Thin film design method for increasing reflection / increasing transmission based on optical interference and mathematical optimization

Abstract

The present application belongs to the technical field of optical film design, and relates to a high-reflection / high-transmission film design method based on optical interference and mathematical optimization. The method comprises the following steps: obtaining the material combination, layer number and thickness of each layer of a film system; based on the principle of optical interference, the transfer matrix method or the Fresnel coefficient recursive formula is used to calculate the theoretical transmittance and reflectance of the current film system at different wavelengths, and an evaluation function for quantifying the difference between the spectral performance of the film system and the preset spectral performance index is constructed; taking the minimization of the evaluation function as the target, the gradient descent method or the genetic algorithm is used to optimize the material combination, layer number and thickness of each layer of the film system until the film system parameters satisfying the spectral performance index are obtained. The present application can efficiently obtain a selective film with high transmittance in the response wavelength band of a photovoltaic cell and high reflectance in the infrared wavelength band, thereby significantly improving the photovoltaic power generation efficiency and reducing the thermal load of the component.

Description

Technical Field

[0001] This invention belongs to the field of optical thin film design technology, and relates to a method for designing antireflective / antitransmittance thin films based on optical interference and mathematical optimization. Background Technology

[0002] Photovoltaic power generation technology is an important way to realize solar energy conversion. In recent years, its conversion efficiency has been continuously improving and its cost has been continuously decreasing, gradually meeting the conditions for large-scale commercial application. However, while generating electricity efficiently, traditional photovoltaic modules also absorb a large amount of infrared light and convert it into heat energy, leading to module temperature rise and efficiency reduction, while also exacerbating the local thermal effect.

[0003] To address this challenge, selective optical thin films, which combine "high-efficiency photovoltaic power generation" and "thermal radiation management," have emerged. These films aim to achieve selective modulation of the solar spectrum: high transmission in the photovoltaic cell response band (e.g., 350~1100nm) to improve photoelectric conversion efficiency; and high reflectivity in the near-infrared band (e.g., >1100nm) to reduce unnecessary heat absorption, thereby lowering the module's operating temperature and the environmental heat load, achieving the dual benefits of "power generation" and "cooling."

[0004] Currently, the design and fabrication of optical thin films mainly revolve around single functions: firstly, antireflective coatings for the visible to near-infrared band, aiming to improve light transmittance; and secondly, high-reflectivity coatings for the infrared band, used for thermal control or energy saving. In terms of antireflective coatings, common materials include SiO2, TiO2, and MgF2, which reduce surface reflection loss through single-layer or multi-layer film designs. However, their designs are mostly focused on broadband antireflection, lacking precise selectivity for specific wavelengths. Regarding reflective coatings, while metal thin films or multilayer dielectric films can achieve high reflectivity, they often also exhibit strong reflection in the visible light band, which is detrimental to photovoltaic power generation.

[0005] Although existing studies have attempted to combine antireflection and reflection functions, achieving selective spectral modulation of high visible light transmittance and high near-infrared reflectance in the same film system still faces many challenges: on the one hand, the refractive index matching and film thickness design of materials are complex, making it difficult to simultaneously meet the opposite optical requirements of two bands; on the other hand, existing designs mostly rely on experience or local optimization, lacking a systematic and customizable multifunctional film system design method, especially in terms of adaptability to different photovoltaic cell response bands and thermal management requirements, there is still considerable room for improvement.

[0006] In recent years, the development of numerical simulation technologies such as TFCalc and other optical design software has provided powerful tools for the spectral design of multilayer films, enabling the design of film structures with specific spectral targets through optimization algorithms. However, research on the system design of selectively transmittant / reflectant thin films integrating photovoltaic and thermal control is still relatively limited, especially in the design and performance verification of film systems that achieve synergistic optimization of high transmittance and high reflectance in the atmospheric window band, for which no mature reports have been found. Summary of the Invention

[0007] To address the problems in the prior art, this invention provides a design method for antireflective / antitransmittance thin films based on optical interference and mathematical optimization. This method combines evaluation functions with numerical simulation optimization to efficiently obtain selective thin films with high transmission in the photovoltaic cell response band and high reflectivity in the infrared band, thereby significantly improving photovoltaic power generation efficiency and reducing module heat load.

[0008] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for designing antireflective / anti-reflective thin films based on optical interference and mathematical optimization, comprising the following steps: Obtain the material composition, number of layers, and thickness of each layer of the membrane system; Based on the principle of optical interference, the theoretical transmittance and reflectance of the current film system at different wavelengths are calculated using the transfer matrix method or Fresnel coefficient recursion formula, and an evaluation function is constructed to quantify the difference between the spectral performance of the film system and the preset spectral performance index. With the goal of minimizing the evaluation function, the material combination, number of layers, and thickness of each layer of the membrane system are optimized using gradient descent or genetic algorithm until the membrane system parameters that meet the spectral performance indicators are obtained.

[0009] Preferably, the evaluation function The expression is:

[0010] In the formula, These are the design variables for the membrane system, including the material combination, the number of layers, and the thickness of each layer; This represents the total number of spectral sampling points; For the first Weighting factors for each sampling point; For the current membrane system in the th spectral characteristics of each sampling point; For the first Ideal spectral characteristics of each sampling point.

[0011] Preferably, the preset spectral performance indicators include: an average transmittance of not less than 85% in the wavelength range of 350nm to 1100nm, and an average reflectance of not less than 90% in the wavelength range of 1100nm to 1500nm.

[0012] Preferably, the film structure that meets the preset spectral performance index is [(LMHM)×10]L; wherein L is CaF2, M is ZrO2, H is TiO2, the film substrate is CaF2, and the working angle is 0°.

[0013] Preferably, the preset spectral performance indicators include: an average transmittance of not less than 85% in the wavelength range of 350nm to 900nm, and an average reflectance of not less than 90% in the wavelength range of 900nm to 1500nm.

[0014] Preferably, the film structure that meets the preset spectral performance index is [(LMHM)×10]L; wherein L is MgF2, M is ZrO2, H is TiO2, the film substrate is CaF2, and the working angle is 0°.

[0015] Preferably, after obtaining the membrane system parameters that meet the spectral performance indicators, the method further includes: designing the antireflective / anti-reflective film based on the membrane system parameters that meet the spectral performance indicators.

[0016] Secondly, the present invention provides a design system for antireflective / anti-reflective thin films based on optical interference and mathematical optimization, comprising: Data acquisition module: used to acquire the material composition, number of layers, and thickness of each layer of the membrane system; Evaluation function construction module: Based on the principle of optical interference, it calculates the theoretical transmittance and reflectance of the current film system at different wavelengths using the transfer matrix method or Fresnel coefficient recursion formula, and constructs an evaluation function to quantify the difference between the spectral performance of the film system and the preset spectral performance index. Membrane system parameter optimization module: This module optimizes the material combination, number of layers, and thickness of each layer of the membrane system using gradient descent or genetic algorithm with the goal of minimizing the evaluation function, until membrane system parameters that meet the spectral performance indicators are obtained.

[0017] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of an antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of an anti-reflective / anti-reflective thin film design method based on optical interferometry and mathematical optimization.

[0019] Compared with the prior art, the present invention has the following beneficial effects: By obtaining the material composition, number of layers, and thickness of each layer of the film system as design variables, and using the transfer matrix method or Fresnel coefficient recursive formula based on the principle of optical interference to accurately calculate the theoretical transmittance and reflectance of the film system at different wavelengths, the spectral performance of the film system can be objectively quantified. On this basis, an evaluation function is constructed to characterize the difference between the current performance and the preset index. Then, with the goal of minimizing the evaluation function, the gradient descent method or genetic algorithm is used to automatically iteratively optimize the material composition, number of layers, and thickness. This transforms the film system design from traditional trial and error based on experience into a systematic search process with clear mathematical guidance and convergence criteria, significantly improving optimization efficiency and global optimization capability. The final obtained film system parameters can be directly used to prepare antireflective / anti-reflective films, thereby achieving high transmittance in the effective response band of photovoltaic cells and high reflectance in the infrared band, effectively reducing module temperature rise and improving photoelectric conversion efficiency. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 The transmission spectrum of the multifunctional optical thin film obtained by simulation in the implementation of the present invention is a theoretical simulation. Figure 2 The transmission spectrum of the multifunctional optical thin film obtained by simulation in the implementation of the present invention is a theoretical simulation. Detailed Implementation

[0022] To enable those skilled in the art to understand the features and effects of the present invention, the terms and expressions used in the specification and claims are explained and defined in general below. Unless otherwise specified, all technical and scientific terms used herein have the ordinary meaning understood by those skilled in the art regarding the present invention, and in case of conflict, the definitions in this specification shall prevail.

[0023] The theories or mechanisms described and disclosed herein, whether right or wrong, should not in any way limit the scope of the invention, that is, the contents of the invention can be implemented without being limited by any particular theory or mechanism.

[0024] In this document, all features defined by numerical ranges or percentage ranges, such as numerical values, quantities, contents, and concentrations, are for the sake of brevity and convenience only. Accordingly, descriptions of numerical ranges or percentage ranges should be considered as covering and specifically disclosing all possible sub-ranges and individual numerical values ​​(including integers and fractions) within those ranges.

[0025] In this article, unless otherwise specified, “contains,” “includes,” “containing,” “has,” or similar terms cover the meanings of “composed of” and “mainly composed of,” for example, “A contains a” covers the meanings of “A contains a and others” and “A contains only a.”

[0026] For the sake of brevity, not all possible combinations of the technical features in each implementation scheme or embodiment are described herein. Therefore, as long as there is no contradiction in the combination of these technical features, the technical features in each implementation scheme or embodiment can be combined arbitrarily, and all possible combinations should be considered within the scope of this specification.

[0027] For ease of understanding, the following explains some key terms in this embodiment: Optical interference principle: This refers to the phenomenon where, during the propagation of light waves, when two or more light waves meet, their amplitudes and phases overlap, leading to a redistribution of light intensity. In thin film design, by precisely controlling the thickness and refractive index of the thin film, the interference effect of light can be used to achieve selective transmission or reflection of light of specific wavelengths.

[0028] Mathematical optimization theory refers to mathematical methods for finding the maximum or minimum value of a certain objective function under given constraints. In thin film design, this theory is applied to find the optimal film material, thickness, and stacking order to ensure that the spectral properties of the thin film meet preset specifications.

[0029] Evaluation function: A mathematical expression used to quantify the difference between the spectral performance of a thin film and the target performance. By calculating the value of the evaluation function, the merits of the current film system design can be objectively assessed, and the optimization algorithm can be guided to iterate towards a better solution.

[0030] Numerical simulation refers to the use of computer programs to calculate and simulate physical systems or processes. In thin film design, numerical simulation is used to predict the optical properties under different material combinations and film structures, thereby verifying and optimizing the design scheme before actual fabrication.

[0031] Optical thin film design software refers to computer programs specifically designed to assist in the design and optimization of multilayer optical thin films. This software typically integrates functions such as optical interferometry calculations, material databases, optimization algorithms, and spectral performance analysis, enabling efficient exploration of complex film structures.

[0032] Film structure optimization refers to the process of adjusting parameters such as the type of thin film material, the thickness of each layer, and the stacking order to make the spectral performance of the thin film reach or approach a predetermined target. This optimization is usually achieved using mathematical optimization algorithms and optical thin film design software.

[0033] Spectral performance indicators refer to the quantitative requirements for the transmittance and reflectance of thin films within a specific wavelength range. In this application, these indicators are set to achieve high transmittance in the effective response band of photovoltaic cells and high reflectance in the infrared band, in order to meet the needs of photovoltaic power generation and thermal management.

[0034] The present invention will now be described in further detail with reference to the accompanying drawings: The first objective of this invention is to provide a method for designing antireflective / anti-reflective thin films based on optical interferometry and mathematical optimization, comprising the following steps: Obtain the material composition, number of layers, and thickness of each layer of the membrane system; Based on the principle of optical interference, the theoretical transmittance and reflectance of the current film system at different wavelengths are calculated using the transfer matrix method or Fresnel coefficient recursion formula, and an evaluation function is constructed to quantify the difference between the spectral performance of the film system and the preset spectral performance index. With the goal of minimizing the evaluation function, the gradient descent method or genetic algorithm is used to optimize the material combination, number of layers and thickness of each layer of the membrane system until the membrane system parameters that meet the spectral performance index are obtained; The antireflective / anti-reflective film is designed based on the film system parameters that meet the aforementioned spectral performance indicators.

[0035] This method first calculates the theoretical transmittance and reflectance of a multilayer film system at different wavelengths based on the principle of optical interference and mathematical optimization theory. Then, it constructs an evaluation function that quantifies the difference between the actual spectral performance of the film system and the preset spectral performance indicators, thus transforming the complex optical design problem into a solvable mathematical optimization problem. Based on this, minimizing the evaluation function is the core optimization objective. Numerical simulation methods (such as gradient descent, genetic algorithms, and other global optimization algorithms) are used to search and optimize the material combination, the total number of film layers, and the physical thickness of each film layer. The material combination is selected from common media materials (such as low-refractive-index MgF2, SiO2, CaF2; medium-refractive-index ZrO2, Al2O3; and high-refractive-index TiO2, Ta2O5, etc.) according to the refractive index requirements of the target wavelength band. The film layer thickness typically varies continuously between a few nanometers and several hundred nanometers until the evaluation function converges below a preset threshold, ultimately obtaining a set of optimal film system parameters that meet specific spectral performance indicators.

[0036] Specifically, the present invention can be implemented in different ways with varying complexity according to actual needs: In a more direct implementation, the transmittance and reflectance of the film in the target wavelength range can be calculated layer by layer using the Fresnel coefficient recursive formula based on the number of film layers, the refractive index of each layer, and the physical thickness. A simple error function (e.g., the sum or square of the absolute values ​​of the differences between the calculated values ​​and the target values ​​at each wavelength) can be manually set to quantitatively evaluate the deviation between the current film system and the preset spectral performance indicators. In another implementation, the transfer matrix method (also known as the characteristic matrix method) derived from Maxwell's equations can be used. Each layer of the film can be represented by a 2×2 characteristic matrix. The reflectance and transmittance coefficients of the entire film system can be quickly obtained through matrix multiplication, thereby accurately calculating the spectral response at any wavelength. Based on this, a target function containing multiple weighting factors can be constructed, that is, different weighting coefficients are assigned to the performance deviations at different bands and different wavelengths to comprehensively evaluate the overall performance of the film in the photovoltaic cell response band and the infrared reflection band.

[0037] Furthermore, to systematically study the influence of different materials and stacking methods on optical performance and provide a reliable reference for fabrication, parameterized scanning can be performed using numerical simulation methods: A series of preset material combinations (e.g., low-refractive-index materials can be SiO2, MgF2, CaF2; high-refractive-index materials can be TiO2, Ta2O5, Nb2O5, etc.) and film thicknesses are manually input, and the corresponding spectral curves are calculated using optical simulation tools. The trends of transmittance and reflectance with material refractive index contrast, film period number, and thickness ratio are observed. For example, a simple periodic stacking structure (such as...) can be used initially. Simulations were conducted to gain a preliminary understanding of the impact of increasing the number of layers or changing the high-low refractive index ratio on the position and width of the cutoff zone, thereby providing a reasonable initial structure for subsequent fine optimization.

[0038] Furthermore, optical thin-film design software is used to optimize the film structure to obtain film parameters that meet specific spectral performance indicators. In one implementation, iterative optimization algorithms can be implemented using scripts written in general numerical calculation software (such as MATLAB or Python), such as gradient descent (which gradually adjusts the thickness by calculating the sensitivity of the evaluation function to the thickness of each layer) or genetic algorithms (which simulate the natural selection process, performing a global search for material combinations, number of layers, and thickness). Each iteration recalculates the spectral performance and updates the evaluation function value until the function value converges below a preset threshold. In another implementation, commercially available mature optical design tools (such as TFCalc and Essential) can be directly utilized. Macleod allows users to manually input the initial film structure and call its built-in optimization modules (such as the simplex method, simulated annealing, or needle optimization) to automatically adjust the film thickness or replace material combinations to approximate the preset spectral performance target. All of these methods are based on the organic integration of optical interference principles and mathematical optimization theory. By transforming the thin film design problem into a quantifiable evaluation function minimization problem, the design process is freed from the blindness of traditional trial-and-error, possessing the advantages of systematization, reproducibility, and objective convergence criteria, significantly shortening the design cycle and reducing experimental prototyping costs. Furthermore, whether using a simple Fresnel error function or a transfer matrix objective function with multiple weighting factors, it can flexibly... By adapting to the spectral response characteristics of different photovoltaic cells, selective thin films with high transmittance in the visible light region and high reflectivity in the near-infrared region can be customized by adjusting the target wavelength and weight distribution. Furthermore, by combining numerical simulation parameter scanning and global optimization algorithms, the vast design space of material combinations and film structures can be effectively explored, avoiding getting trapped in local optima, thereby obtaining film system parameters with better performance and stronger robustness. Finally, when the optical thin film designed and prepared using this method is placed on the surface of photovoltaic modules, it can significantly reflect infrared light while ensuring efficient transmission in the effective response wavelength of the photovoltaic cells, reducing module heat absorption and temperature rise, improving power generation efficiency and long-term operational stability, and achieving significant economic and environmental benefits.

[0039] In summary, this method, by systematically integrating optical interference principles, mathematical optimization theory, and numerical simulation techniques, effectively solves the problems of temperature rise and efficiency decline in traditional photovoltaic modules caused by infrared light absorption. This achieves precise selective control of the solar spectrum within the same thin-film system, realizing high transmission in the effective response band of the photovoltaic cell while simultaneously achieving high reflectivity in the infrared band, thereby reducing the module's operating temperature, improving photoelectric conversion efficiency, and mitigating environmental heat load.

[0040] For example, the evaluation function The expression is:

[0041] In the formula, These are the design variables for the membrane system, including the material combination, the number of layers, and the thickness of each layer; This represents the total number of spectral sampling points; For the first Weighting factors for each sampling point; For the current membrane system in the th spectral characteristics of each sampling point; For the first Ideal spectral characteristics of each sampling point.

[0042] Specifically, design variables It encompasses the material composition of the film system, the total number of layers, and the physical thickness of each layer; these variables collectively determine the optical properties of the thin film. The sampling density should be sufficient to reflect the detailed changes in the spectral curve, and should be the total number of discrete wavelength sampling points selected uniformly or non-uniformly within the solar spectral range of interest (e.g., 350 nm to 1500 nm). For the first The weighting factor corresponding to each sampling point can be flexibly adjusted according to the importance of different bands. For example, a larger weight is given to the main response band of the photovoltaic cell to prioritize the transmission rate, and an appropriate weight is also given to the infrared band that needs to be suppressed to ensure that the reflectivity meets the standard. For the current membrane system in the th The actual spectral characteristics (which can be transmittance, reflectance, or a combination of both) are calculated at each sampling point using the transfer matrix method or the Fresnel coefficient recursive formula. Then it is the first Ideal spectral characteristics at each sampling point (e.g., target transmittance of 100% or target reflectance of 100%); by constructing this evaluation function, the membrane system design problem is transformed into a typical least-squares optimization problem, that is, seeking a set of optimal design variables. This makes the evaluation function When the value is minimized, the actual spectral performance is closest to the ideal target. Furthermore, this invention allows for adjustments to the sampling point range, density, and weighting factor. By flexibly controlling the optimization priority of different wavebands and different optical parameters (transmission / reflection), customized film systems can be obtained for specific photovoltaic cell spectral response characteristics.

[0043] For example, the preset spectral performance indicators include: Indicator 1: The average transmittance in the wavelength range of 350nm to 1100nm is not less than 85%, and the average reflectance in the wavelength range of 1100nm to 1500nm is not less than 90%.

[0044] Indicator 2: The average transmittance in the wavelength range of 350nm to 900nm is not less than 85%, and the average reflectance in the wavelength range of 900nm to 1500nm is not less than 90%.

[0045] The film structure satisfying criterion one is [(LMHM)×10]L, where L is CaF2, M is ZrO2, H is TiO2, the film substrate is CaF2, and the working angle is 0°. This structure utilizes the excellent transparency of CaF2 in the ultraviolet, visible, and near-infrared bands and its good refractive index matching characteristics with the substrate. Combined with alternating stacked units of high, medium, and low refractive indices composed of ZrO2 and TiO2, through a periodic design of 40 basic units plus an outer layer L, precise constructive and destructive interference effects are generated over a wide spectral range, thereby simultaneously achieving high transmission in the target band and high reflectivity in the infrared band. The film structure satisfying criterion two is [(LMHM)×10]L, where L is MgF2, M is ZrO2, H is TiO2, the film substrate is CaF2, and the working angle is 0°. MgF2 has a lower refractive index (approximately 1.38), which can further reduce surface reflection and broaden the antireflection bandwidth. The two types of indicators correspond to different transmission / reflection cutoff wavelengths, which can flexibly adapt to the needs of mainstream photovoltaic technologies. This allows the thin film to ensure efficient light absorption by the battery while significantly reflecting useless infrared radiation, thereby reducing the operating temperature of the module, delaying thermal degradation, and ultimately achieving a dual improvement in the power generation and reliability of the photovoltaic system.

[0046] A second objective of this invention is to provide a design system for antireflective / anti-reflective thin films based on optical interferometry and mathematical optimization, comprising: Data acquisition module: used to acquire the material composition, number of layers, and thickness of each layer of the membrane system; Evaluation function construction module: Based on the principle of optical interference, it calculates the theoretical transmittance and reflectance of the current film system at different wavelengths using the transfer matrix method or Fresnel coefficient recursion formula, and constructs an evaluation function to quantify the difference between the spectral performance of the film system and the preset spectral performance index. Membrane system parameter optimization module: This module optimizes the material combination, number of layers, and thickness of each layer of the membrane system using gradient descent or genetic algorithm with the goal of minimizing the evaluation function, until membrane system parameters that meet the spectral performance indicators are obtained.

[0047] This system acquires the material composition, number of layers, and thickness of each layer of the film system as initial input through a data acquisition module. The evaluation function construction module, based on the principle of optical interference and utilizing the transfer matrix method or Fresnel coefficient recursive formula, accurately calculates the theoretical transmittance and reflectance of the film system at different wavelengths. Simultaneously, it constructs a quantifiable evaluation function to measure the difference between the current performance and preset indicators. The film system parameter optimization module, guided by minimizing the evaluation function, uses gradient descent or genetic algorithms to automatically iteratively optimize the material composition, number of layers, and thickness, outputting the optimal film system parameters that meet the spectral performance indicators. This invention constructs a closed-loop system covering the entire process from data input, performance evaluation, automatic optimization to scheme generation, completely changing the inefficient traditional trial-and-error model. It achieves systematization, automation, and reproducibility in thin film design, significantly shortening the design cycle and reducing experimental prototyping costs. Furthermore, it can flexibly adapt to the spectral response requirements of different photovoltaic cells, efficiently obtaining selective thin films with high transmittance in the target wavelength band and high reflectance in the infrared band, providing reliable technical support for improving the photoelectric conversion efficiency and thermal management performance of photovoltaic modules.

[0048] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0049] The following examples use instruments and equipment conventional in the art. Experimental methods in the following examples, unless otherwise specified, are generally performed under conventional conditions or as recommended by the manufacturer. All raw materials used in the following examples are conventional commercially available products with specifications conventional in the art. In this specification and the following examples, unless otherwise specified, "%" refers to weight percentage, "parts" refers to parts by weight, and "ratio" refers to weight proportion.

[0050] Example 1 Table 1 shows the parameters of the selectively permeable / emitting thin film prepared in this embodiment.

[0051] Table 1. Parameters of the selectively permeable / emitting film in Example 1

[0052] Its thin film design structure is [(LMHM)×10]L, where L is CaF2, M is ZrO2, H is TiO2, the thin film substrate is CaF2, air is incident, the working angle is 0°, and the light source is white light.

[0053] Specifically, the thin film design structure is [(LMHM)×10]L, which is a method for representing the stacked structure of a multilayer dielectric thin film. L, M, and H represent material layers with different refractive indices, (LMHM) is a repeating unit, ×10 indicates that the unit is repeated 10 times, and the final L indicates that an additional L-material layer is added to the outermost layer. This periodic or quasi-periodic stacked structure utilizes the principle of optical interference to achieve selective transmission or reflection of light within a specific wavelength range by precisely controlling the refractive index and thickness of each layer. Besides the specific material combination of L, M, and H in this scheme, L in this structure can also be a low-refractive-index material such as MgF2 or SiO2; M can be a medium-refractive-index material such as Ta2O5 or Nb2O5; and H can be a high-refractive-index material such as ZnO or Al2O3.

[0054] L represents CaF2, M represents ZrO2, and H represents TiO2; these are the specific material choices for constructing the multilayer thin film. CaF2, as a low-refractive-index material, possesses good optical transparency and a relatively low refractive index, which helps reduce interface reflection and improve light transmittance. ZrO2, as a medium-refractive-index material, has a refractive index between low-refractive-index and high-refractive-index materials, playing a transitional and modulating role in the multilayer film system. TiO2, as a high-refractive-index material, has a high refractive index and good chemical stability, effectively enhancing light reflection in specific wavelength bands.

[0055] The thin film substrate is CaF2, which serves as the support material for thin film deposition. CaF2 was chosen as the substrate because it exhibits excellent light transmittance in the ultraviolet, visible, and near-infrared bands, and it has good compatibility with the CaF2 thin film material, helping to reduce interfacial reflection loss between the substrate and the thin film, thus ensuring overall optical performance. Besides CaF2, commonly used thin film substrate materials include quartz glass, sapphire, K9 glass, and BK7 glass. The choice of these substrate materials depends on the application scenario of the thin film, the required spectral range, and compatibility with the thin film material.

[0056] Air incidence refers to light entering the thin-film system from an air medium. This is the most common incidence environment in practical applications, simplifying the complexity of the optical model and making the design results closer to actual working conditions. In addition to air incidence, in some special applications, light may also be incident from other media (such as vacuum, water, or other transparent media). In this case, the design parameters need to be adjusted according to the refractive index of the actual medium.

[0057] The operating angle of 0° refers to light incident perpendicularly to the thin film surface. Under perpendicular incidence conditions, the optical performance of the thin film is typically the most stable and predictable, and in photovoltaic applications, perpendicular sunlight incidence is ideal, helping to maximize light energy utilization efficiency. In practical applications, sunlight is not always perpendicularly incident; there may be a certain angle of incidence. Therefore, in some designs, non-zero operating angles, such as 10 degrees, 30 degrees, or larger, may be considered to optimize the thin film's performance under different incident angles.

[0058] The light source is white light, referring to a broadband light source that simulates the solar spectrum. In photovoltaic applications, sunlight is the primary energy source, with a broad spectral range encompassing ultraviolet, visible, and near-infrared bands. Using white light as the light source in the design ensures that the thin film achieves the desired selective antireflective / antitransmittance functions across the entire solar spectrum. Besides white light, other types of light sources can be used in specific applications, such as monochromatic light, narrowband light sources in specific wavelengths, or light sources simulating specific environments (such as indoor lighting) to meet different design and testing requirements.

[0059] Based on the aforementioned technical solution, and building upon the evaluation function constructed using the principles of optical interference and mathematical optimization theory, and the optimization of the film system through numerical simulation, this application further provides an optimized film structure that meets specific spectral performance indicators. This solution precisely selects CaF2 as the low-refractive-index material (L), ZrO2 as the medium-refractive-index material (M), and TiO2 as the high-refractive-index material (H), employing a specific multilayer stacked structure of [(LMHM)×10]L. Combined with the settings of the CaF2 substrate, air incidence, 0-degree operating angle, and white light source, the film achieves high transmittance in the 350-1100 nm wavelength range and high reflectance in the 1100-1500 nm wavelength range. This refined material combination and structural design effectively utilizes the optical interference effect, achieving precise control of the solar spectrum, thus solving the challenge of achieving high-transmission and high-reflectance selective films in photovoltaic power generation. This film structure can maximize the conversion of light energy into electrical energy in the effective response band of the photovoltaic cell, while effectively blocking the thermal effects of infrared light, reducing the operating temperature of the photovoltaic module, and improving power generation efficiency and long-term stability of the module.

[0060] like Figure 1As shown, the thin film exhibits high transmittance in the 350–1100 nm wavelength range, with an average transmittance of 92.22%, and very low transmittance in the 1100–1500 nm range. Calculations show that the reflectance can reach as high as 98.51%. This satisfies the requirement of selective transmission / emission across different wavelength bands. It also meets the requirement of an average transmittance of not less than 85% in the 350–1100 nm wavelength range and an average reflectance (below 1500 nm) of not less than 90% in the 1100–1500 nm wavelength range.

[0061] Example 2 Table 2 shows the parameters of the selectively permeable / emitting thin film prepared in this embodiment.

[0062] Table 2 Parameters of the selectively permeable / emitting film in Example 2

[0063] The specific structure is [(LMHM)×10]L. This particular multilayer film stacking design, through the combination of repeating units, can precisely control the optical interference effect in different wavelength bands to achieve synergistic and efficient transmission and reflection within the target wavelength range. Here, L represents the low-refractive-index material MgF2. As a low-refractive-index material, MgF2 typically has a refractive index between 1.38 and 1.40. Its main function is to reduce reflection loss at the interface between the film and air, as well as within the film layer, thereby effectively improving the light transmittance in the 350-900nm wavelength range. Besides MgF2, other low-refractive-index materials such as SiO2 or CaF2 can also be used. M represents the medium-refractive-index material ZrO2. As a medium-refractive-index material, ZrO2 typically has a refractive index between 2.0 and 2.1. In the film system, it connects the low-refractive-index layer and the high-refractive-index layer, providing a smooth refractive index gradient, optimizing the optical matching of the multilayer film, and helping to broaden the high-transmission band and make the transition between the high-transmission and high-reflection bands steeper. In addition, materials such as Al2O3 can also be used as medium-refractive-index materials. H represents TiO2, a high-refractive-index material. TiO2, with a refractive index typically between 2.3 and 2.5, is key to achieving high reflectivity in the 900-1500 nm wavelength range. By forming a large refractive index difference with a low-refractive-index layer, the TiO2 layer can generate a strong interference effect, thus achieving efficient reflection in the infrared band. Materials such as Nb2O5 or Ta2O5 can also be used as high-refractive-index materials. CaF2 is chosen as the thin film substrate. CaF2 has excellent broad-spectrum transparency, and its refractive index matches well with the film material, helping to ensure the stability and efficiency of the overall optical performance. In practical applications, other transparent substrates such as quartz glass or BK7 glass can also be selected according to specific requirements. Furthermore, this design method is optimized under standard conditions of air incidence, a working angle of 0°, and white light as the light source, ensuring the reliability and versatility of the design scheme in actual photovoltaic application environments. Air incidence defines the initial medium environment in which light enters the thin film. A working angle of 0 degrees (i.e., perpendicular incidence) is the main working mode for photovoltaic modules to receive sunlight, while white light sources represent the broad spectral characteristics of sunlight.

[0064] The above technical solution provides specific parameters for optimizing the film structure to meet Index 2, including the number of film layers, total thickness, and the material and physical thickness of each layer. These precise parameter settings ensure that thin film design is no longer merely theoretical but feasible and repeatable. Specifically, this detailed film structure ensures precise control of optical interference effects, achieving high transmittance in the 350-900 nm wavelength range and high reflectivity in the 900-1500 nm wavelength range, effectively solving the problem of spectral performance uncertainty caused by the lack of specific parameters. This refined design significantly improves the accuracy of thin film fabrication and the consistency of performance, providing reliable technical support for photovoltaic modules to achieve efficient power generation in specific wavelength bands and thermal management in the infrared band.

[0065] like Figure 2 As shown, the thin film exhibits high transmittance in the 350–900 nm wavelength range, with an average transmittance reaching 92.02%, while displaying very low transmittance in the 900–1500 nm range. Calculations show that the average reflectance of the thin film can reach as high as 93.77%. This satisfies the requirement of selective transmission / emission across different wavelength bands. It also meets the requirement of an average transmittance of not less than 85% in the 350–900 nm wavelength range and an average reflectance of not less than 90% in the 900–1500 nm wavelength range (below 1500 nm).

[0066] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of an anti-reflective / anti-reflective thin film design method based on optical interferometry and mathematical optimization.

[0067] This invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the anti-reflection / anti-reflection thin film design method based on optical interferometry and mathematical optimization in the above embodiments.

[0068] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0069] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0070] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0071] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for designing antireflective / anti-reflective thin films based on optical interference and mathematical optimization, characterized in that, Includes the following steps: Obtain the material composition, number of layers, and thickness of each layer of the membrane system; Based on the principle of optical interference, the theoretical transmittance and reflectance of the current film system at different wavelengths are calculated using the transfer matrix method or Fresnel coefficient recursion formula, and an evaluation function is constructed to quantify the difference between the spectral performance of the film system and the preset spectral performance index. With the goal of minimizing the evaluation function, the material combination, number of layers, and thickness of each layer of the membrane system are optimized using gradient descent or genetic algorithm until the membrane system parameters that meet the spectral performance indicators are obtained.

2. The antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization according to claim 1, characterized in that, The evaluation function The expression is: In the formula, These are the design variables for the membrane system, including the material combination, the number of layers, and the thickness of each layer; This represents the total number of spectral sampling points. For the first Weighting factors for each sampling point; For the current membrane system in the th spectral characteristics of each sampling point; For the first Ideal spectral characteristics of each sampling point.

3. The antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization according to claim 1, characterized in that, The preset spectral performance indicators include: an average transmittance of not less than 85% in the wavelength range of 350nm to 1100nm, and an average reflectance of not less than 90% in the wavelength range of 1100nm to 1500nm.

4. The antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization according to claim 3, characterized in that, The structure of the membrane system is [(LMHM)×10]L; where L is CaF2, M is ZrO2, H is TiO2, the thin film substrate is CaF2, and the working angle is 0°.

5. The antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization according to claim 1, characterized in that, The preset spectral performance indicators include: an average transmittance of not less than 85% in the wavelength range of 350nm to 900nm, and an average reflectance of not less than 90% in the wavelength range of 900nm to 1500nm.

6. The antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization according to claim 5, characterized in that, The structure of the membrane system is [(LMHM)×10]L; where L is MgF2, M is ZrO2, H is TiO2, the thin film substrate is CaF2, and the working angle is 0°.

7. The antireflective / anti-reflective thin film design method based on optical interference and mathematical optimization according to claim 1, characterized in that, After obtaining the membrane system parameters that meet the spectral performance indicators, the method further includes: designing the antireflective / anti-reflective film based on the membrane system parameters that meet the spectral performance indicators.

8. A design system for antireflective / anti-reflective thin films based on optical interferometry and mathematical optimization, characterized in that, include: Data acquisition module: used to acquire the material composition, number of layers, and thickness of each layer of the membrane system; Evaluation function construction module: Based on the principle of optical interference, it calculates the theoretical transmittance and reflectance of the current film system at different wavelengths using the transfer matrix method or Fresnel coefficient recursion formula, and constructs an evaluation function to quantify the difference between the spectral performance of the film system and the preset spectral performance index. Membrane system parameter optimization module: This module optimizes the material combination, number of layers, and thickness of each layer of the membrane system using gradient descent or genetic algorithm with the goal of minimizing the evaluation function, until membrane system parameters that meet the spectral performance indicators are obtained.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

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