Structural color simulation method of SiO2 and Ti3O5 thin layer composite lamination

Abstract

The invention discloses a structural color simulation method for a SiO2 and Ti3O5 thin layer composite laminated layer, which is characterized in that optical calculation of a thin film stack is communicated with an appearance-level rendering process, so that a laminated structure can be linked in the same process from optical characteristics of a material level to a color generation effect in a scene. Through file format alignment and a material attribute import mechanism, results of different thickness combinations are easier to reuse and contrast, uncertainty caused by repeated construction and manual conversion in multi-round scheme screening is reduced, and meanwhile, a thickness gradient discretization and sub-surface binding thought is introduced, so that continuous thickness change can be clearly expressed on a simulation tissue, and the accuracy of the simulation tissue is improved. And the difference of different areas along with the thickness change can be conveniently observed on the same model. Due to the fact that the thickness points, the material files and the sub-surfaces have clear corresponding relations, the simulation process is more convenient to trace and recheck, and positioning of difference sources and stabilizing of output calibers during subsequent iteration are facilitated.

Description

Technical Field

[0001] This invention relates to the field of combined simulation technology of thin film optical simulation and optical rendering, specifically to a method for simulating the structural color of a SiO2 and Ti3O5 thin-layer composite stack. Background Technology

[0002] Structural color films are typically formed by stacking high and low refractive index materials, exhibiting different colors in the visible light range through multi-layer interface reflection and interference effects. For a specific material system and layer sequence, variations in layer thickness, incident angle, and wavelength conditions will cause differences in reflection and transmission responses. Therefore, during the research and development phase, it is usually necessary to calculate and compare multiple thickness combinations to reduce the cost and time required for physical prototyping.

[0003] In existing work, one approach focuses on performing reflection and transmission calculations of multilayer films within the thin film solver and outputting spectra or angle curves. However, such results often remain at the level of "planar stack-curve data," making it difficult to directly correlate with specific 3D appearance scenes. Another approach focuses on scene-level simulation in optical rendering software. However, its material input often relies on coating attribute files in specific formats. Furthermore, in the case of continuous thickness gradients or partitioned thickness stacks, the lack of batch data generation, file format alignment, and surface binding mechanisms can easily lead to problems such as complex file management, misbinding of materials, or difficulty in verification.

[0004] Therefore, there is an urgent need for a simulation process that is designed for specific multilayer material systems and can form a consistent data link between thin film optical simulation and optical rendering, so as to support the simulation organization and result verification of single-thickness and continuous-thickness gradient multilayers under unified rules.

[0005] A search revealed a Chinese patent document disclosing a method and system for simulating coating texture features [Application No.: 202080051520.9, Publication No.: CN114127790A]. This includes a computer-implemented method for simulating the texture features of an n-layer target coating. It can model multi-layer coatings or layer stacks in a virtual environment and obtain angle, spectrum, and spatial intensity distribution through ray tracing and receiver evaluation, outputting images. It has a simulation workflow framework oriented towards appearance and texture output. However, this invention focuses on modeling and parameter organization around a planar stacked structure of alternating SiO2 and Ti3O5 thin layers. Combined with the software links and data organization methods given in the disclosure, it is more suitable for application scenarios centered on specific material system stacks and using thin-film optical calculation results for subsequent appearance simulation and rendering verification. Summary of the Invention

[0006] To address the problems existing in the prior art, the purpose of this invention is to provide a method for simulating the structural color of a thin-layer composite stack of SiO2 and Ti3O5.

[0007] A method for simulating the structural color of a SiO2 and Ti3O5 thin-layer composite stack, characterized in that the method includes the following steps: S1. Construct a multi-layer planar structure model containing SiO2 thin layers and Ti3O5 thin layers in the thin film optical simulation module. The model includes alternating superposition of SiO2 thin layers and Ti3O5 thin layers. Input the refractive index of the material and perform optical simulation under specified wavelength and incident angle conditions through parametric scanning. Output material data file of thin film optical properties. S2. The material data files are batch converted into coating material property files that can be imported into optical rendering software. The files contain optical data such as reflectivity and transmittance. The files are then imported into the optical rendering software to perform optical simulation of a single thickness layer to obtain reflected color and transmitted color data. S3. Discretize the target thickness range into N thickness points using the first script program, and execute steps S1-S2 for each thickness point to generate the corresponding N coating material property files. S4. Discretize the geometric model of the surface to be simulated into N sub-faces using the second script program, and bind the coating material attribute file generated in step S3 that matches the thickness point of the sub-face to each sub-face. S5. Drive the optical rendering software to perform co-simulation through the third script program, and output the optical effect data of the continuous thickness gradient stack.

[0008] Preferably, the multilayer planar structure model includes alternating layers of SiO2 and Ti3O5, with the thickness ratio of the SiO2 and Ti3O5 layers being between 1:1 and 3:2, and the thickness of the SiO2 layer being between 20 nm and 150 nm, and the thickness of the Ti3O5 layer being between 20 nm and 150 nm.

[0009] Through the above technical solution, the present invention limits the thickness ratio of SiO2 thin layer to Ti3O5 thin layer and the thickness range of a single layer, so that the parameter space of the multilayer planar structure model is in a controllable range, which facilitates comparative simulation of different thickness combinations under the same layer sequence conditions, thereby providing a reusable simulation input boundary for the change of structural color with angle.

[0010] Specifically, SiO2 and Ti3O5 have significant differences in refractive index, and changes in thickness combination will alter the optical path difference and interference conditions of the stacked layers. Within the thickness range of 20nm–150nm, by proportionally selecting the thicknesses of the two types of thin layers and alternately stacking them, a set of continuously adjustable thickness combination sequences can be formed to generate reflection and transmission response data in the visible light band.

[0011] In practical applications, the aforementioned limitations on thickness ratios and ranges help to unify subsequent parametric scanning, thickness discretization, and material property file generation under the same set of thickness rules. This allows different thickness schemes to be compared and analyzed in the same simulation process, reducing redundant calculations and file management chaos caused by disordered thickness values.

[0012] Preferably, the parametric scan in step S1 covers an incident angle range of 0° to 90° and a scan wavelength range of 400nm to 700nm in the visible light band, wherein each combination of incident angle and wavelength is used to calculate the reflectivity and transmittance under that combination condition.

[0013] Through the above technical solution, the present invention simultaneously covers the 0°–90° incident angle range and the 400nm–700nm visible light band in the thin film optical simulation stage, so that the simulation output can reflect the variation law of the stack under different observation angles and different incident wavelengths, providing more complete data support for the preview of the angle-dependent color effect.

[0014] Specifically, by using the incident angle as a scanning variable in the STACK module and introducing dispersive refractive index input in the visible light range, the results of how transmittance and reflectance change with angle and incident light wavelength can be obtained. When the angle is simulated in 1° increments, a denser set of angle sampling points can be formed, thus presenting the trend of change with angle more clearly.

[0015] In practical applications, this scanning range setting facilitates the correspondence between thin film optical data and the observation angle settings in the subsequent rendering stage, thereby keeping the data chain of "thin film layer parameters - angle - wavelength" consistent and making it easier to make lateral comparisons and archives of reflection and transmission changes of different thickness combinations.

[0016] Preferably, the batch conversion in step S2 includes converting optical data such as reflectivity and transmittance in the material data file according to the input format of the optical rendering software, wherein the format is txt, CSV or JSON, and the converted file includes the optical properties corresponding to each thickness point.

[0017] Through the above technical solution, the present invention batch aligns the material optical data files output by the thin film optical simulation module into coating material property files that can be directly imported by optical rendering software, establishes a data interface between the two types of software, and enables the simulation results of the same batch of thickness points to enter the rendering environment in a unified format.

[0018] Specifically, the thin film optical simulation stage can output txt or JSON format files; when the output is a txt file, the txt file is renamed and converted to the coated material property file format that Speos can recognize; when the previous step exported a JSON format file, the format conversion process can be omitted, thereby reducing repetitive file processing steps.

[0019] In practical applications, using batch processing commands to automate renaming and batch conversion helps maintain consistency between file names and thickness indexes when there are many thickness points. This reduces the risk of omissions, errors, or version mixing caused by manual file-by-file conversion and facilitates the establishment of a one-to-one correspondence between "thickness point - material file - rendering result" in the future.

[0020] Preferably, the target thickness range in step S3 is 20nm-150nm, and the discrete thickness points within the thickness range are uniformly distributed at specified intervals, wherein the discrete interval is less than or equal to 5nm, and the interval can be adjusted according to the required optical precision.

[0021] Through the above technical solution, the present invention limits the target thickness range to 20nm–150nm, and discretizes it into multiple thickness points at specified intervals within this range, so that continuous thickness changes can enter the script loop calculation and material file generation process in the form of discrete point sequences, providing an executable thickness input set for subsequent joint simulation.

[0022] Specifically, the thickness discretization can be determined by using "1% of the difference between the thickest and thinnest points" as the spacing between discrete points. When applied to the 20nm–150nm range, this method can generate a sufficient number of thickness points to express the gradual change trend. On this basis, controlling the discrete spacing to no more than 5 nm is beneficial for maintaining the continuity of changes between adjacent thickness points when the thickness gradient is relatively smooth.

[0023] In practical applications, thickness point discretization not only provides a clear number of loops and files for batch generation of txt or coated material files, but also provides a basis for the subsequent binding strategy of "the number of sub-faces is consistent with the number of thickness points", so that the expression of gradient thickness can be stably reused in different simulation tasks through "thickness point sequence".

[0024] Preferably, the coating material attribute file bound to each sub-face in step S4 is assigned based on the geometric characteristics and thickness gradient changes of the surface model, wherein the geometric model of each sub-face includes planes and curved surfaces, the number of sub-faces is consistent with the number of discrete thickness points, and the thickness change of each sub-face conforms to a linear or nonlinear gradient pattern.

[0025] Through the above technical solution, the present invention discretizes the geometric model of the surface to be simulated into multiple sub-faces in the optical rendering software, and binds the coating material attribute file generated by the corresponding thickness point to each sub-face, so that the thickness gradient is expressed on the macroscopic surface in the form of "spatial partitioning + material attribute", thereby forming a joint simulation input of continuous thickness gradient stack.

[0026] Specifically, the Speos client can use scripts to divide the surface geometry into 100 equal parts based on thickness points, and create equal material files to bind to each facet; for example, the surface of an object with dimensions of 180mm×90mm can be divided into 100 facets horizontally, and the corresponding coated files can be bound one by one according to the thickness point number to form a gradient mapping relationship from the thickest part to the thinnest part.

[0027] In practical applications, the design of "the number of sub-faces being consistent with the number of discrete thickness points" facilitates the establishment of a strict one-to-one correspondence binding relationship. This not only avoids the same material file being bound repeatedly or omitted, but also makes it easy to quickly trace back to the specific thickness point and the corresponding material file when the output results are abnormal, thereby improving the checkability and reproducibility of the co-simulation.

[0028] Preferably, the optical rendering software is Ansys Speos, and the optical simulation module is the Lumerical STACK module. During the simulation, the optical rendering software calculates the reflectivity, transmittance, and color coordinates of the laminated structure under different incident angles and wavelengths based on the input material data, combined with the theoretical model and actual optical properties, to further evaluate the optical performance of the laminate and obtain detailed optical effect data of the composite material.

[0029] Through the above technical solution, this invention uses the Lumerical STACK module to complete the optical property simulation of multi-layer planar structures, and uses Ansys Speos to complete the reverse simulation and co-simulation on the rendering side, so that "reflection and transmission response at the thin film level" and "color effect obtained by macroscopic surface observation" can be output in the same process.

[0030] Specifically, the STACK module uses RCWA as its core solver engine to scan the incident angle of the multilayer planar structure in the visible light range and output a txt or JSON file of the optical properties of the thin film. Then, after aligning the file to the coated material properties, the coated file is imported into Speos through the material surface properties. The CIE illuminant D65 ambient light is set, and the VR observer sensor is used to simulate the transmission and reflection colors of a single-thickness stack in 5° increments within the 0–90° viewing angle range, thereby obtaining the transmission and reflection colors of the single-thickness stack.

[0031] In practical applications, the above-mentioned collaborative approach enables thin film simulation output files to directly drive rendering simulation tasks: single thickness is used for quick preview of transmitted or reflected colors, while continuous thickness gradients can be used to perform co-simulation after sub-face binding, forming a gradient color distribution on the macroscopic surface, thereby adapting to the rapid verification needs of decorative structural color schemes in the design phase.

[0032] Preferably, the optical effect data includes reflectance, transmittance, color coordinates, and spectral data, wherein the color coordinates are data from the CIE 1931 XYZ or CIE Lab color space, used to quantitatively characterize changes in optical performance, and the spectral data includes reflection and transmission spectra at different incident angles and wavelengths.

[0033] Through the above technical solution, the optical effect data output by the present invention can simultaneously cover the reflection and transmission response of the thin film stack layer and the color results on the rendering side, so that the influence of thickness change, angle change and visible light band change on the final appearance effect has the same source data support.

[0034] Specifically, on the thin film simulation side, data results of the changes in transmittance and reflectance with angle and incident wavelength can be obtained and output in txt or JSON format; on the rendering simulation side, the reflected color and transmitted color effects observed from directly above can be obtained, and the phenomenon of color change under deflection angle can be recorded, thus corresponding the "numerical response" and "visual results" in the same scheme.

[0035] In practical applications, this type of optical effect data can be used to pre-verify the thickness scheme before the physical sample is produced, reducing the cost of repeated preparation and iteration. At the same time, when it is necessary to map from nanoscale thickness distribution to macroscopic visual color, the thickness discretization and co-simulation process can also be used to preview and compare the overall appearance changes of continuous thickness gradient stacks.

[0036] Compared with the prior art, the present invention has the following advantages: 1. This invention integrates the optical computation and appearance-level rendering processes of thin-film stacks, enabling the seamless transition from the optical properties of the layered structure at the material level to the color rendering effect in the scene within the same workflow. Through file format alignment and material property import mechanisms, results from different thickness combinations are easier to reuse and compare, reducing the uncertainty caused by repeated construction and manual conversion in multiple rounds of solution selection.

[0037] 2. This invention introduces the concept of discretizing thickness gradients and binding them to sub-surfaces, enabling continuous thickness variations to be clearly expressed in the simulated microstructure. This facilitates the observation of differences in different regions as thickness changes on the same model. Because there is a clear correspondence between thickness points, material files, and sub-surfaces, the simulation process is easier to trace and verify, which is beneficial for locating the source of differences and stabilizing the output caliber during subsequent iterations. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the overall simulation process of this invention; Figure 2 This is a schematic diagram of the three-layer thin-film stack structure of the present invention; Figure 3 These are the results of the simulation software of this invention, showing the curves of transmittance and reflectance as a function of angle. Figure 4 This is the result of the transmission and reflectivity of the present invention changing together with the angle and the wavelength of the incident light; Figure 5 This is a schematic diagram of the Speos optical field modulation of the present invention; Figure 6 These are simulation results of the uniform thickness thin film stack of the present invention; Figure 7 This is a schematic diagram of the loop logic of a Lumerical loop script; Figure 8 This is a schematic diagram of surface division and material binding in Speos; Figure 9 This is a simulation result of a continuously thickened gradient thin film stack. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] The present invention will be described in detail below through multiple embodiments and comparative examples. These embodiments are intended to further illustrate the technical solutions and beneficial effects of the present invention, and are not intended to limit the scope of protection of the present invention. Unless otherwise specified, all parts mentioned in the present invention are parts by weight, and the process equipment mentioned is conventional equipment in the art.

[0041] Example 1: Reverse Simulation of Single-Thickness Stack 1. Overall process and stacked structure like Figure 1As shown, this embodiment uses a collaborative approach between a thin-film optical simulation module and optical rendering software to simulate and preview the structural color of a SiO2 and Ti3O5 thin-film composite stack. The process includes: establishing a multi-layer planar structure model in the thin-film optical simulation module and outputting a thin-film optical property text file; aligning the output file to the correct format and generating a coating material property file compatible with the optical rendering software; importing the coating material property file into the optical rendering software and performing a reverse simulation of a single-thickness stack to obtain the transmitted color and reflected color.

[0042] like Figure 2 As shown, the thin film stack has a three-layer structure, where the first and third layers are Ti3O5 thin layers and the second layer is a SiO2 thin layer; the thickness of each layer is taken from the range of 20nm–150nm.

[0043] 2. Lumerical STACK: Layered Modeling and Simulation of Material Optical Properties In this embodiment, the thin-film optics simulation module uses Lumerical's STACK module, whose solution engine is based on the rigorous coupled-wave analysis method (RCWA) to simulate and analyze multilayer planar structures.

[0044] (1) Establish a multi-layer planar structure model In the STACK module, a new stacked model is created, defining three dielectric layers sequentially in the order "Ti3O5 / SiO2 / Ti3O5". The thickness of each layer in this embodiment is selected within the range of 20–150 nm, and recorded in the model parameters as t1, t2, and t3 respectively to ensure traceability of subsequent script calls and file naming, for example, "t1_Ti3O5, t2_SiO2, t3_Ti3O5". The structure corresponding to this step... Figure 2 The layer sequence and layer identifier are shown.

[0045] (2) Angle scan under non-dispersive refractive index conditions Under non-dispersive refractive index conditions, the refractive index takes an approximately fixed value within the application range of 400–700 nm, and does not change with the incident light wavelength. By setting the incident angle as a parameterized scanning variable and performing a simulation scan at 1° steps, the curves of transmittance and reflectance as a function of angle are obtained, as shown below. Figure 3 As shown; where Figure 3 (a) shows the simulation results of light incident from above the top layer of the stack. Figure 3 (b) shows the simulation results of light incident from below the bottom layer of the stack.

[0046] (3) Angle + wavelength scan under dispersive refractive index conditions Under dispersive refractive index conditions, the refractive index varies with wavelength. Import a dispersive refractive index data file with an accuracy of 1 nm and a range of 400 nm–700 nm, and set the incident angle as a parameterized scan variable. Perform a simulation scan of the incident angle in 1° increments to obtain the results showing how transmittance and reflectance change together with the angle and the wavelength of the incident light. Figure 4 As shown; where Figure 4 (a) shows the simulation results of light incident from above the top layer of the stack. Figure 4 (b) shows the simulation results of light incident from below the bottom layer of the stack.

[0047] (4) Output thin film optical property files After completing the above simulation, the optical property file of the stacked thin film is output; the output format can be a txt file or a JSON file. To ensure consistency in subsequent software integration, this embodiment synchronously writes the layer sequence identifier and thickness parameter identifier into the name of the output file, such as "Ti3O5_SiO2_Ti3O5_t1_t2_t3", to avoid file confusion in multiple simulation tasks.

[0048] 3. File format alignment to Speos: txt / JSON to coated like Figure 1 As shown, to achieve joint simulation between the thin-film optics simulation module and the optical rendering software, the Lumerical output file needs to be format-aligned. If the output is a txt file, the txt file is renamed and its file format is converted to make it a surface material property coated file format that can be imported into Speos; if a JSON format file is directly exported during the Lumerical stage, no format conversion is required, and the material import process can proceed directly.

[0049] In practice, one or more output files corresponding to a "single thickness stack" can be placed in the same directory, and a material import list corresponding to that directory can be created. The list should at least include the associated fields of "file name - thickness parameter - layer sequence identifier" for consistency verification during subsequent import of the Speos material library, ensuring that each coated file is consistent with its corresponding stack thickness combination.

[0050] 4. Speos: Reverse Simulation and Color Results of Single-Thickness Stack-Ups (1) Material import and light field setting In Speos, the coated file is imported into libraries via surface property settings; a uniform light field is set and imported into a CIE Illuminant D65 simulator to simulate ambient light; a VR observer sensor is configured with a viewing angle range of 0–90°, and simulations are performed in 5° increments. The light field modulation relationship is as follows: Figure 5 As shown, it includes a uniform light source 4, a sensor 6, and an object surface 5 with dimensions of 180mm × 90mm.

[0051] (2) Perform reverse simulation and output the reflected color and transmitted color. After completing the material import, light field, and sensor settings, a reverse simulation of a single-thickness stack was performed to obtain the transmitted and reflected color data of the thin film. The simulation results are as follows: Figure 6 The image shows the effect of a uniformly thick thin film stack as viewed from directly above: Figure 6 (a) is the reflected color; the example color is red. Figure 6 (b) is the transparent color, with the example color being light blue, which is complementary to the reflected color; at the same time, the color changes when the viewing angle is changed, and the color conforms to the color spectrum at large angles.

[0052] (3) Output data archiving method To facilitate reuse in subsequent continuous thickness gradient simulations, this embodiment archives the output of a single-thickness stack simulation task according to the link of "simulation input parameters - coated material file - Speos project - image / data output": the input parameters include at least "incident angle range 0–90°, step every 5°, visible light band 400nm–700nm, dispersive / non-dispersive refractive index mode selection, stack sequence and thickness parameters t1 / t2 / t3".

[0053] Example 2: Co-simulation of continuous thickness gradient stacks 1. For example Figure 1 As shown, this embodiment, based on the "Single Thickness Stack Reverse Simulation" in Embodiment 1, introduces a script automation mechanism to achieve co-simulation of continuous thickness gradient stacks: First, a for loop is constructed in Lumerical based on the single thickness simulation example to discretize the target thickness range into multiple thickness points and output the corresponding thin film optical property txt file for each thickness point; then, the above txt files are batch renamed and converted into Speos-compatible coated material property files through batch processing commands; finally, the surface geometry model to be simulated is discretized into multiple sub-faces in Speos, and the coated material file corresponding to the thickness point is bound to each sub-face. After setting the light source and sensor again, the co-simulation is executed, and the optical effect data of the continuous thickness gradient stack is output.

[0054] 2. Lumerical: Uses a for loop to discretize thicknesses and outputs them in batches. (1) Script construction basis and loop target On the Lumerical side, a for loop script is constructed by combining the "Standard Example Script for Single Thickness STACK" to discretize a gradually changing continuous thickness gradient, forming multiple gradually changing discrete thickness points; and a loop simulation is performed once for each thickness point, and a txt material file is output.

[0055] (2) Definition of loop variable like Figure 7 As shown, the script defines: d as the total thickness of the stack, d_initial as the thickness at the thickest point of the stack, and d_final as the thickness at the thinnest point of the stack. During the loop, the thickness parameter gradually transitions from d_initial to d_final, and the STACK solution process (RCWA solution, incident angle scan, band range setting, and output file generation) is called in each iteration.

[0056] (3) Consistency between simulation scanning conditions and output In the simulation corresponding to each thickness point, the basic scanning conditions are maintained consistent with those in Example 1: import dispersive refractive index data with an accuracy of 1 nm and a range of 400 nm–700 nm, perform simulation scanning at 1° incident angles, and output a txt file of the thin film optical properties. By using the "fixed layer sequence + variable thickness" method, the difference between thickness points is reflected only in the thickness parameters, which facilitates the "thickness point - sub-surface" binding on the Speos end.

[0057] (4) Thickness range and discretization strategy The thickness is discretely distributed across a range of 20 nm to 150 nm, with the spacing between discrete points set to 1% of the difference between the thickest and thinnest points, thus forming a set of discrete thickness points arranged according to the thickness gradient. This discretization strategy ensures that a sufficient density of thickness points can be obtained even with large thickness gradients, supporting the spatial continuity representation in subsequent co-simulations.

[0058] (5) Naming and indexing of thickness point output files To ensure the traceability of subsequent batch processing conversions and Speos binding, this embodiment generates a numbered txt file for each thickness point during the for loop output phase: the number field is consistent with the iteration order of the thickness points; the thickness field records the d value corresponding to this iteration or the layer thickness combination parameter calculated from d. Through this naming convention, the "thickness point number" can be used as the primary key field for binding to the Speos terminal face without changing the simulation mechanism.

[0059] 3. Batch format alignment: Batch rename txt files and convert them to coated format. (1) Conversion between file processing and batch processing Place all the aforementioned txt files in a folder, rename them all using a batch command line command, and then batch convert the txt files in the folder to coated file format in preparation for joint simulation between optical modules.

[0060] (2) File verification after batch processing After batch processing is completed, a consistency check is performed on the coated file set: at least check whether the number of files matches the number of thickness points, whether the sequence numbers are consecutive, and whether the thickness point identifiers are retained; and establish a mapping table of "coated file sequence number - thickness point parameter - generation time" for use by the Speos script for automatic binding.

[0061] 4. Speos: The surface is discretized into 100 sub-faces and bound to materials. (1) Correspondence between sub-face partitioning strategy and quantity On the Speos platform, the surface geometry model to be simulated is divided into equal parts of thickness points using a script. In this embodiment, taking 100 thickness points as an example, the surface geometry is divided into 100 facets, and 100 equal material files are created and bound to each facet. This correspondence of "number of sub-facets = number of thickness discrete points" ensures that the material properties of each facet are matched one-to-one with a specific thickness point.

[0062] (2) Schematic diagram of surface division and binding like Figure 8 As shown, the surface 7 of the 180mm×90mm object is divided into 100 facets in the horizontal direction. When the script is executed, the coated material files corresponding to the serial numbers of the facets from the 1st to the 100th are bound in the horizontal division order, thereby forming a continuous thickness gradient mapping from the thickest part to the thinnest part in space.

[0063] (3) Material import and optical scene setting Import the coated file into libraries by setting surface properties of the material's surface attributes; import the CIE Illuminant D65 to simulate ambient light by setting a uniform light field; use a VR observer sensor to set the viewing angle range to 0–90° and perform simulations in 5° increments. The light field modulation relationship can be found in [reference needed]. Figure 5 The structure shown.

[0064] 5. Co-simulation and result output: Figure 9 (a) and Figure 9 (b) Explain each After completing the "sub-surface division + material binding + light field and sensor settings", a joint simulation of continuous thickness gradient stack is performed to obtain the simulation results of continuous thickness gradient thin film stack observed from directly above; the color gradually changes with the thickness, and the color changes when the deflection angle is changed. At large angles, the color conforms to the color spectrum.

[0065] Figure 9 (a): Reflection color result of continuous thickness gradient stacked layers like Figure 9 As shown in (a), the color distribution effect of a continuous thickness gradient stack under the reflection channel is shown. Compared with a single reflective color of uniform thickness, this figure shows the gradient characteristics of reflective color as the thickness changes. For example, it can be shown as a two-color gradient of red and orange, and it shows a color change with the angle when the viewing angle is changed.

[0066] Figure 9 (b): Transmittance color result of continuous thickness gradient stack. like Figure 9 (b) shows the color distribution effect of a continuous thickness gradient stack under the transmission channel; the example can be a gradient from light blue to dark blue, which complements the reflected color; the color also changes when the viewing angle is changed, thus demonstrating the gradient of the transmission color space and the angle-dependent response characteristics caused by the thickness gradient.

[0067] 6. Key Points for Data Archiving and Review To ensure consistency between the co-simulation results and the thickness gradient input, this embodiment saves at least the following related information during the output stage: (i) Lumerical end thickness point number, corresponding d or thickness parameter, corresponding txt / JSON output file name; (ii) Comparison table of filenames before and after batch file conversion (txt→coated); (iii) Speos terminal face number (1–100), subface space order (horizontal division), and bound coated file number; (iv) Speos simulation conditions (D65 ambient light, VR observer field of view 0–90° in 5° increments, object surface size 180mm×90mm, etc.).

[0068] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for simulating the structural color of a SiO2 and Ti3O5 thin-layer composite stack, characterized in that, The method includes the following steps: S1. Construct a multi-layer planar structure model containing SiO2 thin layers and Ti3O5 thin layers in the thin film optical simulation module. The model includes alternating superposition of SiO2 thin layers and Ti3O5 thin layers. Input the refractive index of the material and perform optical simulation under specified wavelength and incident angle conditions through parametric scanning. Output material data file of thin film optical properties. S2. The material data files are batch converted into coating material property files that can be imported into optical rendering software. The files contain optical data such as reflectivity and transmittance. The files are then imported into the optical rendering software to perform optical simulation of a single thickness layer to obtain reflected color and transmitted color data. S3. Discretize the target thickness range into N thickness points using the first script program, and execute steps S1-S2 for each thickness point to generate the corresponding N coating material property files. S4. Discretize the geometric model of the surface to be simulated into N sub-faces using the second script program, and bind the coating material attribute file generated in step S3 that matches the thickness point of the sub-face to each sub-face. S5. Drive the optical rendering software to perform co-simulation through the third script program, and output the optical effect data of the continuous thickness gradient stack.

2. The method according to claim 1, characterized in that: The multilayer planar structure model includes alternating layers of SiO2 and Ti3O5, with the thickness ratio of the SiO2 and Ti3O5 layers ranging from 1:1 to 3:

2. The thickness of the SiO2 layer is 20 to 150 nm, and the thickness of the Ti3O5 layer is 20 nm to 150 nm.

3. The method according to claim 1, characterized in that: The parameterized scan in step S1 covers an incident angle range of 0° to 90° and a visible light band ranging from 400nm to 700nm, wherein each combination of incident angle and wavelength is used to calculate the reflectivity and transmittance under that combination condition.

4. The method according to claim 1, characterized in that: The batch conversion in step S2 includes converting optical data such as reflectivity and transmittance in the material data file according to the input format of the optical rendering software. The format is txt, CSV or JSON. The converted file includes the optical properties corresponding to each thickness point.

5. The method according to claim 1, characterized in that: The target thickness range in step S3 is 20nm-150nm, and the discrete thickness points within the thickness range are uniformly distributed at specified intervals. The discrete spacing is less than or equal to 5nm, and the spacing can be adjusted according to the required optical precision.

6. The method according to claim 1, characterized in that: In step S4, the coating material attribute file bound to each sub-face is assigned based on the geometric characteristics and thickness gradient changes of the surface model. The geometric model of each sub-face includes planes and curved surfaces. The number of sub-faces is consistent with the number of discrete thickness points, and the thickness change of each sub-face conforms to a linear or nonlinear gradient pattern.

7. The method according to claim 1, characterized in that: The optical rendering software is Ansys Speos, and the optical simulation module is the Lumerical STACK module. During the simulation, the optical rendering software calculates the reflectivity, transmittance, and color coordinates of the laminated structure under different incident angles and wavelengths based on the input material data, combined with the theoretical model and actual optical properties. This further evaluates the optical performance of the laminate and obtains detailed optical effect data of the composite material.

8. The method according to claim 1, characterized in that: The optical performance data includes reflectance, transmittance, color coordinates, and spectral data. The color coordinates are data from the CIE 1931 XYZ or CIE Lab color space, used to quantitatively characterize changes in optical performance. The spectral data includes reflection and transmission spectra at different incident angles and wavelengths.

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