Image calibration method of electron beam device, electron beam device and storage medium

Abstract

This invention provides an image calibration method for an electron beam device, the electron beam device itself, and a storage medium. The image calibration method includes: real-time acquisition of scene parameters of the electron beam device, including beam energy parameters and field-of-view parameters; determination of collaborative calibration parameters for multiple modules of the electron beam device according to a preset mapping table, the mapping table pre-stores collaborative calibration parameters corresponding to different combinations of beam energy parameters and field-of-view parameters; synchronous adjustment of multiple modules based on the collaborative calibration parameters; and calibration verification of the images acquired by the electron beam device, and further adjustment of multiple modules based on the verification results. This invention, through multi-module collaborative calibration, significantly improves the image resolution of the electron beam device, reduces distortion and glitches, and optimizes the overall imaging quality; through adaptive adjustment and fluctuation compensation, it greatly improves calibration efficiency and long-term stability, ensuring consistent calibration results under different scenarios.

Description

Technical Field

[0001] This invention relates to the field of semiconductor technology, and in particular to an image calibration method for an electron beam device, an electron beam device, and a computer-readable storage medium. Background Technology

[0002] Electron beam (EBEAM) equipment, with its advantages of high resolution and high precision, is widely used in the inspection and processing of semiconductors, micro-devices, and other fields. The image quality directly determines the reliability of the inspection results and the processing accuracy. The image formation process of EBEAM equipment involves multiple core modules such as pixel size, dynamic focusing, scanning waveform, and signal acquisition. The parameters of each module are interrelated and affect each other. Deviation in any module parameter will lead to problems such as blurring, distortion, burrs, and dimensional deviations in the image.

[0003] Current EBEAM equipment image calibration mostly adopts a single-module independent calibration mode, such as performing pixel size calibration, focus calibration, or waveform calibration separately, without forming a complete, multi-module overall calibration system. Existing technologies often fall into the following categories: Patent US17 / 728691 focuses only on detector structure optimization, aiming to balance large FOV (Field of View) and large beam current, without involving any image calibration-related design, let alone the technical logic of overall calibration; Patent TW1695407B only calibrates the single module of dynamic focusing, without considering the synergistic effects of other core modules such as pixel size and scanning waveform, and cannot achieve overall image quality optimization; other related technologies only focus on signal acquisition and optical structure optimization, similarly without designing any overall image calibration system.

[0004] In summary, existing technologies in the industry all have limitations, focusing only on calibration of a single module or a subset of modules without considering the synergistic effects between modules, thus failing to fundamentally solve the problem of poor overall image quality. As industries such as semiconductors develop towards greater precision and scale, the requirements for image quality in EBEAM devices are constantly increasing. Single-module calibration can no longer meet the calibration needs of all scenarios and high precision; the lack of overall image calibration has become a key bottleneck restricting the performance improvement of EBEAM devices. Existing technologies mainly suffer from the following specific shortcomings: First, the calibration mode is singular and lacks overall coordination: Existing solutions all use independent calibration of a single module, without considering the parameter correlation between modules such as pixel size, dynamic focusing, and scanning waveform. After calibration, the parameters of each module are not matched, which will still lead to overall image distortion and insufficient accuracy, and cannot achieve accurate calibration of the entire image process.

[0005] Second, the existing calibration schemes are poor in terms of scene adaptability and have low calibration efficiency. Most of the existing calibration schemes are fixed parameter calibrations, which cannot adaptively adjust the calibration parameters according to the dynamic switching of field of view and lower energy (LE). They require frequent manual adjustments, which are cumbersome, time-consuming, and prone to human error.

[0006] Third, there is no unified calibration benchmark and the consistency is poor: different modules use different calibration standards and no unified overall image calibration benchmark has been established, which leads to inconsistent calibration results in different batches and different scenarios. The detection / processing data cannot be unified, which affects product quality control.

[0007] Fourth, the anti-interference ability is weak and the calibration stability is poor: the existing calibration scheme does not have a complete fluctuation compensation mechanism. Affected by the fluctuation of ambient temperature and beam intensity, the calibration parameters are prone to drift. After long-term operation, the image quality deteriorates and repeated recalibration is required, which increases the operation and maintenance costs.

[0008] In summary, existing EBEAM image calibration technologies mostly focus on optimizing a single module and do not design a collaborative calibration mechanism for the overall image quality. They cannot simultaneously solve the four core problems of image distortion, insufficient accuracy, poor consistency, and low calibration efficiency, making it difficult to meet the needs of high-end precision testing. Summary of the Invention

[0009] One objective of this invention is to address the problem that existing electron beam equipment image calibration only adjusts a single module independently and lacks overall coordination, resulting in image distortion, insufficient accuracy, and poor consistency.

[0010] A further objective of this invention is to address the industry pain points of poor adaptability to calibration scenarios, reliance on manual debugging, susceptibility to environmental and beam fluctuations, and insufficient long-term stability.

[0011] Specifically, the present invention provides an image calibration method for an electron beam device, comprising: acquiring scene parameters of the electron beam device in real time, the scene parameters including beam energy parameters and field of view parameters; determining collaborative calibration parameters of multiple modules of the electron beam device according to a preset mapping table, the mapping table pre-stores collaborative calibration parameters corresponding to combinations of different beam energy parameters and field of view parameters; performing synchronous adjustment on multiple modules according to the collaborative calibration parameters; and calibrating and verifying the image acquired by the electron beam device, and further adjusting multiple modules based on the verification results.

[0012] Optionally, the multiple modules include a scanning module, a focusing module, and a waveform amplification module; the step of performing synchronous adjustment on the multiple modules includes: adjusting the scanning module to match the image pixel size corresponding to the current field of view and beam energy; adjusting the focusing module to achieve clear focusing of the electron beam; and adjusting the waveform amplification module to correct electron beam scanning distortion.

[0013] Optionally, the mapping table establishes a mapping relationship between the combination of beam energy parameters and field of view parameters and the co-calibration parameters based on a unified image reference; the unified image reference includes resolution, distortion rate, spurious ratio, and calibration consistency deviation.

[0014] Optionally, the scene parameters also include environmental fluctuation parameters and beam intensity fluctuation parameters; the steps of further adjusting multiple modules based on the verification results include: when the acquired images reach a unified image benchmark, dynamically compensating the collaborative calibration parameters according to the environmental fluctuation parameters and beam intensity fluctuation parameters.

[0015] Optionally, the steps for further adjusting multiple modules based on the verification results include: if the acquired images do not meet the unified image benchmark, re-execute the steps of determining the collaborative calibration parameters and synchronously adjusting multiple modules, and record the number of times the benchmark is not met.

[0016] Optionally, if the number of times the standard is not met is greater than or equal to a preset threshold, an alarm signal is output and fault information is recorded.

[0017] Optionally, the overall calibration process can be automatically executed according to a preset cycle, and / or the overall calibration process can be automatically started when scene parameters are switched.

[0018] Optionally, in addition to performing the overall calibration process according to a preset cycle, the process may also include: recording calibration data during the calibration process and forming a calibration log for calibration traceability and optimization.

[0019] According to another aspect of the present invention, an electron beam device is also provided, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the image calibration method of the electron beam device described above.

[0020] According to another aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the image calibration method of any of the above-described electron beam devices.

[0021] The image calibration method for electron beam equipment of the present invention significantly improves the overall image quality of electron beam equipment through multi-module collaborative calibration and unified benchmark control, achieving lower distortion, fewer burrs, and higher resolution, and fundamentally eliminating imaging defects caused by parameter mismatch.

[0022] Furthermore, the image calibration method for the electron beam equipment of the present invention, relying on full-scene adaptive adjustment and real-time fluctuation compensation, significantly shortens the calibration time, improves the long-term operational stability and result consistency of the equipment, reduces manual intervention and maintenance costs, and meets the stable and reliable requirements of high-end precision testing and processing.

[0023] The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0024] The following sections will describe some specific embodiments of the invention in detail by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or portions. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 This is a schematic flowchart of an image calibration method for an electron beam device according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the overall architecture of an image calibration method for an electron beam device according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a computer program product according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a computer-readable storage medium according to an embodiment of the present invention; and Figure 5 This is a schematic diagram of an electron beam device according to an embodiment of the present invention. Detailed Implementation

[0025] This embodiment provides an image calibration method for electron beam equipment. Through multi-module collaborative calibration, it significantly improves the image resolution of electron beam equipment, reduces distortion and glitches, and optimizes the overall imaging quality. Through adaptive adjustment and fluctuation compensation, it greatly improves calibration efficiency and long-term stability, ensuring consistent calibration results under different scenarios. Figure 1 This is a schematic flowchart of an image calibration method for an electron beam device according to an embodiment of the present invention. Figure 1 As shown, the image calibration method of the electron beam device in this embodiment generally includes: Step S102: Real-time acquisition of scene parameters of the electron beam device, including beam energy parameters and field of view parameters; Step S104: Determine the collaborative calibration parameters of multiple modules of the electron beam device according to the preset mapping table. The mapping table stores the collaborative calibration parameters corresponding to combinations of different beam energy parameters and field parameters in advance. Step S106: Perform synchronous adjustment on multiple modules according to the collaborative calibration parameters; Step S108: The image acquired by the electron beam device is calibrated and verified, and multiple modules are further adjusted based on the verification results.

[0026] In the above steps, the beam energy parameter in step S102 refers to the electron beam accelerating voltage / beam energy level, which determines the electron beam penetration depth, focusing characteristics, scanning speed, and signal strength. It is a core condition affecting image clarity, resolution, and distortion. The field of view parameter refers to the size of the area covered by a single electron beam scan, determining the image field of view size, number of pixels, and scanning step size, and is directly related to pixel size and scanning waveform parameters. The beam energy parameter and field of view parameter together determine the working scenario of electron beam imaging and are the input conditions for overall calibration.

[0027] The multiple modules in step S104 may include a scanning module, a focusing module, and a waveform amplification module. Furthermore, the step S106, which performs synchronous adjustment of the multiple modules, may include: adjusting the scanning module to match the image pixel size corresponding to the current field of view and beam energy; adjusting the focusing module to achieve clear electron beam focusing; and adjusting the waveform amplification module to correct electron beam scanning distortion. The collaborative calibration parameters for the multiple modules are a set of parameters for synchronous matching of the multiple modules, and may include: pixel size parameters, dynamic focusing parameters (focusing current / focusing voltage), scanning waveform parameters (scanning amplification voltage, scanning offset, scanning linearity), and signal acquisition gain / compensation parameters. This embodiment synchronously adjusts and matches these parameters to achieve overall image calibration.

[0028] The mapping table in step S104 establishes a mapping relationship between the combination of beam energy parameters, field of view parameters, and co-calibration parameters based on a unified image reference. In a specific embodiment, the unified image reference may include resolution, distortion rate, glitch ratio, and calibration consistency deviation. Regarding the correlation between beam energy, field of view, and co-calibration parameters, generally, as beam energy increases, the electron beam velocity increases and the focusing depth changes; it is necessary to increase the focusing voltage / current, adjust the scanning waveform amplification factor, and match the corresponding pixel size. As the field of view increases, the scanning range expands and the number of pixels increases; it is necessary to increase the pixel size, adjust the scanning waveform amplitude, and re-match the focusing parameters to ensure clear edges. This embodiment uses a mapping table to automatically match different beam energies, different fields of view, and the optimal co-calibration parameters.

[0029] The scene parameters in step S102 may further include environmental fluctuation parameters and beam intensity fluctuation parameters. Furthermore, the step S108, which involves further adjusting multiple modules based on the verification results, may include: dynamically compensating the collaborative calibration parameters according to the environmental fluctuation parameters and beam intensity fluctuation parameters, provided that the acquired images meet a unified image benchmark. In a specific embodiment, environmental fluctuation parameters may include: ambient temperature, ambient humidity, vibration / magnetic field interference, and power supply voltage fluctuations. Beam intensity fluctuation parameters may include: actual electron beam current value, beam stability, and beam drift. These fluctuations can cause focus shift, scanning distortion, and pixel size deviation, thus requiring real-time monitoring and dynamic compensation.

[0030] In one specific embodiment, step S108, which involves further adjusting multiple modules based on the verification results, may further include: if the acquired image fails to meet a unified image benchmark, re-executing the steps of determining collaborative calibration parameters and synchronously adjusting multiple modules, and recording the number of times the benchmark is not met. In a preferred embodiment, if the number of times the benchmark is not met is greater than or equal to a preset threshold, an alarm signal is output and fault information is recorded. In one specific embodiment, the preset threshold may be 3 times.

[0031] In one specific embodiment, the overall calibration process is automatically executed according to a preset cycle, and / or automatically initiated when scene parameters are switched. Furthermore, the step of executing the overall calibration process according to the preset cycle may also include recording calibration data during the calibration process and generating a calibration log for calibration traceability and optimization. In one specific embodiment, the preset cycle may be 30 minutes. It should be noted that the specific values ​​of the preset threshold and preset cycle mentioned above are merely illustrative and not intended to limit the invention. In other embodiments, the preset threshold and preset cycle may be set to other values ​​depending on the actual situation.

[0032] The image calibration method for the electron beam device in this embodiment has the following objectives: First, we will build an overall image calibration system for EBEAM equipment to achieve collaborative calibration of multiple modules such as pixel size, dynamic focusing, scanning waveform, and signal acquisition, thereby eliminating image distortion caused by parameter mismatch between modules and improving the overall image quality.

[0033] Second, it enables adaptive adjustment of calibration parameters, adapting to the full FOV range of 10-200μm and the full energy range of LE200-LE5000, without the need for manual intervention, thereby improving calibration efficiency and eliminating human error.

[0034] Third, establish a unified image benchmark and combine it with a fluctuation compensation mechanism to ensure stable calibration accuracy, eliminate the influence of environmental and beam fluctuations, and achieve uniformity of calibration results in different batches and scenarios.

[0035] Fourth, optimize the calibration process, shorten the calibration cycle, reduce equipment operation and maintenance costs, improve the long-term operational stability of the equipment, and meet the stringent requirements of high-end semiconductor precision testing and micro-device processing.

[0036] Fifth, avoid technological duplication and form an innovative overall calibration technology path to improve the practicality and scalability of the solution.

[0037] In summary, the core of the image calibration method for electron beam equipment in this embodiment is to construct a full-process image calibration system that integrates scene recognition, multi-module parameter collaborative calculation, adaptive overall adjustment, calibration verification, fluctuation compensation, and closed-loop maintenance. This system integrates scene recognition, multi-module calibration calculation, overall adjustment, calibration verification, fluctuation compensation, and the main control unit. Each unit works collaboratively to achieve full-process, high-precision, and automated overall calibration of EBEAM equipment images. This clearly distinguishes it from existing single-module calibration patents and technologies, and fundamentally addresses the core pain points of poor overall image quality, low calibration efficiency, and poor consistency.

[0038] Figure 2 This is a schematic diagram of the overall architecture of an image calibration method for an electron beam device according to an embodiment of the present invention, as shown below. Figure 2 As shown, in order to achieve the above objectives, the overall architecture of the image calibration method of the electron beam device in this embodiment may include: a scene recognition unit, a multi-module collaborative computing unit, an adaptive overall adjustment unit, a calibration verification unit, a fluctuation compensation unit, and a main control unit.

[0039] Scene recognition unit: Real-time recognition of the current device's field of view parameters (10-200μm) and beam energy parameters (LE200-LE5000), synchronous monitoring of environmental fluctuation parameters and beam intensity fluctuation parameters, collection of basic data such as the clarity, distortion rate, and spur ratio of the current image, and feedback to the main control unit and multi-module collaborative computing unit to provide basic data for the calculation of overall calibration parameters.

[0040] Multi-module collaborative computing unit: Using "image resolution ≥100nm, distortion rate ≤0.5%, spurious ratio ≤2%, calibration consistency deviation ≤5%" as a unified image benchmark, an LE-FOV-multi-module parameter mapping model is established, integrating the calibration logic of pixel size, dynamic focusing, and scanning waveform, testing the optimal collaborative parameters of each module under different LE and FOV, establishing a mapping table, and calculating the multi-module collaborative calibration parameters in the current scene in real time to ensure that the parameters of each module are matched.

[0041] Adaptive overall adjustment unit: Receives multi-module calibration parameters output by the collaborative computing unit, synchronously drives the scanning module, focusing module, and waveform amplification module of the EBEAM device, and realizes coordinated adjustment of pixel size, dynamic focusing, and scanning waveform. The response time is ≤50ms, ensuring rapid adaptation when switching between beam energy parameters and field of view parameters.

[0042] Calibration and verification unit: Real-time acquisition of adjusted image quality data (resolution, distortion rate, spurious ratio) and actual values ​​of parameters of each module, comparison with a unified image benchmark to verify the overall calibration effect; at the same time, periodic execution of multi-module calibration process to correct parameter deviations and ensure stable calibration accuracy.

[0043] Fluctuation compensation unit: Real-time monitoring of environmental fluctuation parameters (ambient temperature fluctuation) and beam intensity fluctuation parameters. Based on the fluctuation amplitude, it dynamically corrects the multi-module collaborative calibration parameters to compensate for the impact of fluctuation on image quality and avoid calibration parameter drift. This compensation mechanism is different from the limitations of no fluctuation compensation and improves long-term operational stability.

[0044] Main control unit: coordinates the collaborative work of each unit, receives feedback signals from each unit, executes process scheduling, parameter optimization and anomaly handling, realizes closed-loop overall calibration control, ensures that image quality is always in the optimal state, and records calibration data for easy traceability and optimization.

[0045] In a specific embodiment, based on the above overall architecture, the core process of the image calibration method for the electron beam device in this embodiment can be performed as follows: Scene acquisition: The scene recognition unit acquires the current field of view parameters and beam energy parameters in real time, and simultaneously monitors environmental fluctuation parameters and beam intensity fluctuation parameters. It also acquires the current image quality basic data (clarity, distortion rate, etc.) and sends them to the main control unit and the multi-module collaborative computing unit.

[0046] Benchmark calibration: Using "image resolution ≥100nm, distortion rate ≤0.5%, spurious ratio ≤2%, and calibration consistency deviation ≤5%" as a unified image benchmark, the optimal combination of pixel size, focusing parameters, and waveform amplification parameters is tested in each FOV range of LE200-LE5000 (every 100V) and 10-200μm. An LE-FOV-multi-module parameter mapping table is established. This calibration process and mapping table design are different from the technical logic of existing single-module calibration and are the basis for realizing overall calibration.

[0047] Collaborative computing: The multi-module collaborative computing unit calls the mapping table based on the collected scene parameters to calculate the optimal collaborative parameters of pixel size, focusing current / voltage, and waveform amplification voltage in the current scene in real time, ensuring that the parameters of each module are matched, and taking into account both image accuracy and calibration efficiency.

[0048] Adaptive overall adjustment: The adaptive overall adjustment unit receives the optimal coordination parameters, synchronously drives each module to adjust the parameters, completes the overall image calibration, with a response time of ≤50ms, and synchronously feeds back the adjustment results to the main control unit and the calibration verification unit.

[0049] Calibration and verification: The calibration and verification unit collects the adjusted image quality data and the actual values ​​of the parameters of each module, and compares them with the unified image benchmark. If the benchmark is met, the fluctuation compensation stage is entered; if the benchmark is not met, the main control unit controls the collaborative calculation unit and the adaptive overall adjustment unit to recalculate and adjust until the benchmark is met.

[0050] Fluctuation compensation: The fluctuation compensation unit dynamically corrects the multi-module collaborative calibration parameters based on the environment and beam fluctuation parameters, compensates for the effects of fluctuations, avoids calibration parameter drift, and ensures stable image quality.

[0051] Closed-loop maintenance: Performs multi-module automatic calibration every 30 minutes to correct parameter deviations; when beam energy parameters and field of view parameters are switched, multi-module calibration is automatically started to achieve rapid overall calibration after scene switching without manual intervention; at the same time, calibration data is recorded to form a calibration log for easy traceability and optimization in the future.

[0052] Anomaly Handling: If the image quality still fails to meet the standard after three consecutive calibrations, an alarm signal will be issued and fault information will be recorded to remind staff to troubleshoot the equipment and ensure stable operation of the equipment.

[0053] It should be emphasized that the image calibration method of the electron beam device in this embodiment has the following key technical points: Multi-module collaborative calibration technology: Integrating three core modules—scanning module, focusing module, and waveform amplification module—and establishing an LE-FOV-multi-module parameter collaborative mapping model, it achieves synchronous adjustment and matching calibration of multi-module parameters, that is, it realizes the collaborative adjustment of pixel size, dynamic focusing, and scanning waveform. This is different from the existing technical path of independent calibration of a single module, and fundamentally solves the problem of image distortion caused by parameter mismatch between modules.

[0054] Unified Image Benchmark Technology: Taking overall image quality as the core, it establishes a unified image benchmark for "resolution, distortion rate, spur ratio, and calibration consistency deviation", breaking the limitations of existing single-module calibration and inconsistent standards, and ensuring consistent calibration results in different batches and scenarios.

[0055] Full-scene adaptive calibration technology: Adaptable to the full FOV range of 10-200μm and the full energy range of LE200-LE5000, with a response time of ≤50ms, it enables rapid adaptive overall calibration when switching scenes without manual intervention. It solves the pain points of low calibration efficiency and poor scene adaptability of existing solutions, and is superior to existing single-module calibration solutions in terms of response speed and adaptation range.

[0056] Multi-factor fluctuation compensation calibration technology: Real-time monitoring of environmental fluctuation parameters and beam intensity fluctuation parameters, dynamic correction of multi-module collaborative calibration parameters, avoiding calibration parameter drift, improving the long-term operational stability of the equipment, and making up for the shortcomings of weak anti-interference capability of existing solutions.

[0057] Closed-loop overall calibration technology: Constructs a closed-loop system covering the entire process of "acquisition-calculation-adjustment-verification-compensation-maintenance" to automate and improve the accuracy of the calibration process, ensuring that image quality continuously meets standards. This is different from the limitations of existing single-module open-loop calibration and improves calibration reliability.

[0058] Differentiated technical approach: With "overall image quality optimization" as the core objective, the core technical approach is "multi-module collaboration + unified image benchmark + closed-loop compensation + adaptive adaptation". It is different from the existing technical approach of "only optimizing the detector without any calibration design" and "only calibrating a single focusing module without overall collaboration". This embodiment solves the four major problems of image quality, calibration efficiency, consistency and stability simultaneously through multi-module linkage calibration, which is highly innovative.

[0059] Furthermore, the image calibration method of the electron beam device in this embodiment can bring the following beneficial effects: Significantly improved overall image quality: Multi-module collaborative calibration eliminates parameter mismatch between modules, resulting in image resolution ≥100nm, distortion rate ≤0.5%, and glitch rate ≤2%. It completely solves the pain points of image distortion, blurring, and obvious glitch in existing solutions, and the image quality is superior to existing single-module calibration solutions and similar patents.

[0060] Significantly improved calibration efficiency: Automated closed-loop overall calibration replaces manual debugging, reducing calibration time from 30 minutes / time in the existing solution to 5 minutes / time, improving efficiency by 83.3%, eliminating human error, and enabling rapid adaptation when switching scenarios without manual intervention. The adaptation efficiency far exceeds that of the existing manual assisted calibration mode.

[0061] Significantly optimized calibration consistency deviation and long-term stability: With a unified image benchmark and fluctuation compensation mechanism, the calibration consistency deviation is ≤5%, the 24-hour calibration parameter drift is ≤0.2nm, and the detection / processing data of different batches and different scenarios can be unified, with stability superior to existing solutions without fluctuation compensation.

[0062] Outstanding innovation: The addition of core functions such as multi-module collaborative calibration, fluctuation compensation, closed-loop verification, and adaptive adaptation completely solves the core shortcomings of design without calibration and inability to improve image quality; it breaks through the limitations of single focusing module calibration, realizing multi-module collaborative calibration of scanning module, focusing module, and waveform amplification module in terms of pixel size, dynamic focusing, and scanning waveform; at the same time, it adds a unified image benchmark and fluctuation compensation mechanism to solve the pain points of existing technologies being unable to optimize overall image quality and poor stability; with overall image calibration as the core, it simultaneously solves the four major problems of accuracy, efficiency, consistency, and stability, with obvious technical advantages and no technological duplication.

[0063] Reduced maintenance costs and strong versatility: The closed-loop maintenance mechanism reduces the number of recalibrations, thus lowering maintenance costs; it is compatible with various EBEAM testing / processing equipment without requiring significant modifications to the core structure of the equipment, resulting in low adaptation costs and easy large-scale promotion, with applications covering multiple fields such as semiconductors and micro-devices.

[0064] Traceable calibration data: The main control unit records a complete calibration log, which facilitates troubleshooting and parameter optimization, improves equipment management efficiency, and makes up for the lack of traceability of calibration data in existing solutions.

[0065] The following describes the image calibration method for the electron beam device in this embodiment, along with specific test examples of several comparative methods: Test equipment: EBEAM instrument for precision semiconductor testing; Test scenarios: field of view parameter range (10μm, 30μm, 60μm, 120μm, 200μm), beam energy parameters (LE200, LE1000, LE3000, LE5000); Comparison schemes: existing single-module calibration scheme, US17 / 728691 patent scheme, TW1695407B patent scheme, and the scheme of this embodiment; Test metrics: image resolution, distortion rate, glitch percentage, calibration time, calibration consistency deviation, and 24-hour calibration parameter drift.

[0066] The parameter settings for this embodiment are as follows: image resolution ≥100nm, distortion rate ≤0.5%, glitch ratio ≤2%, calibration consistency deviation ≤5%, adjustment response time ≤50ms, automatic calibration every 30 minutes, and calibration parameter drift ≤0.2nm over 24 hours. Test environment: Ambient temperature fluctuation ±5℃, beam current fluctuation ±10%. The core test results are shown in Table 1.

[0067] Table 1 The following conclusions can be drawn from the above examples: Test results show that the image calibration method for the electron beam device in this embodiment significantly improves image quality, calibration efficiency, calibration consistency deviation, and operational stability compared to existing single-module calibration schemes, the US17 / 728691 patent scheme, and the TW1695407B patent scheme, completely solving the core pain points of existing technologies and similar patents. Specifically, the US17 / 728691 patent scheme lacks any calibration design and cannot improve image distortion and insufficient accuracy; the TW1695407B patent scheme can only calibrate the focusing module and cannot solve the problem of poor overall image quality caused by parameter mismatch between modules. This embodiment, through the innovative combination of multi-module collaborative calibration, unified image benchmark, fluctuation compensation, and closed-loop maintenance, achieves high-precision, automated overall calibration of the EBEAM device image throughout the entire process. This clearly distinguishes it from the single-module optimization or lack of calibration design of existing similar patents, and avoids technological duplication. Furthermore, this embodiment has strong versatility and low promotion cost, meeting the stringent requirements of high-end semiconductor precision testing and micro-device processing, and possesses extremely high practical value and innovation.

[0068] Specifically, the difference between this embodiment and the US17 / 728691 patent solution lies in their core technical approaches and core objectives. The core technical approach of the US17 / 728691 patent solution is to optimize the detector structure (semiconductor diode detector, PMT detector, etc.), with the core objective of achieving a balance between large FOV and large beam current. It does not involve any image calibration-related design, units, or processes, and lacks functions such as multi-module collaborative calibration, fluctuation compensation, and closed-loop verification. Therefore, it cannot solve problems such as image distortion, insufficient accuracy, and poor consistency in EBEAM equipment. The core technical approach of this embodiment is "multi-module collaboration + overall calibration + closed-loop compensation," with the core objective of optimizing the overall image quality of EBEAM equipment. By integrating a multi-module collaborative calibration system, it simultaneously addresses core pain points such as image distortion and insufficient accuracy. This approach has no technical overlap with the US17 / 728691 patent solution, and the technical problems solved and the technical effects achieved are completely different.

[0069] The differences between this embodiment and the TW1695407B patent solution are as follows: The two solutions differ fundamentally in their technical coverage, core innovations, and technical effects. The TW1695407B patent solution only calibrates the dynamic focusing module, neglecting the synergistic effects of other core modules such as pixel size and scanning waveform. It lacks a unified overall image calibration benchmark and a fluctuation compensation mechanism, only addressing focusing deviation but failing to optimize overall image quality. Furthermore, it suffers from poor calibration stability and weak scene adaptability. This embodiment, however, overcomes the limitations of single-module calibration, achieving collaborative calibration of the scanning module, focusing module, and waveform amplification module across pixel size, dynamic focusing, and scanning waveform. It establishes a unified image benchmark, adds a fluctuation compensation unit and a closed-loop maintenance mechanism, simultaneously addressing four core pain points: image distortion, insufficient accuracy, poor consistency, and low calibration efficiency. It boasts a wider technical coverage and superior calibration results, with core innovations and technical approaches distinct from the TW1695407B patent solution.

[0070] The difference between this embodiment and other technologies in the industry is that existing technologies mostly focus on single-module calibration or optical structure optimization, failing to form a complete calibration system and thus unable to simultaneously solve the four core problems of image distortion, insufficient accuracy, poor consistency, and low calibration efficiency. This embodiment, however, focuses on overall image quality, constructing a closed-loop calibration system to simultaneously address the aforementioned problems, demonstrating significant technological advantages.

[0071] This embodiment also provides a computer program product, a computer-readable storage medium, and an electron beam device. Figure 3 This is a schematic diagram of a computer program product 500 according to an embodiment of the present invention. Figure 4 This is a schematic diagram of a computer-readable storage medium 300 according to an embodiment of the present invention. Figure 5 This is a schematic diagram of an electron beam device 400 according to an embodiment of the present invention.

[0072] Computer program product 500 includes computer program 310, which, when executed by processor 410, implements the image calibration method of any of the aforementioned electron beam devices. Computer-readable storage medium 300 stores the aforementioned computer program 310 thereon, which, when executed by processor 410, implements the image calibration method of any of the aforementioned electron beam devices. Electron beam device 400 may include memory 420, processor 410, and computer program 310 stored in memory 420 and running on processor 410, and when processor 410 executes computer program 310, it implements the image calibration method of any of the aforementioned electron beam devices.

[0073] The computer program 310 used to perform the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, status setting data, integrated circuit configuration data, or source code or object code written in any combination of one or more programming languages ​​and procedural programming languages.

[0074] Computer program 310 may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0075] In some embodiments, in order to perform aspects of the present invention, electronic circuits including, for example, programmable logic circuits, field-programmable gate arrays (FPGAs) or programmable logic arrays (PLAs) can execute computer-readable program instructions to personalize the electronic circuits by utilizing state information of computer-readable program instructions.

[0076] For the purposes of this embodiment, computer program product 500 is a related product containing computer program 310. For the purposes of this embodiment, computer-readable storage medium 300 is a tangible device capable of holding and storing computer program 310, and can be any device capable of containing, storing, communicating, propagating or transmitting computer program 310 for use by or in conjunction with an instruction execution system, apparatus or device.

[0077] More specific examples (a non-exhaustive list) of computer-readable storage media 300 include the following: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable optical disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, and any suitable combination of the foregoing.

[0078] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any machine-readable storage medium for use by, or in conjunction with, instruction execution systems, apparatuses or devices (such as computer-based systems, processor-based systems or other systems that can fetch and execute instructions from, or instruction execution systems, apparatuses or devices).

[0079] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system.

[0080] Electron beam device 400 may include a computer device, such as a server, desktop computer, laptop computer, tablet computer, or smartphone. In some examples, the computer device may be a cloud computing node. The computer device can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules may include routines, programs, object programs, components, logic, data structures, etc., that perform specific tasks or implement specific abstract data types. The computer device may be implemented in a distributed cloud computing environment where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules may reside on local or remote computing system storage media, including storage devices.

[0081] The computer device may include a processor 410 adapted to execute stored instructions and a memory 420 that provides temporary storage space for the operation of the instructions during operation. The processor 410 may be a single-core processor, a multi-core processor, a computing cluster, or any other configuration. The memory 420 may include random access memory (RAM), read-only memory, flash memory, or any other suitable storage system.

[0082] The processor 410 can be connected via a system interconnect (e.g., PCI, PCI-Express, etc.) to an I / O interface (input / output interface) suitable for connecting a computer device to one or more I / O devices (input / output devices). I / O devices may include, for example, a keyboard and indicating devices, where indicating devices may include a touchpad or touchscreen, etc. I / O devices may be built into the computer device or may be external devices connected to the computing device.

[0083] The processor 410 can also be linked via a system interconnect to a display interface suitable for connecting computer devices to a display device. The display device may include a display screen that is a built-in component of the computer device. The display device may also include a computer monitor, television, or projector, etc., externally connected to the computer device. Furthermore, a network interface controller (NIC) may be adapted to connect computer devices to a network via a system interconnect. In some embodiments, the NIC may use any suitable interface or protocol (such as an Internet Minicomputer System Interface) to transmit data. The network may be a cellular network, a radio network, a wide area network (WAN), a local area network (LAN), or the Internet, etc. Remote devices can connect to the computing device via the network.

[0084] Therefore, those skilled in the art should recognize that although numerous exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Thus, the scope of the present invention should be understood and construed as covering all such other variations or modifications.

Claims

1. An image calibration method for an electron beam device, comprising: Real-time acquisition of scene parameters of the electron beam device, including beam energy parameters and field of view parameters; The collaborative calibration parameters of multiple modules of the electron beam device are determined according to a preset mapping table, which pre-stores collaborative calibration parameters corresponding to combinations of different beam energy parameters and field of view parameters. The multiple modules are synchronized according to the aforementioned collaborative calibration parameters; as well as The images acquired by the electron beam device are calibrated and verified, and the multiple modules are further adjusted based on the verification results.

2. The method according to claim 1, wherein, The multiple modules include a scanning module, a focusing module, and a waveform amplification module; The steps for performing synchronization adjustment on the multiple modules include: Adjust the scanning module to match the image pixel size corresponding to the current field of view and beam energy; Adjust the focusing module to achieve clear electron beam focusing; Adjust the waveform amplification module to correct electron beam scanning distortion.

3. The method according to claim 1, wherein, The mapping table establishes a mapping relationship between the combination of beam energy parameters and field of view parameters and the co-calibration parameters based on a unified image reference. The unified image benchmark includes resolution, distortion rate, spurious ratio, and calibration consistency deviation.

4. The method according to claim 3, wherein, The scenario parameters also include environmental fluctuation parameters and beam intensity fluctuation parameters; The step of further adjusting the multiple modules based on the verification results includes: when the acquired image reaches the unified image benchmark, dynamically compensating the collaborative calibration parameters according to the environmental fluctuation parameters and the beam intensity fluctuation parameters.

5. The method according to claim 3, wherein the step of further adjusting the plurality of modules based on the verification results includes: If the acquired image fails to meet the unified image benchmark, the steps of determining the collaborative calibration parameters and synchronously adjusting the multiple modules are repeated, and the number of times the benchmark is not met is recorded.

6. The method according to claim 5, wherein, If the number of times the standard is not met is greater than or equal to a preset threshold, an alarm signal is output and fault information is recorded.

7. The method according to claim 1, wherein, The overall calibration process is automatically executed according to a preset cycle, and / or the overall calibration process is automatically started when the scenario parameters are switched.

8. The method according to claim 7, wherein the step of performing the overall calibration process according to a preset cycle further comprises: Record calibration data during the calibration process and generate a calibration log for calibration traceability and optimization.

9. An electron beam device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the image calibration method of the electron beam device according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the image calibration method of the electron beam apparatus according to any one of claims 1 to 8.

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