Brightness enhancement film center wavelength optimization method based on genetic algorithm and electronic device

Abstract

This application relates to the field of optical thin film technology, and more particularly to a method and electronic device for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm. The method includes: obtaining preset environmental parameters and defining optimization variable parameters; based on the preset environmental parameters and optimization variable parameters, performing parametric inverse design on a multilayer film model using finite element simulation to obtain an objective function; based on the objective function, performing iterative simulation on the multilayer film model using a genetic algorithm, and optimizing using a fitness function during the iteration process until the optimization objective is met or the number of iterations reaches a preset number; obtaining the optimal solution after iteration, the optimal solution including the center wavelength combination and the number of film layers. This application can obtain precise optimization parameters to achieve optimal reflectivity performance of the multilayer film.

Description

Technical Field

[0001] This application relates to the field of optical thin film technology, and in particular to a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm and an electronic device. Background Technology

[0002] Optical multilayer films are widely used in brightness enhancement films, filters, interference mirrors, and anti-reflective coatings. Their reflection and transmission properties typically depend on parameters such as film thickness, film material, and arrangement order. Among these, the center wavelength is a key parameter for adjusting the reflectivity of the multilayer film. Dual Brightness Enhancement Film (DBEF) is a multilayer film that uses optical interference technology to improve the brightness of a display. Its main function is to use optical interference to recover S-waves that do not pass through the polarizer and convert them into P-waves, thereby increasing not only the brightness of the front of the display but also the brightness of the viewing angle.

[0003] Optimizing the center wavelength not only affects the thickness and number of stacked layers of the film, but also directly determines the optical properties of the film in the target wavelength band. In optical design, setting the center wavelength is a complex computational problem, and the optimization difficulty increases significantly with the increase in the number of layers or the expansion of the bandwidth.

[0004] Related technologies use high-precision optical testing equipment (such as synchrotron radiation sources) to test the reflectivity of multilayer films in order to find the optimized center parameters. However, this method relies on manual experiments, which can easily lead to deviations and inaccurate experimental results. Summary of the Invention

[0005] To address the problem that the accuracy of the center wavelength parameter determined by existing technologies to achieve optimal reflectivity performance is not high, this application provides a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, as well as an electronic device.

[0006] Firstly, this application provides a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, employing the following technical solution:

[0007] A method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm includes:

[0008] Obtain preset environment parameters and define optimization variable parameters;

[0009] Based on the preset environmental parameters and the optimized variable parameters, the multilayer membrane model is parametrically inversely designed using finite element simulation to obtain the objective function;

[0010] Based on the objective function, a genetic algorithm is used to perform iterative simulation on the multilayer membrane model, and a fitness function is used to optimize it during the iteration process until the optimization objective is met or the number of iterations reaches the preset number of iterations.

[0011] Obtain the optimal solution after iteration, which includes the combination of center wavelengths and the number of film layers.

[0012] By adopting the above technical solution, preset environmental parameters (such as multilayer film structure parameters, wavelength range, target reflectivity, etc.) are obtained and optimization variable parameters (such as center wavelength combination and number of film layers) are defined. Finite element simulation is used to perform parametric inverse design on the multilayer film model to construct an objective function. Based on the objective function, a genetic algorithm is used to perform iterative simulation on the multilayer film model. The center wavelength combination is evaluated and optimized through a fitness function to gradually approach the optimal solution. The final optimal solution includes the center wavelength combination and the number of film layers, ensuring that the reflectivity of the multilayer film reaches the optimal within the target wavelength range. This application can efficiently and accurately optimize multilayer film design to meet complex optical performance requirements. At the same time, the global search capability of the genetic algorithm avoids getting trapped in local optima, improving the accuracy of parameter optimization.

[0013] In a preferred embodiment, this application can be further configured as follows: obtaining preset environmental parameters and defining optimization variable parameters includes:

[0014] The preset environmental parameters are obtained, including: the structural parameters, wavelength range parameters, and target reflectivity of the multilayer film model;

[0015] A preset number of center wavelengths is defined as a center wavelength combination, and the center wavelength combination and the number of film layers are used as the optimization variable parameters.

[0016] The multilayer film model is composed of alternating stacks of high-refractive-index films and low-refractive-index films. The number of groups of the multilayer film model is equal to the preset number, and the sum of the number of high-refractive-index films and low-refractive-index films in each group is the number of film layers.

[0017] By adopting the above technical solution, preset environmental parameters are obtained and optimization variable parameters are defined, providing clear input conditions for subsequent optimization design. The multilayer film model is composed of alternating stacks of high-refractive-index and low-refractive-index films. The number of multilayer film models is consistent with the preset number of center wavelengths, ensuring the structural rationality and optimizability of the model. Through this step, the complex optical thin film design problem can be transformed into a computable optimization problem, laying the foundation for subsequent finite element simulation and genetic algorithm optimization, thereby achieving efficient and accurate multilayer film design to meet the target reflectivity requirements.

[0018] In a preferred embodiment, this application may be further configured such that: the structural parameters of the multilayer film model include: the refractive index of the high-refractive-index film, the refractive index of the low-refractive-index film, the refractive index of the substrate, and the total thickness range of the film layers; the wavelength range parameters include: the traversal wavelength range and the center wavelength range;

[0019] Based on the preset environmental parameters and the optimized variable parameters, a parametric inverse design of the multilayer membrane model is performed using finite element simulation to obtain the objective function, including:

[0020] Apply a sequence constraint to the center wavelength combination;

[0021] Based on the aforementioned center wavelength combination, the overall system transmission matrix of the multilayer film model is constructed;

[0022] Obtain the air refractive index, and calculate the reflectivity based on the total system transmission matrix, the air refractive index, and the substrate refractive index; construct an objective function, the expression of which is:

[0023] F=(λ c ,n1,n2,n air ,n sub ,λ,H,L,tR,λ s ,λ e )

[0024] Where F is the objective function, λ c For the center wavelength combination, n1 is the refractive index of the high-refractive-index film, n2 is the refractive index of the low-refractive-index film, n air n is the refractive index of air. sub λ is the refractive index of the substrate, λ is the traversed wavelength range, H is the total thickness of the film, L is the number of film layers, tR is the target reflectivity, and λ s λ is the upper bound of the center wavelength range. e This is the lower bound of the center wavelength range.

[0025] By adopting the above technical solution, the structural parameters and wavelength range parameters of the multilayer film model are clarified. Based on these parameters, finite element simulation is used to perform parametric inverse design of the multilayer film model. By applying sequential constraints on the center wavelength combination, constructing the overall system transmission matrix and calculating the reflectivity, the objective function is finally constructed. The objective function comprehensively considers factors such as the center wavelength combination, material refractive index, air refractive index, substrate refractive index, traversal wavelength range, total film thickness, number of film layers and target reflectivity, and can comprehensively reflect the optical performance of the multilayer film.

[0026] In a preferred embodiment, this application can be further configured such that the method also includes:

[0027] A center wavelength constraint and a total film thickness constraint are applied to the objective function;

[0028] Wherein, the center wavelength constraint is that the combination of center wavelengths in the objective function is within the center wavelength range; the total film thickness constraint is that the total film thickness in the objective function is within the total film thickness range, and the total film thickness is determined based on the combination of center wavelengths, the refractive index of the high refractive index film, the refractive index of the low refractive index film, and the number of film layers.

[0029] By employing the above technical solution, center wavelength constraints and total film thickness constraints are applied to the objective function, ensuring that the center wavelength combination and total film thickness remain within a preset reasonable range during the optimization process. The center wavelength constraint ensures that the center wavelength combination is arranged in an orderly manner within the target wavelength range, avoiding the generation of invalid solutions; the total film thickness constraint ensures that the total thickness of the multilayer film conforms to the physical limitations of actual manufacturing and application.

[0030] In a preferred embodiment, this application can be further configured such that: the construction of the total system transmission matrix of the multilayer film model based on the center wavelength combination includes:

[0031] For each group in the multilayer film model, the first thickness of the high-refractive-index film and the second thickness of the low-refractive-index film in the group are calculated based on the center wavelength combination; a first transmission matrix of the group is constructed based on the first thickness, a second transmission matrix of the group is constructed based on the second thickness, and a transmission matrix of the group is constructed based on the first transmission matrix, the second transmission matrix, and the number of film layers;

[0032] The total system transmission matrix of the multilayer membrane model is obtained by multiplying the transmission matrices of the preset number of groups.

[0033] By adopting the above technical solution, the thickness of the high-refractive-index film and the low-refractive-index film in each group is calculated based on the combination of center wavelengths, and their transmission matrices are constructed respectively. Finally, the total transmission matrix of each film is obtained by matrix multiplication, and the total system transmission matrix of the multilayer film model is obtained by multiplying the transmission matrices of all film layers. This process can accurately describe the propagation behavior of light in multilayer films. Combined with the transmission matrix method, reflectivity and transmittance are efficiently calculated, providing an accurate mathematical model for optimization design.

[0034] In a preferred embodiment, this application can be further configured such that the calculation of reflectivity based on the total system transmission matrix, the air refractive index, and the substrate refractive index includes:

[0035] Substituting the total system transmission matrix, the air refractive index, and the substrate refractive index into the reflection coefficient formula, we obtain the reflection coefficient, which is:

[0036]

[0037] Where r is the reflection coefficient, T is the total system transmission matrix, and nair n is the refractive index of air. sub The refractive index of the substrate;

[0038] Substituting the reflection coefficient into the reflectance formula, we obtain the reflectance, which is:

[0039] R = |r| 2

[0040] Where R is reflectivity and r is the reflection coefficient.

[0041] By adopting the above technical solution and based on the transfer matrix algorithm, the propagation behavior of light in multilayer films can be accurately described, and reflectivity can be efficiently calculated using rigorous mathematical formulas. This provides a high-precision reflectivity calculation method, offering a reliable quantitative basis for the optical performance evaluation and optimized design of multilayer films.

[0042] In a preferred embodiment, this application can be further configured as follows: based on the objective function, an iterative simulation of the multilayer membrane model is performed using a genetic algorithm, and optimization is performed using a fitness function during the iteration process until the optimization objective is met or the number of iterations reaches a preset number of iterations, including:

[0043] The initial population is randomly generated based on the objective function;

[0044] Using the fitness function, the fitness value of each individual is calculated based on the objective function value corresponding to each individual in the initial population. The fitness value is the average of the reflectance values ​​corresponding to the center wavelength range.

[0045] Perform iterative optimization operations until the fitness value obtained in the current iteration satisfies the optimization objective or the number of iterations reaches the preset number of iterations;

[0046] The iterative optimization operation includes: taking the population obtained in the previous iteration as the parent population, performing selection, crossover, and mutation operations on the parent population based on the fitness value of the parent population to obtain a new population and an updated objective function value, and calculating the fitness value of each individual obtained in the current iteration based on the updated objective function value; determining a penalty factor, and updating the fitness value of each individual obtained in the current iteration based on the penalty factor.

[0047] By adopting the above technical solution, the global search capability of the genetic algorithm is used to efficiently explore the complex design space and avoid getting trapped in local optima. At the same time, the fitness function and penalty factor are used to ensure that the optimization results meet the target reflectivity requirements and physical constraints, and finally achieve high-precision optimization of multilayer film design.

[0048] In a preferred embodiment, this application can be further configured such that: determining the penalty factor and updating the fitness value of each individual obtained in the current iteration round based on the penalty factor includes:

[0049] For each individual obtained in the current iteration, the difference between the individual's fitness value and the target reflectivity is calculated; the product of the difference and the adjustment coefficient is calculated as a penalty factor, and the individual's fitness value is adjusted based on the penalty factor.

[0050] By adopting the above technical solution and introducing a penalty mechanism, the optimization process can be effectively guided towards meeting the target reflectivity, avoiding the algorithm from generating solutions that do not meet the requirements, and improving both optimization efficiency and solution quality.

[0051] In a preferred embodiment, this application can be further configured such that the method also includes:

[0052] After the iteration is completed, the reflectivity of the traversed wavelength range corresponding to the optimal solution is determined, and a reflectivity curve is plotted based on the reflectivity of the traversed wavelength range.

[0053] The reflectance corresponding to the center wavelength range is selected from the reflectance of the traversed wavelength range, and the mean reflectance and standard deviation of reflectance are calculated based on the reflectance corresponding to the center wavelength range, so as to verify the iteration results through the mean reflectance and the standard deviation of reflectance.

[0054] By adopting the above technical solution, the quality of the optimization results is comprehensively evaluated using reflectivity curves and quantitative indicators (mean and standard deviation), ensuring that the reflectivity of the multilayer film reaches the optimal and is uniformly distributed within the target wavelength range.

[0055] Secondly, this application provides an electronic device that adopts the following technical solution:

[0056] One or more processors;

[0057] Memory;

[0058] At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the genetic algorithm-based method for optimizing the center wavelength of a brightening film as described in any of the first aspects.

[0059] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0060] A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm as described in any of the first aspects.

[0061] Fourthly, this application provides a computer program product, which adopts the following technical solution:

[0062] A computer program product includes a computer program that, when executed by a processor, implements the method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm as described in any of the first aspects.

[0063] In summary, this application includes the following beneficial technical effects:

[0064] This application obtains preset environmental parameters (such as multilayer film structure parameters, wavelength range, target reflectivity, etc.) and defines optimization variable parameters (such as center wavelength combination and number of film layers). It then uses finite element simulation to perform parametric inverse design on the multilayer film model to construct an objective function. Based on the objective function, a genetic algorithm is used to perform iterative simulation on the multilayer film model. The center wavelength combination is evaluated and optimized through a fitness function, gradually approaching the optimal solution. The final optimal solution includes the center wavelength combination and the number of film layers, ensuring that the reflectivity of the multilayer film reaches its optimum within the target wavelength range. This application can efficiently and accurately optimize multilayer film design to meet complex optical performance requirements. Simultaneously, the global search capability of the genetic algorithm avoids getting trapped in local optima, improving the accuracy of parameter optimization. Attached Figure Description

[0065] Figure 1 This is a flowchart illustrating a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, as provided in an embodiment of this application.

[0066] Figure 2 This is a schematic diagram of the structure of the multilayer film provided in the embodiments of this application;

[0067] Figure 3 This is a flowchart illustrating a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, provided in another embodiment of this application.

[0068] Figure 4 This is a convergence diagram of the iterative process of the genetic algorithm provided in the embodiments of this application;

[0069] Figure 5 This is a schematic diagram of the reflectance curve provided in the embodiments of this application;

[0070] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0071] The following is in conjunction with the appendix Figure 1 -Appendix Figure 6 This application will be described in further detail.

[0072] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0073] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0074] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0075] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0076] The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm provided in this application can be widely applied in fields such as the design of brightness enhancement films for liquid crystal displays, the design of optical filters, and the optimization of anti-reflection coatings, and has practical production application value.

[0077] This application provides a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, such as... Figure 1As shown, the method provided in this embodiment is executed by an electronic device, which can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet computer, laptop computer, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected through wired or wireless communication, and this embodiment does not impose any restrictions.

[0078] Dual-brightness enhancement film (DBEF) is a type of multilayer film. Given the structural parameters of a multilayer film, its reflectivity can be calculated directly, which is a straightforward problem. Conversely, this application employs a genetic algorithm-based inverse design method for the structural parameters of birefringence multilayer films. Knowing the target refractive index of the multilayer film, the method inversely designs the structural parameters (center wavelength combination and number of layers). Based on the optimized center wavelength combination and number of layers, and combined with the refractive indices of the high-refractive-index and low-refractive-index films, the total thickness of the film can be calculated.

[0079] The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm provided in this application includes steps S101-S104, wherein:

[0080] S101. Obtain preset environment parameters and define optimization variable parameters.

[0081] Specifically, the preset environmental parameters are pre-defined and include: the structural parameters of the multilayer film model, the wavelength range parameters, and the target reflectivity.

[0082] See Figure 2 It shows a schematic diagram of a multilayer film structure, which consists of multiple high-refractive-index films and low-refractive-index films periodically and alternately stacked on a substrate material. The number of multilayer structures is a predetermined number N, i.e. Figure 2 Groups 1 through N are each composed of stacked high-refractive-index and low-refractive-index films. The sum of the number of high-refractive-index and low-refractive-index films in each group is the number of film layers. The model parameters for multilayer films include: the refractive index of the high-refractive-index film, the refractive index of the low-refractive-index film, the refractive index of the substrate, and the total thickness range of the film layers. The refractive indices of the high-refractive-index film, the low-refractive-index film, and the substrate are determined by the material properties of the multilayer film. The total thickness range indicates that the final designed total thickness of the film layers needs to be limited to a certain range. Optionally, the center value of the total thickness range can be set to 30 μm, and the preset number N is 9.

[0083] The wavelength range parameters include: the traversal wavelength range and the center wavelength range. Based on the wavelength range of visible light, the traversal wavelength range can be determined as 300nm-1000nm. The center wavelength range is set based on the actual application requirements of the brightness enhancement film. The center wavelength range serves as the target wavelength range, and the purpose of the scheme is to optimize the reflectivity of the multilayer film within the target wavelength band. Optionally, the center wavelength range is 400nm-850nm.

[0084] Wavelength traversal and simulation are crucial steps in optimizing multilayer film design. Simulations are performed for each wavelength value within a defined traversal wavelength range. This includes setting a wavelength step size (e.g., 1 nm), starting from the lower bound of 300 nm, and sequentially increasing the wavelength value (301 nm, 302 nm, ..., 1000 nm). Simulation calculations are performed for each wavelength value. The simulation process uses a transfer matrix algorithm to calculate the reflectivity of the multilayer film at each wavelength value. A genetic iterative algorithm iteratively optimizes the center wavelength combination and the number of film layers to achieve the optimal reflectivity of the multilayer film within the target wavelength range (center wavelength range) while satisfying the target reflectivity. Finally, the optimal center wavelength combination and number of film layers are output as the optimal solution. The target reflectivity is the optimal value of the optimized center wavelength to achieve the best reflectivity of the multilayer film; the target reflectivity can be set to 0.98.

[0085] The optimized variable parameters are dynamically optimized during the iteration process. The final optimal solution output includes the optimal combination of center wavelengths and the number of film layers that maximizes the reflectivity of the multilayer film. The combination of center wavelengths includes a preset number of N center wavelengths.

[0086] S102. Based on preset environmental parameters and optimized variable parameters, finite element simulation is used to perform parametric inverse design on the multilayer membrane model to obtain the objective function.

[0087] Specifically, this scheme uses a genetic algorithm to find N center wavelengths, which are used to calculate the film thickness. An order constraint is applied to the combination of center wavelengths, meaning the N center wavelengths are arranged in ascending order. The purpose is to simulate the actual film layer arrangement in numerical simulation, i.e., the film thickness arranged in ascending order. The order constraint can be expressed as:

[0088]

[0089] Where, λ c1 To λ cN This represents a combination of center wavelengths arranged from smallest to largest. The upper and lower bounds of the center wavelengths are the upper and lower bounds of the center wavelength range. Setting matrices A and B satisfies the order constraint. The element δ in matrix B is an infinitesimal value.

[0090] Furthermore, the air refractive index is obtained, and the total reflectivity of the multilayer film is calculated based on the air refractive index, the refractive index of the high refractive index film, the refractive index of the low refractive index film, the substrate refractive index, and the center wavelength combination.

[0091] Construct the objective function, the expression of which is:

[0092] F=(λ c ,n1,n2,n air ,n sub ,λ,H,L,tR,λ s ,λ e )

[0093] Where F is the objective function, λ c For the center wavelength combination, n1 is the refractive index of the high-refractive-index film, n2 is the refractive index of the low-refractive-index film, n air n is the refractive index of air. sub λ is the refractive index of the substrate, λ is the traversed wavelength range, H is the total thickness of the film, L is the number of film layers, tR is the target reflectivity, and λ s λ is the upper bound of the center wavelength range. e This is the lower bound of the center wavelength range.

[0094] S103. Based on the objective function, a genetic algorithm is used to perform iterative simulation on the multilayer membrane model, and the fitness function is used for optimization during the iteration process until the optimization objective is met or the number of iterations reaches the preset number of iterations.

[0095] Specifically, based on the genetic algorithm, an initial population is generated, and the combination of central wavelengths and the number of film layers are gradually optimized through iterative optimization operations. During this process, the value of the objective function also changes dynamically. The iterative optimization operations include selection, crossover, and mutation operations. Using the optical transfer matrix theory, the fitness function is used to evaluate whether the reflectivity of the multilayer film meets the target reflectivity, and the optimization direction is adjusted accordingly.

[0096] S104. Obtain the optimal solution after the iteration is completed. The optimal solution includes the combination of center wavelengths and the number of film layers.

[0097] After the iteration is completed, the reflectance curve is plotted based on the optimal solution, and the mean reflectance and standard deviation of reflectance are calculated to verify the iteration results.

[0098] See Figure 3This document illustrates a flowchart of a method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, according to another embodiment of this application. Preset environmental parameters and optimization variable parameters are given, including refractive index parameters, total film thickness, traversed wavelength range, center wavelength range, and target reflectivity requirements. An objective function is constructed based on the transfer matrix. Constraints and iteration conditions are set, including upper and lower bounds on the center wavelength, population size, and maximum number of iterations. Iterative optimization is performed using a genetic algorithm. The iterative optimization process includes population selection, crossover, and mutation. A fitness function is used to evaluate whether the obtained population meets the target reflectivity requirements. If it does, the optimal solution is output, including the center wavelength combination and the number of film layers. The reflectivity is calculated, and a reflectivity curve is plotted. If it does not meet the requirements, the magnitude of the deviation is determined, a penalty value is assigned based on the deviation, and another round of iterations is performed until the optimization objective is met or the maximum number of iterations is reached. After iteration, a Pareto optimal solution set is obtained.

[0099] This application's embodiments obtain preset environmental parameters (such as multilayer film structure parameters, wavelength range, target reflectivity, etc.) and define optimization variable parameters (such as center wavelength combination and number of film layers). Finite element simulation is used to perform parametric inverse design on the multilayer film model to construct an objective function. Based on the objective function, a genetic algorithm is used to perform iterative simulation on the multilayer film model. The center wavelength combination is evaluated and optimized through a fitness function, gradually approaching the optimal solution. The final optimal solution includes the center wavelength combination and the number of film layers, ensuring that the reflectivity of the multilayer film reaches its optimal value within the target wavelength range. This application can efficiently and accurately optimize multilayer film design, meeting complex optical performance requirements. Simultaneously, the global search capability of the genetic algorithm avoids getting trapped in local optima, improving the accuracy of parameter optimization.

[0100] One possible implementation of this application embodiment involves obtaining preset environmental parameters and defining optimization variable parameters, including:

[0101] Obtain preset environmental parameters, including: structural parameters of the multilayer film model, wavelength range parameters, and target reflectivity;

[0102] A preset number of center wavelengths is defined as the center wavelength combination, and the center wavelength combination and the number of film layers are used as optimization variable parameters. Among them, the multilayer film model is composed of alternating stacks of high refractive index film and low refractive index film. The number of groups of the multilayer film model is equal to the preset number, and the sum of the number of high refractive index film and low refractive index film contained in each group is the number of film layers.

[0103] This application embodiment obtains preset environmental parameters and defines optimization variable parameters, providing clear input conditions for subsequent optimization design; the multilayer film model is composed of alternating stacks of high-refractive-index and low-refractive-index films, and the number of multilayer film models is consistent with the preset number of center wavelengths, ensuring the structural rationality and optimizability of the model; through this step, the complex optical thin film design problem can be transformed into a computable optimization problem, laying the foundation for subsequent finite element simulation and genetic algorithm optimization, thereby achieving efficient and accurate multilayer film design to meet the target reflectivity requirements.

[0104] One possible implementation of this application embodiment includes the following structural parameters of the multilayer film model: the refractive index of the high-refractive-index film, the refractive index of the low-refractive-index film, the refractive index of the substrate, and the total thickness range of the film layers; the wavelength range parameters include: the traversal wavelength range and the center wavelength range.

[0105] Based on preset environmental parameters and optimized variable parameters, finite element simulation is used to perform parametric inverse design on the multilayer film model to obtain the objective function, including:

[0106] Apply sequential constraints to the combination of center wavelengths;

[0107] Based on the combination of center wavelengths, the total system transmission matrix of the multilayer film model is constructed.

[0108] Obtain the air refractive index, and calculate the reflectivity based on the total system transmission matrix, the air refractive index, and the substrate refractive index;

[0109] Construct the objective function, the expression of which is:

[0110] F=(λ c ,n1,n2,n air ,n sub ,λ,H,L,tR,λ s ,λ e )

[0111] Where F is the objective function, λ c For the center wavelength combination, n1 is the refractive index of the high-refractive-index film, n2 is the refractive index of the low-refractive-index film, n air n is the refractive index of air. sub λ is the refractive index of the substrate, λ is the traversed wavelength range, H is the total thickness of the film, L is the number of film layers, tR is the target reflectivity, and λ s λ is the upper bound of the center wavelength range. e This is the lower bound of the center wavelength range.

[0112] This embodiment aims to calculate the total reflectivity of a multilayer film by combining the refractive index of the high-refractive-index film, the refractive index of the low-refractive-index film, the total thickness of the film layers, and the center wavelength parameters, using a transfer matrix algorithm, and to meet the target reflectivity requirements.

[0113] Specifically, the total transmission matrix of the multilayer film model is constructed based on the combination of center wavelengths, including: for each group in the multilayer film model, based on the corresponding center wavelength, the first transmission matrix corresponding to the high refractive index film and the second transmission matrix of the low refractive index film in the group are calculated; the transmission matrix of the group is constructed based on the first transmission matrix, the second transmission matrix and the number of film layers; and then, the product of the transmission matrices of all groups in the multilayer film model is taken as the total system transmission matrix of the multilayer film model.

[0114] Then, the total system transmission matrix, air refractive index, and substrate refractive index are substituted into a preset reflection coefficient formula to obtain the reflection coefficient. The reflection coefficient is then substituted into a preset reflection rate formula to obtain the reflectivity of the multilayer film.

[0115] This application embodiment defines the structural parameters and wavelength range parameters of the multilayer film model. Based on these parameters, finite element simulation is used to perform parametric inverse design of the multilayer film model. By applying sequential constraints on the center wavelength combination, constructing the overall system transmission matrix and calculating the reflectivity, an objective function is finally constructed. The objective function comprehensively considers factors such as the center wavelength combination, material refractive index, air refractive index, substrate refractive index, traversing wavelength range, total film thickness, number of film layers, and target reflectivity, and can comprehensively reflect the optical performance of the multilayer film.

[0116] One possible implementation of this application embodiment includes:

[0117] Apply center wavelength constraints and total film thickness constraints to the objective function;

[0118] Among them, the center wavelength constraint is that the combination of center wavelengths in the objective function is within the center wavelength range; the total film thickness constraint is that the total film thickness in the objective function is within the total film thickness range, and the total film thickness is determined based on the combination of center wavelengths, the refractive index of the high refractive index film, the refractive index of the low refractive index film, and the number of film layers.

[0119] This application embodiment ensures that the combination of center wavelengths and the total thickness of the film remain within a preset reasonable range during the optimization process by imposing center wavelength constraints and total film thickness constraints on the objective function. The center wavelength constraint ensures that the combination of center wavelengths is arranged in an orderly manner within the target wavelength range, avoiding the generation of invalid solutions; the total film thickness constraint ensures that the total thickness of the multilayer film meets the physical limitations of actual manufacturing and application.

[0120] One possible implementation of this application embodiment involves constructing the total system transmission matrix of a multilayer film model based on a combination of center wavelengths, including:

[0121] For each group in the multilayer film model, the first thickness of the high-refractive-index film and the second thickness of the low-refractive-index film in the group are calculated based on the combination of center wavelengths; the first transfer matrix of the group is constructed based on the first thickness, the second transfer matrix of the group is constructed based on the second thickness, and the transfer matrix of the group is constructed based on the first transfer matrix, the second transfer matrix and the number of film layers;

[0122] The total system transmission matrix of the multilayer membrane model is obtained by multiplying the transmission matrices of a predetermined number of groups.

[0123] In this embodiment, any group in the multilayer film model is represented as i, and the expression for the first transport matrix of that group of films is determined as follows:

[0124]

[0125] Where, φ i1 For phase thickness, λ is the current traversal wavelength, and n1 is the refractive index of the high-refractive-index film. λ ci Let j be the center wavelength corresponding to group i, and j be the imaginary unit. 2 =-1.

[0126] The expression for the second transfer matrix of group i is:

[0127]

[0128] Where, φ i2 For phase thickness, λ is the current traversal wavelength, and n2 is the refractive index of the low-refractive-index film. λ ci Let j be the center wavelength corresponding to group i, and j be the imaginary unit. 2 =-1.

[0129] The transmission matrix of group i is In the formula, L represents the number of film layers.

[0130] The expression for the overall system transport matrix of the multilayer membrane model is:

[0131] The embodiments of this application calculate the thickness of the high-refractive-index film and the low-refractive-index film in each group based on the combination of center wavelengths, and construct their respective transmission matrices. Finally, the total transmission matrix of each film is obtained by matrix multiplication. Then, the total system transmission matrix of the multilayer film model is obtained by multiplying the transmission matrices of all film layers. This process can accurately describe the propagation behavior of light in multilayer films. Combined with the transmission matrix method, reflectivity and transmittance are efficiently calculated, providing an accurate mathematical model for optimized design.

[0132] One possible implementation of this application embodiment calculates reflectivity based on the total system transmission matrix, air refractive index, and substrate refractive index, including:

[0133] Substituting the total system transfer matrix, air refractive index, and substrate refractive index into the reflection coefficient formula, we obtain the reflection coefficient, which is:

[0134]

[0135] Where r is the reflection coefficient, T is the total system transmission matrix, and n air n is the refractive index of air. sub The refractive index of the substrate;

[0136] Substituting the reflection coefficient into the reflectance formula, we obtain the reflectance, which is:

[0137] R = |r| 2

[0138] Where R is reflectivity and r is the reflection coefficient.

[0139] This application's embodiments, based on a transfer matrix algorithm, can accurately describe the propagation behavior of light in multilayer films and efficiently calculate reflectance using rigorous mathematical formulas. This provides a high-precision reflectance calculation method, offering a reliable quantitative basis for the optical performance evaluation and optimized design of multilayer films.

[0140] One possible implementation of this application embodiment involves using a genetic algorithm to perform iterative simulations on a multilayer membrane model based on an objective function, and optimizing the model using a fitness function during the iteration process until the optimization objective is met or the number of iterations reaches a preset number. This includes:

[0141] The initial population is randomly generated based on the objective function;

[0142] Using the fitness function, the fitness value of each individual is calculated based on the objective function value of each individual in the initial population. The fitness value is the average of the reflectance values ​​corresponding to the central wavelength range.

[0143] Perform iterative optimization operations until the fitness value obtained in the current iteration satisfies the optimization objective or the number of iterations reaches the preset number of iterations;

[0144] The iterative optimization operation includes: taking the population obtained in the previous iteration as the parent population, performing selection, crossover, and mutation operations on the parent population based on the fitness value of the parent population to obtain a new population and an updated objective function value, and calculating the fitness value of each individual obtained in the current iteration based on the updated objective function value; determining the penalty factor, and updating the fitness value of each individual obtained in the current iteration based on the penalty factor.

[0145] Specifically, based on the objective function which sets the order constraints of the center wavelength combinations, the center wavelength constraints, and the total film thickness constraints, an initial population is randomly generated to ensure that it can cover the possible solution space. Each individual in the initial population represents a set of center wavelength combinations and the number of film layers. For example, each individual can be represented as a vector, x = [λ1, λ2, ..., λ]. N , L], where, λ1, λ2,…,λ N is the combination of center wavelengths, and L is the number of film layers. Substituting the center wavelength combination and the number of film layers for each individual into the objective function yields the objective function value for that individual.

[0146] For each individual in the initial population, the reflectance over the traversed wavelength range is calculated using the transfer matrix algorithm. The process includes: constructing the transfer matrix for each layer of the multilayer film; calculating the overall system transfer matrix based on the transfer matrix of each layer; and calculating the reflectance at each wavelength within the traversed wavelength range using the overall system transfer matrix. The mean reflectance within the center wavelength range is calculated, and this mean reflectance is defined as the fitness value of the individual. Each individual in the resulting initial population corresponds to an objective function value and a fitness value.

[0147] Furthermore, iterative optimization is performed, repeating the iteration optimization operation until the fitness value obtained in a certain iteration meets the optimization objective or the number of iterations reaches the preset number of iterations. The optimization objective includes maximizing the fitness value of the optimal solution and exceeding the target reflectivity by 0.98. The maximum number of iterations can be set to a number between 200 and 300 according to actual needs.

[0148] Iterative optimization operations include: selection, which selects individuals with better fitness values ​​as parents; common selection methods include roulette wheel selection and tournament selection, where individuals with higher fitness values ​​have a higher probability of being selected; crossover selection, which performs a crossover operation on the selected parents to generate new offspring, for example, partially exchanging the central wavelength combination of two parents, or exchanging the number of membrane layers of two parents to form a new central wavelength combination and / or membrane layer distribution; and mutation, which randomly mutates the offspring to increase population diversity, for example, randomly adjusting the value of a certain central wavelength or number of membrane layers to explore new design spaces. Finally, the population is updated by replacing the parents with the newly generated offspring to form a new generation of the population.

[0149] For each individual in the new generation population, based on the updated objective function value, its fitness value is recalculated using the optical transfer matrix algorithm, and the fitness value is updated using a penalty factor. The new fitness value is compared to see if it meets the optimization objective, and the optimization direction is adjusted accordingly.

[0150] See Figure 4The graph shows the convergence of the iterative process of the genetic algorithm, with the horizontal axis representing the iteration round and the vertical axis representing the fitness value obtained in the intermediate iteration round.

[0151] This application utilizes the global search capability of genetic algorithms to efficiently explore complex design spaces, avoid getting trapped in local optima, and ensure that the optimization results meet the target reflectivity requirements and physical constraints through fitness functions and penalty factors, ultimately achieving high-precision optimization of multilayer film designs.

[0152] One possible implementation of this application embodiment involves determining a penalty factor and updating the fitness value of each individual obtained in the current iteration based on the penalty factor, including:

[0153] For each individual obtained in the current iteration, calculate the difference between the individual's fitness value and the target reflectivity; calculate the product of the difference and the adjustment coefficient as a penalty factor, and adjust the individual's fitness value based on the penalty factor.

[0154] In this embodiment, a penalty factor is used to penalize individuals that do not meet the target reflectivity requirement, thereby reducing their fitness value. The penalty factor is calculated based on the difference between the individual's fitness value and the target reflectivity.

[0155] For each individual, calculate the difference between its fitness value and the target reflectivity. When the difference is less than 0, it means that the individual's fitness value does not meet the target reflectivity requirement.

[0156] In one possible scenario, technicians can determine a positive number as the adjustment factor based on experience. The product of this difference and the adjustment coefficient is then calculated as the penalty factor, resulting in a negative penalty factor. The sum of the penalty factor and the individual's fitness value is then calculated as the adjusted fitness value. For example, if an individual's fitness value is 0.95, which does not meet the requirement of being greater than the target reflectivity of 0.98, the difference between the fitness value and the target reflectivity is calculated to be -0.03. The adjustment coefficient is set to 10, and the product of the difference and the adjustment coefficient is calculated to be -0.3, which is used as the penalty factor. The sum of the penalty factor and the fitness value, 0.65, is then used as the adjusted fitness value.

[0157] In another possible scenario, a technician can empirically determine a negative number as the adjustment coefficient, and calculate the product of this difference and the adjustment coefficient as the penalty factor, with the penalty factor ranging from 0 to 1. Then, the product of the penalty factor and the individual's fitness value is calculated as the adjusted fitness value.

[0158] This application's embodiments introduce a penalty mechanism to effectively guide the optimization process toward meeting the target reflectivity, avoiding the algorithm from generating unacceptable solutions, while improving optimization efficiency and solution quality.

[0159] One possible implementation of this application embodiment includes:

[0160] After the iteration is completed, the reflectivity of the wavelength range corresponding to the optimal solution is determined, and the reflectivity curve is plotted based on the reflectivity of the wavelength range.

[0161] The reflectance corresponding to the center wavelength range is selected from the reflectances traversed across the wavelength range, and the mean and standard deviation of reflectance are calculated based on the reflectances corresponding to the center wavelength range, so as to verify the iteration results through the mean and standard deviation of reflectance.

[0162] In this embodiment, the optimal solution includes the combination of center wavelengths (N center wavelengths) and the number of film layers L. Within the traversal wavelength range, the reflectance of the multilayer film is calculated for each wavelength value, resulting in a reflectance dataset. This dataset is then used as plotting data, and a plotting tool (such as Matplotlib, Excel, etc.) is used to draw a reflectance curve. Figure 5 As shown, the horizontal axis of the reflectivity curve represents the wavelength value, and the vertical axis represents the reflectivity. Furthermore, based on the optimal solution and the refractive indices of both the high-refractive-index and low-refractive-index films, the total film thickness corresponding to the optimal solution can be calculated, and this total film thickness can be used as an evaluation metric.

[0163] Select the reflectivity within the center wavelength range and calculate the mean and standard deviation of reflectivity. If the mean reflectivity is greater than the target reflectivity of 0.98, it indicates that the optimization result meets the design requirements. A pre-set standard deviation requirement for reflectivity can also be set. Comparing the calculated standard deviation with the pre-set requirement allows for checking whether the reflectivity distribution is uniform within the center wavelength range and whether the smoothness of the reflectivity curve meets the requirements.

[0164] The embodiments of this application utilize reflectivity curves and quantitative indicators (mean and standard deviation) to comprehensively evaluate the quality of the optimization results, ensuring that the reflectivity of the multilayer film reaches the optimal and is uniformly distributed within the target wavelength range.

[0165] Genetic algorithms are intelligent optimization algorithms that simulate biological evolution, characterized by their ability to rapidly search for the global optimum in complex, multi-layered, and multi-parameter nonlinear optimization spaces. Therefore, using genetic algorithms to optimize the design of optical multilayer films can achieve high performance within the target wavelength range. Furthermore, other intelligent optimization algorithms such as simulated annealing and particle swarm optimization can replace genetic algorithms.

[0166] The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm provided in this application is also applicable to other wavelength ranges and to different reflectivity requirements. It is not only applicable to dual brightness enhancement film (DBEF) structures, but can also be applied to the design of other types of optical thin films such as bandpass filters and antireflection films.

[0167] This application utilizes a genetic algorithm to avoid the local minima problem of traditional methods, and has global search capabilities in high-dimensional, multi-constraint problems; it can flexibly adjust the target reflectivity and wavelength range, and supports multi-target thin film design; it introduces constraints through penalty terms to automatically meet requirements such as film thickness sorting and total thickness limits; the method can be extended to other types of multilayer film design, such as bandpass filters and antireflection films.

[0168] This application provides an electronic device, such as... Figure 6 As shown, Figure 6 The illustrated electronic device 600 includes a processor 601 and a memory 603. The processor 601 and the memory 603 are connected, for example, via a bus 602. Optionally, the electronic device 600 may also include a transceiver 604. It should be noted that in practical applications, the transceiver 604 is not limited to one type, and the structure of this electronic device 600 does not constitute a limitation on the embodiments of this application.

[0169] Processor 601 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 601 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0170] Bus 602 may include a pathway for transmitting information between the aforementioned components. Bus 602 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 602 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The symbol is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0171] The memory 603 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0172] The memory 603 stores the application code that executes the scheme of this application, and its execution is controlled by the processor 601. The processor 601 executes the application code stored in the memory 603 to implement the content shown in the aforementioned embodiment of the brightness enhancement film center wavelength optimization method based on genetic algorithm.

[0173] Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0174] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the content shown in the aforementioned embodiment of the method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm.

[0175] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0176] This application provides a computer program product, including a computer program that, when executed by a processor, implements the content shown in the aforementioned embodiment of the method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm.

[0177] The above are only some embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm, characterized in that, include: Obtain preset environment parameters and define optimization variable parameters; Based on the preset environmental parameters and the optimized variable parameters, the multilayer membrane model is parametrically inversely designed using finite element simulation to obtain the objective function; Based on the objective function, a genetic algorithm is used to perform iterative simulation on the multilayer membrane model, and a fitness function is used to optimize it during the iteration process until the optimization objective is met or the number of iterations reaches the preset number of iterations. Obtain the optimal solution after iteration, wherein the optimal solution includes the combination of center wavelengths and the number of film layers; The process of obtaining preset environmental parameters and defining optimization variable parameters includes: The preset environmental parameters are obtained, including: the structural parameters, wavelength range parameters, and target reflectivity of the multilayer film model; A preset number of center wavelengths is defined as a center wavelength combination, and the center wavelength combination and the number of film layers are used as the optimization variable parameters. The multilayer film model is composed of alternating stacks of high-refractive-index films and low-refractive-index films. The number of groups of the multilayer film model is equal to the preset number. The sum of the number of high-refractive-index films and low-refractive-index films in each group is the number of film layers. The structural parameters of the multilayer film model include: the refractive index of the high-refractive-index film, the refractive index of the low-refractive-index film, the refractive index of the substrate, and the total thickness range of the film layers; the wavelength range parameters include: the traversal wavelength range and the center wavelength range. Based on the preset environmental parameters and the optimized variable parameters, a parametric inverse design of the multilayer membrane model is performed using finite element simulation to obtain the objective function, including: Apply a sequence constraint to the center wavelength combination; Based on the aforementioned center wavelength combination, the overall system transmission matrix of the multilayer film model is constructed; Obtain the air refractive index, and calculate the reflectivity based on the total system transmission matrix, the air refractive index, and the substrate refractive index; Construct the objective function, the expression of which is: ； in, Let be the objective function. For center wavelength combination, The refractive index of a high-refractive-index film, The refractive index of a low-refractive-index film, The refractive index of air, The refractive index of the substrate, To traverse the wavelength range, The total thickness of the film layer. For the number of film layers, For target reflectivity, This is the upper limit of the center wavelength range. This is the lower bound of the center wavelength range; The overall system transmission matrix of the multilayer film model, constructed based on the center wavelength combination, includes: For each group in the multilayer film model, the first thickness of the high-refractive-index film and the second thickness of the low-refractive-index film in the group are calculated based on the center wavelength combination; a first transmission matrix of the group is constructed based on the first thickness, a second transmission matrix of the group is constructed based on the second thickness, and a transmission matrix of the group is constructed based on the first transmission matrix, the second transmission matrix, and the number of film layers; The total system transmission matrix of the multilayer membrane model is obtained by multiplying the transmission matrices of the preset number of groups.

2. The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm according to claim 1, characterized in that, The method further includes: A center wavelength constraint and a total film thickness constraint are applied to the objective function; Wherein, the center wavelength constraint is that the combination of center wavelengths in the objective function is within the center wavelength range; the total film thickness constraint is that the total film thickness in the objective function is within the total film thickness range, and the total film thickness is determined based on the combination of center wavelengths, the refractive index of the high refractive index film, the refractive index of the low refractive index film, and the number of film layers.

3. The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm according to claim 1, characterized in that, The calculation of reflectivity based on the total system transmission matrix, the air refractive index, and the substrate refractive index includes: Substituting the total system transmission matrix, the air refractive index, and the substrate refractive index into the reflection coefficient formula, we obtain the reflection coefficient, which is: ； in, The reflection coefficient, For the overall system transmission matrix, The refractive index of air, The refractive index of the substrate; Substituting the reflection coefficient into the reflectance formula, we obtain the reflectance, which is: ； in, For reflectivity, This is the reflection coefficient.

4. The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm according to claim 1, characterized in that, The step of performing iterative simulations on the multilayer membrane model using a genetic algorithm based on the objective function, and optimizing it using a fitness function during the iteration process, until the optimization objective is met or the number of iterations reaches a preset number, includes: The initial population is randomly generated based on the objective function; Using the fitness function, the fitness value of each individual is calculated based on the objective function value corresponding to each individual in the initial population. The fitness value is the average of the reflectance values ​​corresponding to the center wavelength range. Perform iterative optimization operations until the fitness value obtained in the current iteration satisfies the optimization objective or the number of iterations reaches the preset number of iterations; The iterative optimization operation includes: taking the population obtained in the previous iteration as the parent population, performing selection, crossover, and mutation operations on the parent population based on the fitness value of the parent population to obtain a new population and an updated objective function value, and calculating the fitness value of each individual obtained in the current iteration based on the updated objective function value; determining a penalty factor, and updating the fitness value of each individual obtained in the current iteration based on the penalty factor.

5. The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm according to claim 4, characterized in that, The step of determining the penalty factor and updating the fitness value of each individual obtained in the current iteration round based on the penalty factor includes: For each individual obtained in the current iteration, the difference between the individual's fitness value and the target reflectivity is calculated; the product of the difference and the adjustment coefficient is calculated as a penalty factor, and the individual's fitness value is adjusted based on the penalty factor.

6. The method for optimizing the center wavelength of a brightness enhancement film based on a genetic algorithm according to claim 1, characterized in that, The method further includes: After the iteration is completed, the reflectivity of the traversed wavelength range corresponding to the optimal solution is determined, and a reflectivity curve is plotted based on the reflectivity of the traversed wavelength range. The reflectance corresponding to the center wavelength range is selected from the reflectance of the traversed wavelength range, and the mean reflectance and standard deviation of reflectance are calculated based on the reflectance corresponding to the center wavelength range, so as to verify the iteration results through the mean reflectance and the standard deviation of reflectance.

7. An electronic device, characterized in that, include: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, said at least one application being configured to: execute the genetic algorithm-based center wavelength optimization method for brightening films according to any one of claims 1-6.

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