processing Conditions" column of Table 1.

[0038] As shown in Table 3 below, the parameters for the optical system 120 include parameters related to laser light B, such as the wavelength, pulse width, brightness, repetition frequency, and beam profile of laser light B. These parameters are shown in the "Laser Light B" column of the optical system 120 in Table 3. The parameters for the optical system 120 also include parameters related to the laser focusing unit 127, such as the numerical aperture, magnification, focal length, working distance, depth of focus, and, if necessary, diffractive optical elements for splitting laser light B into multiple beams. The parameters for the diffractive optical elements may include focusing conditions, such as parameters related to the shape, number, and arrangement of the laser transmitted light that splits laser light B using the diffractive optical elements. These parameters are shown in the "Laser Focusing Unit 127" column of the optical system 120 in Table 3. The parameters related to the driving of the stage 112 include the driving direction, driving speed, and rotational speed. Here, the rotational speed applies when the stage 112 is rotationally driven. These parameters are shown in the "Stage Driving" column of Table 3. Since the driving of stage 112 is relatively equivalent to scanning laser beam B, the stage driving can be interpreted as scanning laser beam B.

[0039] [Table 3]

[0040] The substrate processing machine learning unit 11 applies a substrate processing model generated by supervised machine learning to the input explanatory variables. It then outputs parameters related to the optical system 120, such as laser wavelength and laser output, and parameters of the substrate support device 110, such as the driving direction and driving speed of the stage 112, as target variables.

[0041] Referring again to Figure 2, the target variable output from the substrate processing machine learning unit 11 of the substrate processing control device 10 is supplied to the control unit 12. The control unit 12 controls the substrate processing device 100 based on the target variable supplied from the substrate processing machine learning unit 11. For example, it sets the optical system 120 of the substrate processing device 100 based on parameters related to the optical system 120, such as the wavelength and repetition frequency of the laser light B supplied from the substrate processing machine learning unit 11. It also tracks and controls the position and speed of the stage 112 of the substrate support device 110 in real time based on parameters related to the driving of the stage 112, such as the driving direction and driving speed of the stage 112 supplied from the substrate processing machine learning unit 11.

[0042] Thus, according to this embodiment, the substrate processing apparatus can be controlled to process the crystal substrate 200 using an appropriate processing method according to the crystal substrate 200 to be processed and the processing conditions. Therefore, there is no need to individually consider the substrate processing apparatus 100 according to the material of the crystal substrate 200 or the processing conditions of the substrate, and the workload for substrate processing can be reduced. Furthermore, because it is controlled by artificial intelligence machine learning, substrate processing can be performed accurately and reliably.

[0043] Thus, according to this embodiment, by using machine learning of artificial intelligence, in addition to the material, crystal structure, bonding mode, crystal plane orientation, crystal growth off-angle, and other parameters of the crystal substrate 200 made of the single crystal material to be processed, it is also possible to consider processing condition parameters such as the characteristics of the laser beam B, focusing of the laser beam B into the crystal substrate 200, scanning method of the laser beam B, and depth and thickness of the modified layer to be formed, and to form a peelable modified layer using an appropriate laser beam B processing technique for single crystal materials having various solid structures and types of chemical bonds.

[0044] In this embodiment, it was assumed that a removable modified layer would be formed by irradiating the main surface 200a of the crystal substrate 200 with laser light B, thereby creating a processing mark at a predetermined depth from the main surface 200a. However, the edges of the crystal substrate 200 may also be appropriately processed. For example, processing marks may not be formed at a predetermined distance from the outer edge of the crystal substrate 200, and cleavage may spontaneously occur from the processing marks along the edge toward the edge, thereby forming the modified layer. Such processing of the edges of the crystal substrate 200 can also be taught to the substrate processing model through supervised learning.

[0045] Furthermore, the substrate processing state of the crystalline substrate 200 processed by controlling the substrate processing apparatus 100 with the substrate processing control device 10 of this embodiment may be evaluated. For example, the modified layer formed on the crystalline substrate 200 may be evaluated using image data from sensing results of images obtained from an infrared microscope or an optical microscope, such as the cleavage direction, the appearance on the side irradiated by the laser beam B (crack formation, etc.), and the depth of crystal disorder. The evaluation results may be displayed on the display of the console 13, for example. [Examples]

[0046] The following describes an example of forming a modified layer on a specific crystalline substrate 200 by irradiating it with laser light B using the substrate processing control device 10 and substrate processing control system of this embodiment. In this embodiment, parameters such as the material, size, and crystal orientation of the crystalline substrate 200, as shown in Table 1, may be detected by measuring the crystalline substrate 200 to be processed with a sensor 14. These parameters may also be input from the console 13. Furthermore, the sensor 14 may also detect the XYZ coordinates of crystal defects and the XY coordinates of surface foreign matter on the crystalline substrate 200. Since parameters such as the crystal structure, chemical bonding, and surface orientation of the crystalline substrate 200 are specified according to the material of the crystalline substrate 200, they may be read from a database or, if necessary, input from the console 13. Parameters related to processing conditions, such as the slicing thickness and the thickness of the modified layer, may also be input from the console 13.

[0047] As shown in Figure 5, these parameters are input as explanatory variables to the substrate processing machine learning unit 11, and the substrate processing machine learning unit 11 outputs the corresponding objective variables using artificial intelligence. As shown in Table 3, the objective variables include the wavelength, pulse width, and repetition frequency of the laser light B, the driving direction of the stage 112, and the driving speed. The substrate processing control device 10 controls the substrate processing apparatus 100 based on these objective variables to process the crystal substrate 200 appropriately. Therefore, processing by the substrate processing apparatus 100 does not need to be adjusted even if the crystal substrate 200 to be processed is changed, and an appropriate processing method according to the crystal substrate 200 to be processed is selected under the control of artificial intelligence. [Examples]

[0048] Figure 6 is a perspective view showing the crystal structure of a zincblende-type structure. The zincblende-type structure shown in Figure 6 is found in III-V group compounds such as gallium arsenide (GaAs) and gallium nitride (GaN). In Figure 6, white circles represent group III atoms such as gallium (Ga), black circles represent group V atoms such as arsenic (As) and nitrogen (N), and the lines connecting the white or black circles represent covalent bonds. The zincblende-type structure is based on a regular tetrahedron formed with four other atoms surrounding one atom as its vertices. Figure 6 also shows the (011) plane, which is a cleavage plane.

[0049] Figure 7 is a perspective view showing the crystal structure of a diamond-type structure. When a zincblende-type structure, as shown in Figure 6, is composed of the same type of elements, it becomes the diamond-type structure shown in Figure 7. Diamond-type structures are found, for example, in carbon and silicon, which belong to group IV elements. In Figure 6, the white circles represent atoms of carbon, silicon, etc., and the lines connecting the white circles represent covalent bonds. The diamond-type structure is constructed with a regular tetrahedron as its basic structure, formed with four other atoms surrounding one atom as its vertices. Figure 7 also shows the (001) plane, which is the cleavage plane, and the (001) plane, which is sometimes considered to be the main surface 200a of the crystal substrate 200.

[0050] Figure 8 is a perspective view showing the wurtzite structure of gallium nitride. Gallium nitride, which belongs to group III-V compounds, can also have the zincblende structure shown in Figure 6, but the wurtzite structure shown in Figure 8 is the stable form under room temperature and constant pressure. In Figure 8, white circles represent gallium (Ga) atoms, black circles represent nitrogen (N) atoms, and the lines connecting the white or black circles indicate covalent bonds.

[0051] Figure 9 is a perspective view showing the hexagonal crystal structure of gallium nitride. The unit cell of wurtzite-type gallium nitride is hexagonal, as shown in Figure 9. In Figure 9, which shows the hexagonal structure, as in Figure 8, white circles represent gallium atoms and black circles represent nitrogen atoms. The unit cell of hexagonal gallium nitride shown in Figure 9 has different cleavage planes depending on its polarity. The gallium and nitrogen atomic layers are stacked alternately in the c-axis direction, and polarization occurs due to the difference in electronegativity between gallium and nitrogen atoms. The c-plane is a polar plane, the a-plane and m-plane, which are perpendicular to the c-plane, are nonpolar planes, and the r-plane is a semipolar plane. Here, the cleavage planes are the a-plane {11-20} and the m-plane {1-100}. Note that due to restrictions on the characters that can be used in patent application documents, a negative sign "-" is used instead of an overline for Miller indices. Such hexagonal gallium nitride can be grown along the c-axis on a base substrate. In a hexagonal crystal, the base and apex faces are {0001} planes.

[0052] Figure 10 is a schematic diagram showing the relationship between the basic structure of the tetrahedrons constituting the crystal substrate 200 and the laser scanning direction. Single crystals having crystal structures such as the zincblende type structure shown in Figure 6 and the diamond type structure shown in Figure 7, and crystal substrates 200 composed of such single crystals, are constructed with tetrahedrons as their basic structure. In crystal substrates 200 where the main surface 200a has a plane orientation such as (100) or (111), one face of the tetrahedron of the basic structure is arranged parallel to the main surface. In this case, the laser beam B can be scanned in a specific direction considering the arrangement of the tetrahedrons of the basic structure so that cleavage can be formed from dislocations in the crystal material due to laser irradiation. The figure illustrates the arrangement of the tetrahedrons of the basic structure relative to the main surface 200a of the crystal substrate 200, and the direction in which the laser beam B is scanned toward the main surface 200a of the crystal substrate 200, using the tetrahedrons of the basic structure as a reference.

[0053] Referring to Figure 1, the direction in which the laser beam B is scanned toward the main surface 200a with respect to the regular tetrahedron corresponds to the direction in which the laser beam B is scanned from the optical system 120 including the laser light source 121 along the main surface 200a of the crystal substrate 200. In the substrate processing machine learning unit 11 in Figure 3, the direction in which the laser is scanned is provided to the substrate processing learning unit 31 from the substrate processing training data storage unit 21 as training data for the type of crystal substrate 200 to be processed, based on the occurrence and direction of cleavage originating from displacements due to dislocations in the crystal material for the surface orientation of the crystal substrate 200 such as (100) and (111), and may be stored as parameters in the substrate processing model storage unit 23. The substrate processing inference unit 32 can output an appropriate direction for scanning the laser based on the parameters read from the substrate processing model storage unit 23.

[0054] Figure 10(a) shows a first embodiment of the scanning direction of the laser beam B. The dashed lines in the figure indicate the lines along which the laser beam B is scanned. The laser beam B is scanned along the lines at regular intervals (dot pitch) across the crystal substrate 200, scanning over the entire main surface 200a of the crystal substrate 200 so that adjacent lines are at regular intervals (line pitch) from each other. The thick arrows in the figure indicate the direction in which the lines are moved. In the first embodiment, the direction of the lines along which the laser beam B is scanned is perpendicular to one of the sides of an equilateral triangle that constitutes one face of a regular tetrahedron of the basic figure, which is parallel to the main surface 200a. By scanning in this direction, it is possible to break specific covalent bonds extending from the atom located at the center of the tetrahedron of the basic figure toward each face of the tetrahedron, thereby generating cleavage.

[0055] Figure 10(b) shows a second embodiment of the scanning direction of the laser beam B. In the second embodiment as well, the dashed lines in the figure indicate the lines along which the laser beam B is scanned. The laser beam B is scanned along the lines at regular intervals (dot pitch) on the crystal substrate 200, and is scanned over the entire main surface 200a of the crystal substrate 200 so that adjacent lines are at regular intervals (line pitch) from each other. The thick arrows in the figure indicate the direction in which the lines are moved. In the second embodiment, the direction of the lines along which the laser beam B is scanned is parallel to one of the sides of an equilateral triangle that constitutes one face of a regular tetrahedron of the basic figure parallel to the main surface. By scanning in this direction, it is possible to break specific covalent bonds extending from the atom located at the center of the regular tetrahedron of the basic figure toward each face of the tetrahedron, thereby generating cleavage.

[0056] Figure 11 is a schematic diagram showing the scanning direction of laser beam B on the crystal substrate 200. Laser beam B is scanned in an appropriate direction to cause cleavage in the crystal according to the (100), (111), etc., plane orientations of the crystal substrate 200. The scanning direction of laser beam B is determined on the main surface 200a of the crystal substrate 200, taking into consideration the arrangement of the tetrahedra, which are the basic structures constituting the crystal substrate 200, as explained in Figure 10. On the main surface 200a of the crystal substrate 200, laser beam B is scanned along lines at regular intervals (dot pitch) on the crystal substrate 200, scanning over the entire main surface 200a of the crystal substrate 200 so that adjacent lines are at a regular interval (line pitch) from each other. These scanning directions are set in combination with parameters such as laser beam parameters, dot pitch, and line pitch for the material to be processed and crystal orientation, and processing conditions are selected that form a peelable processed layer by the resulting cleavage and peel the crystal substrate 200 in the plane direction at the cleavage plane to create a new substrate.

[0057] Figure 11(a) is a schematic diagram showing a first embodiment of a laser beam B scanning the main surface 200a of the crystal substrate 200. In the first embodiment, the laser beam B may scan along the substantially rectangular main surface 200a of the crystal substrate 200 in one direction, such as from right to left or from left to right in the figure. Alternatively, the scanning direction of the laser beam B may be switched between scanning from right to left and from left to right for each adjacent line. The line on which the laser beam B is scanned may move along the main surface 200a from bottom to top or from top to bottom in the figure.

[0058] Figure 11(b) is a schematic diagram showing a second embodiment of the laser beam B scanning the main surface 200a of the crystal substrate 200. The second embodiment is obtained by rotating the scanning direction of the laser beam in the first embodiment shown in Figure 11(a) by 90° within the main surface 200a. In the second embodiment, the laser beam may scan along the main surface 200a of the substantially rectangular crystal substrate 200 in one direction, such as from bottom to top or from top to bottom in the figure. The scanning direction of the laser beam B may also be switched between going from bottom to top and from top to bottom for each adjacent line. The line on which the laser beam B is scanned may move along the main surface 200a from right to left in the figure, or from left to right in the figure.

[0059] Figure 11(c) is a schematic diagram showing a third embodiment of the laser beam B scanning the main surface 200a of the crystal substrate 200. The third embodiment is obtained by rotating the scanning direction of the laser beam B in the first embodiment shown in Figure 11(a) over a predetermined angle within the main surface. In the third embodiment, the laser beam B may scan the main surface 200a of the crystal substrate 200 in one direction, either in a predetermined direction or in the opposite direction. The scanning direction of the laser beam B may be switched for each adjacent line in a predetermined direction and in the opposite direction. The line scanning the laser beam B may move in any direction as long as it can scan the entire main surface 200a.

[0060] Figure 12 illustrates the formation of processing marks 212 on a crystal substrate 210 in which the plane orientation of the main surface 210a and the cleavage plane are the same. Figure 12(a) is a top view of the crystal substrate 210 in which processing marks 212 are formed, and Figures 12(b) and 12(c) are cross-sectional views of the crystal substrate 210 in which processing marks 212 are formed. Examples of crystal substrates 210 in which the plane orientation of the main surface 210a and the cleavage plane are the same include single-crystal silicon or single-crystal diamond crystal substrates 210 in which the main surface 210a is (111) plane, and rock salt type crystal substrates 210 in which the main surface 210a is (100) plane, which will be described later.

[0061] As shown in Figure 12(b), the laser beam B is focused from the main surface 210a to a predetermined depth in the crystal substrate 210, forming a processing mark 212. Cracks 214 extend from the processing mark 212 along a cleavage plane with the same surface orientation as the main surface 210a. As shown in Figure 12(a), the laser beam B is irradiated so as to scan the entire main surface 210a. Since the laser beam B is irradiated in a pulsed manner at a predetermined repetition frequency, the processing marks 212 are formed along the line through which the laser beam B is scanned with a predetermined dot pitch. The thin arrows in Figures 12(a) and 12(b) indicate the direction of scanning of the laser beam B along the line, and the thick arrow in Figure 12(a) indicates the direction of movement along the line through which the laser beam B is scanned. The laser beam B is scanned so as to have a predetermined line pitch with respect to adjacent lines.

[0062] As shown in Figure 12(b), around the processing marks 212, cracks 214 that have cleaved from the processing marks 212 extend in the scanning direction of the laser beam B along the direction of the cleavage plane, which has the same surface orientation as the main surface 210a. As shown in Figure 12(c), the cracks 214 extending from each processing mark 212 connect with the cracks 214 extending from adjacent processing marks 212, thereby forming a modified layer inside the crystal substrate 210 in which processing marks 212 and cracks 214 extending parallel to the main surface 210a are connected. The connection of cracks 214 extending from adjacent processing marks 212 is achieved by appropriately setting parameters related to the optical system 120, as shown in Table 3.

[0063] The modified layer separates the crystalline substrate 210 into the crystalline substrate from the main surface 210a to the modified layer and the remaining crystalline substrate deeper than the modified layer. Since the modified layer is formed by the connection of processing marks 212 and cracks 214, the crystalline substrate from the main surface 210a to the modified layer and the remaining crystalline substrate deeper than the modified layer can be separated by cleavage in the modified layer. The crystalline substrate from the main surface 210a to the modified layer is called a sliced ​​substrate because, similar to slicing, a thin crystalline substrate is cut from the original crystalline substrate 210. The thickness of the sliced ​​substrate is called the slicing thickness. By separating the sliced ​​substrate in the modified layer, a new crystalline substrate is obtained from the crystalline substrate 210.

[0064] Figures 13 and 14 illustrate the formation of processing marks 222 on a crystal substrate 220 in which the plane orientation of the main surface 220a and the cleavage plane are different. Figures 13(a) and 13(b) are top and cross-sectional views of the crystal substrate 220 in which processing marks 222 have been formed by scanning with the laser beam B for the first time, and Figures 14(a) to 14(c) are top and cross-sectional views of the crystal substrate 220 in which processing marks 222 have been formed by scanning with the laser beam B for the second time. Examples of crystal substrates 220 in which the plane orientation of the main surface 220a and the cleavage plane are different include single-crystal silicon or single-crystal diamond crystal substrates 220 in which the main surface 220a is (001) plane, and rock salt type crystal substrates 220 in which the main surface 220a is (111) plane, which will be described later.

[0065] As shown in Figure 13(b), during the first scan of the laser beam B, the laser beam B is focused from the main surface 220a to a predetermined depth in the crystal substrate 220, forming a processing mark 222. Following the first scan of the laser beam B, a crack 224 extends from the processing mark 222 along a first cleavage plane with a different surface orientation from the main surface 220a, in the scanning direction of the laser beam B. As shown in Figure 13(a), the laser beam B is irradiated so as to scan the entire main surface 220a. Because the laser beam B is irradiated in pulses at a predetermined repetition frequency, the processing marks 222 are formed along the scanning line of the laser beam B with a predetermined dot pitch. The thin arrows in Figures 13(a) and 13(b) indicate the direction of scanning of the laser beam B along the line, and the thick arrow in Figure 13(a) indicates the direction of movement along the scanning line of the laser beam B. The laser beam B is scanned such that it has a predetermined line pitch with respect to adjacent lines. The same applies to Figures 14(a) through 14(c).

[0066] As shown in Figure 14(b), in the second scan as well, the laser beam B is focused from the main surface 220a to a predetermined depth in the crystal substrate 220, forming a processing mark 222. As shown by the thin arrows in Figures 14(a) and 14(b), the second scan of the laser beam B is performed by scanning along the same line as the first scan of the laser beam B, but in the opposite direction. As shown by the thick arrow in Figure 14(a), the direction in which the line scanning the laser beam B moves is also the opposite direction to that of the first scan of the laser beam B. The interval between scans of the laser beam B along the line (dot pitch) and the interval in the direction in which the line scanning the laser beam B moves (line pitch) in the second scan of the laser beam B are the same as in the first scan of the laser beam B.

[0067] As shown in Figure 14(b), in the second scan of the laser beam B, the laser beam B is focused from the main surface 220a to a processing mark 222 of a predetermined depth in the crystal substrate 220. Due to the second scan of the laser beam B, a crack 224 extends from the processing mark 222 along a second cleavage plane, which has a different surface orientation from both the main surface 220a and the first cleavage plane, in the scanning direction of the laser beam B. Here, since the scanning direction of the laser beam B in the second scan is reversed compared to the first scan of the laser beam B, the profile of the laser beam B in the second scan is reversed with respect to the line compared to the first scan of the laser beam B. As shown in Figure 14(b), when the first and second scans of laser beam B are performed together, the processing marks 222 formed by the irradiation of laser beam B and the cracks 224 extending from the processing marks 222 along the first and second cleavage planes are formed symmetrically with respect to the line.

[0068] In Figure 14(c), cracks 224 are formed symmetrically from the processing marks 222 with respect to the line, and the cracks 224 extending from each processing mark 222 are connected to one another. The connection of the cracks 224 that are not parallel to the main surface 220a extending from each processing mark 222, i.e., the first cleavage plane and the second cleavage plane, creates a modified layer parallel to the main surface 220a inside the crystal substrate 220. The connection of cracks 224 extending from adjacent processing marks 222 is achieved by appropriately setting parameters related to the optical system 120, as shown in Table 3.

[0069] The modified layer separates the crystalline substrate 220 into the crystalline substrate 220 from the main surface 220a to the modified layer and the remaining crystalline substrate 220 deeper than the modified layer. By advancing cleavage across the entire crystalline substrate 220 using this connected modified layer, the crystalline substrate from the main surface 220a to the modified layer and the remaining crystalline substrate deeper than the modified layer can be separated. The crystalline substrate from the main surface 220a to the modified layer is called a sliced ​​substrate because, similar to slicing, it is a thin substrate crystal cut from the original crystalline substrate 220. The thickness of the sliced ​​substrate is called the slicing thickness. By peeling off the sliced ​​layer with the modified layer, a new crystalline substrate is obtained from the crystalline substrate 220.

[0070] In this embodiment, the material, crystal structure, bonding form, crystal plane orientation, crystal growth off-angle, and other parameters of the crystal substrate 200 to be processed are confirmed. Furthermore, processing conditions such as the characteristics of the laser beam, focusing of the laser beam into the substrate, laser beam scanning method, and depth and thickness of the modified layer to be formed are also considered, and a processing method suitable for the crystal substrate 200 is implemented under the control of artificial intelligence. This reduces the burden on the operator slicing the crystal substrate 200 and ensures that the crystal substrate is sliced ​​under the desired conditions. [Examples]

[0071] Figure 15 is a perspective view showing the crystal structure of rock salt (NaCl). In Example 2, single-crystal gallium nitride (GaN), single-crystal gallium arsenide (GaAs), and single-crystal gallium phosphide (GaP) are used as examples of materials for the crystal substrate 200. These single-crystal gallium nitride, single-crystal gallium arsenide, or single-crystal gallium phosphide chlorides have a sodium-type unit cell. In Figure 14, white circles represent gallium (Ga) atoms, black circles represent nitrogen (N), arsenic (As), or phosphorus (P) atoms, and the lines connecting the white or black circles represent covalent bonds.

[0072] Similarly to Example 1, a modified layer that causes wall openings can be formed inside the crystal substrate 200, which is made of single-crystal gallium nitride, single-crystal gallium arsenide, or single-crystal gallium phosphide, by irradiating it with laser light B based on the target variable output from the substrate processing machine learning unit 11. By cleaving the crystal substrate 200 with this modified layer, a crystal substrate thinner than the crystal substrate 200 can be obtained, similar to Example 1.

Claims

1. A substrate processing control device controls a substrate processing apparatus to irradiate a laser beam toward the main surface of a crystal substrate placed on a stage, and to focus the laser beam to a predetermined depth from the main surface to form a peelable modified layer, A machine learning unit receives explanatory variables, including parameters related to the crystal substrate to be processed and parameters related to the processing conditions of the crystal substrate, and outputs a target variable, including parameters related to the optical system for irradiating the crystal substrate with laser light and parameters related to the driving of the stage, according to the explanatory variables. A control unit that controls the substrate processing apparatus based on the target variable output from the machine learning unit. A circuit board processing control device that includes this.

2. The aforementioned machine learning unit, A circuit board processing model generation unit generates a circuit board processing model by learning multiple training data sets, with respect to training data consisting of pairs of explanatory variables and corresponding objective variables. A substrate processing model storage unit for storing the substrate processing model generated by the substrate processing model generation unit, A substrate processing model application unit applies the substrate processing model stored in the substrate processing model storage unit to infer the objective variable from the explanatory variables. Includes, The substrate processing control device according to claim 1, wherein the input explanatory variables are processed in the substrate processing model application unit, and the target variable inferred by the substrate processing model application unit is output.

3. The substrate processing control device according to claim 2, wherein the substrate processing model generation unit and the substrate processing model storage unit constitute a substrate processing learning unit that learns the training data to generate a substrate processing model and stores the generated substrate processing model.

4. The substrate processing control device according to claim 2, wherein the substrate processing model application unit and the substrate processing model storage unit store the generated substrate processing model and constitute a substrate processing inference unit that applies the substrate processing model to infer the target variable from the input explanatory variables.

5. The substrate processing control device according to claim 1, wherein the explanatory variables include, as parameters relating to the crystal substrate, at least one of the crystal material, crystal structure, crystal type, plane orientation, off-angle, cleavage plane, slip plane, Burgers vector, and dislocation plane.

6. The substrate processing control device according to claim 5, wherein the explanatory variable further includes at least one of the wavelength dependence of transmittance, the coordinates of crystal defects, and the coordinates of surface foreign matter as parameters relating to the crystal substrate.

7. The substrate processing control device according to claim 1, wherein the explanatory variable includes, as a parameter relating to the processing conditions, at least one of the thickness to which the crystal substrate is sliced, the depth from the surface of the crystal substrate to the modified layer, and the thickness of the modified layer.

8. The substrate processing control device according to claim 1, wherein the objective variable includes at least one of the wavelength, pulse width, brightness, and repetition frequency of the laser light as parameters relating to the optical system.

9. The substrate processing control device according to claim 1, wherein the objective variable includes at least one of scanning direction and scanning speed as a parameter relating to the driving of the stage.

10. The substrate processing control device according to claim 1, further comprising a console on which the explanatory variables can be input.

11. The substrate processing control device according to claim 1, further comprising a sensor for detecting the parameters of the crystal substrate.

12. A substrate processing control device according to any one of claims 1 to 11, The aforementioned substrate processing apparatus, A substrate support apparatus including a stage on which the crystal substrate is placed and a stage drive device for driving the stage, An optical system that irradiates laser light toward the main surface of a crystal substrate placed on the stage of the substrate support device, Includes a substrate processing apparatus, The substrate processing apparatus is a substrate processing system controlled by the substrate processing control device.

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