Dual-path laser etching method and device for perovskite cells

Abstract

The present application relates to the technical field of laser etching, and discloses a dual-path laser etching method and device for a perovskite cell. The method comprises: performing deposition processing on a perovskite substrate to obtain a basic structure of a perovskite cell; performing optical parameter collection on the basic structure of the perovskite cell to generate structural parameter data; performing parameter sampling based on the structural parameter data to obtain an initial parameter group for dual-path laser etching; performing three-dimensional convex polyhedron construction and point coordinate projection on the initial parameter group for dual-path laser etching to obtain a dual-path laser etching process constraint model; performing mixed integer linear programming calculation on the front light path and the back light path to obtain optimal etching parameters; applying the optimal etching parameters to a dual-path laser system to perform synchronous etching processing on the basic structure of the perovskite cell to obtain an etched structure of the perovskite cell. The present application realizes precise control of etching parameters, realizes precise synchronization of dual light paths, and solves the problem of synchronous control in traditional processes.

Description

Technical Field

[0001] The present application relates to the field of laser etching technology, and in particular to a dual-path laser etching method and device for perovskite cells. Background Art

[0002] In the preparation process of perovskite solar cells, laser etching is a key process to achieve the partitioning of each functional layer of the cell and the patterning of the electrode. When processing multi-layer composite perovskite cells, the traditional single-path laser etching method often causes problems such as irregular etching edges and severe interlayer thermal damage due to the heat accumulation effect.

[0003] As perovskite cells develop towards large areas and high efficiency, the requirements for the accuracy and consistency of the etching process are constantly increasing. When processing large-area cells, the existing etching methods have problems such as uneven etching quality and difficulty in optimizing process parameters. Especially when processing multi-layer composite structures, a single optical path is difficult to simultaneously take into account the etching quality control of each layer, affecting the overall performance of the cell. Summary of the invention

[0004] The present application provides a dual-light path laser etching method and device for perovskite cells. The present application realizes precise control of etching parameters, realizes precise synchronization of dual light paths, and solves the synchronization control problem in traditional processes.

[0005] In a first aspect, the present application provides a dual-light path laser etching method for a perovskite cell, the dual-light path laser etching method for a perovskite cell comprising: The perovskite substrate is sequentially subjected to deposition treatments of a light absorption layer, an electron transport layer, a hole transport layer, and a metal electrode layer to obtain the basic structure of a perovskite cell; Collecting optical parameters of the perovskite battery basic structure to generate structural parameter data including interlayer thickness and optical properties; Based on the structural parameter data, the parameters of laser power, scanning speed and spot overlap rate are sampled to obtain an initial parameter group for dual-path laser etching; Performing three-dimensional convex polyhedron construction and point coordinate projection on the dual-path laser etching initial parameter group to obtain a dual-path laser etching process constraint model; According to the dual-light-path laser etching process constraint model, mixed integer linear programming calculations are performed on the front light path and the back light path to obtain optimal etching parameters including laser power, scanning speed, and incident angle; The optimal etching parameters are applied to a dual-path laser system to perform synchronous etching on the perovskite cell basic structure to obtain a perovskite cell etching structure.

[0006] The second aspect of the present application provides a dual-light path laser etching device for a perovskite cell, the dual-light path laser etching device for a perovskite cell comprising: A deposition processing module is used to sequentially deposit a light absorption layer, an electron transport layer, a hole transport layer, and a metal electrode layer on the perovskite substrate to obtain a perovskite battery basic structure; An optical parameter acquisition module, used to acquire optical parameters of the perovskite battery basic structure and generate structural parameter data including interlayer thickness and optical properties; A parameter sampling module, used for sampling the parameters of laser power, scanning speed and spot overlap rate based on the structural parameter data to obtain an initial parameter group for dual-path laser etching; A projection module, used for constructing a three-dimensional convex polyhedron and performing point coordinate projection on the dual-path laser etching initial parameter group to obtain a dual-path laser etching process constraint model; A calculation module, used for performing mixed integer linear programming calculation on the front light path and the back light path according to the dual-light path laser etching process constraint model to obtain optimal etching parameters including laser power, scanning speed, and incident angle; The synchronous etching module is used to apply the optimal etching parameters to a dual-path laser system to perform synchronous etching on the perovskite battery basic structure to obtain a perovskite battery etching structure.

[0007] The third aspect of the present application provides an electronic device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes the above-mentioned dual-path laser etching method for perovskite cells.

[0008] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned dual-path laser etching method for perovskite cells.

[0009] Compared with the prior art, the present application has the following beneficial effects: by introducing dual-path laser synchronous etching technology, the front and back collaborative processing is realized, the heat accumulation effect is effectively reduced, and the quality and precision of the etching edge are improved. A multi-step parameter optimization method is adopted to establish a systematic process parameter optimization process, realize the precise control of etching parameters, and overcome the limitations of traditional experience dependence. Through the construction of three-dimensional convex polyhedrons and mixed integer linear programming algorithms, a complete process constraint model is established, which provides a theoretical basis for parameter optimization and improves the reliability of the optimization results. An online monitoring method based on optical parameter acquisition is designed to realize real-time control of the etching process and ensure the stability and repeatability of the process. Through layered structure parameter acquisition and multi-layer heat transfer analysis, the etching characteristics of each functional layer are accurately grasped, and the etching quality of multi-layer composite structures is improved. The dual-path synchronous control and multi-pass superposition scanning strategy are adopted to significantly improve the etching uniformity of large-area batteries and improve the product yield. By introducing delay compensation and energy closed-loop control, the precise synchronization of the dual-path is achieved, solving the problem of synchronous control in traditional processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0011] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0012] Figure 1 It is a schematic flow chart of a dual-light-path laser etching method for a perovskite cell provided in an embodiment of the present invention; Figure 2 It is a schematic block diagram of the structure of a dual-light-path laser etching device for a perovskite cell provided in an embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0013] 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 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.

[0014] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0015] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0016] It should be further understood that the term "and / or" used in the specification and appended claims of this application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. Figure 1 , an embodiment of the dual-path laser etching method for perovskite cells in the embodiment of the present application includes: Step S100, depositing a light absorbing layer, an electron transport layer, a hole transport layer, and a metal electrode layer on a perovskite substrate in sequence to obtain a perovskite battery basic structure; It is understandable that the execution subject of the present application can be a dual-path laser etching device for a perovskite cell, or a terminal or a server, which is not specifically limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0017] Specifically, the perovskite substrate is subjected to plasma surface treatment to remove surface pollutants and increase the active functional groups on the substrate surface to form a surface activated substrate with good wettability and reactivity. Lead iodide and methylamine iodine are prepared into a mixed solution in a certain proportion, and a uniformly distributed coating operation is performed on the surface activated substrate using spin coating technology. Through the spin coating process, the solution is evenly spread under the action of centrifugal force, and a uniformly distributed perovskite precursor film layer is gradually formed. The uniformity of this film layer determines the integrity and performance of the subsequent perovskite crystal structure. The perovskite precursor film layer is subjected to temperature gradient annealing. Temperature gradient annealing is a process that can gradually regulate the heating rate and heating interval within a specific temperature range, which can effectively promote the directional growth of perovskite crystals, reduce defects and non-uniform areas, and form a light-absorbing layer with a regular crystal structure. As the core functional layer of the perovskite battery, the crystal quality of the light-absorbing layer has a decisive influence on the photoelectric conversion efficiency. After the light-absorbing layer is prepared, the zinc oxide nanoparticle solution is evenly distributed on the surface of the light-absorbing layer by a spraying process to form an electron transport precursor layer. By controlling the nozzle flow rate and scanning trajectory of the spraying equipment, the zinc oxide nanoparticles can be evenly distributed to ensure the conductivity and optical transparency of the subsequent electron transport layer. In order to improve the functional performance of the electron transport layer, the electron transport precursor layer is subjected to multi-segment temperature-controlled annealing. The annealing process gradually optimizes the crystal quality in different temperature ranges through the zone temperature control technology, improves the conductivity and stability of the material, and forms a complete electron transport layer. After the preparation of the electron transport layer is completed, it is placed in an inert atmosphere, and a hole transport layer is formed on its surface by an organic material evaporation process. By precisely controlling the substrate temperature, vacuum degree and evaporation rate of the evaporation equipment, a thin film with high-efficiency hole transport performance can be uniformly deposited on the electron transport layer, enhancing the carrier separation and transmission efficiency inside the battery. In order to optimize the interface performance of the hole transport layer, its surface is subjected to plasma treatment. This treatment step changes the chemical environment and energy level distribution on the surface of the film through the high energy effect of the plasma, forming a composite film structure with surface energy level regulation function. Reasonable regulation of the surface energy level can effectively reduce the interface recombination loss inside the battery and improve the injection and transmission efficiency of carriers. The composite thin film structure is input into the magnetron sputtering system for metal layer sputtering deposition, and a metal electrode layer with high conductivity and stability is formed on its surface by sputtering. The sputtering deposition process can achieve uniform metal electrode deposition by adjusting the composition of the sputtering target, the pressure of the working gas and the beam power, thereby enhancing the charge collection and conduction performance of the perovskite cell. Through the above preparation process, the basic structure of the perovskite cell including the light absorption layer, the electron transport layer, the hole transport layer and the metal electrode layer is obtained.

[0018] Step S200, collecting optical parameters of the basic structure of the perovskite battery to generate structural parameter data including interlayer thickness and optical properties; Specifically, a vertically incident light beam is applied to the surface of the basic structure of the perovskite battery, and the reflected light signal is collected through a precise optical detection device, and the original light intensity data containing the incident light intensity and the reflected light intensity information is recorded. The original light intensity data is decomposed into spectral information of different bands by wavelength decomposition. Through the wavelength decomposition technology, the original light intensity data is refined into sub-band spectral data, and the decomposed data can accurately reflect the optical response characteristics between material layers under different light wavelengths. The sub-band spectral data is Fourier transformed to convert the time domain signal into a frequency domain signal to obtain frequency domain characteristic data, characterize the propagation characteristics of the light signal inside the battery structure, and facilitate the analysis of the light intensity response behavior of the reflection interface. By performing light intensity response analysis on the frequency domain characteristic data, the interface reflection characteristic data is extracted to reflect the important parameters such as the reflection intensity, phase change and interface roughness of each layer of the material interface under the action of light waves. The interface reflection characteristic data is input into the wave propagation equation, and the reflection characteristics of each interface are calculated to obtain the propagation characteristic data in each layer, including the refraction, diffraction and absorption information when the light wave propagates in each layer of the material, revealing the spatial distribution of the optical characteristics inside the material. Polarization state analysis is performed on the propagation characteristic data within the layer to obtain the optical hysteresis vector of each layer of material. The optical hysteresis vector is the core parameter that describes the delay change caused by the difference in optical path when polarized light propagates in a multilayer structure. It is closely related to the optical anisotropy of the material and the interaction between layers. The optical hysteresis vector is processed by phase decoupling technology to extract the polarization characteristic data of the interface. These data characterize the polarization state change of light waves at each interface of the multilayer structure. The interface polarization characteristic data is input into the thin film calculation model, and the interference field data containing the interference intensity distribution is obtained by simulating and calculating the interlayer optical interference effect. The interference field data is the core representation of the optical behavior of the thin film structure, which can reflect the thickness change between material layers and the modulation effect of interference on the optical signal. By processing the interference field data, the thickness distribution data of each layer of material is calculated to quantify the physical thickness of each layer. At the same time, these thickness distribution data are visualized by spatial scanning mapping technology to form the distribution characteristics of the interlayer structure, showing the spatial thickness change and distribution law of each component layer of the battery. On the basis of obtaining these interlayer structure data, the key parameters such as the refractive index, absorption coefficient, and optical band gap of each layer are analyzed through the optical characteristic parameter extraction technology to generate a characteristic data set containing multiple optical properties. Multi-dimensional feature combinations are performed on the optical characteristic data to generate an optical characteristic mapping matrix. This matrix can integrate and quantify the associations between multi-dimensional characteristic data and provide a global description of optical performance. The interlayer structure distribution characteristics are fused with the optical characteristic mapping matrix, and the thickness, spatial distribution and optical performance characteristics are integrated through the data fusion algorithm to generate structural parameter data.

[0019] Step S300, sampling parameters of laser power, scanning speed and spot overlap rate based on the structural parameter data to obtain an initial parameter group for dual-path laser etching; It should be noted that the optical response of each layer of the perovskite battery is analyzed and calculated using the structural parameter data, and the absorption coefficient matrix of each layer of material is obtained through the interlayer optical response calculation model to describe the energy absorption law of light in the material. The absorption coefficient matrix is ​​numerically discretized and converted into a discrete data form that is easier to handle, and the absorption intensity distribution data reflecting the interlayer light energy absorption characteristics are obtained. The interlayer absorption intensity distribution data is input into the heat conduction model to establish a material response analysis framework based on thermal characteristics. Through the calculation of the heat conduction model, the thermal response distribution data of each layer of material is obtained, reflecting the distribution of laser energy after it is converted into thermal energy inside the material. In order to simulate the transfer law of interlayer thermal energy, multi-layer heat transfer calculation is performed on the thermal response distribution data to obtain interlayer heat transfer characteristic data. By considering factors such as thermal diffusion, heat source distribution and material thermal conductivity, the thermal coupling characteristics between the layers of the material are described. Based on the interlayer heat transfer characteristic data, an energy density distribution function is established, which characterizes the spatial distribution and power threshold characteristics of laser energy in the material. In order to define the laser parameters more accurately, the energy density distribution function is partitioned and integrated to obtain layered laser power threshold data. The partition integration process can refine the power requirements of each layer, so that the subsequent laser power setting is more in line with the actual material characteristics. By analyzing the layered laser power threshold data, the numerical range of the laser power is divided into intervals, and on this basis, laser power sampling data is generated to provide the possibility of combining multiple power parameters. Spot energy superposition calculation is performed based on laser power sampling data. Based on the energy distribution characteristics of the spot, the spot overlap rate calculation model is used to analyze the coverage of the laser spot and the material during the scanning process, and the spot overlap rate sampling data is obtained to reflect the uniformity of laser processing and the efficiency of material removal. The laser power sampling data and the spot overlap rate sampling data are input into the scanning speed calculation model, and the speed response characteristic data related to the scanning speed is calculated by analyzing the thermal response time of the material and the laser energy distribution law. In order to make the scanning speed more suitable for specific processing requirements, the speed response characteristic data is sampled in intervals to generate scanning speed sampling data. By combining the laser power sampling data, the spot overlap rate sampling data and the scanning speed sampling data with global parameters, an original sampling data group containing multiple parameter configurations is constructed. In order to ensure the physical feasibility of the parameter combination and the quality of the etching process, the original sampling data group is subjected to boundary constraint screening. The screening process sets the physical constraints of laser power, scanning speed and spot overlap rate as well as the process optimization target to eliminate parameter combinations that do not meet the requirements. The remaining parameter sets after screening constitute the initial parameter set of dual-path laser etching that meets the process requirements.

[0020] Step S400, constructing a three-dimensional convex polyhedron and performing point coordinate projection on the dual-path laser etching initial parameter group to obtain a dual-path laser etching process constraint model; Specifically, the initial parameter group of dual-path laser etching is mapped in parameter space, and the numerical range of each parameter is mapped to a point set in three-dimensional space to generate a three-dimensional parameter point set, which reflects the diversity and correlation of the initial parameter group in three-dimensional space. The nearest neighbor search is performed on the three-dimensional parameter point set, the neighboring relationship of the point set in space is calculated, and the spatial distribution data of the point set is generated. The Delaunay triangulation technology is applied to the spatial distribution data of the point set, and the initial triangular mesh data is generated by constructing a triangular mesh connecting adjacent points. Delaunay triangulation can maximize the minimum angle in the mesh, ensure the stability of the triangulation and the rationality of the geometric structure. On this basis, the boundary of the initial triangular mesh data is extracted to generate convex hull boundary data. The convex hull boundary represents the minimum convex polyhedron outside the point set. The convex hull boundary data is reconstructed by patch operation, and the discrete boundary data is generated into a complete three-dimensional convex polyhedron mesh data. Then, the three-dimensional convex polyhedron mesh data is mesh optimized to eliminate redundant points and abnormal mesh units, and a regularized mesh structure is obtained by adjusting the connection relationship and unit shape of the mesh. Based on the regularized grid structure, the main direction of the grid data is extracted through principal component analysis to obtain the main direction projection data, which reflects the main distribution direction and geometric characteristics of the three-dimensional grid structure. On this basis, the main direction projection data is transformed to map the information of the three-dimensional space to the two-dimensional projection plane to generate the projection plane parameters. The normal vector of the projection plane parameters is calculated to obtain the projection direction data, which describes the directionality of the projection plane in the three-dimensional space. Based on the projection direction data, the three-dimensional parameter point set is transformed into a two-dimensional projection point set by point coordinate projection transformation. The two-dimensional projection point set shows the distribution form of the initial parameter group under different projection directions in the two-dimensional space. On the basis of the projection point set, the minimum convex hull containing all projection points is generated through the convex hull generation algorithm to obtain the projection area boundary data, which describes the effective range of the parameter distribution in the projection plane. In order to make the projection area boundary data smoother and adapt to the actual process requirements, interpolation fitting operations are performed on it to generate a continuous constraint boundary curve. The constraint boundary curve eliminates the discreteness on the boundary through the fitting algorithm, so that the curve can better reflect the actual range and change law of the parameter distribution. The constraint boundary curve is parameterized and expressed in the form of a mathematical function to generate a boundary constraint function that describes the boundary shape. Based on the boundary constraint function, the parameter space is divided into feasible domains to generate process parameter constraint intervals including laser power, scanning speed, spot overlap rate, etc. By associating the process parameter constraint intervals with the three-dimensional convex polyhedron mesh data, a dual-path laser etching process constraint model containing geometric boundaries and physical constraints is generated.

[0021] Step S500, performing mixed integer linear programming calculations on the front optical path and the back optical path according to the dual-optical path laser etching process constraint model to obtain optimal etching parameters including laser power, scanning speed, and incident angle; Specifically, the dual-path laser etching process constraint model is decomposed into optical paths, and the constraint interval data corresponding to the front optical path and the back optical path are extracted respectively. By mapping the parameters of the front and back constraint intervals, an optical path coupling matrix is ​​established to reflect the parameter association and influence relationship between the front and back optical paths. The objective function is constructed based on the optical path coupling matrix, and a linear objective equation containing optical path parameters is set. The design of the objective equation takes into account the comprehensive influence of laser power, scanning speed and incident angle on etching quality, uniformity and efficiency, and aims to optimize the etching effect. While constructing the objective function, the discrete variables and continuous variables in the mixed integer optimization problem are decoupled by the integer variable separation method to generate mixed integer constraint conditions with clear constraint relationships. The mixed integer constraint conditions are input into the branch and bound model to comprehensively explore the initial solution space of the problem. The branch and bound model generates initial solution space data by gradually refining the solution space, eliminating infeasible solutions and retaining potential optimal solutions. In order to improve the computational efficiency, the initial solution space data is linearly relaxed and a set of continuous solution vectors are quickly generated by ignoring integer constraints. The continuous solution vector is integerized to meet the actual process requirements. Through the integerization operation, the continuous solution is converted into discrete solution set data, which contains the feasible laser power, scanning speed and discrete values ​​of related parameters. Based on the discrete solution set data, branch search is performed to extract the local optimal solution data. The local optimal solution can reflect the optimal combination of parameters under different etching conditions by refining and optimizing the local solution space. In order to ensure the globality of the optimal solution, the local optimal solution data is input into the simplex method model for linear programming iteration. The simplex method generates global solution space data by iteratively solving the linear objective equation. In the global solution space, the solution range is optimized by cutting plane generation technology, the infeasible area is eliminated, and the optimal solution interval is finally determined. The optimal solution interval describes the optimal parameter range of laser power, scanning speed and incident angle. The parameters in the optimal solution interval are discretized and reconstructed to refine the laser power parameters and scanning speed parameters of the front optical path and the back optical path. By analyzing these parameters and combining the physical characteristics of the optical path system, the incident angles of the front and back optical paths are optimized and calculated to obtain the optimal optical path angle parameters. The laser power parameters, scanning speed parameters and incident angle parameters are combined to form an optimal etching parameter set including the three core parameters.

[0022] Step S600: Apply the optimal etching parameters to the dual-path laser system to perform synchronous etching on the basic structure of the perovskite cell to obtain the perovskite cell etching structure.

[0023] Specifically, the optimal etching parameters are input into the dual-optical path synchronization controller, and the controller configures the parameters of the front optical path laser and the back optical path laser according to these parameters, and generates a dual-optical path synchronization control signal for the etching process. These signals are processed through precise timing synchronization to generate a synchronization trigger sequence to ensure the simultaneous start-up and synchronous operation of the front and back lasers. The synchronization trigger sequence is compensated for the optical path delay to eliminate the asynchronism caused by equipment differences or signal delays between the front and back optical paths, and a delay compensation sequence is generated. Based on the delay compensation sequence, the laser power of the optical path is precisely modulated to obtain a dual-optical path power control signal. The dual-optical path power control signal is input into the laser energy feedback system, and through real-time energy monitoring and regulation, the energy closed-loop control of the dual-optical path laser output is realized to obtain a steady-state energy output. The closed-loop control technology effectively avoids the influence of power fluctuations on the etching quality through dynamic adjustment of the feedback data, ensuring that the laser energy is always maintained within the target range. After obtaining steady-state energy output, the laser beam is subjected to spot shaping processing, and the energy distribution of the laser beam is optimized through a precise optical control system to generate dual-path spot distribution data reflecting the spot shape and distribution characteristics. Based on the spot distribution data, the spot positioning operation is implemented to clarify the action area of ​​the laser on the basic structure of the perovskite battery and generate accurate scanning path data. After the scanning path data is input into the galvanometer control system, the synchronous control of the dual-path scanning is realized through high-precision motion control technology to generate a synchronous motion trajectory to ensure that the scanning paths on the front and back are completely consistent. On this basis, the synchronous motion trajectory is optimized to eliminate redundant paths and redundant motions to obtain an optimized motion trajectory. Based on the optimized motion trajectory, the basic structure of the perovskite battery is subjected to dual-path synchronous scanning to complete the initial etching process and form the initial etching structure. The initial etching structure is subjected to multiple superimposed scanning. Through the cumulative effect of each scan, the etching depth, edge clarity and surface uniformity are gradually optimized to form a multiple etching structure. The surface morphology of the multiple etched structures is analyzed, and the shape characteristics and error distribution of the etched areas are accurately evaluated by surface morphology measurement technology. Based on the analysis results, shape compensation processing is performed on the etched structure to correct the local non-uniformity caused by material characteristics or processing deviations, and an optimized compensated etched structure is obtained. The surface of the compensated etched structure is cleaned to remove the debris, dust and oxides remaining in the etching process to obtain a smooth and clean perovskite cell etched structure.

[0024] In the embodiment of the present application, by introducing the dual-path laser synchronous etching technology, the front and back collaborative processing is achieved, the heat accumulation effect is effectively reduced, and the quality and precision of the etching edge are improved. A multi-step parameter optimization method is adopted to establish a systematic process parameter optimization process, achieve precise control of etching parameters, and overcome the limitations of traditional experience dependence. Through the construction of three-dimensional convex polyhedrons and mixed integer linear programming algorithms, a complete process constraint model is established, which provides a theoretical basis for parameter optimization and improves the reliability of the optimization results. An online monitoring method based on optical parameter acquisition is designed to achieve real-time control of the etching process and ensure the stability and repeatability of the process. Through layered structure parameter acquisition and multi-layer heat transfer analysis, the etching characteristics of each functional layer are accurately grasped, and the etching quality of the multi-layer composite structure is improved. The dual-path synchronous control and multi-pass superposition scanning strategy are adopted to significantly improve the etching uniformity of large-area batteries and improve the product yield. By introducing delay compensation and energy closed-loop control, the precise synchronization of the dual-path is achieved, solving the problem of synchronous control in traditional processes.

[0025] In a specific embodiment, the process of executing step S100 may specifically include the following steps: Plasma surface treatment is performed on the perovskite substrate to obtain a surface activated substrate, and a mixed solution of lead iodide and methylamine iodine is spin-coated on the surface activated substrate to obtain a uniformly distributed perovskite precursor film layer; The perovskite precursor film layer is subjected to temperature gradient annealing to obtain a light-absorbing layer having a crystal structure, and a zinc oxide nanoparticle solution is input into a spraying system to spray the light-absorbing layer to obtain an electron transport precursor layer; Performing multi-section temperature-controlled annealing on the electron transport precursor layer to obtain an electron transport layer, and placing the electron transport layer in an inert atmosphere for organic material evaporation treatment to obtain a hole transport layer; The surface of the hole transport layer is subjected to plasma treatment to obtain a composite thin film structure with surface energy level regulation, and the composite thin film structure with surface energy level regulation is input into a magnetron sputtering system for metal layer sputtering deposition to obtain the basic structure of the perovskite battery.

[0026] Specifically, the perovskite substrate is subjected to plasma surface treatment. The high energy of the plasma removes organic pollutants and oxides on the substrate surface, and introduces active functional groups, such as hydroxyl or carboxyl groups, to improve surface wettability and adhesion. After the surface activation is completed, lead iodide and methylamine iodine are dissolved in a solvent in a certain proportion to prepare a mixed solution. The solution is evenly distributed on the substrate surface through a spin coating process. During the spin coating process, the uniformity of the solution is related to the rotation speed. and viscosity Closely related to its thickness Estimated by the following formula: ; in, is a constant related to the viscosity of the solution, is the spin coating kinetic index. By optimizing the spin speed and solution concentration, a uniformly distributed perovskite precursor film layer is formed. The perovskite precursor film layer is subjected to temperature gradient annealing to promote the growth and formation of perovskite crystals. Temperature gradient annealing is performed by gradually increasing the temperature. The way of driving solvent evaporation and crystal self-assembly is expressed as: ; in, Indicates the degree of crystal growth. and are the rate constants of solvent evaporation and crystal growth, respectively. is the activation energy, is the gas constant, is the absolute temperature. By optimizing the annealing temperature distribution, a light-absorbing layer with a regular crystal structure is obtained. After the light-absorbing layer is prepared, the zinc oxide nanoparticle (ZnO) solution is input into the spraying system, and the nanoparticles are evenly distributed on the surface of the light-absorbing layer by spraying technology to form an electron transport precursor layer. The coverage of the spraying process Expressed as ; in, is the coverage area of ​​the sprayed particles, By adjusting the spraying rate and particle concentration, the coverage is close to The electron transport precursor layer is subjected to multi-zone temperature controlled annealing. Through the zone temperature control method, the material undergoes different structural evolutions in different temperature zones to form an electron transport layer with excellent electrical conductivity. Its thermal conductivity and conductivity The optimization of is expressed by the Wiedemann-Franz law: ; in, is the Lorenz constant, is the absolute temperature. Through annealing optimization, , thereby enhancing the electron transport performance. The electron transport layer is placed in an inert atmosphere, and the hole transport layer is deposited using an organic material evaporation process. The deposition rate of organic evaporation Described by the following formula: ; in, is the vapor pressure of the evaporating substance, is the molecular mass, is the Boltzmann constant, is the evaporation temperature. By precisely controlling the temperature and vapor flow rate, a uniform and dense hole transport layer is formed. After the hole transport layer is completed, its surface is subjected to plasma treatment, and the surface energy level distribution is adjusted by introducing specific functional groups to form a composite film structure with surface energy level regulation. The composite film structure is input into the magnetron sputtering system, and the metal electrode layer is formed by sputtering deposition of the metal target. The deposition rate of magnetron sputtering is With power and working pressure The relationship is: ; in, is a constant related to materials and sputtering equipment. By optimizing the sputtering parameters, a low-resistance, high-stability metal layer is formed to complete the preparation of the entire perovskite cell infrastructure.

[0027] In a specific embodiment, the process of executing step S200 may specifically include the following steps: Apply a vertical incident light beam to the basic structure of the perovskite cell and collect reflected light signals to obtain original light intensity data, and perform wavelength decomposition on the original light intensity data to obtain sub-band spectrum data; Performing Fourier transformation on the sub-band spectrum data to obtain frequency domain characteristic data, and performing light intensity response analysis on the frequency domain characteristic data to obtain interface reflection characteristic data; Input the interface reflection characteristic data into the wave propagation equation, calculate the reflection characteristics of each interface, and obtain the intra-layer propagation characteristic data; Perform polarization state analysis on the propagation characteristic data within the layer to obtain the optical hysteresis vector of each layer, and perform phase decoupling on the optical hysteresis vector to obtain the interface polarization characteristic data; The interface polarization characteristic data is input into the thin film calculation model, and the interlayer optical interference effect is calculated and processed to obtain the interference field data; The interlayer thickness is calculated for the interference field data to obtain the thickness distribution data of each layer, and the thickness distribution data of each layer is spatially scanned and mapped to obtain the interlayer structure distribution characteristics; Extract optical characteristic parameters from the interlayer structure distribution characteristics to obtain optical characteristic data of each layer, and perform multi-dimensional feature combination on the optical characteristic data to obtain an optical characteristic mapping matrix; The interlayer structure distribution characteristics and the optical property mapping matrix are fused to obtain the structural parameter data.

[0028] Specifically, by applying a vertical incident light beam and using a highly sensitive detection device to collect the reflected light signal, the original light intensity data reflecting the interaction between light and the multilayer structure of the perovskite cell is obtained. The reflectivity formula is described as: ; in, is the reflectivity, is the incident light intensity. It is closely related to the wavelength (λ) of the incident light and the optical properties of the material. The original light intensity data is decomposed by wavelength, and separated into sub-band spectral data of different wavelengths using a spectrometer or Fourier spectrometer to obtain the light intensity distribution of each band. These sub-band spectral data are Fourier transformed and converted into the frequency domain to extract the frequency domain feature data. The formula for Fourier transform is: ; in, is the frequency domain feature data, is the spatial frequency, is the light intensity distribution in the wavelength domain. Through Fourier transform, the contribution of different frequency components in the signal is separated, so as to extract the optical properties related to each layer of material. The light intensity response analysis is performed on the frequency domain characteristic data to calculate the reflection characteristics generated by the interaction between light and different interfaces. The interface reflection characteristics are calculated by the Fresnel equation, and its expression is: ; in, and are the refractive indices of the incident medium and the transmission medium, respectively, and is the angle of incidence and the angle of refraction. The reflection characteristic data describes the optical behavior of each interface. The interface reflection characteristic data is input into the wave propagation equation to simulate the propagation behavior of light in the multilayer structure. The basic equation for wave propagation is the Helmholtz equation: ; in, is the electric field strength, is the wave vector, is the refractive index of the material. By numerically solving the equation, the propagation characteristic data of light in each layer, such as phase change and amplitude attenuation, are obtained. The polarization state analysis of the propagation characteristic data within the layer is performed to extract the polarization characteristics of the light. The polarization state of light can be expressed by the Jones vector as follows: ; in, and Light in and The electric field component in the direction of the light is extracted from the analysis results to describe the effect of the material layer on the polarized light. The optical hysteresis vector is processed by phase decoupling technology to extract the interface polarization characteristic data. The interface polarization characteristic data is input into the thin film calculation model to simulate the interference effect of light between layers. The calculation formula for the interference field data is: ; in, and are the intensities of the two light beams, is the phase difference. The interference field data provides a complete description of the optical interference pattern and is used to analyze the interlayer optical properties. Based on the interference field data, the interlayer thickness is calculated. For each layer, its thickness The phase relationship is calculated as: ; in, is the phase difference, is the refractive index. After the thickness distribution data is spatially scanned and mapped, the interlayer structure distribution characteristics are generated to reflect the thickness uniformity of each layer of material. On this basis, the optical characteristic parameters of the interlayer structure distribution characteristics are extracted, such as the refractive index , absorption coefficient and the optical band gap . These parameters are extracted by the following formula: ; in, is the extinction coefficient, is the wavelength corresponding to the absorption edge, is Planck's constant, The extracted optical property data is combined with multi-dimensional features to generate an optical property mapping matrix, which describes the comprehensive optical behavior of each layer. The interlayer structure distribution characteristics are fused with the optical property mapping matrix, and multivariate statistical analysis is used to generate structural parameter data, including key information such as thickness, refractive index, and absorption coefficient.

[0029] In a specific embodiment, the process of executing step S300 may specifically include the following steps: The interlayer optical response is calculated for the structural parameter data to obtain the absorption coefficient matrix of each layer material, and the absorption coefficient matrix is ​​numerically discretized to obtain the interlayer absorption intensity distribution data; Input the interlayer absorption intensity distribution data into the heat conduction model to obtain the thermal response distribution data of each layer, and perform multi-layer heat transfer calculation on the thermal response distribution data to obtain the interlayer heat transfer characteristic data; An energy density distribution function is established based on the interlayer heat transfer characteristic data, and the energy density distribution function is subjected to partition integral operation to obtain the layered laser power threshold data; The layered laser power threshold data is divided into parameter intervals to obtain laser power sampling data, and spot energy superposition calculation is performed based on the laser power sampling data to obtain spot overlap rate sampling data; Inputting the laser power sampling data and the spot overlap rate sampling data into the scanning speed calculation model to obtain the speed response characteristic data, and performing interval sampling on the speed response characteristic data to obtain the scanning speed sampling data; The laser power sampling data, the spot overlap rate sampling data and the scanning speed sampling data are combined to obtain an original sampling data group, and the original sampling data group is subjected to boundary constraint screening to obtain an initial parameter group for dual-path laser etching.

[0030] Specifically, the interlayer optical response calculation is performed on the structural parameter data, and the absorption coefficient matrix of each layer is calculated based on the optical properties of the material. By the refractive index of the material and extinction coefficient Use the following formula to obtain: ; in, is the wavelength of light, is an optical constant related to the absorption characteristics of the material. The calculation results are organized into a matrix form to construct a complete absorption coefficient matrix , each element of which Indicates Layer material at wavelength The absorption coefficient matrix is ​​numerically discretized to convert continuous spectral data into segmented data for subsequent processing. The absorption intensity distribution of each layer of material is calculated by numerical integration methods, such as rectangular integration method or trapezoidal integration method. , the formula is: ; in, is the intensity distribution of the incident light, and are the upper and lower limits of the spectral range respectively. The interlayer absorption intensity distribution data is input into the thermal conduction model to calculate the thermal response distribution of each layer. Based on Fourier's heat conduction law, the thermal conduction model is expressed as: ; in, It is The temperature distribution of the layer, is the thermal conductivity, is the power density of the absorption intensity converted into heat, is the material density, is the specific heat capacity. By numerically solving the partial differential equation, we obtain the thermal response distribution data , describing the temperature change within the material layer. Perform multi-layer heat transfer calculations on the thermal response distribution data and analyze the inter-layer heat transfer characteristics. Calculate the inter-layer heat flow through the continuity condition of the interface heat flow : ; in, It is Layer and The interface position of the layer. The heat transfer calculation results reveal the distribution and transfer characteristics of heat between different material layers. Based on the interlayer heat transfer characteristic data, the energy density distribution function is established , whose expression is: ; in, is the thickness of each layer, is the local absorption intensity. Perform partition integration on this function to calculate the layered laser power threshold data : ; Divide the layered laser power threshold data into parameter intervals to generate laser power sampling data . Combined with the calculation formula of spot overlap rate: ; in, is the spot overlap ratio, is the spot radius, is the scanning speed, Get the spot overlap rate sampling data These data reflect the energy coverage and uniformity of the etching process. and Input the scanning speed calculation model and obtain the speed response characteristic data based on the thermal diffusion characteristics of the material. Thermal diffusion coefficient Defined as: ; Combined thermal diffusion time : ; in, is the scanning speed sampling data. , and The parameter combination is used to form the original sampling data group, and the boundary constraints are combined for screening. For example, the laser power is within the allowable range of the material, and the spot overlap rate ensures the processing uniformity. After screening, the initial parameter group of dual-path laser etching is obtained.

[0031] In a specific embodiment, the process of executing step S400 may specifically include the following steps: Perform parameter space mapping on the initial parameter group of dual-path laser etching to obtain a three-dimensional parameter point set, and perform nearest neighbor search on the three-dimensional parameter point set to obtain point set spatial distribution data; Perform Delaunay triangulation on the spatial distribution data of the point set to obtain initial triangular mesh data, and perform boundary extraction on the initial triangular mesh data to obtain convex hull boundary data; Performing facet reconstruction on the convex hull boundary data to obtain three-dimensional convex polyhedron mesh data, and performing mesh optimization on the three-dimensional convex polyhedron mesh data to obtain a regularized mesh structure; Based on the regularized grid structure, principal component analysis is performed to obtain the main direction projection data, and the main direction projection data is transformed into coordinates to obtain the projection plane parameters; Calculate the normal vector of the projection plane parameters to obtain projection direction data, and perform point coordinate projection transformation based on the projection direction data to obtain a two-dimensional projection point set; The convex hull is generated based on the two-dimensional projection point set to obtain the projection area boundary data, and the projection area boundary data is interpolated and fitted to obtain the constraint boundary curve; The constraint boundary curve is parameterized to obtain the boundary constraint function, and the feasible domain is divided based on the boundary constraint function to obtain the process parameter constraint interval. The process parameter constraint interval is data-associated with the three-dimensional convex polyhedron mesh data to obtain the dual-path laser etching process constraint model.

[0032] Specifically, the initial parameter group is mapped into parameter space, and the laser power , Scanning speed and spot overlap As parameter coordinate axes, construct a three-dimensional parameter space point set , where each point Represents a parameter combination. Point set The distribution in three-dimensional space reflects the diversity of the initial parameter group. The point set is searched by the nearest neighbor algorithm. Perform analysis, calculate the distance between each point and its neighboring points, and obtain the spatial distribution data of the point set The distance calculation formula for the nearest neighbor search is: ; in, Indicate point and Point The Euclidean distance between them. These distance data reveal the clustering or dispersion characteristics of the parameter points in space. Delaunay triangulation is performed on the point set spatial distribution data D, and the initial triangular mesh data is constructed by connecting the nearest neighbor points in the point set. The geometric characteristics of Delaunay triangulation ensure that the circumscribed circle of each triangle does not contain other points, generating a stable and reasonable triangular mesh. The initial triangular mesh data is represented as ,in It is by point , , The initial triangular mesh data Perform boundary extraction to determine the convex hull boundary of the point set by examining the outer edges of the grid The convex hull boundary describes the outermost point set in the parameter point set, which is generated by scanning or fast convex hull algorithm and meets the following conditions: ; in, is the normal vector to the boundary plane, is the boundary position constant. For the convex hull boundary data Perform face reconstruction to transform discrete boundary points into continuous three-dimensional convex polyhedron mesh data M. In order to improve the mesh quality, Mesh optimization is performed to obtain a regularized mesh structure by adjusting the positions of mesh vertices and the connection relationship of edges. The goal of mesh optimization is to maximize the shape quality factor of each mesh unit: ; in, is the quality factor of the grid unit, and the optimization process makes Maximization. Based on regularized grid structure , perform principal component analysis and extract the main direction characteristics of the data. By calculating the covariance matrix of the grid vertex coordinates And decompose its eigenvalues ​​to obtain the main direction projection data. The calculation formula of the covariance matrix is: ; in, is the mean vector of the point set, is the number of points. The direction corresponding to the eigenvector is the main direction. The main direction projection data is transformed into coordinates, and the three-dimensional grid data is mapped to the two-dimensional plane to obtain the projection plane parameters. The projection formula is: ; in, is the eigenvector matrix of principal component analysis, is the projection point. Calculate the normal vector for the projection plane parameters using the cross product formula: ; Get the normal vector , and perform point coordinate projection transformation based on the normal vector to generate a two-dimensional projection point set. Based on the two-dimensional projection point set, the projection area boundary data is obtained through the convex hull generation algorithm, and the discrete boundary is converted into a continuous constraint boundary curve through interpolation fitting. The interpolation fitting adopts B-spline interpolation, and its formula is: ; in, is the boundary curve, is the B-spline basis function, is the control point. Parameterize the constraint boundary curve to generate the boundary constraint function , and divide the feasible region based on the constraint function. The expression of the constraint function is: ; Combine the process parameter constraint interval with the three-dimensional convex polyhedron mesh data Data association is performed, and the geometric and physical parameter characteristics are combined to finally obtain the dual-path laser etching process constraint model.

[0033] In a specific embodiment, the process of executing step S500 may specifically include the following steps: The dual-path laser etching process constraint model is decomposed into the front light path and the back light path to obtain the front constraint interval and the back constraint interval, and the parameters of the front constraint interval and the back constraint interval are mapped to obtain the light path coupling matrix; The objective function is constructed for the optical path coupling matrix to obtain the linear objective equation containing the optical path parameters, and the linear objective equation is separated into integer variables to obtain mixed integer constraints; Inputting mixed integer constraints into the branch and bound model to obtain initial solution space data, and performing linear relaxation on the initial solution space data to obtain a continuous solution vector; Integer processing is performed on the continuous solution vector to obtain discrete solution set data, and branch search is performed based on the discrete solution set data to obtain local optimal solution data; Input the local optimal solution data into the simplex method model, perform linear programming iteration, obtain the global solution space data, and generate cutting planes for the global solution space data to obtain the optimal solution interval; Discrete parameter reconstruction is performed on the optimal solution interval to obtain laser power parameters and scanning speed parameters of the front optical path and the back optical path, and the optical path angle is optimized based on the laser power parameters and the scanning speed parameters to obtain the incident angle parameters; The laser power parameters, scanning speed parameters and incident angle parameters are combined to obtain the optimal etching parameters.

[0034] Specifically, the dual-path laser etching process constraint model is decomposed into light paths, and the parameters corresponding to the front light path and the back light path in the model are extracted. The constraint interval is divided based on the laser power. )、Scanning speed and spot overlap For the front optical path, the constraint interval is expressed as , Similarly, for the back light path, the constraint interval is , . Parameter mapping is performed on the front constraint interval and the back constraint interval to form an optical path coupling matrix , where each element of the matrix Indicates The optical path Parameters. Specifically defined as: ; Optical coupling matrix It reflects the coupling relationship between the front and back optical paths in laser parameters and provides a mathematical description of the optimized etching parameters. , construct an objective function, the goal is to minimize or maximize certain process indicators (such as etching efficiency or uniformity). The objective function is expressed as a linear equation: ; in, is the objective function value, is the weight coefficient, which is used to represent the influence weight of each parameter on the target. After decomposing the objective function into integer variables and continuous variables, mixed integer constraints are obtained, such as: ; These constraints ensure that the laser power is a discrete value, the scanning speed and the spot overlap rate are continuous variables, and the physical limitations of the process are met. The mixed integer constraints are input into the branch and bound model, and the initial solution space is divided by the tree search method. Initial solution space data is a set containing all possible solutions. Perform linear relaxation, that is, ignore the constraints of integer variables and treat all variables as continuous variables. The objective function becomes a pure linear programming problem, and its solution is a continuous solution vector , obtained by solving the following equation: ; in, and are constraint matrices and vectors, is the target coefficient vector. For the continuous solution vector Perform integer processing, round off the discrete variables or use heuristic methods to adjust them to integer values ​​to obtain discrete solution set data .based on Perform branch search to further refine the solution of each subspace and extract the local optimal solution data . The local optimal solution data Input the simplex method model and optimize the global solution space data through linear programming iteration. In the global solution space, the infeasible area is eliminated by the cutting plane method to generate the optimal solution interval. The cutting plane generation formula is: Cutting Plane: ; in, and The constraints are generated by the cutting plane method. Discrete the optimal solution interval and reconstruct the laser power parameters of the front and back optical paths. and scanning speed parameters , and optimize the optical path angle based on these parameters . Incident angle parameter Calculated by the following formula: ; in, and are the refractive indices of the front light path and the back light path, respectively. is the laser incident angle. The laser power parameters, scanning speed parameters and incident angle parameters are combined to generate the optimal etching parameters.

[0035] In a specific embodiment, the process of executing step S600 may specifically include the following steps: The optimal etching parameters are input into the dual-optical path synchronization controller, the parameters of the front optical path laser and the back optical path laser are configured to obtain the dual-optical path synchronization control signal, and the dual-optical path synchronization control signal is processed in time sequence synchronization to obtain a synchronization trigger sequence; Performing optical path delay compensation on the synchronous trigger sequence to obtain a delay compensation sequence, and performing optical path power modulation based on the delay compensation sequence to obtain a dual optical path power control signal; The dual-path power control signal is input into the laser energy feedback system to perform energy closed-loop control on the dual-path laser output to obtain steady-state energy output; Performing spot shaping on the steady-state energy output to obtain dual-path spot distribution data, and performing spot positioning based on the dual-path spot distribution data to obtain scanning path data; The scanning path data is input into the galvanometer control system to perform dual-optical path scanning synchronous control to obtain a synchronous motion trajectory, and the synchronous motion trajectory is optimized to obtain an optimized motion trajectory; Based on the optimized motion trajectory, the basic structure of the perovskite battery is scanned synchronously by dual optical paths to obtain the primary etching structure, and the primary etching structure is scanned by multiple superposition passes to obtain multiple etching structures; The surface morphology analysis and shape compensation are performed on the multiple etching structures to obtain the compensated etching structure, and the compensated etching structure is surface cleaned to obtain the perovskite cell etching structure.

[0036] Specifically, the optimal etching parameters obtained by mixed integer programming, including laser power , Scanning speed and the angle of incidence , input the dual-path synchronization controller to configure the parameters of the front light path laser and the back light path laser respectively. The controller generates a dual-path synchronization control signal, which contains the power, scanning speed and synchronization control information of the two beams. The timing alignment ensures the synchronization of the laser trigger signals on the front and back to avoid uneven energy distribution. The synchronization trigger sequence generated by the timing alignment The trigger points of the front and back light paths on the time axis are expressed by the following formula: ; in, is the initial trigger time, is the time interval. In order to compensate for the timing deviation caused by the difference in optical path length or device delay, the synchronous trigger sequence Perform optical path delay compensation. The delay compensation is calculated using the following formula: ; in, is the optical path length difference, is the speed of light. Delay compensation sequence is the adjusted trigger time sequence. Based on the delay compensation sequence, the optical path power is dynamically modulated to generate a dual optical path power control signal. The dynamic control of laser power modulation is achieved by setting the target power and actual output power Error , achieved through proportional-integral-derivative (PID) control: ; in, , , They are proportional, integral and differential gain coefficients respectively. The dual optical path power control signal is input into the laser energy feedback system, and closed-loop control is achieved by real-time monitoring of the laser output energy and spot power distribution to ensure steady-state energy output. The steady-state output of the closed-loop control meets the following conditions: ; After obtaining steady-state energy output, the light spot is shaped by the optical shaping module to adjust the light spot shape to the required elliptical or rectangular distribution. The result of the light spot shaping is expressed by the light spot distribution function. express: ; in, is the light intensity at the center of the spot, and are the semi-axis widths of the light spot, respectively. Based on the light spot distribution data, the light spot is positioned and the scanning path data is generated. The calculation of the scanning path needs to be combined with the geometric shape and distribution of the laser etching area. The path planning adopts the snake scanning method, and its path length It is expressed as: ; The scanning path data is input into the galvanometer control system, and the dual-light path scanning synchronization control is realized through the high-speed galvanometer. Synchronous motion trajectory Optimization is the key to improving machining efficiency and accuracy. The optimization goal is to minimize the path error. and processing time ; in, is the weight factor. After trajectory optimization, the optimized motion trajectory is generated Based on the optimized motion trajectory, the dual-optical path synchronous scanning of the perovskite battery basic structure is completed to complete the generation of the primary etching structure. On this basis, multiple superimposed scanning is performed on the primary etching structure to improve the etching depth and uniformity. Etching depth of superimposed scanning It is expressed by the following formula: ; in, It is After multiple etchings are completed, the surface morphology of the etched structure is analyzed, the surface shape is measured by scanning electron microscopy or atomic force microscopy, and shape compensation is performed. The goal of shape compensation is to eliminate residual non-uniformity, and its compensation function is: ; in, is the target shape, The surface of the compensation etching structure is cleaned, and the surface residues and particles are removed by ultrasonic cleaning or plasma cleaning to obtain the final perovskite cell etching structure.

[0037] The above describes the dual-path laser etching method for perovskite cells in the embodiment of the present application. The following describes the dual-path laser etching device 10 for perovskite cells in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of the dual-path laser etching device 10 for perovskite cells includes: The deposition processing module 11 is used to sequentially deposit a light absorption layer, an electron transport layer, a hole transport layer, and a metal electrode layer on the perovskite substrate to obtain a perovskite battery basic structure; An optical parameter acquisition module 12 is used to acquire optical parameters of the basic structure of the perovskite cell and generate structural parameter data including interlayer thickness and optical properties; A parameter sampling module 13 is used to perform parameter sampling of laser power, scanning speed and spot overlap rate based on the structural parameter data to obtain an initial parameter group for dual-path laser etching; The projection module 14 is used to construct a three-dimensional convex polyhedron and perform point coordinate projection on the initial parameter group of the dual-path laser etching to obtain a dual-path laser etching process constraint model; A calculation module 15 is used to perform mixed integer linear programming calculations on the front light path and the back light path according to the dual-light path laser etching process constraint model to obtain optimal etching parameters including laser power, scanning speed, and incident angle; The synchronous etching module 16 is used to apply the optimal etching parameters to the dual-path laser system to perform synchronous etching on the basic structure of the perovskite battery to obtain the perovskite battery etching structure.

[0038] Through the synergy of the above components and the introduction of dual-path laser synchronous etching technology, the front and back collaborative processing is achieved, which effectively reduces the heat accumulation effect and improves the quality and precision of the etching edge. A multi-step parameter optimization method is adopted to establish a systematic process parameter optimization process, realize the precise control of etching parameters, and overcome the limitations of traditional experience dependence. Through the construction of three-dimensional convex polyhedrons and mixed integer linear programming algorithms, a complete process constraint model is established, which provides a theoretical basis for parameter optimization and improves the reliability of optimization results. An online monitoring method based on optical parameter acquisition is designed to achieve real-time control of the etching process and ensure the stability and repeatability of the process. Through layered structure parameter acquisition and multi-layer heat transfer analysis, the etching characteristics of each functional layer are accurately grasped, and the etching quality of multi-layer composite structures is improved. The dual-path synchronous control and multi-pass superposition scanning strategy are adopted to significantly improve the etching uniformity of large-area batteries and improve the product yield. By introducing delay compensation and energy closed-loop control, the precise synchronization of the dual-path is achieved, solving the problem of synchronous control in traditional processes.

[0039] See also Figure 3 , Figure 3 This is a schematic block diagram of the structure of an electronic device 300 provided in an embodiment of the present application. The electronic device 300 includes a processor 301 and a memory 302. The processor 301 and the memory 302 are connected via a device bus 303, wherein the memory 302 may include a non-volatile storage medium and an internal memory.

[0040] The non-volatile storage medium can store a computer program. The computer program includes program instructions, and when the program instructions are executed by the processor 301, the processor 301 can execute any of the above-mentioned perovskite cell dual-path laser etching methods.

[0041] The processor 301 is used to provide computing and control capabilities to support the operation of the entire electronic device 300 .

[0042] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor 301, the processor 301 can execute any of the above-mentioned perovskite cell dual-path laser etching methods.

[0043] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a partial structure related to the present application scheme, and does not constitute a limitation on the electronic device 300 involved in the present application scheme. The specific electronic device 300 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0044] It should be understood that the processor 301 may be a central processing unit (CPU), and the processor 301 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0045] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the electronic device 300 described above can refer to the corresponding process of the aforementioned perovskite cell dual-path laser etching method, and will not be repeated here.

[0046] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by one or more processors, the one or more processors implement the dual-path laser etching method for perovskite cells as provided in the embodiment of the present application.

[0047] The computer-readable storage medium may be an internal storage unit of the electronic device 300 in the aforementioned embodiment, such as a hard disk or memory of the electronic device 300. The computer-readable storage medium may also be an external storage device of the electronic device 300, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped with the electronic device 300.

[0048] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0049] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0050] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A dual-path laser etching method for perovskite cells, characterized in that: The method comprises: The perovskite substrate is sequentially subjected to deposition treatments of a light absorption layer, an electron transport layer, a hole transport layer, and a metal electrode layer to obtain the basic structure of a perovskite cell; Collecting optical parameters of the perovskite battery basic structure to generate structural parameter data including interlayer thickness and optical properties; Based on the structural parameter data, the parameters of laser power, scanning speed and spot overlap rate are sampled to obtain an initial parameter group for dual-path laser etching; Performing three-dimensional convex polyhedron construction and point coordinate projection on the dual-path laser etching initial parameter group to obtain a dual-path laser etching process constraint model; According to the dual-light-path laser etching process constraint model, mixed integer linear programming calculations are performed on the front light path and the back light path to obtain optimal etching parameters including laser power, scanning speed, and incident angle; The optimal etching parameters are applied to a dual-path laser system to perform synchronous etching on the perovskite cell basic structure to obtain a perovskite cell etching structure.

2. The dual-path laser etching method for perovskite cells according to claim 1, characterized in that: The perovskite substrate is sequentially subjected to deposition treatment of a light absorption layer, an electron transport layer, a hole transport layer, and a metal electrode layer to obtain a perovskite battery basic structure, including: Performing plasma surface treatment on the perovskite substrate to obtain a surface activated substrate, and performing spin coating treatment on the surface activated substrate with a mixed solution of lead iodide and methylamine iodine to obtain a uniformly distributed perovskite precursor film layer; Performing temperature gradient annealing on the perovskite precursor film layer to obtain a light-absorbing layer having a crystal structure, and inputting a zinc oxide nanoparticle solution into a spraying system to spray the light-absorbing layer to obtain an electron transport precursor layer; Performing multi-section temperature-controlled annealing on the electron transport precursor layer to obtain an electron transport layer, and placing the electron transport layer in an inert atmosphere for organic material evaporation treatment to obtain a hole transport layer; The surface of the hole transport layer is subjected to plasma treatment to obtain a composite thin film structure with surface energy level regulation, and the composite thin film structure with surface energy level regulation is input into a magnetron sputtering system for metal layer sputtering deposition to obtain a perovskite battery basic structure.

3. The dual-path laser etching method for perovskite cells according to claim 2, characterized in that: The optical parameter collection of the perovskite battery basic structure to generate structural parameter data including interlayer thickness and optical properties includes: Applying a vertical incident light beam to the perovskite cell infrastructure and collecting reflected light signals to obtain original light intensity data, and performing wavelength decomposition on the original light intensity data to obtain sub-band spectrum data; Performing Fourier transformation on the sub-band spectrum data to obtain frequency domain characteristic data, and performing light intensity response analysis on the frequency domain characteristic data to obtain interface reflection characteristic data; Inputting the interface reflection characteristic data into the wave propagation equation, calculating the reflection characteristics of each interface, and obtaining the intra-layer propagation characteristic data; Performing polarization state analysis on the intra-layer propagation characteristic data to obtain optical hysteresis vectors of each layer, and performing phase decoupling on the optical hysteresis vectors to obtain interface polarization characteristic data; Inputting the interface polarization characteristic data into a thin film calculation model, calculating and processing the interlayer optical interference effect, and obtaining interference field data; Calculating the interlayer thickness of the interference field data to obtain thickness distribution data of each layer, and performing spatial scanning and mapping on the thickness distribution data of each layer to obtain interlayer structure distribution characteristics; Extracting optical characteristic parameters from the interlayer structure distribution characteristics to obtain optical characteristic data of each layer, and performing multi-dimensional feature combination on the optical characteristic data to obtain an optical characteristic mapping matrix; The interlayer structure distribution characteristics are fused with the optical property mapping matrix to obtain structural parameter data.

4. The dual-path laser etching method for perovskite cells according to claim 3, characterized in that: The parameter sampling of laser power, scanning speed and spot overlap rate based on the structural parameter data to obtain the initial parameter group of dual-light path laser etching includes: Performing interlayer optical response calculation on the structural parameter data to obtain an absorption coefficient matrix of each layer of material, and numerically discretizing the absorption coefficient matrix to obtain interlayer absorption intensity distribution data; Inputting the interlayer absorption intensity distribution data into a heat conduction model to obtain thermal response distribution data of each layer, and performing multi-layer heat transfer calculation on the thermal response distribution data to obtain interlayer heat transfer characteristic data; An energy density distribution function is established based on the interlayer heat transfer characteristic data, and a partition integral operation is performed on the energy density distribution function to obtain layered laser power threshold data; Dividing the layered laser power threshold data into parameter intervals to obtain laser power sampling data, and performing spot energy superposition calculation based on the laser power sampling data to obtain spot overlap rate sampling data; Inputting the laser power sampling data and the spot overlap rate sampling data into a scanning speed calculation model to obtain speed response characteristic data, and performing interval sampling on the speed response characteristic data to obtain scanning speed sampling data; The laser power sampling data, the spot overlap rate sampling data and the scanning speed sampling data are combined to obtain an original sampling data group, and the original sampling data group is subjected to boundary constraint screening to obtain an initial parameter group for dual-path laser etching.

5. The dual-path laser etching method for perovskite cells according to claim 4, characterized in that: The three-dimensional convex polyhedron construction and point coordinate projection of the dual-path laser etching initial parameter group are performed to obtain a dual-path laser etching process constraint model, including: Performing parameter space mapping on the dual-path laser etching initial parameter group to obtain a three-dimensional parameter point set, and performing nearest neighbor search on the three-dimensional parameter point set to obtain point set spatial distribution data; Performing Delaunay triangulation on the point set spatial distribution data to obtain initial triangular mesh data, and performing boundary extraction on the initial triangular mesh data to obtain convex hull boundary data; Performing facet reconstruction on the convex hull boundary data to obtain three-dimensional convex polyhedron mesh data, and performing mesh optimization on the three-dimensional convex polyhedron mesh data to obtain a regularized mesh structure; Performing principal component analysis based on the regularized grid structure to obtain main direction projection data, and performing coordinate transformation on the main direction projection data to obtain projection plane parameters; Performing normal vector calculation on the projection plane parameters to obtain projection direction data, and performing point coordinate projection transformation based on the projection direction data to obtain a two-dimensional projection point set; Generating a convex hull based on the two-dimensional projection point set to obtain projection area boundary data, and performing interpolation fitting on the projection area boundary data to obtain a constraint boundary curve; The constraint boundary curve is parameterized to obtain a boundary constraint function, and the feasible domain is divided based on the boundary constraint function to obtain a process parameter constraint interval, and the process parameter constraint interval is data-associated with the three-dimensional convex polyhedron mesh data to obtain a dual-light path laser etching process constraint model.

6. The dual-path laser etching method for perovskite cells according to claim 5, characterized in that: The mixed integer linear programming calculation is performed on the front light path and the back light path according to the dual-light path laser etching process constraint model to obtain the optimal etching parameters including laser power, scanning speed, and incident angle, including: Decomposing the dual-light-path laser etching process constraint model into a front light path and a back light path to obtain a front constraint interval and a back constraint interval, and performing parameter mapping on the front constraint interval and the back constraint interval to obtain a light path coupling matrix; Constructing an objective function for the optical path coupling matrix to obtain a linear objective equation containing optical path parameters, and performing integer variable separation on the linear objective equation to obtain a mixed integer constraint condition; Inputting the mixed integer constraint condition into a branch and bound model to obtain initial solution space data, and performing linear relaxation on the initial solution space data to obtain a continuous solution vector; Integerizing the continuous solution vector to obtain discrete solution set data, and performing branch search based on the discrete solution set data to obtain local optimal solution data; Inputting the local optimal solution data into a simplex method model, performing linear programming iteration to obtain global solution space data, and performing cutting plane generation on the global solution space data to obtain an optimal solution interval; Reconstructing the optimal solution interval with discrete parameters to obtain laser power parameters and scanning speed parameters of the front optical path and the back optical path, and optimizing the optical path angle based on the laser power parameters and scanning speed parameters to obtain an incident angle parameter; The laser power parameter, the scanning speed parameter and the incident angle parameter are combined to obtain the optimal etching parameter.

7. The dual-path laser etching method for perovskite cells according to claim 6, characterized in that: The step of applying the optimal etching parameters to a dual-path laser system to perform synchronous etching on the perovskite cell basic structure to obtain a perovskite cell etching structure includes: Input the optimal etching parameters into the dual-light path synchronization controller, configure the parameters of the front light path laser and the back light path laser to obtain a dual-light path synchronization control signal, and perform timing synchronization processing on the dual-light path synchronization control signal to obtain a synchronization trigger sequence; Performing optical path delay compensation on the synchronous trigger sequence to obtain a delay compensation sequence, and performing optical path power modulation based on the delay compensation sequence to obtain a dual optical path power control signal; The dual-light path power control signal is input into the laser energy feedback system to perform energy closed-loop control on the dual-light path laser output to obtain a steady-state energy output; Performing spot shaping on the steady-state energy output to obtain dual-light path spot distribution data, and performing spot positioning based on the dual-light path spot distribution data to obtain scanning path data; The scanning path data is input into the galvanometer control system to perform dual-light path scanning synchronous control to obtain a synchronous motion trajectory, and the synchronous motion trajectory is optimized to obtain an optimized motion trajectory; Based on the optimized motion trajectory, dual-optical path synchronous scanning is performed on the perovskite battery basic structure to obtain a primary etching structure, and multiple-pass superposition scanning is performed on the primary etching structure to obtain a multiple etching structure; The multiple etching structures are subjected to surface morphology analysis and shape compensation to obtain a compensated etching structure, and the compensated etching structure is subjected to surface cleaning treatment to obtain a perovskite cell etching structure.

8. A dual-path laser etching device for perovskite cells, characterized in that: Used to perform the dual-path laser etching method for a perovskite cell according to any one of claims 1 to 7, the dual-path laser etching device for a perovskite cell comprises: A deposition processing module is used to sequentially deposit a light absorption layer, an electron transport layer, a hole transport layer, and a metal electrode layer on the perovskite substrate to obtain a perovskite battery basic structure; An optical parameter acquisition module, used to acquire optical parameters of the perovskite battery basic structure and generate structural parameter data including interlayer thickness and optical properties; A parameter sampling module, used for sampling the parameters of laser power, scanning speed and spot overlap rate based on the structural parameter data to obtain an initial parameter group for dual-path laser etching; A projection module, used for constructing a three-dimensional convex polyhedron and performing point coordinate projection on the dual-path laser etching initial parameter group to obtain a dual-path laser etching process constraint model; A calculation module, used for performing mixed integer linear programming calculation on the front light path and the back light path according to the dual-light path laser etching process constraint model to obtain optimal etching parameters including laser power, scanning speed, and incident angle; The synchronous etching module is used to apply the optimal etching parameters to a dual-path laser system to perform synchronous etching on the perovskite battery basic structure to obtain a perovskite battery etching structure.

9. An electronic device, characterized in that: The electronic device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory so that the electronic device executes the dual-path laser etching method for perovskite cells as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the dual-path laser etching method for perovskite cells according to any one of claims 1 to 7 is implemented.

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