A design method for anti-reflective surfaces based on light field response characteristics

Abstract

The present invention discloses a method for designing an anti-reflective surface based on light field response characteristics, which relates to the field of optical surface treatment technology. The method comprises the following steps: S1, establishing a finite element model based on wave optics theory; S2, constructing a workpiece model based on two-dimensional air and substrate material using the finite element model, and dividing the entire workpiece model into multiple geometric regions according to different functions and properties; S3, performing nonlinear meshing on each region, and in the nonlinear meshing process, locally encrypting regions where the light field is repeatedly coupled; S4, conducting electromagnetic field simulation experiments on the microstructures of the workpiece model under various parameterizations, and screening out microstructure designs with relatively low reflectivity by analyzing the effects of different microstructure morphologies on reflectivity. The present invention provides a method for designing an anti-reflective surface based on light field response characteristics, analyzing the anti-reflection mechanism of the anti-reflective microstructure, and exploring the effects of microstructure-related parameters on anti-reflection performance.

Description

Technical Field

[0001] The present invention relates to the technical field of optical surface treatment, and more particularly to a method for designing an anti-reflection surface based on light field response characteristics. Background Art

[0002] In today's optical technology, surface reflection remains a pressing challenge, severely hindering further improvements in optical component performance. Traditional anti-reflection technologies primarily rely on multilayer thin-film interference systems composed of materials with varying refractive indices, such as magnesium fluoride and titanium dioxide. To achieve antireflection effects within specific wavelength bands, thin films with an optical thickness of λ / 4 must be precisely stacked. For example, a typical ultra-broadband antireflection coating system may require over 15 nanometer-scale deposition layers. This complex process requires production equipment equipped with an ultra-high vacuum magnetron sputtering system, significantly increasing manufacturing costs, accounting for approximately 30% to 45% of the total component cost. However, this traditional technology suffers from inherent limitations in multi-wavelength compatibility. When light waves enter at oblique incidence (θ > 30°), the altered equivalent optical path causes the designed interference conditions to fail. This angle-sensitivity significantly limits its application in wide-angle imaging systems, which require excellent optical performance at varying angles of incidence.

[0003] With continuous breakthroughs in nanofabrication technology, a new anti-reflection technology—biomimetic structural anti-reflection surfaces—has begun to attract widespread attention. Inspired by the super-hydrophobic moth-eye surfaces found in nature, researchers have developed a wide-spectrum anti-reflection structure based on subwavelength conical arrays. Theoretical calculations show that when the unit period is less than 1 / 4 of the incident wavelength, the refractive index exhibits a gradient along the height of the structure. Using equivalent medium theory, near-perfect impedance matching can be achieved, addressing the shortcomings of traditional technologies to a certain extent. However, this new design is not without flaws; it suffers from the common problem of wavelength-angle coupling. When the structural parameters are fixed, the quasi-linear distribution of the refractive index deviates from the design wavelength, triggering a Brillouin zone folding effect, leading to the appearance of anomalous transmission bands. This phenomenon makes existing technologies difficult to cope with the complex working conditions of a wide spectrum and multiple incident angles.

[0004] Most of the existing anti-reflection technologies are based on the optimization of a single optical parameter. This approach fails to fully consider the complex response characteristics of the light field in different spaces and frequencies. Therefore, the anti-reflection effect of these technologies is limited, and it is difficult to adapt to light of multiple wavelengths and incident angles. However, nanostructures can significantly enhance the local electromagnetic field through "plasmon resonance", thereby achieving a local "light absorption" effect. This feature provides a new approach to solving the anti-reflection problem. The combination of multi-sized nanostructures and two-dimensional gratings may be a possible way to achieve efficient multi-wavelength-wide-angle anti-reflection. However, how to design surface micro-nanostructures to give full play to the advantages of this combination is a difficult problem currently faced. This requires researchers to conduct in-depth exploration in theory and experiment in order to develop more efficient and adaptable anti-reflection technologies. Summary of the Invention

[0005] An object of the present invention is to solve at least the above problems and / or disadvantages and to provide at least the advantages which will be described hereinafter.

[0006] In order to achieve these objectives and other advantages of the present invention, a method for designing an anti-reflection surface based on light field response characteristics is provided, comprising:

[0007] S1. Establishing a finite element model based on wave optics theory, wherein the parameterized design of the finite element model is to optimize the reflectivity of the microstructure surface to adjust the microstructure surface morphology;

[0008] S2. constructing a workpiece model based on two-dimensional air and substrate material through a finite element model, and dividing the entire workpiece model into multiple geometric regions according to different functions and properties;

[0009] S3, performing nonlinear mesh division on each region, and in the process of nonlinear mesh division, locally encrypting the region where the light field is coupled multiple times;

[0010] S4. Conduct electromagnetic field simulation experiments on the microstructures of the workpiece model under various parameterizations, and calculate the reflectivity of each microstructure under different incident conditions. By analyzing the impact of different microstructure morphologies on reflectivity, we can screen out microstructure designs with relatively low reflectivity.

[0011] Preferably, in S1, the wave optics theory is the following Maxwell equations:

[0012]

[0013] In the above formula, D is the electric displacement field, ρ is the charge density, E is the electric field intensity, B is the magnetic flux density, H is the magnetic field intensity, J is the current density, and t is time.

[0014] Preferably, in S1, the size of the finite element model is in the micrometer order, and the size of the microstructure surface is in the nanometer order.

[0015] Preferably, in S2, the region is divided into two parts: air and substrate material, and in each region, the optical parameters of the material are defined according to the role and expected performance of each part in the optical system, and the optical parameters include: the nonlinear refractive index of the material and the absorption coefficient of the material.

[0016] Preferably, in S3, the local densification is concentrated in the area where the interface between air and substrate material is located, and the difference in mesh size between the densified area and the edge is designed to adopt a gradual transition method to achieve a smooth transition of mesh density between different areas;

[0017] In the meshing process, the maximum cell size of each region grid is set to 0.01 μm, and the maximum cell growth rate is limited to 1.05;

[0018] The minimum cell size of the grid in each region is 0.001 μm;

[0019] The curvature factor of the mesh in each region is set to 0.2, and the resolution in narrow regions is set to 1.

[0020] Preferably, in S4, the electromagnetic field simulation experiment includes: setting parameters of the incident light source and arranging monitors in various areas;

[0021] The parameter settings of the incident light source include:

[0022] The wavelength of the incident light is 0.25um-25um;

[0023] The polarization state of the incident light is one of linear polarization, circular polarization, and elliptical polarization;

[0024] The polarization direction of the incident light is parallel to the cross section of the model;

[0025] The incident angle of the incident light is 0° to 70°;

[0026] The monitor is used to obtain the excitation electromagnetic field, the coupling electromagnetic field, the reflected electromagnetic field and the transmitted electromagnetic field.

[0027] Preferably, the monitor collects light field data of each grid node in the model and outputs coupling data of the entire light field in the form of the following regional integration:

[0028]

[0029]

[0030]

[0031] In the above formula, R is the intensity of the reflected light field, S is the intensity of the scattered light field, D is the intensity of the diffracted light field, T is the intensity of the transmitted light field, and A is the intensity of the absorbed light field. is the incident light field intensity, is the light field intensity obtained by the reflection monitor, is the light field intensity acquired by the transmission monitor, is the intensity of the absorbed light field, and x and y correspond to the independent variables along the x and y axes.

[0032] Preferably, in S4, analyzing the influence of different microstructure morphologies on reflectivity means adjusting the geometric parameters of the microstructure to find a microstructure morphology that can achieve relatively low reflectivity, and finally screening out a microstructure morphology with lower reflectivity by comparing the reflectivity results under different combinations of incident light source parameters.

[0033] The present invention has at least the following beneficial effects: It provides a method for designing antireflective surfaces based on light field response characteristics. Using wave optics theory, a finite element model is established to analyze the antireflection mechanism of antireflective microstructures and explore the influence of microstructure parameters on antireflection performance. Combined with numerical simulation results, the mechanism of the microstructure's antireflection performance is revealed. The range of microstructure parameters (such as period, depth, and duty cycle) that achieve optimal antireflection performance is calculated, providing a theoretical basis for subsequent simulation and experimental research. This technology is not limited to the base metal material.

[0034] Other advantages, objectives and features of the present invention will be reflected in part from the following description and will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of the light field coupling model in the present invention;

[0036] Figure 2 is a refractive index data diagram of metallic copper in the present invention;

[0037] Figure 3 A schematic diagram of the size selection and final grid distribution of the grid in an embodiment of the present invention;

[0038] Figure 4 Schematic diagram of electric field distribution simulation results in an embodiment of the present invention;

[0039] Figure 5 Schematic diagram of reflectivity changes corresponding to different wavelengths and different incident angle ranges in an embodiment of the present invention;

[0040] Among them, material surface structure-1, incident light-2, incident angle-3, reflected light-4, material absorption area-5, transmission area-6, transmission light field monitor-7, and reflection light field monitor-8. DETAILED DESCRIPTION

[0041] The present invention will be described in further detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0042] A method for designing an anti-reflection surface based on light field response characteristics comprises the following steps:

[0043] Step 1: A finite element model is established based on wave optics to construct a parametric microstructure surface. The parametric design of the finite element model is to adjust the microstructure surface morphology by optimizing the reflectivity of the microstructure surface. At the same time, the finite element model is divided into multiple regions with different functions and properties (for example, the finite element model region is divided into air and copper substrate materials, and the nonlinear refractive index of the material is defined). In each region, the corresponding material parameters are precisely defined according to its role in the optical system and expected performance, including but not limited to key optical characteristic parameters such as refractive index and absorption coefficient. This strategy of region division and parameter definition can accurately simulate and optimize the specific needs of different regions, thereby providing a numerical basis for achieving high-performance optical microstructure design;

[0044] In step 1, wave optics theory specifically refers to Maxwell's equations, as shown below:

[0045]

[0046] Where D is the electric displacement field, ρ is the charge density, E is the electric field strength, B is the magnetic flux density, H is the magnetic field strength, J is the current density, and t is time.

[0047] The finite element model is solved directly by the electric field continuity equation: .

[0048] Step 2: In order to further improve the calculation accuracy and simulation effect of the model, the finite element model was divided into nonlinear grids.

[0049] In step two, a nonlinear meshing strategy is employed to locally refine the region where the optical field is repeatedly coupled. The mesh size is controlled based on the strength of the optical field coupling. Specifically, this localized meshing process focuses on the air-material interface, as this region often experiences the most dramatic changes in key physical quantities in optical phenomena, making precise meshing crucial for accurately capturing the physical processes. This step involves locally refining the mesh near the air-material interface to ensure that the complex physical behavior at this interface is fully captured.

[0050] In addition, to ensure smooth meshing and computational stability throughout the model, a gradual transition from the refined area to the edge was designed, allowing for smooth changes in mesh density between regions and avoiding numerical errors that could be introduced by sudden mesh changes. This nonlinear meshing strategy, combined with localized refinement and smooth transitions, significantly improves computational accuracy in key areas while ensuring overall computational efficiency and reliability, providing a high-quality numerical foundation for subsequent optical performance analysis and optimization.

[0051] Step 3: In order to accurately conduct optical property research, a parameterized incident light source is set, covering key parameters such as polarization direction, incident angle, wavelength, etc., to achieve flexible simulation of different optical scenes. In the implementation process, the incident light source in step 3 is set to:

[0052] The wavelength of the incident light is 0.25um-25um;

[0053] The polarization state of the incident light is linear polarization, circular polarization, and elliptical polarization;

[0054] The polarization direction of the incident light is parallel to the cross section of the model;

[0055] The incident angle of the incident light is 0° to 70°.

[0056] Furthermore, multiple monitors are rationally arranged in the model. These monitors can efficiently collect key data such as the excitation electromagnetic field, coupled electromagnetic field, reflected electromagnetic field, and transmitted electromagnetic field. Specifically, the monitors collect data from each grid node in the model and then calculate and output the coupling data of the entire light field in the form of regional integration. The calculation formula is as follows:

[0057]

[0058]

[0059]

[0060] Where R is the reflected light field intensity, S is the scattered light field intensity, D is the diffracted light field intensity, T is the transmitted light field intensity, and A is the absorbed light field intensity. is the incident light field intensity, is the light field intensity obtained by the reflection monitor, is the light field intensity acquired by the transmission monitor, is the intensity of the absorbed light field, and x and y correspond to the independent variables along the x and y axes.

[0061] Step 4: After completing the above model construction and parameter setting, the simulation program performs detailed electromagnetic field simulations on each parameterized microstructure. Through precise calculations, the reflectivity of each microstructure under different incident conditions is obtained. In other words, through steady-state calculations, the corresponding reflectivity of each parameterized structure is output.

[0062] To further optimize the optical performance of the microstructures, extensive parametric scanning experiments were conducted. This involved obtaining reflectivity data through parametric scanning to optimize the microstructure morphology, ultimately achieving relatively low reflectivity. In actual implementation, the geometric parameters of the microstructures, such as height, width, and period, were adjusted to identify microstructure morphologies that could achieve relatively low reflectivity. By comparing the reflectivity results under different parameter combinations, a microstructure morphology with relatively low reflectivity was ultimately selected. This morphology exhibited excellent optical performance under specific incident conditions, providing an important theoretical basis for subsequent experimental verification and practical applications.

[0063] Example:

[0064] (1) A numerical model of the two-dimensional interface between air and metallic copper was established using COMSOL software for in-depth analysis of optical properties. The interface of the model is designed as a parametric surface microstructure, which can adjust the surface morphology of the microstructure by parametric design to optimize the reflectivity of the microstructure surface, and can be flexibly adjusted to adapt to different optical scenarios. In order to effectively reduce the size of the basic model and improve computational efficiency, the Floquet rule was used to establish a periodic model. By defining the wave vector and applying periodic boundary conditions, the model can introduce a phase factor at the boundary, thereby simulating the behavior of the periodic structure in wave propagation. The geometric area of ​​the model is divided into different parts to distinguish the physical properties of air and metallic copper. By selecting the corresponding material library in COMSOL, the material properties of air and metallic copper are accurately defined, including nonlinear reflectivity related to the wavelength of light. The definition of these material property parameters provides the basis for subsequent optical property analysis. The geometric division and material property settings of the model are as follows: Figure 1 and Figure 2 shown. Figure 1 The regional division of the model is shown, which clearly reflects the interface structure between air and metallic copper; Figure 2 The material properties related parameters used in the simulation model are listed in detail. Through this precise model construction and parameter setting, this study provides a reliable numerical basis for in-depth analysis of optical properties.

[0065] (2) In order to ensure the accuracy and computational efficiency of the numerical simulation, the workpiece model was finely meshed. The model was discretized using free triangular meshes and combined with nonlinear meshing techniques to adapt to the geometric characteristics and physical requirements of different regions. In the air-material interface region, the simulation accuracy of this critical region was significantly improved by locally refining the mesh. At the same time, the mesh cells transitioned smoothly from the refining region to the edge, effectively reducing the computational complexity of the overall model, thereby significantly shortening the simulation time while ensuring accuracy. The geometric dimensions of the model are: workpiece height 4μm, width 2μm. During the meshing process, the size and distribution of the mesh cells were strictly controlled. The maximum cell size of the regional mesh was set to 0.01μm and the minimum cell size was set to 0.001μm to ensure that complex physical phenomena could be captured in critical areas (such as interfaces). In addition, the maximum cell growth rate was limited to 1.05 to ensure smooth changes in the mesh cells between the refining region and the transition region. The curvature factor was set to 0.2 to adapt to the geometric curvature changes of the model surface and ensure that the mesh can accurately fit the complex geometric shape. The resolution of the narrow area is set to 1, which further enhances the mesh adaptability of the model in narrow areas. The meshing of the entire model is divided by free triangle meshing rules to achieve efficient discretization of complex geometric shapes. Through this fine meshing strategy, the model can accurately reflect the physical phenomena during the simulation process, while avoiding calculation errors or waste of computing resources caused by mesh sizes that are too large or too small. The size selection of the mesh and the final mesh distribution are as follows: Figure 3 The figure clearly shows the mesh refinement in key areas and the mesh distribution of the overall model, providing a reliable geometric basis for subsequent numerical simulations.

[0066] (3) In the process of conducting electromagnetic field simulation experiments, the first step is to accurately parameterize the incident light source. This setting process involves the detailed definition of the key parameters of the incident light source, including but not limited to the polarization direction, incident angle and wavelength. The polarization direction determines the polarization state of the electromagnetic wave, the incident angle affects the interaction between the electromagnetic wave and the medium, and the wavelength determines the frequency and energy characteristics of the electromagnetic wave. By accurately setting these parameters, it can be ensured that the simulation experiment can cover a wide range of physical scenarios and provide diverse experimental conditions for subsequent electromagnetic field analysis. After completing the parameterization of the incident light source, the next step of the experiment is to arrange monitors in various areas of the model. These monitors play a vital role in the experiment. Their main function is to collect various electromagnetic field data generated during the experiment in real time. The data that the monitor needs to collect covers multiple aspects of the electromagnetic field, mainly including the excitation electromagnetic field, coupling electromagnetic field, reflection electromagnetic field and transmission electromagnetic field. The excitation electromagnetic field reflects the initial electromagnetic response excited by the incident light source in the medium; the coupling electromagnetic field reveals the energy transfer mechanism between different media or between different modes; the reflection electromagnetic field and the transmission electromagnetic field describe the reflection and transmission behavior of the electromagnetic wave at the interface respectively. By accurately collecting these electromagnetic field data, we can fully understand the propagation characteristics, energy distribution and interaction laws of electromagnetic waves in the experimental environment.

[0067] (4) By running numerical simulations, the reflectivity corresponding to each parameterized structure was calculated. Based on the parameterized scanning technology, the influence of different microstructure morphologies on reflectivity was systematically analyzed, thereby screening out microstructure designs with relatively low reflectivity. The simulation results of the electric field distribution are shown in Figure 2. Figure 4 As shown in the figure, the significant "light absorption effect" on the surface of the microstructure is clearly demonstrated. This phenomenon shows that the optimized microstructure can effectively capture and guide the incident light and reduce reflection loss. The final simulation results show that the reflectivity of the designed microstructure is less than 10% under the condition of a wavelength of 2.2μm. In addition, the minimum reflectivity is less than 20% in the range of incident angles from 0° to 70°. These results are shown in the figure. Figure 5The results shown in the figure intuitively demonstrate the accuracy and effectiveness of the established light field simulation model. This result also verifies the feasibility of the proposed anti-reflective surface design method based on light field response characteristics, providing strong theoretical support for subsequent experimental verification and practical application. By systematically scanning different microstructure parameters, structural morphologies with excellent anti-reflective performance were successfully screened, demonstrating the efficiency of the parameterized approach in design optimization. The designed microstructures exhibited significant low reflectivity at a specific wavelength (2.2μm) and across a wide range of incident angles (0° to 70°), providing a theoretical basis for achieving efficient light absorption. The proposed design method based on light field response characteristics can effectively reduce reflectivity to optimize microstructure surface morphology, providing a new approach and method for the design of anti-reflective surfaces with broad application prospects. In summary, through precise simulation analysis, this paper successfully achieved the design goal of low-reflectivity microstructures and verified the effectiveness of the proposed method, providing an important reference for further experimental research and practical application.

[0068] The above solution is only an illustration of a preferred embodiment, but is not limited thereto. When implementing the present invention, appropriate replacements and / or modifications can be made according to user needs.

[0069] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and exemplary embodiments. They can be applied to a variety of fields suitable for the present invention. Further modifications will be readily apparent to those skilled in the art. Therefore, the present invention is not limited to the specific details and illustrations shown and described herein without departing from the general concept defined by the claims and their equivalents.

Claims

1. A method for designing an anti-reflection surface based on light field response characteristics, characterized in that: include: S1. Establishing a finite element model based on wave optics theory, wherein the parameterized design of the finite element model is to optimize the reflectivity of the microstructure surface to adjust the microstructure surface morphology; S2. constructing a workpiece model based on two-dimensional air and substrate material through a finite element model, and dividing the geometric area of ​​the entire workpiece model into multiple parts according to different functions and properties; S3, performing nonlinear mesh division on each region, and in the process of nonlinear mesh division, locally encrypting the region where the light field is coupled multiple times; S4. Conduct electromagnetic field simulation experiments on the microstructures of the workpiece model under various parameterizations, and calculate the reflectivity of each microstructure under different incident conditions. By analyzing the impact of different microstructure morphologies on reflectivity, the microstructure design with relatively low reflectivity can be selected; In S3, the local densification is concentrated in the area where the air and substrate material interface is located, and the difference in mesh size between the densified area and the edge is designed to adopt a gradual transition method to achieve a smooth transition of mesh density between different areas; In the meshing process, the maximum cell size of each region grid is set to 0.01 μm, and the maximum cell growth rate is limited to 1.05; The minimum cell size of the grid in each region is 0.001 μm; The curvature factor of the mesh in each region is set to 0.2, and the resolution in narrow regions is set to 1.

2. The anti-reflection surface design method based on light field response characteristics according to claim 1, characterized in that: In S1, the wave optics theory is the following Maxwell equations: In the above formula, D is the electric displacement field, ρ is the charge density, E is the electric field intensity, B is the magnetic flux density, H is the magnetic field intensity, J is the current density, and t is time.

3. The anti-reflection surface design method based on light field response characteristics according to claim 1, characterized in that: In S1, the size of the finite element model is in the micrometer order, and the size of the microstructure surface is in the nanometer order.

4. The anti-reflection surface design method based on light field response characteristics according to claim 1, characterized in that: In S2, the region is divided into two parts: air and substrate material. In each region, the optical parameters of the material are defined according to the role and expected performance of each part in the optical system. The optical parameters include: the nonlinear refractive index of the material and the absorption coefficient of the material.

5. The anti-reflection surface design method based on light field response characteristics according to claim 1, characterized in that: In S4, the electromagnetic field simulation experiment includes: setting parameters of the incident light source and arranging monitors in various areas; The parameter settings of the incident light source include: The wavelength of the incident light is 0.25um-25um; The polarization state of the incident light is one of linear polarization, circular polarization, and elliptical polarization; The polarization direction of the incident light is parallel to the cross section of the model; The incident angle of the incident light is 0° to 70°; The monitor is used to obtain the excitation electromagnetic field, the coupling electromagnetic field, the reflected electromagnetic field and the transmitted electromagnetic field.

6. The anti-reflection surface design method based on light field response characteristics according to claim 5, characterized in that: The monitor collects light field data from each grid node in the model and outputs the coupled data of the entire light field in the form of the following regional integration: In the above formula, R is the intensity of the reflected light field, S is the intensity of the scattered light field, D is the intensity of the diffracted light field, T is the intensity of the transmitted light field, and A is the intensity of the absorbed light field. is the incident light field intensity, is the light field intensity obtained by the reflection monitor, is the light field intensity acquired by the transmission monitor, is the intensity of the absorbed light field, and x and y correspond to the independent variables along the x and y axes.

7. The anti-reflection surface design method based on light field response characteristics according to claim 1, characterized in that: In S4, analyzing the effects of different microstructure morphologies on reflectivity refers to adjusting the geometric parameters of the microstructure to find a microstructure morphology that can achieve relatively low reflectivity, and finally screening out a microstructure morphology with lower reflectivity by comparing the reflectivity results under different combinations of incident light source parameters.

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