Abnormality monitoring system applied to plasma etching machine

Abstract

Embodiments of the present application disclose an abnormality monitoring system applied to a plasma etching machine. The abnormality monitoring system comprises a constant current source device, a coil, a coil detection circuit and a controller. The constant current source device is configured to output a driving current according to preset etching process parameters. The coil is configured to generate a magnetic field in an etching cavity in response to the input of the driving current, so as to guide the movement of plasma towards the direction of a substrate to etch the substrate. The coil detection circuit is configured to detect coil state data of the coil. The controller is configured to generate device maintenance information based on the coil state data. Embodiments of the present application monitor the working state of the coil through the coil state data, and reflect the actual situation of the coil through the device maintenance information, so that the user can quickly know whether the coil is in an abnormal state, help the user quickly locate the maintenance direction, and avoid wasting various resource inputs when the user disassembles and maintains the coil from the etching cavity without finding that the coil is abnormal.

Description

Technical Field

[0001] This application relates to the field of semiconductor equipment technology, specifically to an anomaly monitoring system applied to a plasma etching machine. Background Technology

[0002] During substrate etching, a constant current source provides a continuous and stable drive current to the coils of the plasma etching machine. This drives the coils to generate a specific magnetic field, which guides the ion beam to bombard the substrate surface, thus completing the etching operation. Typically, the coils operate in a sealed environment. When the coil's resistance becomes abnormal due to factors such as the outer insulation layer peeling off or incorrect placement, the magnetic field changes, causing the ion beam to deviate from its intended trajectory and thus reducing the etching effect. When troubleshooting substrate etching abnormalities, staff must sequentially check various devices along the etching path to pinpoint the malfunctioning device. Checking the coils, in particular, requires removing them from the etching chamber to inspect for abnormalities, resulting in significant time consumption and low efficiency. Summary of the Invention

[0003] To address the aforementioned technical problems, this application provides an anomaly monitoring system that improves upon the limitations of related technologies in quickly locating coil malfunctions, resulting in low maintenance efficiency.

[0004] In a first aspect, embodiments of this application provide an anomaly monitoring system for a plasma etching machine. The plasma etching machine includes a gas output module, an etching chamber, and an electrostatic chuck. The electrostatic chuck is disposed at the bottom of the etching chamber and configured to hold a substrate. The anomaly monitoring system includes: a constant current source device, a coil, a coil detection circuit, and a controller. The constant current source device is configured to output a driving current according to preset etching process parameters. The coil is electrically connected to the constant current source device and configured to generate a magnetic field in the etching chamber in response to the input of the driving current to guide the plasma inside the etching chamber to move toward the substrate to etch the substrate. The coil detection circuit is electrically connected between the constant current source device and the current loop of the coil and is configured to detect the coil status data. The controller is electrically connected to both the constant current source device and the coil detection circuit and is configured to generate equipment maintenance information based on the coil status data.

[0005] Optionally, the anomaly monitoring system further includes a magnetic field detection module, which is configured to collect emitted light from plasma at different locations to obtain spectral data; the step of generating equipment maintenance information based on the coil status data includes: determining the target anomaly type based on the coil status data and the spectral data, and generating equipment maintenance information based on the target anomaly type.

[0006] Optionally, determining the target anomaly type based on the coil state data and the spectral data includes: determining the coil resistance of the coil based on the coil state data; generating a magnetic field strength distribution map based on the spectral data; and determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map.

[0007] Optionally, the target anomaly type includes a coil anomaly type or a power supply anomaly type. Determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map includes: determining the target anomaly type as a power supply anomaly type in response to an anomaly in the magnetic field strength distribution map and the coil resistance being within the normal resistance range; and determining the target anomaly type as a coil anomaly type in response to an anomaly in the magnetic field strength distribution map and the coil resistance being outside the normal resistance range.

[0008] Optionally, the coil state data includes voltage sampling data and coil voltage data applied across the coil. Determining the coil resistance based on the coil state data includes: determining the coil current flowing through the coil based on the voltage sampling data and a preset resistance value; and calculating the coil resistance based on the coil current and the coil voltage data.

[0009] Optionally, generating a magnetic field intensity distribution map based on the spectral data includes: determining the splitting morphology of the target spectral line based on the spectral data; determining the wavelength difference of the target spectral line under the splitting morphology; determining the magnetic field intensity at the target location based on the Zeeman effect formula and the wavelength difference; and combining the magnetic field intensities at different target locations to obtain a magnetic field intensity distribution map.

[0010] Optionally, the target anomaly type includes a coil anomaly type or a power supply anomaly type, the equipment maintenance information includes coil maintenance information or power supply maintenance information, and the step of generating equipment maintenance information based on the target anomaly type includes: generating coil maintenance information in response to the target anomaly type being a coil anomaly type; and generating power supply maintenance information in response to the target anomaly type being a power supply anomaly type.

[0011] Optionally, the coil state data includes voltage sampling data and coil voltage data applied across the coil. The coil detection circuit includes: a sampling resistor electrically connected between the constant current source device and the current loop of the coil, configured to generate a sampling voltage in response to a drive current flowing through the coil; a voltage conditioning circuit electrically connected to the sampling resistor and the controller, configured to perform signal conditioning processing on the sampling voltage to obtain voltage sampling data; and a voltage detection circuit electrically connected between the two ends of the coil and the controller, configured to detect the voltage applied across the coil to obtain coil voltage data.

[0012] Optionally, the voltage detection circuit includes a first-stage voltage amplifier circuit and a final-stage voltage amplifier circuit connected in series. The first-stage voltage amplifier circuit is electrically connected between the two ends of the coil to amplify the voltage across the coil. The final-stage voltage amplifier circuit is electrically connected to the controller to output coil voltage data.

[0013] Optionally, the magnetic field detection module includes a spectrometer configured to collect emitted light from plasma at different locations to obtain spectral data.

[0014] The beneficial effects of this application's embodiments: This application's embodiments monitor the working status of the coil through coil status data and reflect the actual situation of the coil through equipment maintenance information, so that users can quickly know whether the coil is in an abnormal state, help users quickly locate the direction of maintenance, and avoid the various resource investments wasted by users disassembling and maintaining the coil from the etching cavity without discovering that the coil is abnormal. Attached Figure Description

[0015] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0016] Figure 1 This is a schematic diagram of the circuit structure of an anomaly monitoring system provided in an embodiment of this application;

[0017] Figure 2 A schematic diagram of a plasma etching machine provided for related technologies;

[0018] Figure 3 This is a schematic diagram of the circuit structure of an anomaly monitoring system provided in an embodiment of this application;

[0019] Figure 4 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0020] Figure 5 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0021] Figure 6 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0022] Figure 7 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0023] Figure 8 A schematic diagram of the sampling resistor and voltage conditioning circuit provided in the embodiments of this application;

[0024] Figure 9 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0025] Figure 10 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0026] Figure 11 A circuit structure diagram of an anomaly monitoring system provided in another embodiment of this application;

[0027] Figure 12 A schematic diagram of the circuit structure of the voltage detection circuit provided in the embodiments of this application;

[0028] Figure 13 A schematic diagram of the circuit structure of the anomaly monitoring system and the host computer provided in another embodiment of this application;

[0029] Figure 14 A flowchart illustrating an anomaly monitoring method provided in an embodiment of this application;

[0030] Figure 15 This is a schematic diagram of the structure of an anomaly monitoring device provided in an embodiment of this application;

[0031] Figure 16 This is a schematic diagram of the structure of a controller provided in an embodiment of this application. Detailed Implementation

[0032] To facilitate understanding of this application, a more detailed description is provided below with reference to the accompanying drawings and specific embodiments. It should be noted that when an element is described as being "fixed to" another element, it can be directly on the other element, or one or more intermediate elements may exist between them. When an element is described as being "electrically connected" to another element, it can be directly connected to the other element, or one or more intermediate elements may exist between them. The terms "upper," "lower," "inner," "outer," "bottom," etc., used in this specification indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0033] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items. Furthermore, technical features involved in the different embodiments of this application described below may be combined with each other as long as they do not conflict with each other.

[0034] The following embodiments of this application provide an anomaly monitoring system applied to a plasma etching machine. Please refer to... Figure 1 The plasma etching machine 200 is used to etch a substrate, and the anomaly monitoring system 300 is used to monitor the operating status of the coil that causes the plasma etching machine 200 to generate a magnetic field and the changes in the magnetic field of the plasma etching machine 200. It is understood that the plasma etching machine described in this embodiment can be a prior art plasma etching machine. However, the working principle of the anomaly monitoring system 300 provided in this embodiment is closely related to the product structure and principle of the plasma etching machine, and can cooperate with the plasma etching machine to monitor the operating status of the coil and the changes in the magnetic field of the plasma etching machine 200.

[0035] To facilitate understanding of the embodiments of this application, the plasma etching machine 200 is described in detail below. Please refer to... Figure 2 The plasma etching machine 200 includes a gas output module 21, an etching chamber 22, and an electrostatic chuck 23.

[0036] The gas output module 21 is configured to input gas into the gas inlet of the etching chamber 22. The gas output module 21 is located outside the plasma etching machine 200 and is connected to the gas inlet of the etching chamber 22 via a pipeline. The gas inlet of the etching chamber 22 is typically designed at the top of the etching chamber 22 to ensure that the gas can diffuse evenly throughout the entire etching chamber 22, cover the substrate surface, and then exit from the gas output port at the bottom. The gas output module 21 can output specific types of gas as needed, including CF4 gas, SF6 gas, CHF3 gas, etc.

[0037] An electrostatic chuck 23 is disposed at the bottom of the etching cavity 22 and is configured to hold the substrate 23a. The substrate can be a wafer, a display panel substrate, etc. After the substrate 23a is placed on the surface of the electrostatic chuck 23, the electrostatic chuck 23 firmly fixes the substrate 23a in place through electrostatic adsorption, preventing the substrate 23a from shifting or vibrating during the etching process.

[0038] Please see Figure 3 The abnormal monitoring system 300 includes a constant current source device 31, a coil 32, a coil detection circuit 33, and a controller 34.

[0039] The constant current source device 31 is configured to output a drive current according to preset etching process parameters. The constant current source device is an adjustable linear constant current power supply with an output current range of 0-25A, used to drive the coil 32 to generate a magnetic field, controlling the plasma ion density during the etching process. The etching process parameters include substrate material, etching pattern precision, and other parameters. Based on these parameters, the constant current source device 31 determines the corresponding drive current and transmits it to the coil 32 to drive it to generate a magnetic field.

[0040] Coil 32 is electrically connected to constant current source device 31 and is sleeved on etching cavity 22. Coil 32 is configured to generate a magnetic field within etching cavity 22 in response to the input of driving current, guiding the plasma inside etching cavity 22 towards the substrate for etching. It is understood that when coil 32 receives driving current, it can form a magnetic field of specific intensity and distribution within etching cavity 22. This magnetic field constrains and guides the ionized plasma within etching cavity 22, ensuring that active ions move precisely towards the target area on the substrate surface, thus guaranteeing the directionality and precision of etching.

[0041] The coil detection circuit 33 is electrically connected between the constant current source device 31 and the current loop of the coil 32, and is configured to detect the coil status data of the coil 32. The coil status data is used to describe the operating state of the coil 32, including the coil resistance of the coil 32, the magnitude of the current flowing through the coil 32, or the magnitude of the voltage applied across the coil 32.

[0042] The controller 34 is electrically connected to the constant current source device 31 and the coil detection circuit 33, respectively, and is configured to generate equipment maintenance information based on coil status data. The equipment maintenance information includes coil maintenance information or power supply maintenance information. Coil maintenance information indicates that coil 32 is malfunctioning and requires maintenance, while power supply maintenance information indicates that coil 32 does not require maintenance but other parts need maintenance, such as the constant current source device 31. When the coil status data indicates that the working state of coil 32 is abnormal, the controller 34 generates coil maintenance information. When the coil status data indicates that the working state of coil 32 is normal but the magnetic field within the etching cavity 22 is abnormal, the controller 34 generates power supply maintenance information. This embodiment monitors the working state of coil 32 through coil status data and reflects the actual situation of coil 32 through equipment maintenance information, allowing users to quickly determine whether coil 32 is in an abnormal state. This helps users quickly locate the maintenance direction and avoids wasting resources by disassembling and repairing coil 32 from the etching cavity 22 without discovering the malfunction.

[0043] It is understandable that the controller 34 can be integrated into the constant current source device 31 as a component of the constant current source device 31, or the controller 34 and the constant current source device 31 can be two independent components in parallel.

[0044] There are several reasons that can cause abnormal changes in the magnetic field of the etching cavity 22, including abnormalities in the coil 32, abnormal current output from the constant current source device 31, or other causes. In some scenarios, the coil 32 may function normally, but the magnetic field may still be abnormal. If the operating status of the coil 32 is monitored solely based on its coil status data, the user will not be promptly alerted to any abnormal magnetic field conditions. In other scenarios, if monitoring the operating status of the coil 32 based on its coil status data is not required, the user will need to sequentially check various devices along the etching process, leading to the technical problems described in the background section.

[0045] Based on this, the embodiments of this application can quickly locate whether the magnetic field abnormality is caused by coil 32 or by other non-coil factors.

[0046] Please see Figure 4 The anomaly monitoring system 300 also includes a magnetic field detection module 35, which is configured to collect emitted light from plasma at different locations to obtain spectral data.

[0047] In some embodiments, the magnetic field detection module 35 can be disposed on the top of the etching cavity 22 of the plasma etching machine 200, so as to avoid interfering with the plasma movement and etching process in the etching cavity 22, and to achieve detection by sensing changes in the magnetic field.

[0048] In some embodiments, the magnetic field detection module 35 can be disposed on the side wall of the etching cavity 22 of the plasma etching machine 200, so as to accurately collect the emitted light of the plasma.

[0049] Please see Figure 5 The magnetic field detection module 35 is a spectrometer 350, which is configured to collect emitted light from plasma at different locations to obtain spectral data. Multiple transparent windows 51 are provided on the sidewalls of the etching cavity 22 at different heights or circumferential positions, and / or multiple transparent windows are provided on the top or bottom of the etching cavity 22. The optical probe of the spectrometer 350 is positioned adjacent to the transparent windows. The transparent windows are made of crystalline materials such as KBr and ZnS that are resistant to etching and have good light transmittance.

[0050] Please see Figure 6 The spectrometer 350 includes an optical probe 351, a spectrometer module 352, and an optical signal processing module 353.

[0051] An optical probe 351 is used to collect emitted light generated by plasma at different locations in the etching cavity 22. The optical probe 351 includes a collection head and an optical fiber transmission assembly. The collection head is aligned with the transparent window of the etching cavity 22 to capture emitted light generated by plasma in a specific area and to converge the divergent emitted light into parallel light. The optical fiber transmission assembly is used to transmit the parallel light output from the collection head to the beam splitting module 352. The beam splitting module 352 is used to split the emitted light transmitted by the optical probe 351 according to wavelength order. An optical signal processing module 353 is used to process the split optical signal to obtain spectral data.

[0052] The magnetic field within the etching cavity 22 directly affects the distribution and activity of the plasma. The emission spectrum of the plasma is strongly correlated with its density and the concentration of active groups. When the magnetic field becomes abnormal, the state of the plasma changes, and the spectral data can reflect this change in state, thus indicating whether the magnetic field is abnormal. Spectral data includes parameters such as the intensity and peak position of characteristic spectral lines. For example, if the driving current of the coil is abnormal, the magnetic field weakens, plasma diffusion intensifies, and the intensity of characteristic spectral lines at relevant locations decreases. Furthermore, if the magnetic field is non-uniform, the difference in spectral intensity at different locations will increase.

[0053] The target anomaly type is determined based on coil status data and spectral data, and equipment maintenance information is generated based on the target anomaly type. The target anomaly type includes coil anomaly type or power supply anomaly type. The coil anomaly type indicates an abnormal operating state of coil 32, while the power supply anomaly type indicates that coil 32 is not abnormal but other components are malfunctioning. When the target anomaly type is coil anomaly type, the controller 34 generates coil maintenance information; when the target anomaly type is power supply anomaly type, the controller 34 generates power supply maintenance information.

[0054] This application embodiment, by fusing coil status data and spectral data, can promptly detect whether the magnetic field is abnormal, and when the magnetic field is abnormal, it can perform non-destructive inspection of whether the coil 32 is in an abnormal state without removing the coil 32 from the etching cavity 22. This helps to more accurately determine the magnetic field changes caused by non-coil factors.

[0055] When coil 32 malfunctions, its resistance deviates from the normal range, and its magnetic field also becomes abnormal. For example, coil 32 may age due to prolonged operation in a high-temperature environment, resulting in damaged turns and decreased energizing efficiency. When coil 32 is normal but the magnetic field is abnormal, it may indicate a malfunction in the constant current source device 31. Based on this characteristic, in some embodiments, determining the target anomaly type based on coil status data and spectral data includes: determining the coil resistance based on coil status data, generating a magnetic field strength distribution map based on spectral data, and determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map. The embodiments of this application combine the coil resistance of coil 32 and the magnetic field strength distribution map to generate the target anomaly type, which helps to reliably and accurately distinguish between magnetic field anomalies caused by coil 32 and those caused by non-coil factors.

[0056] The coil status data includes voltage sampling data and coil voltage data applied across the coil. The voltage sampling data is the voltage across the sampling resistor, which is the resistance through which the driving current flows through the coil; that is, the driving current flowing through the coil is equal to the current flowing through the sampling resistor. The coil voltage data is the voltage across the coil.

[0057] Please see Figure 7 The coil detection circuit 33 includes a sampling resistor 331, a voltage conditioning circuit 332, and a voltage detection circuit 333.

[0058] The sampling resistor 331 is electrically connected between the constant current source device 31 and the current loop of the coil 32, and is configured to generate a sampling voltage in response to the drive current flowing through the coil 32.

[0059] The voltage conditioning circuit 332 is electrically connected to the sampling resistor 331 and the controller 34 respectively, and is configured to perform signal conditioning processing on the sampled voltage to obtain voltage sampling data.

[0060] The voltage detection circuit 333 is electrically connected between the two ends of the coil 32 and to the controller 34, and is configured to detect the voltage applied to the two ends of the coil 32 to obtain coil voltage data.

[0061] Please see Figure 8 The sampling resistor 331 is the first resistor R1. The voltage conditioning circuit 332 includes a second resistor R2, a third resistor R3, a fourth resistor R4, a fifth resistor R5, a sixth resistor R6, a seventh resistor R7, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, and a first operational amplifier U1. The first resistor R1 is electrically connected between the constant current source device 31 and the current loop of the coil 32. The first end of the second resistor R2 is electrically connected to the first end of the first resistor R1. The first end of the third resistor R3 is electrically connected to the second end of the first resistor R1. The second end of the second resistor R2 is electrically connected to the first end of the first capacitor C1 and the first end of the fourth resistor R4, respectively. The second end of the third resistor R3 is electrically connected to the second end of the first capacitor C1 and the first end of the fifth resistor R5, respectively. The second end of the fourth resistor R4 is connected to the first input terminal of the first operational amplifier U1 and the first end of the second capacitor C2, respectively. Electrically connected, the second end of the fifth resistor R5 is electrically connected to the second input terminal of the first operational amplifier U1 and the second end of the second capacitor C2. The sixth resistor R6 is electrically connected between the third and fourth input terminals of the first operational amplifier U1. The output terminal of the first operational amplifier U1 is electrically connected to the first end of the seventh resistor R7. The second end of the seventh resistor R7 is electrically connected to the first end of the third capacitor C3 and the controller 34. The second end of the third capacitor C3 is grounded. The positive power supply terminal of the first operational amplifier U1 is electrically connected to the first end of the fourth capacitor C4 and is subjected to a preset voltage value. The second end of the fourth capacitor C4 is grounded. The preset voltage can be any value between 18V and 28V.

[0062] exist Figure 8 In the middle, coil 32 is electrically connected to constant current source device 31 through coil connector 36.

[0063] The drive current output by the constant current source device 31 is transmitted to the coil 32 through the first resistor R1. The voltage across the first resistor R1 (i.e. the sampling voltage) is applied to the first operational amplifier U1 through the second resistor R2, the third resistor R3, the fourth resistor R4, and the fifth resistor R5. The first operational amplifier U1 amplifies the voltage across the first resistor R1 to obtain voltage sampling data.

[0064] Please see Figure 9The coil detection circuit 33 also includes a current switching circuit 334, which is electrically connected between the constant current source device 31 and the current loop of the coil 32 and is electrically connected to the controller 34. It is configured to switch the current direction of the drive current flowing through the coil 32 so that the coil 32 generates a magnetic field.

[0065] Please combine Figure 8 The current switching circuit 334 includes a first relay K1, a first freewheeling diode D1, a second relay K2, and a second freewheeling diode D2. The first relay K1 includes a first actuator and a first relay coil, coupled together. The first terminal of the first actuator is electrically connected to the constant current source device 31, and the second terminal of the first actuator can be electrically connected to either the first or second terminal of the coil 32. The first actuator, influenced by the magnetic field of the first relay coil, can switch between being electrically connected to either the first or second terminal of the coil 32. The first freewheeling diode D1 is electrically connected across the two ends of the first relay coil. The second relay K2 includes a second actuator and a second relay coil, coupled together. The first terminal of the second actuator can be electrically connected to either the first or second terminal of the coil 32, and the second terminal of the second actuator is grounded. The second actuator, influenced by the magnetic field of the second relay coil, can switch between being electrically connected to either the first or second terminal of the coil 32. The second freewheeling diode D2 is electrically connected across the two ends of the second relay coil.

[0066] When the controller 34 applies a low level to the first relay K1 and the second relay K2, the first relay K1 and the second relay K2 are not energized. The first end of the first actuator is electrically connected to the first end of the coil 32, and the first end of the second actuator is electrically connected to the second end of the coil 32. The direction of the driving current flowing through the coil 32 is clockwise.

[0067] When the controller 34 applies a high-level signal to the first relay K1 and the second relay K2, the first relay K1 and the second relay K2 are energized, causing the first actuator and the second actuator to operate. This results in the first terminal of the first actuator being electrically connected to the second terminal of the coil 32, and the first terminal of the second actuator being electrically connected to the first terminal of the coil 32. The direction of the drive current flowing through the coil 32 is counterclockwise. When the controller 34 stops applying a high-level signal to the first relay K1 and the second relay K2, the first relay K1 continues to flow through the first freewheeling diode D1, and the second relay K2 continues to flow through the second freewheeling diode D2.

[0068] Please see Figure 10The coil detection circuit 33 also includes a voltage regulator circuit 335 and a filter circuit 336. The voltage regulator circuit 335 is electrically connected across the two ends of the coil 32 and is configured to regulate the voltage applied across the two ends of the coil 32. The filter circuit 336 is electrically connected between the constant current source device 31 and the current loop of the coil 32 and is configured to filter the drive current flowing through the coil 32.

[0069] The voltage regulator circuit 335 includes a first voltage regulator diode ZD1 and a second voltage regulator diode ZD2, and the filter circuit 336 includes a fifth capacitor C5, a sixth capacitor C6, a seventh capacitor C7, an eighth capacitor C8, a ninth capacitor C9, a tenth capacitor C10, an eleventh capacitor C11, a twelfth capacitor C12, and a thirteenth capacitor C13.

[0070] The anode of the first Zener diode ZD1 is electrically connected to the anode of the second Zener diode ZD2, the cathode of the first Zener diode ZD1 is electrically connected to the first end of the coil 32, and the cathode of the second Zener diode ZD2 is electrically connected to the second end of the coil 32.

[0071] The fifth capacitor C5, the sixth capacitor C6, the seventh capacitor C7, the eighth capacitor C8, the ninth capacitor C9, the tenth capacitor C10, the eleventh capacitor C11, the twelfth capacitor C12, and the thirteenth capacitor C13 are connected in parallel across the two ends of coil 32.

[0072] When the direction of the driving current is clockwise and the voltage applied across the coil 32 is greater than the voltage regulation threshold of the first Zener diode ZD1, the first Zener diode ZD1 is reverse-broken down, thereby clamping the voltage across the coil 32 within the normal voltage range and preventing the coil 32 from being subjected to excessive voltage.

[0073] When the direction of the driving current is counterclockwise and the voltage applied across the coil 32 is greater than the voltage regulation threshold of the second Zener diode ZD2, the second Zener diode ZD2 is reverse-broken down, thereby clamping the voltage across the coil 32 within the normal voltage range and preventing the coil 32 from being subjected to excessive voltage.

[0074] Please see Figure 11 The voltage detection circuit 333 includes a first-stage voltage amplifier circuit 337 and a final-stage voltage amplifier circuit 338 connected in series. The first-stage voltage amplifier circuit 337 is electrically connected between the two ends of the coil 32 to amplify the voltage across the coil 32. The final-stage voltage amplifier circuit 338 is electrically connected to the controller 34 and is used to output coil voltage data. This embodiment of the application samples and amplifies the voltage across the coil 32 to filter out noise interference, so that the controller 34 can obtain accurate and reliable coil voltage data.

[0075] Please see Figure 12The first-stage voltage amplifier circuit 337 includes an eighth resistor R8, a ninth resistor R9, a tenth resistor R10, an eleventh resistor R11, a fourteenth capacitor C14, and a second operational amplifier U2. The first end of the eighth resistor R8 is electrically connected to the first end of the coil 32. The second end of the eighth resistor R8 is electrically connected to the first end of the ninth resistor R9 and the first input terminal of the second operational amplifier U2. The second end of the ninth resistor R9 is grounded. The first end of the tenth resistor R10 is grounded. The second end of the tenth resistor R10 is electrically connected to the first end of the eleventh resistor R11 and the second input terminal of the second operational amplifier U2. The second end of the eleventh resistor R11 is electrically connected to the output terminal of the second operational amplifier U2. The first end of the fourteenth capacitor C14 is applied with a 5V voltage and is electrically connected to the first power supply terminal of the second operational amplifier U2. The second end of the fourteenth capacitor C14 is grounded. The second power supply terminal of the second operational amplifier U2 is grounded.

[0076] The final stage voltage amplifier circuit 338 includes a twelfth resistor R12, a thirteenth resistor R13, a fourteenth resistor R14, a fifteenth resistor R15, and a third operational amplifier U3. The first terminals of the twelfth resistor R12 and the thirteenth resistor R13 are electrically connected to the output terminal of the second operational amplifier U2. The second terminal of the twelfth resistor R12 is grounded. The second terminal of the thirteenth resistor R13 is electrically connected to the first input terminal of the third operational amplifier U3. The second input terminal of the third operational amplifier U3 is electrically connected to the first terminal of the fourteenth resistor R14. The second terminal of the fourteenth resistor R14 is electrically connected to both the output terminal of the third operational amplifier U3 and the first terminal of the fifteenth resistor R15. The second terminal of the fifteenth resistor R15 is grounded.

[0077] The voltage across coil 32 is sampled by resistors R8 and R9, and then amplified in phase by op-amps U2 and U3 to obtain the coil voltage data.

[0078] The controller 34 determines the coil current flowing through the coil 32 based on the voltage sampling data and the preset resistance value, and calculates the coil resistance of the coil 32 based on the coil current and coil voltage data. For example, the voltage sampling data is the voltage across the sampling resistor 331, the preset resistance value is the resistance value of the sampling resistor 331, the drive current flowing through the sampling resistor 331 is equal to the drive current flowing through the coil 32, and the coil resistance of the coil 32 is obtained by dividing the voltage sampling data by the preset resistance value.

[0079] The controller 34 compares the coil resistance of the coil 32 with the normal resistance range. When the coil resistance is within the normal resistance range, the coil 32 is not abnormal. When the coil resistance is not within the normal resistance range, the coil 32 is abnormal.

[0080] Generating a magnetic field intensity distribution map based on spectral data includes the following steps: determining the splitting pattern of the target spectral line based on the spectral data, determining the wavelength difference of the target spectral line under the splitting pattern, determining the magnetic field intensity at the target location based on the Zeeman effect formula and the wavelength difference, and combining the magnetic field intensities at different target locations to obtain a magnetic field intensity distribution map.

[0081] According to the Zeeman effect, when a light source is in a magnetic field, a single spectral line emitted by an atom will split into multiple polarized spectral lines. In a plasma etching cavity scenario, plasma emission produces a corresponding spectrum. After the magnetic field detection module 35 acquires the spectral data, the controller 34 filters out target spectral lines that are sensitive to changes in the magnetic field. For example, it selects the spectral lines of specific atoms or ions in the plasma as target spectral lines, such as ArI at 750.4 nm. The controller 34 determines the splitting pattern of the target spectral lines based on the number of spectral lines and their polarization characteristics. For example, under a longitudinal magnetic field (i.e., a magnetic field parallel to the observation direction), the spectral line splits into two circularly polarized branches, one left-handed and one right-handed; under a transverse magnetic field (i.e., a magnetic field perpendicular to the observation direction), the spectral line splits into a single linearly polarized main line in the middle and two linearly polarized branches on either side.

[0082] After the target spectral line splits, there is a fixed wavelength interval (i.e., wavelength difference) between the different branches, and this wavelength difference is positively correlated with the magnetic field strength. The controller 34 calculates the difference between the wavelength of each branch after splitting and the wavelength of the target spectral line through wavelength calibration of the spectral data. For example, the wavelength of the target spectral line is... After splitting, it forms a first branch and a second branch. The wavelength of the first branch is... The wavelength of the second branch The first wavelength difference is The difference in the second wavelength is .

[0083] According to the Zeeman effect formula, the energy level has an additional energy. , , For Bohr magneton, It is the magnetic quantum number. For Landes factor, The magnetic field strength, is Planck's constant. At the speed of light, λ is the wavelength of the target spectral line, and i is the branch number.

[0084] The controller 34 obtains the additional energy of the first energy level of the first branch based on the first wavelength difference, the wavelength of the target spectral line, Planck's constant, and the speed of light. The controller 34 also obtains the wavelength, Planck's constant, and speed of light at the target location based on the additional energy of the first energy level, the Bohr magneton, the magnetic quantum number, and the Landé factor, and thus obtains the additional energy of the second energy level of the second branch. In this embodiment, the second magnetic field strength at the target location is obtained based on the additional energy of the second energy level, the Bohr magneton, the magnetic quantum number, and the Landé factor.

[0085] The controller 34 calculates the average of the first magnetic field strength and the second magnetic field strength to obtain the final magnetic field strength at the target location. The controller 34 combines the magnetic field strengths at different target locations to obtain a magnetic field strength distribution map.

[0086] The controller 34 is pre-configured with a reference magnetic field distribution map. It compares the reference magnetic field distribution map with the magnetic field intensity distribution map. If the magnetic field intensity distribution map does not match the reference magnetic field distribution map, it is determined that the magnetic field intensity distribution map is abnormal. Figure 1 If the result is consistent, then it can be determined that there are no abnormalities in the magnetic field intensity distribution map.

[0087] The etching cavity contains several critical locations that affect the process, including the substrate center, 1 cm from the substrate edge, and the center of the plasma reaction zone. The controller 34 acquires the target magnetic field intensity at these critical locations from the magnetic field intensity distribution map and the reference magnetic field intensity from the reference magnetic field distribution map. It calculates a first magnetic field intensity difference between the target and reference magnetic field intensities. If this first difference is greater than a first preset difference, the magnetic field intensity distribution map is determined to be inconsistent with the reference magnetic field distribution map. If this first difference is less than the first preset difference, the controller 34 averages the magnetic field intensity at all target locations based on the magnetic field intensity distribution map to obtain a global average real-time magnetic field. It then averages the magnetic field intensity at all target locations based on the reference magnetic field distribution map to obtain a global average reference magnetic field. Finally, it calculates a second magnetic field intensity difference between the global average real-time magnetic field and the global average reference magnetic field. If this second difference is greater than a second preset difference, the magnetic field intensity distribution map is determined to be inconsistent with the reference magnetic field distribution map. If this second difference is less than the second preset difference, the magnetic field intensity distribution map is determined to be inconsistent with the reference magnetic field distribution map. Figure 1 To.

[0088] In some embodiments, determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map includes: determining the target anomaly type as a power supply anomaly type in response to an anomaly in the magnetic field strength distribution map and the coil resistance being within the normal resistance range; and determining the target anomaly type as a coil anomaly type in response to an anomaly in the magnetic field strength distribution map and the coil resistance being outside the normal resistance range.

[0089] The controller 34 generates coil maintenance information in response to the target abnormality type being a coil abnormality type, or the controller 34 generates power maintenance information in response to the target abnormality type being a power supply abnormality type.

[0090] It is understandable that when the magnetic field strength distribution diagram is abnormal and the coil resistance is not within the normal resistance range, this embodiment of the application can at least determine that the coil 32 is in an abnormal state. However, it is also possible for both the coil 32 and the constant current source device 31 to malfunction simultaneously. Typically, in this situation, maintenance personnel first repair the coil 32, and after the coil 32 is repaired, they re-run the anomaly monitoring system. At this time, if the constant current source device 31 malfunctions, and the anomaly monitoring system detects an abnormal magnetic field strength distribution diagram, but the coil resistance is within the normal resistance range, maintenance personnel can repair the constant current source device 31. Therefore, the anomaly monitoring system provided in this embodiment of the application can still monitor both the coil 32 and the constant current source device 31 for anomalies, providing maintenance personnel with accurate anomaly source information.

[0091] Please see Figure 13 When the controller 34 detects an abnormality in the magnetic field strength distribution map, it controls the constant current source device 31 to stop working and uploads the equipment maintenance information to the host computer 37. This can prompt the user that the plasma etching machine 200 needs to be shut down for maintenance, and can also indicate to the user whether the specific source of the fault is the coil 32, the constant current source device 31, or other places.

[0092] As another aspect of this application, this application provides an anomaly monitoring method applied to the controller of the anomaly monitoring system described in the above embodiments. Please refer to... Figure 14 The anomaly monitoring method includes the following steps:

[0093] Step S141: Obtain the coil status data output by the coil detection circuit.

[0094] Step S142: Generate equipment maintenance information based on coil status data.

[0095] In some embodiments, generating equipment maintenance information based on coil status data includes the following steps: acquiring spectral data collected by the magnetic field detection module, determining the target anomaly type based on the coil status data and the spectral data, and generating equipment maintenance information based on the target anomaly type.

[0096] In some embodiments, determining the target anomaly type based on coil state data and spectral data includes: determining the coil resistance based on coil state data, generating a magnetic field strength distribution map based on spectral data, and determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map.

[0097] In some embodiments, the target anomaly type includes a coil anomaly type or a power supply anomaly type. Determining the target anomaly type based on the coil resistance and magnetic field strength distribution map includes: determining the target anomaly type as a power supply anomaly type in response to an anomaly in the magnetic field strength distribution map and the coil resistance being within the normal resistance range; and determining the target anomaly type as a coil anomaly type in response to an anomaly in the magnetic field strength distribution map and the coil resistance being outside the normal resistance range.

[0098] In some embodiments, the coil state data includes voltage sampling data and coil voltage data applied across the coil. Determining the coil resistance based on the coil state data includes: determining the coil current flowing through the coil based on the voltage sampling data and a preset resistance value, and calculating the coil resistance based on the coil current and coil voltage data.

[0099] In some embodiments, generating a magnetic field intensity distribution map based on spectral data includes: determining the splitting pattern of the target spectral line based on the spectral data, determining the wavelength difference of the target spectral line under the splitting pattern, determining the magnetic field intensity at the target location based on the Zeeman effect formula and the wavelength difference, and combining the magnetic field intensities at different target locations to obtain a magnetic field intensity distribution map.

[0100] In some embodiments, the target anomaly type includes a coil anomaly type or a power supply anomaly type, and the equipment maintenance information includes coil maintenance information or power supply maintenance information. Generating equipment maintenance information based on the target anomaly type includes: generating coil maintenance information in response to the target anomaly type being a coil anomaly type, and generating power supply maintenance information in response to the target anomaly type being a power supply anomaly type.

[0101] It should be noted that in the above embodiments, there is no necessarily a certain order between the steps. Those skilled in the art can understand from the description of the embodiments of this application that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0102] As another aspect of the embodiments of this application, this application provides an anomaly monitoring device. The anomaly monitoring device can be a software module, which includes several instructions stored in a memory. A processor can access the memory and execute the instructions to complete the anomaly monitoring methods described in the various embodiments above.

[0103] In some implementations, the anomaly monitoring device can also be constructed from hardware components. For example, the anomaly monitoring device can be constructed from one or more chips, which can work in coordination to complete the anomaly monitoring methods described in the various implementations above. As another example, the anomaly monitoring device can also be constructed from various logic devices, such as general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), microcontrollers, ARM (Acorn RISC Machine) or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination of these components.

[0104] Please see Figure 15 The anomaly monitoring device 150 includes a data acquisition module 151 and a maintenance determination module 152. The data acquisition module 151 is used to acquire coil status data output by the coil detection circuit. The maintenance determination module 152 is used to generate equipment maintenance information based on the coil status data.

[0105] In some embodiments, the maintenance determination module 152 is specifically used to: acquire spectral data collected by the magnetic field detection module, determine the target anomaly type based on the coil status data and the spectral data, and generate equipment maintenance information based on the target anomaly type.

[0106] In some embodiments, the inspection determination module 152 is specifically used to: determine the coil resistance based on coil status data, generate a magnetic field strength distribution map based on spectral data, and determine the target anomaly type based on the coil resistance and the magnetic field strength distribution map.

[0107] In some embodiments, the target anomaly type includes a coil anomaly type or a power supply anomaly type. The troubleshooting determination module 152 is specifically used to: determine the target anomaly type as a power supply anomaly type in response to an anomaly in the magnetic field strength distribution diagram and the coil resistance being within the normal resistance range; and determine the target anomaly type as a coil anomaly type in response to an anomaly in the magnetic field strength distribution diagram and the coil resistance being outside the normal resistance range.

[0108] In some embodiments, the coil state data includes voltage sampling data and coil voltage data applied across the coil. The maintenance determination module 152 is specifically used to: determine the coil current flowing through the coil based on the voltage sampling data and a preset resistance value, and calculate the coil resistance based on the coil current and coil voltage data.

[0109] In some embodiments, the inspection determination module 152 is specifically used to: determine the splitting pattern of the target spectral line based on spectral data, determine the wavelength difference of the target spectral line under the splitting pattern, determine the magnetic field strength at the target location based on the Zeeman effect formula and the wavelength difference, and combine the magnetic field strength at different target locations to obtain a magnetic field strength distribution map.

[0110] In some embodiments, the target anomaly type includes a coil anomaly type or a power supply anomaly type, and the equipment maintenance information includes coil maintenance information or power supply maintenance information. The maintenance determination module 152 is specifically used to: generate coil maintenance information in response to the target anomaly type being a coil anomaly type, and generate power supply maintenance information in response to the target anomaly type being a power supply anomaly type.

[0111] It should be noted that the above-mentioned anomaly monitoring device can execute the anomaly monitoring method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects of the method. Technical details not described in detail in the embodiments of the anomaly monitoring device can be found in the anomaly monitoring method provided in the embodiments of this application.

[0112] See Figure 16 , Figure 16 This is a schematic diagram of a controller provided in an embodiment of this application. The controller 160 includes one or more processors 161 and a memory 162. The memory 162 is connected to one or more processors 161, for example, via a bus.

[0113] Processor 161 is configured to support the controller in performing the corresponding functions in the methods described in the above method embodiments. The processor may be a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof. The aforementioned hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0114] Memory 162 is used to store program code, etc. Memory may include volatile memory (VM), such as random access memory (RAM); memory may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); memory may also include combinations of the above types of memory.

[0115] The memory 162 can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the anomaly monitoring method in the embodiments of this application. The processor executes various functional applications and data processing of the anomaly monitoring method and anomaly monitoring device by running the non-volatile software programs, instructions, and modules stored in the memory, thereby realizing the functions of each module or unit of the anomaly monitoring method and anomaly monitoring device provided in the above method embodiments.

[0116] The memory 162 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function. The data storage area may store data created based on the use of the anomaly monitoring device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the anomaly monitoring device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0117] The one or more modules are stored in the memory. When executed by the one or more processors, they perform the exception monitoring method in any of the above method embodiments. For example, they perform the method steps described in the above method embodiments to realize the functions of the modules described in the above device embodiments.

[0118] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a controller, cause the controller to perform the method described in the foregoing embodiments.

[0119] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0120] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. An anomaly monitoring system for a plasma etching machine, the plasma etching machine comprising a gas output module, an etching chamber, and an electrostatic chuck, the electrostatic chuck being disposed at the bottom of the etching chamber and configured to hold a substrate, characterized in that, The anomaly monitoring system includes: The constant current source device is configured to output drive current according to preset etching process parameters; A coil, electrically connected to the constant current source device, is configured to generate a magnetic field within the etching cavity in response to the input of the drive current to guide the plasma inside the etching cavity toward the substrate to etch the substrate. A coil detection circuit, electrically connected between the constant current source device and the current loop of the coil, is configured to detect the coil state data of the coil; The controller is electrically connected to the constant current source device and the coil detection circuit, respectively, and is configured to generate equipment maintenance information based on the coil status data. A magnetic field detection module is configured to collect emitted light from plasma at different locations to obtain spectral data. The step of generating equipment maintenance information based on the coil status data includes: determining the coil resistance based on the coil status data; generating a magnetic field strength distribution map based on the spectral data; determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map; and generating equipment maintenance information based on the target anomaly type. The magnetic field detection module includes a spectrometer. Multiple transparent windows are provided at the top or bottom of the etching cavity. The optical probe of the spectrometer is positioned adjacent to the transparent windows to collect emitted light from plasma at different locations to obtain spectral data. The step of determining the target anomaly type based on the coil resistance and the magnetic field strength distribution map includes: in response to an anomaly in the magnetic field strength distribution map and the coil resistance being within the normal resistance range, determining the target anomaly type as a power supply anomaly type; and in response to an anomaly in the magnetic field strength distribution map and the coil resistance being outside the normal resistance range, determining the target anomaly type as a coil anomaly type. The target anomaly type includes a coil anomaly type or a power supply anomaly type, and the equipment maintenance information includes coil maintenance information or power supply maintenance information. The step of generating equipment maintenance information based on the target anomaly type includes: generating coil maintenance information in response to the target anomaly type being a coil anomaly type; and generating power supply maintenance information in response to the target anomaly type being a power supply anomaly type.

2. The anomaly monitoring system according to claim 1, characterized in that, The coil state data includes voltage sampling data and coil voltage data applied across the coil. Determining the coil resistance based on the coil state data includes: The coil current flowing through the coil is determined based on the voltage sampling data and the preset resistance value; The coil resistance is calculated based on the coil current and coil voltage data.

3. The anomaly monitoring system according to claim 1, characterized in that, The generation of the magnetic field intensity distribution map based on the spectral data includes: The splitting morphology of the target spectral line is determined based on the spectral data; Determine the wavelength difference of the target spectral line under the splitting morphology; The magnetic field strength at the target location is determined based on the Zeeman effect formula and the wavelength difference. By combining the magnetic field strength at different target locations, a magnetic field strength distribution map is obtained.

4. The anomaly monitoring system according to claim 1, characterized in that, The coil state data includes voltage sampling data and coil voltage data applied across the coil terminals. The coil detection circuit includes: A sampling resistor, electrically connected between the constant current source device and the current loop of the coil, is configured to generate a sampling voltage in response to the drive current flowing through the coil; A voltage conditioning circuit, electrically connected to the sampling resistor and the controller respectively, is configured to perform signal conditioning processing on the sampled voltage to obtain voltage sampling data; A voltage detection circuit, electrically connected between the two ends of the coil and to the controller, is configured to detect the voltage applied across the two ends of the coil to obtain coil voltage data.

5. The anomaly monitoring system according to claim 4, characterized in that, The voltage detection circuit includes a first-stage voltage amplifier circuit and a final-stage voltage amplifier circuit connected in series. The first-stage voltage amplifier circuit is electrically connected between the two ends of the coil to amplify the voltage across the coil. The final-stage voltage amplifier circuit is electrically connected to the controller to output coil voltage data.

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