A femtosecond laser etching method and system for perovskite thin film

Abstract

The present invention discloses a femtosecond laser etching method and system for perovskite thin film, which relates to the field of semiconductor processing technology. The system comprises: a laser light source module for generating femtosecond laser pulses with high repetition rate, adjustable laser power, frequency and beam diffusion angle; an optical path control module, which is equipped with an optical element group, an optical element alignment system, a beam shaper and an adaptive optical element, for adjusting the path, focus and energy distribution of the laser beam; wherein the adaptive optical element comprises an adjustable deformable mirror and a liquid crystal spatial light modulator. The femtosecond laser etching method and system for perovskite thin film, combined with real-time wavefront monitoring and distortion correction and an optical element driving system, ensures the stability and consistency of the optical path, and solves the problem that the traditional etching method is difficult to maintain the consistency and uniformity of etching on a large-area thin film, resulting in the instability and reduction of device performance.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor processing technology, and in particular to a femtosecond laser etching method and system for a perovskite film. Background Art

[0002] Perovskite thin films have become an important research object in the field of solar cells due to their excellent optoelectronic properties and potential high efficiency. However, in the large-scale manufacturing process of perovskite thin films in practical applications, the precise processing and patterned etching of thin films still face many challenges. Although femtosecond lasers have ultrashort pulse characteristics and can achieve high-precision etching, in practical applications, as the size of the device increases, traditional etching methods are difficult to maintain the consistency and uniformity of etching on large-area thin films, resulting in instability and degradation of device performance. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides a femtosecond laser etching method and system for perovskite thin films, which solves the problem that traditional etching methods are difficult to maintain etching consistency and uniformity on large-area thin films, resulting in unstable and reduced device performance.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a femtosecond laser etching method and system for perovskite thin film, the system comprising:

[0005] Laser source module for generating femtosecond laser pulses with high repetition rate, adjustable laser power, frequency and beam spread angle;

[0006] An optical path control module is configured with an optical element group, an optical element alignment system, a beam shaper and an adaptive optical element, and is used to adjust the path, focus and energy distribution of the laser beam; wherein the adaptive optical element includes an adjustable deformable mirror and a liquid crystal spatial light modulator, wherein the adjustable deformable mirror is used to adjust the focus state of the laser beam in real time and compensate for thermal distortion and mechanical vibration in the optical system; and the liquid crystal spatial light modulator is used to adjust the phase and amplitude of the laser beam in real time to achieve dynamic optimization of the optical path;

[0007] A scanning system module, including a motion platform and a scanning mirror, is used to achieve nanometer-level precision scanning of the laser beam on the surface of the perovskite film;

[0008] Thermal management system module, used to control the temperature of each component of the system to prevent overheating of the equipment or thermal damage to the perovskite film due to the heat generated by laser etching;

[0009] The control system module includes a central control computer, intelligent control algorithms, and a human-computer interaction interface for overall system control and management. It also uses machine learning-based parameter prediction and optimization to analyze etching data, predict etching quality, and automatically optimize laser parameters using machine learning models.

[0010] Monitoring and feedback module, including high-resolution optical monitoring system, spectrum analyzer, temperature sensor and data fusion analysis platform, used to monitor the etching process in real time and provide feedback;

[0011] The quality inspection module is used for sample cleaning and quality inspection after etching is completed.

[0012] Among them, the control system module also integrates an optical microscope, a spectrometer, and a temperature sensor, and realizes etching process monitoring and feedback through a data fusion analysis platform.

[0013] Preferably, the laser light source module comprises:

[0014] A pulse modulation unit for adjusting the energy, repetition rate, laser power, frequency and beam divergence angle of femtosecond laser pulses;

[0015] The cooling system is used to maintain the operating temperature of the laser and ensure the stability and consistency of the laser output.

[0016] The machine learning model is used to analyze etching data, predict etching quality, and automatically optimize laser parameters. The process is as follows: during the femtosecond laser etching process, multi-dimensional data including laser parameters (such as pulse energy, repetition rate, power, frequency, and beam diffusion angle), etching effects (such as etching depth, uniformity, etc.) and environmental parameters (such as temperature, humidity, etc.) are collected; the machine learning model (such as neural network, support vector machine, etc.) is trained using the above collected data to establish a predictive relationship between laser parameters and etching quality, ensuring that the model can accurately predict the impact of different laser parameter combinations on the etching effect;

[0017] During the etching process, the current laser parameters and etching effect data are collected in real time; the real-time collected data is input into the trained machine learning model to make real-time predictions on the etching quality; based on the prediction results of the model, optimization suggestions are generated to determine the best combination of laser parameters to improve the etching quality; according to the prediction results of the machine learning model, the optimal combination of laser parameters, including pulse energy, repetition rate, and scanning speed, is automatically calculated; the optimized laser parameters are transmitted to the laser light source module and the optical path control module through the control system module, and the laser output and beam shape are adjusted in real time to ensure high precision and consistency of the etching process; the adjusted etching effect data is fed back to the machine learning model again for further analysis. Continuous learning and optimization; regularly update and optimize the machine learning model to improve the model's prediction accuracy and the system's adaptability, and realize dynamic optimization and automated management of the etching process; use the machine learning model to monitor the data in the etching process and identify potential abnormalities (such as sudden changes in etching quality, equipment failure, etc.). When an abnormality is detected, automatically adjust the laser parameters or start the protection mechanism (such as reducing the laser power or stopping the laser pulse) to prevent further equipment damage or degradation of etching quality; through these steps, the system can realize intelligent adjustment of laser parameters, ensure high precision, uniformity and consistency of the etching process, and significantly improve the quality and efficiency of the perovskite thin-film solar cell manufacturing process.

[0018] The process of training the machine learning model is as follows: during the femtosecond laser etching process, the laser parameters are recorded in real time, including but not limited to pulse energy, repetition rate, power, frequency and beam diffusion angle; the morphological data of the etched surface is obtained through a high-resolution optical monitoring system; the etching depth, edge clarity and uniformity are recorded; the environmental conditions during the etching process are monitored using temperature sensors and humidity sensors; temperature changes and humidity levels are recorded; noise and outliers in the collected data are removed to ensure the accuracy and reliability of the data; data from different sources and scales are normalized and converted into a unified standard format for subsequent analysis and processing; high-pass filtering and low-pass filtering are then applied to further purify the data, eliminate system noise and interference signals, and obtain preprocessed data; and then key features closely related to etching quality are extracted from the preprocessed data, such as the relationship between laser pulse energy and etching depth; principal component analysis PCA is used to screen out the most influential features and reduce Data dimension, improve model training efficiency, and then select appropriate machine learning algorithms, including neural networks, support vector machines (SVMs), decision trees or integrated learning methods, according to the complexity of the etching process and data characteristics, build the architecture of the machine learning model, set the appropriate number of layers, number of neurons and other hyperparameters, ensure that the model can effectively learn the patterns in the data, divide the preprocessed data set into training sets, validation sets and test sets, ensure the comprehensiveness and generalization ability of model training, use the training set to train the machine learning model, minimize the loss function through the gradient descent method, improve the prediction accuracy of the model, use the validation set to evaluate the model performance, adjust the hyperparameters to prevent overfitting or underfitting, ensure the performance of the model on unknown data, use the test set to conduct a final evaluation of the trained model, and calculate the performance indicators: prediction accuracy, mean square error (MSE); then, based on the evaluation results, further optimize the model structure and parameters to improve the prediction ability and stability of the model;

[0019] The trained machine learning model is then deployed to the central control computer and integrated into the system's intelligent control algorithm module. During the femtosecond laser etching process, the current laser parameters and environmental data are input into the model in real time to obtain the prediction results of the etching quality. Based on the model's prediction results, the laser parameters, including pulse energy, repetition rate, and scanning speed, are automatically adjusted to optimize the etching process and ensure high precision and consistency of the etching quality. Subsequently, during the etching process, new laser parameters, etching effects, and environmental data are continuously collected to enrich the training data set. The machine learning model is regularly retrained using the latest collected data to improve the model's prediction accuracy and adaptability. The incremental learning method is used to enable the model to dynamically adapt to changes in the etching process and achieve real-time optimization and self-improvement.

[0020] Preferably, in the optical path control module, the optical element is made of high-purity quartz or molten silicon material to reduce energy loss during laser transmission; the surface of the high-precision optical element is coated with an anti-pollution coating to prevent dust and impurities from adhering to maintain the high transmittance and low reflectivity of the optical element; wherein the optical element group includes a high-quality reflector, a high-quality lens and a high-quality beam splitter, and the high-quality reflector has low wavefront distortion and high optical transmission efficiency; the high-quality lens is used for focusing and collimating the laser beam; the high-quality beam splitter is used to divide the laser beam into multiple sub-laser beams to achieve superposition of multiple laser beams.

[0021] Preferably, the optical path control module includes:

[0022] Shack-Hartmann wavefront sensor, used to monitor the wavefront shape and distortion of the laser beam in real time and obtain monitoring data;

[0023] The wavefront distortion correction algorithm adjusts the shape of the adaptive optical element in real time to compensate for the wavefront distortion based on the monitoring data of the wavefront sensor;

[0024] The optical path control module uses a phase plate or a spatial light modulator (SLM) to convert the Gaussian laser beam into a uniform top-hat profile to achieve uniform distribution of laser energy in a large etching area;

[0025] An optical element alignment system comprises a nanometer-level adjustment stage and a fine-tuning drive, as well as an automatic alignment and calibration system, and monitors and adjusts the position of the optical element in real time through a Shack-Hartmann wavefront sensor and a feedback mechanism.

[0026] Preferably, the wavefront distortion correction algorithm adjusts the shape of the adaptive optical element in real time based on the monitoring data of the wavefront sensor to compensate for the wavefront distortion, and the steps are as follows:

[0027] Step a: The monitoring data collected in real time by the Shack-Hartmann wavefront sensor is transmitted to the central control computer in the form of digital signals, and then the monitoring data is preprocessed, including denoising, normalization and filtering, to obtain wavefront distortion data;

[0028] Step b: Then, the wavefront distortion data is analyzed using Zernike polynomial expansion to identify and quantify specific distortion modes (such as spherical aberration, coma aberration, etc.), and the distortion amount of each distortion mode is calculated, including amplitude and phase information;

[0029] Step c: applying the least square method to calculate the distortion compensation parameters required to compensate the wavefront distortion based on the identified distortion mode and distortion amount;

[0030] Step d: generating corresponding control instructions according to the calculated distortion compensation parameters; transmitting the control instructions to the adaptive optical element (such as an adjustable deformable mirror or a liquid crystal spatial light modulator) to adjust its surface shape to achieve compensation of wavefront distortion;

[0031] Step e: Using real-time monitoring data, the new wavefront data is fed back to the central control computer through the data fusion analysis platform; and based on the feedback data, the wavefront distortion correction parameters are dynamically adjusted and optimized, and steps a to d are continuously iterated to gradually improve the accuracy and stability of the wavefront correction.

[0032] Preferably, the scanning system module further comprises:

[0033] Scanning path optimization algorithm, used to optimize the movement path of the laser beam to improve scanning efficiency and consistency;

[0034] Optical element drive systems, including microsecond-level response speed drive systems and low-latency feedback mechanisms to ensure that adaptive optical elements can quickly respond and adjust optical paths;

[0035] The central control computer runs the control software, coordinates the operation of each submodule, and performs laser parameter setting and scanning path planning;

[0036] Human-computer interaction interface provides an intuitive operation interface, which is convenient for operators to set and adjust etching parameters;

[0037] Among them, the scanning system module adopts a laser interferometer measurement positioning system to achieve nanometer-level positioning accuracy and ensure positioning accuracy during long-distance movement.

[0038] Preferably, the thermal management system module comprises:

[0039] The zoned cooling system divides the etching area into multiple independent cooling zones and adopts a modular cooling design to achieve efficient heat dissipation;

[0040] The thermal simulation optimization module optimizes the layout and parameters of the cooling system based on the thermal simulation model to ensure uniform heat distribution.

[0041] Preferably, the monitoring feedback module further comprises:

[0042] High-resolution optical monitoring system, used to monitor the morphology and accuracy of the etched surface in real time and obtain etched surface data;

[0043] Spectrum analyzer, used to analyze the spectral signals generated during the etching process, evaluate the material removal situation, and obtain material evaluation results;

[0044] Temperature sensor, used to monitor the temperature change of the etching area, obtain etching temperature data, and ensure the effective operation of the thermal management system;

[0045] The data fusion analysis platform is used to integrate and analyze the etching surface data, material evaluation results and etching temperature data from various sensors in real time to provide support for intelligent control algorithms.

[0046] Preferably, the quality inspection module further comprises:

[0047] Cleaning system, used to remove residues produced during etching to ensure the cleanliness of the film surface;

[0048] Microscope inspection system, which uses a high-resolution microscope to inspect the etching quality and evaluate the etching depth and edge clarity;

[0049] The data recording system is used to record etching parameters and quality inspection results, providing data support for subsequent process optimization.

[0050] A femtosecond laser etching method for a perovskite film comprises the following steps:

[0051] Step 1: First, a femtosecond laser pulse is generated through a laser light source module, and the path and energy distribution of the laser beam are adjusted through a beam shaper and adaptive optical elements to ensure high-precision focusing of the laser beam on the surface of the perovskite film;

[0052] Step 2: The adjusted laser beam is guided to the surface of the perovskite film by the scanning mirror. The scanning system module controls the movement path of the laser beam to ensure the accuracy and uniformity of the etched pattern. The heat generated during the scanning process is efficiently dissipated through the partitioned cooling system of the thermal management system module to prevent overheating of the equipment and the film.

[0053] Step 3: The control system module coordinates the operation of the laser light source, optical path control, scanning system, and thermal management system modules through the central control computer to ensure the overall operation of the system;

[0054] Step 4: Multi-sensors are used to collect data during the etching process. The data fusion analysis platform transmits the data to the control system module. The intelligent control algorithm predicts and optimizes parameters based on the data and dynamically adjusts the laser parameters and scanning path.

[0055] Step 5: After etching is completed, the quality inspection module cleans and inspects the samples, and the inspection results are fed back to the control system module through the data recording system for further optimization of the etching process parameters.

[0056] The present invention provides a femtosecond laser etching method and system for perovskite thin films, which have the following beneficial effects:

[0057] The femtosecond laser etching method and system of the perovskite film ensures efficient transmission and precise focusing of the laser beam through the optical element group and automatic alignment system in the optical path control module. At the same time, through the parameter prediction and optimization based on machine learning and the real-time monitoring system of multi-sensor fusion, the intelligent management and dynamic optimization of the etching process are realized. In addition, the stability and consistency of the optical path are ensured by combining real-time wavefront monitoring and distortion correction as well as the optical element driving system, which solves the problem that traditional etching methods are difficult to maintain etching consistency and uniformity on large-area films, resulting in unstable and reduced device performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the process of a femtosecond laser etching method of a perovskite film according to the present invention;

[0059] Figure 2 It is a schematic diagram of the process of compensating wavefront distortion according to the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] See also Figure 1 and Figure 2 The present invention provides a technical solution: a femtosecond laser etching method and system for perovskite thin film, the system comprising:

[0062] Laser source module for generating femtosecond laser pulses with high repetition rate, adjustable laser power, frequency and beam spread angle;

[0063] The optical path control module is configured with an optical element group, an optical element alignment system, a beam shaper and an adaptive optical element, and is used to adjust the path, focus and energy distribution of the laser beam; wherein the adaptive optical element includes an adjustable deformable mirror and a liquid crystal spatial light modulator, the adjustable deformable mirror is used to adjust the focus state of the laser beam in real time and compensate for thermal distortion and mechanical vibration in the optical system; the liquid crystal spatial light modulator is used to adjust the phase and amplitude of the laser beam in real time to achieve dynamic optimization of the optical path;

[0064] A scanning system module, including a motion platform and a scanning mirror, is used to achieve nanometer-level precision scanning of the laser beam on the surface of the perovskite film;

[0065] Thermal management system module, used to control the temperature of each component of the system to prevent overheating of the equipment or thermal damage to the perovskite film due to the heat generated by laser etching;

[0066] The control system module includes a central control computer, intelligent control algorithms, and a human-computer interaction interface for overall system control and management. It also uses machine learning-based parameter prediction and optimization to analyze etching data, predict etching quality, and automatically optimize laser parameters using machine learning models.

[0067] The specific process of training a machine learning model includes the following steps:

[0068] During the femtosecond laser etching process, the pulse energy (range: 50mJ to 200mJ), repetition rate (range: 100kHz to 500kHz), power (range: 5W to 100W), frequency (range: 100kHz to 500kHz) and beam divergence angle (range: 0.1mrad to 1mrad) of the laser were recorded; the morphological data of the etched surface were obtained through a high-resolution optical monitoring system (such as microscope imaging), and the etching depth (range: 100nm to 1μm), edge clarity (with edge sharpness score 0-10) and uniformity (expressed as a percentage of light intensity distribution uniformity) were recorded; the environmental conditions during the etching process were monitored using temperature sensors and humidity sensors, and the temperature (20°C to 40°C) and humidity ( 30% to 70%); use the Pandas library in Python to remove outliers and missing values ​​in the data set to ensure data integrity and accuracy, and use the Min-Max normalization method to unify the numerical range of laser parameters, etching effects, and environmental parameters to [0,1] for model training; use the high-pass filter in the SciPy library to remove low-frequency noise to ensure the purity of the wavefront distortion data, extract laser pulse energy, repetition rate, power, frequency and beam diffusion angle, temperature and humidity from the preprocessed data as key features, associate etching depth, edge clarity and uniformity, and use the principal component analysis (PCA) method to reduce data dimensions, retain the features that mainly affect etching quality, reduce model complexity, and improve training efficiency;

[0069] Because deep neural networks are excellent in processing nonlinear complex relationships and are suitable for the prediction and optimization of etching quality, DNN is selected as the machine learning algorithm. A DNN with three hidden layers is constructed. Each layer contains 128, 64 and 32 neurons respectively. The activation function uses ReLU, and the output layer uses a linear activation function, which is suitable for regression tasks. The data set is divided into 80% training set, 10% validation set and 10% test set to ensure the generalization ability of the model. The TensorFlow framework is used, the Adam optimizer is adopted, the learning rate is set to 0.001, and the model is trained for 100 epochs. By minimizing The mean square error (MSE) loss function is used to improve prediction accuracy. The model performance is evaluated on the validation set. The number of neurons and layers are adjusted to prevent overfitting. The training is terminated early through the EarlyStopping strategy to optimize the model. The prediction accuracy of the model is calculated on the test set. The mean square error (MSE) is 0.02 and the determination coefficient (R²) is 0.95, indicating that the model has good prediction ability. According to the test results, the model hyperparameters are further adjusted, the regularization term (L2 regularization) is added to reduce overfitting, the network structure is optimized to improve the model stability, and the trained DNN model is exported as TensorFlow. SavedModel format, deployed in the intelligent control algorithm module of the central control computer, integrated into the software environment of the femtosecond laser etching system, during the femtosecond laser etching process, the current laser parameters and environmental data are input into the DNN model in real time, the prediction results of etching quality are obtained, and the laser parameters, including pulse energy, repetition rate and scanning speed, are automatically adjusted according to the prediction results to optimize the etching process, ensure high precision and consistency, and continuously collect new laser parameters, etching effects and environmental data during the etching process, dynamically enrich the training data set, ensure that the model can adapt to different process conditions, and use the latest collected data to retrain the DNN model every month, update the model weights, improve the model's adaptability to new data and prediction accuracy, and use incremental learning methods to enable the model to update its knowledge base in real time without interrupting the etching process, so as to achieve real-time optimization and self-improvement, and further improve the automation and intelligence level of the etching process. By implementing the above specific embodiments, the perovskite thin film femtosecond laser etching system of the present invention uses a deep neural network machine learning model to achieve accurate prediction and optimization of the complex relationship between laser parameters and etching quality. This method not only improves the accuracy and consistency of the etching process, but also ensures the stability and adaptability of the system under different process conditions through continuous learning and model updating, significantly improving the quality and production efficiency of perovskite solar cell manufacturing, and has broad application prospects and commercial value.

[0070] Monitoring and feedback module, including high-resolution optical monitoring system, spectrum analyzer, temperature sensor and data fusion analysis platform, used to monitor the etching process in real time and provide feedback;

[0071] The quality inspection module is used for sample cleaning and quality inspection after etching is completed.

[0072] Among them, the control system module also integrates an optical microscope, a spectrometer, and a temperature sensor, and realizes etching process monitoring and feedback through a data fusion analysis platform.

[0073] The laser source module includes:

[0074] A pulse modulation unit for adjusting the energy, repetition rate, laser power, frequency and beam divergence angle of femtosecond laser pulses;

[0075] Cooling system, used to maintain the operating temperature of the laser and ensure the stability and consistency of the laser output;

[0076] The cooling system includes a liquid cooling loop, a heat exchanger, a temperature sensor, a temperature control unit, an automatic feedback mechanism and a filtering system. The liquid cooling loop includes a cooling pump, a coolant pipe and a radiator, which are used to circulate the coolant and take away the heat generated by the laser. The heat exchanger is located near the laser and transfers the heat generated by the laser to the flowing coolant through direct contact with the laser heat source or close conduction. The temperature sensor is installed in the laser and the coolant loop to monitor the operating temperature of the laser and the temperature of the coolant in real time. The temperature control unit adjusts the flow rate of the cooling pump and the working state of the radiator according to the data of the temperature sensor to maintain the operating temperature of the laser within a preset range. When the temperature exceeds the preset range, the automatic feedback mechanism automatically activates an alarm and adjusts the working parameters of the cooling system to ensure the stable operation of the laser. The filtering system is located in the coolant loop to remove impurities and particles in the coolant to prevent blockage and damage to the cooling system components.

[0077] In the optical path control module, the optical elements are made of high-purity quartz or molten silicon materials to reduce energy loss during laser transmission; the surface of the high-precision optical elements is coated with an anti-pollution coating to prevent dust and impurities from adhering to maintain the high transmittance and low reflectivity of the optical elements; the optical element group includes high-quality mirrors, high-quality lenses and high-quality beam splitters. The high-quality mirrors have low wavefront distortion and high optical transmission efficiency; the high-quality lenses are used for focusing and collimating the laser beam; the high-quality beam splitter is used to divide the laser beam into multiple sub-laser beams to achieve superposition of multiple laser beams.

[0078] The optical path control module includes:

[0079] The Shack-Hartmann wavefront sensor is used to monitor the wavefront shape and distortion of the laser beam in real time and obtain monitoring data. The process includes:

[0080] First, a group of lens arrays are used to split the incident Gaussian laser beam into multiple sub-beams. Each sub-beam is focused onto the detection array of the wavefront sensor through an independent lens. Each sub-beam is then focused by a lens to form multiple focal points on the detection array. The position of the focal point corresponds to the local wavefront slope of the sub-beam. A high-resolution detector CCD camera is then installed on the detection array to capture and record the position offset of each focal point in real time. The local wavefront slope of each sub-beam is calculated by comparing the offset between the actual focal position and the ideal focal position. The wavefront slope data of each sub-beam is integrated using Zernike polynomial expansion to reconstruct the wavefront shape of the entire laser beam, identify and quantify the wavefront distortion, and transmit the reconstructed wavefront data in the form of a digital signal to the central control computer for subsequent wavefront distortion correction and system optimization. Finally, based on the wavefront reconstruction data, the control system module adjusts the shape of the adaptive optical element in real time through a wavefront distortion correction algorithm to compensate for the detected wavefront distortion and ensure high-quality focusing and uniform energy distribution of the laser beam.

[0081] The wavefront distortion correction algorithm adjusts the shape of the adaptive optical element in real time to compensate for the wavefront distortion based on the monitoring data of the wavefront sensor;

[0082] The optical path control module uses a phase plate or a spatial light modulator (SLM) to convert the Gaussian laser beam into a uniform top-hat profile to achieve uniform distribution of laser energy over a large etching area.

[0083] Optical component alignment system,The optical component alignment system includes a nanometer-level adjustment stage and fine-tuning drive, as well as an automatic alignment and calibration system, which monitors and adjusts the position of optical components in real time through a Shack-Hartmann wavefront sensor and feedback mechanism.

[0084] according to Figure 2 As shown, the wavefront distortion correction algorithm adjusts the shape of the adaptive optical element in real time based on the monitoring data of the wavefront sensor to compensate for the wavefront distortion. The steps are as follows:

[0085] Step a: The monitoring data collected in real time by the Shack-Hartmann wavefront sensor is transmitted to the central control computer in the form of a digital signal, and then the monitoring data is preprocessed, including denoising, normalization and filtering, to obtain wavefront distortion data; wherein, a filtering algorithm is applied to remove random noise in the data to improve data quality, and wavefront data of different amplitudes are normalized to ensure data consistency and comparability, and a high-pass or low-pass filter is used to further purify the data to eliminate system noise and interference, so as to obtain accurate wavefront distortion data;

[0086] Step b: Then, the wavefront distortion data is analyzed by using Zernike polynomial expansion to identify and quantify specific distortion modes, where the distortion modes include but are not limited to spherical aberration and coma aberration, and the distortion amount of each distortion mode is calculated, including amplitude and phase information, to quantify the degree of distortion;

[0087] Step c: Apply the least square method to mathematically model the quantified distortion mode and distortion amount. Based on the identified distortion mode and distortion amount, apply the least square method to calculate the phase modulation pattern and amplitude modulation pattern that need to be applied to the liquid crystal spatial light modulator, ensure that the calculated modulation parameters can effectively compensate for the detected phase and amplitude distortion, ensure that the calculation result can minimize the wavefront distortion, and achieve the optimization of the optical path, that is, efficient distortion compensation;

[0088] Step d: converting the distortion compensation parameter into a specific control instruction to instruct the adaptive optical element to make corresponding adjustments; transmitting the control instruction to the adjustable deformable mirror in the adaptive optical element to adjust its surface shape to achieve compensation of wavefront distortion. Specifically, the generated control instruction is sent to the adjustable deformable mirror in the system through a high-speed data transmission interface. The adjustable deformable mirror adjusts its surface shape according to the instruction to compensate for the wavefront distortion of the laser beam in real time to achieve accurate wavefront correction.

[0089] The process of the adjustable deformable mirror adjusting its surface shape according to the command includes: the adjustable deformable mirror adjusts its surface shape in real time according to the control command to compensate for thermal distortion and mechanical vibration in the optical system, and the liquid crystal spatial light modulator adjusts the phase and amplitude of the laser beam in real time to further optimize the wavefront shape of the beam;

[0090] Step e: Using real-time monitoring data, the new wavefront data is fed back to the central control computer through the data fusion analysis platform. The data fusion analysis platform integrates the new wavefront monitoring data and transmits it to the central control computer to provide the latest etching process status information; and based on the feedback data, the wavefront distortion correction parameters are dynamically adjusted and optimized. The central control computer analyzes the feedback data, evaluates the effect of the current wavefront correction, and dynamically adjusts and optimizes the distortion compensation parameters according to the analysis results to ensure the continuous accuracy and stability of the wavefront correction;

[0091] Continuously iterate steps a to d to achieve gradual correction and optimization of wavefront distortion. Through continuous iteration, the accuracy and stability of wavefront correction are gradually improved to ensure high accuracy and consistency during laser etching. This process ensures high accuracy, uniformity and consistency of the femtosecond laser etching system on the perovskite film, overcoming the problem of unstable etching quality caused by wavefront distortion.

[0092] The scanning system module further includes:

[0093] Scanning path optimization algorithm, used to optimize the movement path of the laser beam to improve scanning efficiency and consistency;

[0094] Optical element drive systems, including microsecond-level response speed drive systems and low-latency feedback mechanisms to ensure that adaptive optical elements can quickly respond and adjust optical paths;

[0095] The central control computer runs the control software, coordinates the operation of each submodule, and performs laser parameter setting and scanning path planning;

[0096] Human-computer interaction interface provides an intuitive operation interface, which is convenient for operators to set and adjust etching parameters;

[0097] Among them, the scanning system module adopts a laser interferometer measurement positioning system to achieve nanometer-level positioning accuracy and ensure positioning accuracy during long-distance movement.

[0098] It should be further explained that, in a specific implementation process, the optical path control module uses a phase plate or a spatial light modulator to convert a Gaussian laser beam into a uniform flat-top spot to achieve uniform distribution of laser energy in a large area of ​​etching, and the process includes:

[0099] A specific phase distortion is applied to the Gaussian laser beam through a phase plate to change the phase front of the laser beam, and the phase distortion interference effect is used to convert the laser beam originally with Gaussian distribution into a flat-top spot with uniform light intensity distribution; for the phase plate, a specific geometric shape and phase delay parameters are designed so that it can effectively convert the Gaussian beam into a flat-top spot at a specific wavelength; then a high-resolution CCD camera is used to perform real-time imaging and monitoring of the converted flat-top spot to evaluate the uniformity and edge clarity of the spot; then, according to the monitoring results, the position of the phase plate is adjusted to optimize the light intensity distribution of the spot and achieve a highly uniform flat-top spot; the real-time monitoring data is transmitted to the central control computer, and the deviation of the spot shape is analyzed by an intelligent control algorithm. Based on the analysis results, the parameters of the phase plate are automatically adjusted to continuously optimize the spot shape to ensure the uniform distribution of laser energy in a large area of ​​etching during the etching process. Thus, through the steps of beam shaping, phase pattern design and application, spot shape verification and optimization, and closed-loop feedback control, the system can achieve a highly uniform distribution of laser energy in a large area of ​​etching, significantly improving the consistency and accuracy of etching.

[0100] The thermal management system module includes:

[0101] The zoned cooling system divides the etching area into multiple independent cooling zones and adopts a modular cooling design to achieve efficient heat dissipation;

[0102] The thermal simulation optimization module optimizes the layout and parameters of the cooling system based on the thermal simulation model to ensure uniform heat distribution.

[0103] The monitoring feedback module further includes:

[0104] High-resolution optical monitoring system, used to monitor the morphology and accuracy of the etched surface in real time and obtain etched surface data;

[0105] Spectrum analyzer, used to analyze the spectral signals generated during the etching process, evaluate the material removal situation, and obtain material evaluation results;

[0106] Temperature sensor, used to monitor the temperature change of the etching area, obtain etching temperature data, and ensure the effective operation of the thermal management system;

[0107] The data fusion analysis platform is used to integrate and analyze the etching surface data, material evaluation results and etching temperature data from various sensors in real time to provide support for intelligent control algorithms.

[0108] It should be further explained that, in the specific implementation process, the data fusion analysis platform integrates and analyzes the etching surface data, material evaluation results and etching temperature data from various sensors in real time as follows:

[0109] First, the real-time morphological data of the etched surface is obtained through a high-resolution optical monitoring system, and the spectral signals generated during the etching process are collected through a spectrometer to evaluate the material removal situation. The temperature change of the etching area is monitored in real time through a temperature sensor. At the same time, a timestamp is used to ensure that the data from different sensors remain consistent and relevant in time, which is convenient for subsequent integration and analysis. Noise and outliers are removed to ensure the accuracy and reliability of the data, and data from different sources and formats are converted into a unified standard format for easy integration and comparison. A multi-sensor data fusion algorithm is applied: weighted averaging, which integrates data from different sensors to form a comprehensive description of the etching process, and then the integrated data is mapped to a unified etching parameter space to generate a comprehensive etching process model.

[0110] The comprehensive data after data fusion is used to conduct real-time etching process analysis, including the evaluation of key performance indicators such as etching speed, depth, and uniformity. Based on historical and real-time data, machine learning models are used to predict potential problems in the etching process, and adjustment measures are taken in advance. The analysis results and prediction information are fed back to the control system module to provide a decision-making basis for the intelligent control algorithm. Based on the analysis results, control instructions for adjusting laser parameters including pulse energy, repetition rate, and scanning speed are automatically generated to optimize the etching process. Real-time data analysis results and prediction information are displayed through the human-computer interaction interface for operators to monitor and make decisions. A detailed report of the etching process is generated, including data analysis results, adjustment records, and quality assessment, to provide support for process optimization and quality control. In other words, through data acquisition and synchronization, data preprocessing, data integration and fusion, real-time data analysis and processing, feedback generation and control instructions, and user interface and reporting steps, the system can comprehensively and accurately monitor and optimize the etching process to ensure etching quality and consistency.

[0111] The quality inspection module further includes:

[0112] Cleaning system, used to remove residues produced during etching to ensure the cleanliness of the film surface;

[0113] Microscope inspection system, which uses a high-resolution microscope to inspect the etching quality and evaluate the etching depth and edge clarity;

[0114] The data recording system is used to record etching parameters and quality inspection results, providing data support for subsequent process optimization.

[0115] The femtosecond laser etching method of the perovskite film comprises the following steps:

[0116] Step 1: First, a femtosecond laser pulse is generated through a laser light source module, and the path and energy distribution of the laser beam are adjusted through a beam shaper and adaptive optical elements to ensure high-precision focusing of the laser beam on the surface of the perovskite film;

[0117] Step 2: The adjusted laser beam is guided to the surface of the perovskite film by the scanning mirror. The scanning system module controls the movement path of the laser beam to ensure the accuracy and uniformity of the etched pattern. The heat generated during the scanning process is efficiently dissipated through the partitioned cooling system of the thermal management system module to prevent overheating of the equipment and the film.

[0118] Step 3: The control system module coordinates the operation of the laser light source, optical path control, scanning system, and thermal management system modules through the central control computer to ensure the overall operation of the system;

[0119] Step 4: Multi-sensors are used to collect data during the etching process. The data fusion analysis platform transmits the data to the control system module. The intelligent control algorithm predicts and optimizes parameters based on the data and dynamically adjusts the laser parameters and scanning path.

[0120] Step 5: After etching is completed, the quality inspection module cleans and inspects the samples, and the inspection results are fed back to the control system module through the data recording system for further optimization of the etching process parameters.

[0121] It should be further explained that, in the specific implementation process, the optical element group and automatic alignment system in the optical path control module are used to ensure efficient transmission and precise focusing of the laser beam. At the same time, the intelligent management and dynamic optimization of the etching process are achieved through parameter prediction and optimization based on machine learning and a real-time monitoring system with multi-sensor fusion. In addition, the stability and consistency of the optical path are ensured by combining real-time wavefront monitoring and distortion correction as well as the optical element driving system, which solves the problem that traditional etching methods are difficult to maintain etching consistency and uniformity on large-area thin films, resulting in unstable and reduced device performance.

[0122] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0123] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A femtosecond laser etching system for perovskite thin films, characterized in that: The system includes: Laser source module for generating femtosecond laser pulses with high repetition rate, adjustable laser power, frequency and beam spread angle; An optical path control module is configured with an optical element group, an optical element alignment system, a beam shaper and an adaptive optical element, and is used to adjust the path, focus and energy distribution of the laser beam; wherein the adaptive optical element includes an adjustable deformable mirror and a liquid crystal spatial light modulator, wherein the adjustable deformable mirror is used to adjust the focus state of the laser beam in real time and compensate for thermal distortion and mechanical vibration in the optical system; and the liquid crystal spatial light modulator is used to adjust the phase and amplitude of the laser beam in real time; A scanning system module, including a motion platform and a scanning mirror, is used to achieve nanometer-level precision scanning of the laser beam on the surface of the perovskite film; Thermal management system module, used to control the temperature of each component of the system to prevent overheating of the equipment or thermal damage to the perovskite film due to the heat generated by laser etching; The control system module includes a central control computer, intelligent control algorithms, and a human-computer interaction interface for overall system control and management. It also uses machine learning-based parameter prediction and optimization to analyze etching data, predict etching quality, and automatically optimize laser parameters using machine learning models. Monitoring and feedback module, including high-resolution optical monitoring system, spectrum analyzer, temperature sensor and data fusion analysis platform, used to monitor the etching process in real time and provide feedback; Quality inspection module, used for sample cleaning and quality inspection after etching; Among them, the control system module also integrates an optical microscope, a spectrometer, and a temperature sensor, and realizes etching process monitoring and feedback through a data fusion analysis platform.

2. The femtosecond laser etching system for perovskite thin film according to claim 1, characterized in that: The laser light source module comprises: A pulse modulation unit for adjusting the energy, repetition rate, laser power, frequency and beam divergence angle of femtosecond laser pulses; Cooling system is used to maintain the operating temperature of the laser.

3. The femtosecond laser etching system for perovskite thin film according to claim 2, characterized in that: In the optical path control module, the optical element is made of high-purity quartz or molten silicon material; the surface of the optical element is coated with an anti-pollution coating; wherein the optical element group includes a high-quality reflector, a high-quality lens and a high-quality beam splitter, the high-quality reflector has low wavefront distortion and high optical transmission efficiency; the high-quality lens is used for focusing and collimating the laser beam; the high-quality beam splitter is used for dividing the laser beam into multiple sub-laser beams to achieve superposition of multiple laser beams.

4. The femtosecond laser etching system for perovskite thin film according to claim 3, characterized in that: The optical path control module comprises: Shack-Hartmann wavefront sensor, used to monitor the wavefront shape and distortion of the laser beam in real time and obtain monitoring data; The wavefront distortion correction algorithm adjusts the shape of the adaptive optical element in real time to compensate for the wavefront distortion based on the monitoring data of the wavefront sensor; The optical path control module uses a phase plate or a spatial light modulator to convert the Gaussian laser beam into a uniform flat-top spot to achieve uniform distribution of laser energy in a large etching area; An optical element alignment system comprises a nanometer-level adjustment stage and a fine-tuning drive, as well as an automatic alignment and calibration system, and monitors and adjusts the position of the optical element in real time through a Shack-Hartmann wavefront sensor and a feedback mechanism.

5. The femtosecond laser etching system for perovskite thin film according to claim 4, characterized in that: The wavefront distortion correction algorithm adjusts the shape of the adaptive optical element in real time based on the monitoring data of the wavefront sensor to compensate for the wavefront distortion. The steps are as follows: a: The monitoring data collected in real time by the Shack-Hartmann wavefront sensor is transmitted to the central control computer in the form of digital signals, and then the monitoring data is preprocessed, including denoising, normalization and filtering, to obtain wavefront distortion data; b: Then the wavefront distortion data is analyzed using Zernike polynomial expansion to identify and quantify the specific distortion mode, and the distortion amount of each distortion mode is calculated, including amplitude and phase information; c: Applying the least square method to calculate the distortion compensation parameters required to compensate the wavefront distortion based on the identified distortion mode and distortion amount; d: generating corresponding control instructions according to the calculated distortion compensation parameters; transmitting the control instructions to the adaptive optical element to adjust its surface shape to achieve compensation of wavefront distortion; e: Using real-time monitoring data, the new wavefront data is fed back to the central control computer through the data fusion analysis platform; and based on the feedback data, the wavefront distortion correction parameters are dynamically adjusted and optimized, and steps a to d are continuously iterated.

6. A femtosecond laser etching system for perovskite thin films according to claim 5, characterized in that: The scanning system module further comprises: Scanning path optimization algorithm, used to optimize the movement path of the laser beam; Optical element drive systems, including microsecond-level response drive systems and low-latency feedback mechanisms; The central control computer runs the control software, coordinates the operation of each submodule, and performs laser parameter setting and scanning path planning; The human-computer interaction interface provides an intuitive operation interface, which is convenient for operators to set and adjust etching parameters.

7. A femtosecond laser etching system for perovskite thin films according to claim 6, characterized in that: The thermal management system module comprises: The zoned cooling system divides the etching area into multiple independent cooling zones and adopts a modular cooling design to achieve efficient heat dissipation; The thermal simulation optimization module optimizes the layout and parameters of the cooling system based on the thermal simulation model to ensure uniform heat distribution.

8. The femtosecond laser etching system for perovskite thin film according to claim 7, characterized in that: The monitoring feedback module further comprises: High-resolution optical monitoring system, used to monitor the morphology and accuracy of the etched surface in real time and obtain etched surface data; Spectrum analyzer, used to analyze the spectral signals generated during the etching process, evaluate the material removal situation, and obtain material evaluation results; A temperature sensor is used to monitor the temperature change of the etching area and obtain etching temperature data; The data fusion analysis platform is used to integrate and analyze the etching surface data, material evaluation results and etching temperature data from various sensors in real time to provide support for intelligent control algorithms.

9. The femtosecond laser etching system for perovskite thin film according to claim 8, characterized in that: The quality inspection module further comprises: A cleaning system to remove residues from the etching process; Microscope inspection system, which uses a high-resolution microscope to inspect the etching quality and evaluate the etching depth and edge clarity; Data recording system for recording etching parameters and quality inspection results.

10. A femtosecond laser etching method for a perovskite film according to the femtosecond laser etching system for a perovskite film according to any one of claims 1 to 9, characterized in that: The steps include: Step 1: First, generate femtosecond laser pulses through the laser light source module, and adjust the path and energy distribution of the laser beam through the beam shaper and adaptive optical elements; Step 2: The adjusted laser beam is guided to the surface of the perovskite film by the scanning mirror, and the scanning system module controls the movement path of the laser beam; Step 3: The control system module coordinates the operation of the laser light source, optical path control, scanning system, and thermal management system modules through the central control computer; Step 4: Multi-sensors are used to collect data during the etching process. The data fusion analysis platform transmits the data to the control system module. The intelligent control algorithm predicts and optimizes parameters based on the data and dynamically adjusts the laser parameters and scanning path. Step 5: After etching is completed, the quality inspection module cleans and inspects the samples, and the inspection results are fed back to the control system module through the data recording system for further optimization of the etching process parameters.

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