Folding display method based on flexible electronic paper display screen

Abstract

The invention relates to a folding display method based on a flexible electronic paper display screen. The folding display method comprises the following steps: acquiring microcapsule arrangement density data of a folding area and a plane area of the electronic paper display screen; acquiring folding curvature distribution data and folding times of the folding area; according to the standard deviation and the average value of the size distribution of the microcapsules, establishing an evaluation model of the size distribution and the display uniformity of the microcapsules; constructing a multi-objective optimization model of display uniformity and folding performance; the preparation method comprises the following steps: preparing a microcapsule array with optimized arrangement on a flexible substrate, and characterizing the mechanical properties of a folding region; representing the display effect of the optimized microcapsule array electronic paper display screen in the folded state; and judging whether the optimized microcapsule array electronic paper display screen meets a preset requirement or not. The display uniformity is improved while the electronic paper display screen keeps good folding performance, and a new solution is provided for development of the flexible electronic paper display technology.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic paper display screens, and in particular to a folding display method based on a flexible electronic paper display screen. Background Art

[0002] Electronic paper displays have a problem of uneven display in the folding area. The microcapsule arrangement density at the folding area is different from that in the flat area. The distance between the microcapsules changes during the folding action, resulting in inconsistent local reflectivity. In addition, the stress in the folding area causes the microcapsules to deform, further affecting the arrangement and display effect. The uneven distribution of microcapsule sizes also exacerbates this problem. Therefore, how to strike a balance between display uniformity and folding performance and minimize the impact of folding on display through the optimized design of the microcapsule array is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In order to solve the problems existing in the above-mentioned prior art, the present invention aims to provide a folding display method based on a flexible electronic paper display. The folding display method based on a flexible electronic paper display achieves the electronic paper display while maintaining good folding performance and improving display uniformity, providing a new solution for the development of flexible electronic paper display technology.

[0004] The present invention provides a folding display method based on a flexible electronic paper display screen, comprising the following steps: S1, obtaining microcapsule arrangement density data of the folding area and the flat area of ​​the electronic paper display screen, and determining the relationship between the change in the microcapsule spacing and the local reflectivity under the folding action; S2, obtaining the folding curvature distribution data and the folding times of the folding area, analyzing the deformation of the microcapsules under the target stress distribution, and obtaining the relationship between the deformation and arrangement density of the microcapsules under the folding action; S3. Establishing an evaluation model of microcapsule size distribution and display uniformity based on the standard deviation and mean value of microcapsule size distribution, and determining a uniformity threshold of microcapsule size distribution; S4. According to the influence of the change of microcapsule spacing, microcapsule deformation and microcapsule size distribution on display uniformity during folding action, a multi-objective optimization model of display uniformity and folding performance is constructed; S5. Prepare microcapsule arrays with optimized arrangement on flexible substrates and characterize the mechanical properties of the folded regions to verify the folding performance of the optimized design. S6. Characterize the display effect of the optimized microcapsule array electronic paper display in the folded state, obtain reflectivity data of the folded area and the flat area, and calculate the display uniformity index; S7. Determine whether the optimized microcapsule array electronic paper display screen meets preset requirements, and obtain microcapsule array parameters that meet the performance requirements.

[0005] Preferably, the step S1 specifically includes: The microcapsule arrangement density data of the folding area and the flat area of ​​the electronic paper display are obtained, and a folding area microcapsule arrangement density model is established for the folding area. A flat area microcapsule arrangement density model is established for the flat area. By comparing the difference in microcapsule arrangement density between the folding area and the flat area, the relationship between the change in microcapsule spacing and the local reflectivity under the folding action is determined.

[0006] Preferably, the step S2 specifically includes: Acquire surface contour data of the folding area, and use Gaussian curvature algorithm to calculate folding curvature distribution data and folding times of the folding area; Conduct tensile and compression tests on the microcapsules to measure the material characteristic parameters of the microcapsules; A three-dimensional finite element model of the microcapsule is established according to the folding curvature distribution data and the material characteristic parameters, and deformation data of the microcapsule under the target stress distribution is obtained by numerical simulation calculation; A multivariate nonlinear regression method is adopted to establish a relationship model among microcapsule deformation, folding times and arrangement density according to the deformation data and the folding times, and a quantitative relationship among the three is obtained.

[0007] Preferably, the step S3 specifically includes: Calculate the coefficient of variation of the microcapsule size distribution according to the standard deviation and the average value of the microcapsule size distribution, wherein the coefficient of variation is a parameter for measuring the uniformity of the microcapsule size distribution; According to the coefficient of variation and average value of microcapsule size distribution and the reflectivity of the display screen, an evaluation model of microcapsule size distribution and display uniformity is established, and the uniformity threshold of microcapsule size distribution is determined by the evaluation model.

[0008] Preferably, the step S4 specifically includes: According to the influence of the change of microcapsule spacing, microcapsule deformation and microcapsule size distribution on display uniformity under folding action, a display uniformity evaluation function and a folding performance evaluation function are established, wherein the display uniformity evaluation function adopts the inverse of the grayscale standard deviation, and the folding performance evaluation function adopts the ratio of the maximum stress to the yield strength; Combining the display uniformity evaluation function and the folding performance evaluation function as the objective function of a multi-objective optimization problem, and constructing a multi-objective optimization model of display uniformity and folding performance; Genetic algorithm was used to obtain the optimized parameter combination of microcapsule array that takes into account both display uniformity and folding performance.

[0009] Preferably, the step S5 specifically includes: According to the optimized microcapsule array parameters, a microcapsule array with optimized arrangement is prepared on a flexible substrate; Controlling the size and spacing of microcapsules according to the microcapsule array word optimization parameters; The microcapsule array is characterized by using an atomic force microscope to obtain actual size and spacing data of the microcapsules; Measure the mechanical properties of the folded area and obtain the data on the changes of storage modulus and loss modulus with temperature; According to the data of the storage modulus and the loss modulus changing with temperature, a curve of the storage modulus changing with the number of folding times is plotted; measuring the reflectivity of the microcapsule array in different areas, wherein the reflectivity is used to calculate a standard deviation; The microcapsule array having a standard deviation smaller than a preset threshold is judged to exhibit improved uniformity.

[0010] Preferably, the step S6 specifically includes: Imaging the optimized microcapsule array electronic paper display screen to obtain initial image data of the display screen; According to the initial image data, the microcapsule array electronic paper display screen is folded into a plurality of preset angles to obtain microscopic images of the folded area and the plane area; Performing grayscale analysis on the microscopic image by image processing software to obtain grayscale distribution data of the folded area and the plane area at different folding angles; The reflectivity of the folded area and the plane area at each folding angle is measured to obtain the reflectivity curves of the folded area and the plane area in the visible light band at different folding angles; According to the reflectivity curve data, the average reflectivity of the folded area and the flat area at each folding angle is calculated, and the display uniformity index is calculated using a preset formula, and it is determined whether the display uniformity of the optimized design meets the preset threshold; If the display uniformity index is less than a preset threshold, the display uniformity of the optimized design meets the requirement; If the display uniformity index is greater than or equal to the preset threshold, the display uniformity of the optimized design does not meet the requirements, and the microcapsule array parameters are readjusted.

[0011] Preferably, the step S7 specifically includes: Determine whether the optimized microcapsule array electronic paper display screen meets preset requirements, including display uniformity and folding performance of the microcapsule array electronic paper display screen; If both the display uniformity and the folding performance meet the preset requirements, it is determined that the optimized microcapsule array electronic paper display screen meets the preset requirements, and the optimization design process is terminated to obtain microcapsule array parameters that meet the performance requirements; If the display uniformity and / or the folding performance do not meet the preset requirements, it is determined that the optimized microcapsule array electronic paper display screen does not meet the preset requirements, and the multi-objective optimization model is reconstructed, the weight coefficient of the multi-objective optimization model is adjusted, and the optimization design of the microcapsule array is re-executed until the display uniformity and the folding performance both meet the preset requirements, and the microcapsule array parameters that meet the performance requirements are obtained.

[0012] The folding display method based on a flexible electronic paper display screen described in the present invention has the following advantages: A folding display method based on a flexible electronic paper display screen of the present invention can accurately analyze the influence of the folding action on the microcapsule spacing and local reflectivity by acquiring the microcapsule arrangement density data of the folding area and the plane area, thereby ensuring the accuracy of the optimized design; not only the deformation and arrangement density of the microcapsules are considered, but also the influence of the size distribution of the microcapsules on the display uniformity is combined to construct a comprehensive multi-objective optimization model, which helps to ensure the uniformity of the display effect while improving the folding performance; a microcapsule array with an optimized arrangement is prepared on a flexible substrate, and the mechanical properties of the folding area are characterized, which helps to verify the actual effect of the optimized design and ensure the consistency between theoretical analysis and practical application; the display effect of the optimized microcapsule array electronic paper display screen in the folded state can be characterized, and it can be judged according to the reflectivity data and the display uniformity index, which provides a flexible adjustment space and can optimize the display screen according to actual needs. The present invention realizes that the electronic paper display screen improves the display uniformity while maintaining good folding performance, and provides a new solution for the development of flexible electronic paper display technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of a folding display method based on a flexible electronic paper display screen described in the present invention. DETAILED DESCRIPTION

[0014] like Figure 1 As shown, the folding display method based on the flexible electronic paper display screen described in the present invention comprises the following steps: S1, obtaining microcapsule arrangement density data of the folding area and the flat area of ​​the electronic paper display screen, and determining the relationship between the change in the microcapsule spacing and the local reflectivity under the folding action; S2, obtaining the folding curvature distribution data and the folding times of the folding area, analyzing the deformation of the microcapsules under the target stress distribution, and obtaining the relationship between the deformation and arrangement density of the microcapsules under the folding action; S3. Establishing an evaluation model of microcapsule size distribution and display uniformity based on the standard deviation and mean value of microcapsule size distribution, and determining a uniformity threshold of microcapsule size distribution; S4. According to the influence of the change of microcapsule spacing, microcapsule deformation and microcapsule size distribution on display uniformity during folding action, a multi-objective optimization model of display uniformity and folding performance is constructed; S5. Prepare microcapsule arrays with optimized arrangement on flexible substrates and characterize the mechanical properties of the folded regions to verify the folding performance of the optimized design. S6. Characterize the display effect of the optimized microcapsule array electronic paper display in the folded state, obtain reflectivity data of the folded area and the flat area, and calculate the display uniformity index; S7. Determine whether the optimized microcapsule array electronic paper display screen meets preset requirements, and obtain microcapsule array parameters that meet the performance requirements.

[0015] Furthermore, in this embodiment, step S1 specifically includes: Obtaining microcapsule arrangement density data of the folding area and the plane area of ​​the electronic paper display screen, establishing a folding area microcapsule arrangement density model for the folding area, establishing a plane area microcapsule arrangement density model for the plane area, and determining the relationship between the change in microcapsule spacing and the local reflectivity under the folding action by comparing the difference in microcapsule arrangement density between the folding area and the plane area; Specifically, a digital microscope is used to perform microscopic imaging of the folding area and the plane area of ​​the electronic paper display, and the microscopic images are processed and analyzed by the OpenCV library to obtain the microcapsule arrangement density values ​​of the folding area and the plane area; According to the microcapsule arrangement density value, the least square method was used to perform polynomial regression, the best fitting curve was determined, and the microcapsule arrangement density model of the folded area and the microcapsule arrangement density model of the plane area were established; By comparing the parameter differences between the microcapsule arrangement density model in the folded area and the microcapsule arrangement density model in the plane area, the variation of the microcapsule spacing is calculated, and a physical model of the microcapsule spacing and reflectivity is established. After the physical model is established, the theoretical reflectivity at different spacings is calculated to determine the quantitative relationship between the variation of microcapsule spacing and the local reflectivity. According to the relationship model between the change in microcapsule spacing and local reflectivity, experimental schemes with different folding angles were designed to apply preset folding stress to the electronic paper display and measure the corresponding actual local reflectivity changes; The actual local reflectivity change is compared with the model prediction value, the error is calculated and the model parameters are optimized, and the microcapsule arrangement density distribution under different folding angles is obtained through repeated iterative adjustments; Here is an example: According to the structural characteristics of the electronic paper display, a digital microscope is used to perform microscopic imaging of the folding area and the plane area. The obtained microscopic images are processed and analyzed by the OpenCV library to extract the microcapsule arrangement density data and obtain the microcapsule arrangement density values ​​of the folding area and the plane area. The least square method was uniformly used to perform polynomial regression on the microcapsule arrangement density data of the folded area and the plane area to determine the best fitting curve, and the microcapsule arrangement density model of the folded area and the microcapsule arrangement density model of the plane area were established respectively; By comparing the parameter differences between the microcapsule arrangement density model in the folded area and the microcapsule arrangement density model in the plane area, the variation of the microcapsule spacing is calculated, a physical model of the microcapsule spacing and reflectivity is established, and the theoretical reflectivity at different spacings is calculated, thereby determining the quantitative relationship between the variation of the microcapsule spacing and the local reflectivity. According to the established model of the relationship between the change in microcapsule spacing and local reflectivity, experimental schemes with different folding angles were designed, and a preset folding stress was applied to the electronic paper display. The corresponding actual local reflectivity change was measured and compared with the model prediction value. The error was calculated and the model parameters were optimized. The microcapsule arrangement density distribution at different folding angles was obtained through repeated iterative adjustments. For example, an Olympus BX53M digital microscope was used to image the electronic paper display, with the magnification set to 200 times, and the folded area and the flat area were photographed separately to obtain high-definition microscopic images; The image was binarized using the cv2.threshold function in the OpenCV library, with the threshold set to 128 to separate the microcapsules from the background. The cv2.findContours function was then used to detect the contours of the microcapsules, count the number of microcapsules per unit area, and calculate the microcapsule arrangement density values ​​in the folded area and the plane area. The polyfit function in the numpy library was used to perform polynomial regression on the acquired density data. The polynomial order was set to 3, and the density models of the folded area and the plane area were fitted respectively. The change in the microcapsule spacing was calculated by comparing the coefficients of the two models. Based on the principle of electronic paper display, a physical model of microcapsule spacing and reflectivity is established, assuming that the reflectivity R and the spacing d are exponentially related: R=a*e (-b*d) , where a and b are unknown coefficients; According to the curve_fit function in the scipy library, the coefficients a=0.8 and b=0.05 were obtained by fitting the experimental data; Design a folding experiment, use a precision angle controller to fold the electronic paper display to 30°, 60°, and 90°, and use an X-Rite SpectroEye spectrophotometer to measure the local reflectivity at each angle; The measured data were compared with the model prediction values, and the root mean square error (RMSE) was calculated. If the RMSE was greater than the preset threshold of 0.05, the model parameters were optimized by the gradient descent algorithm, and the model parameters were iteratively adjusted until the RMSE was less than the threshold. Finally, the microcapsule arrangement density distribution at different folding angles was obtained.

[0016] Furthermore, in this embodiment, step S2 specifically includes: Acquire surface contour data of the folding area, and use Gaussian curvature algorithm to calculate folding curvature distribution data and folding times of the folding area; Conduct tensile and compression tests on the microcapsules to measure the material characteristic parameters of the microcapsules; According to the folding curvature distribution data and material characteristic parameters, a three-dimensional finite element model of the microcapsule is established, and the deformation data of the microcapsule under the target stress distribution is obtained through numerical simulation calculation; The multivariate nonlinear regression method was used to establish the relationship model between microcapsule deformation, folding times and arrangement density based on the deformation data and folding times, and the quantitative relationship between the three was obtained. If the number of folding times changes, the stress distribution change is calculated according to the cumulative damage model, the deformation data of the microcapsule is updated, and then the relationship model between the microcapsule deformation, folding times and arrangement density is established based on the updated deformation data and the number of folding times, and the quantitative relationship between the three is obtained; Specifically, the surface contour data of the folding area is obtained by a three-dimensional scanner, the curvature distribution of the folding area is calculated by a Gaussian curvature algorithm, and the folding number information is obtained by combining the data recorded by the real-time folding sensor and stored in a time series database, and the initial stress distribution of the folding area is calculated according to the curvature distribution and the folding number; The microcapsules were subjected to tensile and compression tests using an Instron 5967 universal material testing machine to measure the elastic modulus, Poisson's ratio and yield strength of the microcapsules, and the test data were stored in the material property database. According to the initial stress distribution data of the folding area and the material property parameters of the microcapsules, a three-dimensional finite element model of the microcapsules was established using ANSYS Workbench software, the parameters in the material property database were imported into the model, and the deformation of the microcapsules under the target stress distribution was obtained through numerical simulation calculation; Through the cumulative damage model, the stress distribution changes under different folding times are calculated, and the deformation data of the microcapsules are updated; Combining the updated microcapsule deformation data with the previously obtained arrangement density data, a multivariate nonlinear regression method was used to establish a relationship model between microcapsule deformation, folding times and arrangement density under folding action, and the quantitative relationship between the three was obtained. Here is an example: The folding area was scanned using an Artec Space Spider 3D scanner to obtain point cloud data with a resolution of 0.1 mm. Use the pcfitplane function in MATLAB to fit the local plane, calculate the normal vector of each point, and then calculate the curvature distribution through the Gaussian curvature formula K=k1*k2, where k1 and k2 are the principal curvatures; The folding sensor uses FlexiForceA201 thin film pressure sensor with a sampling frequency of 100 Hz, and records the folding times and timestamps in the InfluxDB time series database; According to Kachanov cumulative damage theory, the stress distribution changes under different folding times are calculated, and the initial value of the stress concentration factor is set to 1.5, which increases by 0.05 for each folding; The mechanical properties of microcapsules were tested using an Instron 5967 universal material testing machine. The tensile rate was set to 2 mm / min, and the compression rate was 1 mm / min. The elastic modulus E = 2.5 GPa, Poisson's ratio ν = 0.35, and yield strength σy = 50 MPa were measured. The data were stored in the PostgreSQL database. A three-dimensional model of microcapsules was established in ANSYS Workbench. The unit type was SOLID186, the mesh size was 0.01 mm, the material parameters were imported and boundary conditions were applied. The maximum stress was set to 60 MPa. The nonlinear equations were solved by the Newton-Raphson iteration method to calculate the deformation of the microcapsules. The RandomForestRegressor function in the scikit-learn library was used for multivariate nonlinear regression. The independent variables included microcapsule deformation (range 0-0.5 mm) and folding times (range 0-1000 times), and the dependent variable was arrangement density (range 1000-5000 / mm²). The number of trees was set to 100 and the maximum depth was 10. The optimal parameters were determined by cross-validation, and finally a regression model with a determination coefficient R²=0.95 was obtained, which revealed the quantitative relationship between microcapsule deformation, folding times and arrangement density.

[0017] Furthermore, in this embodiment, step S3 specifically includes: The coefficient of variation of the microcapsule size distribution is calculated based on the standard deviation and mean value of the microcapsule size distribution. The coefficient of variation is a parameter for measuring the uniformity of the microcapsule size distribution. According to the coefficient of variation and average value of microcapsule size distribution and the reflectivity of the display screen, an evaluation model of microcapsule size distribution and display uniformity is established, and the uniformity threshold of microcapsule size distribution is determined through the evaluation model; Specifically, a microscope is used to measure the size of microcapsules of electronic paper display screen samples, and the microcapsule size measurement is performed by extracting microcapsule diameter data through image analysis software; According to the microcapsule diameter data, the probability density function of the microcapsule size is fitted using the kernel density estimation method to obtain the distribution law of the microcapsule size. According to the distribution law of microcapsule size, the standard deviation and the average value of the microcapsule size are calculated, and the standard deviation and the average value are obtained, and the coefficient of variation of the microcapsule size distribution is calculated using the coefficient of variation formula; Obtain the grayscale value standard deviation of the electronic paper display screen, where the grayscale value standard deviation is calculated by image analysis software; According to the gray value standard deviation, coefficient of variation and reflectivity of the electronic paper display, a random forest regression algorithm was used to establish an evaluation model for microcapsule size distribution and display uniformity. The samples were evaluated by the evaluation model, and a curve showing the relationship between the uniformity score and the coefficient of variation was drawn to obtain a relationship curve; The inflection point of the relationship curve was determined by the second-order derivative method, and this inflection point was used as the uniformity threshold to obtain the optimal microcapsule size distribution range; Here is an example: The microcapsule sizes of 100 electronic paper display samples were measured using an Olympus BX53 microscope. The microcapsule diameter data were extracted using ImageJ software. The probability density function of the microcapsule size was fitted using the kernel density estimation method to obtain the distribution law of the microcapsule size. According to the microcapsule size data set, the standard deviation and mean value of the microcapsule size were calculated, and the coefficient of variation of the microcapsule size distribution was obtained using the coefficient of variation formula CV = standard deviation / mean value, which was used as a parameter to measure the uniformity of the microcapsule size distribution; The standard deviation of the grayscale value of the display screen was calculated using image analysis software as an objective evaluation index of display uniformity. The coefficient of variation and mean value of the microcapsule size distribution and the reflectivity of the display screen were used as input variables, and a random forest regression algorithm was used to establish an evaluation model of microcapsule size distribution and display uniformity. A large number of samples were evaluated through the evaluation model, and a curve showing the relationship between the uniformity score and the coefficient of variation was drawn. The inflection point of the curve was determined using the second-order derivative method, that is, the point where the second-order derivative of the curve was zero was found as the uniformity threshold to obtain the optimal microcapsule size distribution range; Using the cross-validation method, the samples are divided into training sets and test sets to verify the applicability of the determined uniformity threshold on different samples; For example, the microcapsule size of 100 e-paper display samples was measured using an Olympus BX53 microscope, with the magnification set to 400 times and the acquisition resolution of 2048x2048 pixels; The microcapsule diameter data was extracted using the ParticleAnalysis function of ImageJ software, with the threshold range set to 0-255 and the particle size range to 1-100 μm²; The gaussian_kde function in the SciPy library was used for kernel density estimation, and the bandwidth selection method was Scott's Rule to obtain the probability density function of the microcapsule size; The calculated average diameter of the microcapsules was 25 μm, the standard deviation was 3 μm, and the coefficient of variation CV = 0.12; The OpenCV library is used to calculate the standard deviation of the grayscale image of the display screen, and a 3x3 Gaussian filter is used for preprocessing, and the average grayscale standard deviation is 5.6; The coefficient of variation, mean value, and display screen reflectivity of the microcapsule size distribution, with a measured value of 60%, were input into the random forest regression model, with the number of trees set to 100, the maximum depth to 10, and the minimum number of leaf node samples to 5; Through GridSearchCV, we optimized the hyperparameters and obtained the R² value of the optimal model to be 0.92. We plotted the relationship between the uniformity score and the coefficient of variation. We used the gradient function of the numpy library to calculate the second-order derivative, found the point where the derivative was zero, and determined the uniformity threshold CV_threshold = 0.15. Using 5-fold cross validation, 100 samples were randomly divided into 80 training samples and 20 test samples. The validation was repeated 5 times, and the average accuracy of the uniformity threshold on the test set was 88%, with a standard deviation of 2.3%, which proved the stability and applicability of the determined threshold.

[0018] Furthermore, in this embodiment, step S4 specifically includes: According to the influence of the change of microcapsule spacing, microcapsule deformation and microcapsule size distribution on display uniformity under folding action, the display uniformity evaluation function and folding performance evaluation function are established. The display uniformity evaluation function adopts the inverse of the grayscale standard deviation, and the folding performance evaluation function adopts the ratio of the maximum stress to the yield strength. The display uniformity evaluation function and the folding performance evaluation function are combined as the objective function of the multi-objective optimization problem, and a multi-objective optimization model of display uniformity and folding performance is constructed; A genetic algorithm is used to obtain a microcapsule array optimization parameter combination that takes into account both display uniformity and folding performance. The genetic algorithm includes: setting a value range and constraint conditions for the microcapsule array optimization parameters, including a microcapsule spacing range, a size range, and an arrangement mode, and encoding the microcapsule array optimization parameters into chromosomes of the genetic algorithm; Initialize the genetic algorithm population, set the population size, crossover probability and mutation probability, and evaluate the performance of each individual through the fitness function; Execute the selection, crossover and mutation operations of the genetic algorithm to generate a new generation of populations, and repeat the iterative process until the preset termination condition is reached; After reaching the preset termination condition, the Pareto optimal solution set is output, and the best solution is selected from them through the hierarchical analysis method to obtain the optimized parameter combination of the microcapsule array that takes into account both display uniformity and folding performance; According to the optimized parameter combination of the microcapsule array, the performance of the optimized microcapsule array at multiple folding angles was simulated using ANSYS finite element analysis software to verify the improvement of display uniformity and folding performance; Specifically, based on the microcapsule spacing change, deformation and size distribution data obtained in the early stage, a display uniformity evaluation function and a folding performance evaluation function are established, wherein the display uniformity evaluation function adopts the inverse of the grayscale standard deviation, and the folding performance evaluation function adopts the ratio of the maximum stress to the yield strength. These two evaluation functions are combined into the objective function of the multi-objective optimization problem; The value range and constraint conditions of the optimization parameters of the microcapsule array are set, including the microcapsule spacing range of 10-50 μm, the size range of 20-40 μm, and the arrangement of square and hexagon, and these parameters are encoded as chromosomes of the genetic algorithm; Initialize the genetic algorithm population, set the population size to 100, the crossover probability to 0.8, the mutation probability to 0.1, and evaluate the performance of each individual through the fitness function F=[(w1*fdisplay uniformity)+(w2*ffolding performance)], where w1 and w2 are weight coefficients, fdisplay uniformity represents the display uniformity evaluation function, and ffolding performance represents the folding performance evaluation function; Execute the selection, crossover and mutation operations of the genetic algorithm to generate a new generation of populations, repeat the iterative process until the preset termination condition is reached, such as reaching a maximum number of iterations of 1000 or the optimal solution changes less than 0.1% for 50 consecutive generations, and finally output the Pareto optimal solution set, select the best solution from it through the hierarchical analysis method, and obtain the optimized parameter combination of the microcapsule array that takes into account both display uniformity and folding performance; Here is an example: The performance of the optimized microcapsule array at five folding angles of 0°, 45°, 90°, 135°, and 180° was simulated using ANSYS finite element analysis software to verify the improvement in display uniformity and folding performance; f1 represents f display uniformity, and f2 represents f folding performance; Based on the previous data, the display uniformity evaluation function f1=1 / (σ+0.01) was constructed, where σ is the grayscale standard deviation; the folding performance evaluation function f2=1-(σmax / σy), σmax is the maximum stress, and σy is the yield strength; The NSGA-II algorithm was used to achieve multi-objective optimization. The chromosome encoding length was set to 20 bits, with the first 10 bits representing the microcapsule spacing, ranging from 10 to 50 μm, the next 10 bits representing the microcapsule size, ranging from 20 to 40 μm, and the last bit representing the arrangement, where 0 represents a square and 1 represents a hexagon; Initialize the population of 100 individuals, use the binary tournament selection operation, single-point crossover probability 0.8, and bit flip mutation probability 0.1; The fitness function F=0.6f1+0.4f2, the weight is determined according to the importance of display effect and folding performance, and it is stopped when the optimal solution changes less than 0.1% after 1000 iterations or 50 consecutive generations; The Pareto front solution was selected by crowding distance sorting, and the best solution was determined by analytic hierarchy process with a weight vector of [0.7, 0.3], which resulted in the optimal parameter combination: microcapsule spacing of 32 μm, size of 35 μm, and hexagonal arrangement; Use ANSYS Workbench to build a microcapsule array model and set material properties: Young's modulus 2 GPa, Poisson's ratio 0.3, yield strength 50 MPa; Static analysis was performed at five folding angles: 0°, 45°, 90°, 135°, and 180°. The mesh unit type was SOLID186 and the size was 0.5μm. The calculation showed that the display uniformity before and after optimization was improved by 12% and the maximum stress was reduced by 8%, which verified the optimization effect. Further, the microcapsule array parameters are obtained, and the microcapsule array parameters are encoded using a real number encoding method to obtain an individual consisting of three real numbers; If the termination condition is not reached, the selection, crossover and mutation operations are repeated until the termination condition is reached, and the current microcapsule array parameter combination is output; The performance of the optimized microcapsule array at a preset folding angle was simulated using ANSYS finite element analysis software, and the display uniformity and folding performance indicators were calculated; Specifically, a multi-objective optimization model is constructed according to display uniformity and folding performance, and the multi-objective optimization model uses the weighted sum of display uniformity and folding performance as the objective function; Acquiring microcapsule array parameters, the microcapsule array parameters including microcapsule spacing, deformation, and coefficient of variation of size distribution parameters; The microcapsule array parameters are encoded using real number encoding, and an individual consisting of three real numbers is obtained; The fitness value is calculated based on the individual, and the fitness value is equal to the weighted sum of display uniformity and folding performance; Select excellent individuals through the tournament selection method, perform arithmetic crossover and Gaussian mutation operations on the excellent individuals to generate a new generation of population; Determine whether the termination condition is met, if not, repeat the selection, crossover and mutation operations, if the termination condition is met, output the current microcapsule array parameter combination; ANSYS finite element analysis software was used to simulate the performance of the optimized microcapsule array at a preset folding angle, and the display uniformity and folding performance indicators were calculated; Here is an example: A multi-objective optimization model was constructed based on the microcapsule spacing, deformation, and size distribution parameters, and the weighted sum of display uniformity and folding performance was set as the objective function, where the display uniformity was calculated using the inverse of the grayscale standard deviation, and the folding performance was calculated using the ratio of the maximum stress to the yield strength. The display uniformity weight was 0.6, and the folding performance weight was 0.4. Constraints were set based on the microcapsule material properties and manufacturing process capabilities, including a microcapsule spacing range of 10-50 μm, a deformation range of 0-20%, and a coefficient of variation range of 0-0.2 for the size distribution parameters. The microcapsule array parameters are encoded using real number coding. Each individual consists of three real numbers, representing the coefficient of variation of the microcapsule spacing, deformation, and size distribution parameters. The population size is set to 100, the crossover probability is 0.8, and the mutation probability is 0.1. The population is initialized and the fitness value of each individual is calculated. The fitness value is equal to 0.6 times the display uniformity plus 0.4 times the folding performance. Excellent individuals are selected through the tournament selection method, with a tournament size of 5, and the arithmetic crossover operator is used for crossover operation, with an arithmetic crossover weight of 0.5, and the Gaussian mutation operator is used for mutation operation, with a standard deviation of 0.1, to generate a new generation of population. The selection, crossover and mutation operations are repeated. When the number of iterations reaches 1000 or the optimal solution for 50 consecutive generations changes by less than 0.001, the iteration is terminated and the current microcapsule array parameter combination is output; The performance of the optimized microcapsule array at five folding angles of 0°, 45°, 90°, 135°, and 180° was simulated using ANSYS finite element analysis software. The display uniformity and folding performance indicators were calculated and compared with the initial values ​​to verify the effectiveness of the optimization results. For example, based on the microcapsule spacing, deformation, and size distribution parameters, a multi-objective optimization model was constructed, and the display uniformity was calculated using 1 / (σ+0.01), where σ is the grayscale standard deviation; The folding performance is 1-(σ max / σ y ) calculation, σ max is the maximum stress, σ y is the yield strength; The objective function was set to 0.6×display uniformity+0.4×folding performance, and the constraints were: microcapsule spacing 10–50 μm, deformation 0–20%, and size distribution variation coefficient 0–0.2; Real number coding is used, each individual consists of three real numbers, the population size is set to 100, and individuals that meet the constraints are randomly generated during initialization; The NSGA-II algorithm was used for multi-objective optimization, with a crossover probability of 0.8, simulated binary crossover (SBX), and a distribution index of 20; the mutation probability was 0.1, polynomial mutation was used, and the distribution index was 20; The selection operation uses the tournament method with a scale of 5. During the iteration process, the non-dominated sorting and crowding distance of individuals in each generation are calculated; When the iteration reaches 1000 times or the optimal solution changes less than 0.001 for 50 consecutive generations, the solution is terminated, the Pareto optimal solution set is output, and the best solution is selected using the TOPSIS method; Substitute the best solution into ANSYS Workbench, establish the microcapsule array model, and set the material properties: Young's modulus 2GPa, Poisson's ratio 0.3, yield strength 50MPa; Static analysis was performed at five folding angles: 0°, 45°, 90°, 135°, and 180°. The mesh type was SOLID186 and the size was 0.5 μm. Calculations show that the display uniformity before and after optimization increased by 15%, and the maximum stress decreased by 10%, verifying the optimization effect.

[0019] Furthermore, in this embodiment, step S5 specifically includes: According to the optimized microcapsule array parameters, a microcapsule array with optimized arrangement is prepared on a flexible substrate; wherein the microcapsule array is prepared by using a Fujifilm Dimatix DMP-2850 inkjet printer, and the microcapsule array consists of a polyacrylate shell and an electrophoretic ink core; According to the microcapsule array word optimization parameters, the size and spacing of the microcapsules are controlled; The microcapsule array is characterized by an atomic force microscope to obtain the actual size and spacing data of the microcapsules; if there is an error between the actual size and spacing data and the optimized parameters, the inkjet printing parameters are adjusted, and the inkjet printing parameters include the nozzle temperature, the piezoelectric pulse waveform and the frequency; Measure the mechanical properties of the folding area and obtain the data on the change of storage modulus and loss modulus with temperature; use TA Instruments Q800 dynamic mechanical analyzer to measure the mechanical properties of the folding area; According to the data of storage modulus and loss modulus changing with temperature, a curve of storage modulus changing with folding times is drawn; The reflectivity of the microcapsule array in different areas is measured, and the reflectivity is used to calculate the standard deviation; the reflectivity of the microcapsule array in different areas is measured using an X-Rite SpectroEye spectrophotometer; The microcapsule arrays with a standard deviation less than a preset threshold are judged to show improved uniformity; Specifically, according to the optimized microcapsule array parameters, a Fujifilm Dimatix DMP-2850 inkjet printer was used to prepare a microcapsule array on a polyethylene terephthalate (PET) flexible substrate. The microcapsules consisted of a polyacrylate shell and an electrophoretic ink core. The size and spacing of the microcapsules were controlled by a high-precision nozzle to ensure consistency with the optimized parameters. The prepared microcapsule arrays were characterized using atomic force microscopy, the actual size and spacing of the microcapsules were measured, compared with the optimized parameters, the error rate was calculated, and the inkjet printing parameters, including nozzle temperature, piezoelectric pulse waveform and frequency, were adjusted to reduce the error; The mechanical properties of the folded area were tested using a TA Instruments Q800 dynamic mechanical analyzer, with the temperature range set to -50°C to 150°C, the heating rate to 3°C / min, the vibration frequency to 1Hz, and the strain amplitude to 0.1%. The changes in storage modulus and loss modulus with temperature were measured; By repeatedly folding the samples and performing dynamic mechanical analysis, the storage modulus curve versus folding times was plotted, the dynamic mechanical performance curves before and after optimization were compared, the changes in glass transition temperature, storage modulus and loss factor were calculated, and the folding performance of the optimized design was verified; The reflectivity of the optimized microcapsule array in different areas was measured using an X-Rite SpectroEye spectrophotometer, and the standard deviation was calculated and compared with that before optimization to verify the degree of improvement in display uniformity. Here is an example: A Fujifilm Dimatix DMP-2850 inkjet printer was used to prepare microcapsule arrays on a PET substrate. The microcapsules consisted of a polyacrylate shell and an electrophoretic ink core. The nozzle temperature was set to 35°C, the piezoelectric pulse waveform was a double triangle wave, the frequency was 5kHz, and the ink drop volume was 10pL. The optimized parameters of microcapsule spacing of 32μm and size of 35μm were achieved. The samples were characterized using a Bruker Dimension Icon atomic force microscope in tapping mode with a scan rate of 0.5 Hz and a resolution of 512 × 512 pixels. The actual microcapsule spacing was measured to be 31.8 ± 0.5 μm and the size was 34.7 ± 0.8 μm. The error was reduced to less than 1% by increasing the nozzle temperature to 36 °C and adjusting the piezoelectric pulse frequency to 5.2 kHz; The mechanical properties were tested using a TA Instruments Q800 dynamic mechanical analyzer. The storage modulus and loss modulus were measured at a temperature range of -50°C to 150°C, a heating rate of 3°C / min, a vibration frequency of 1Hz, and a strain amplitude of 0.1%. The results showed that the glass transition temperature of the optimized sample increased from 65°C to 68°C, and the storage modulus at room temperature increased by 15%. The sample was folded 1000 times at room temperature with a frequency of 1 Hz and an amplitude of 0.5 mm. The storage modulus was measured every 100 times, and the storage modulus-folding number curve was drawn. It was shown that the storage modulus of the optimized sample decreased from the original 25% to 18% after 1000 folds. The reflectivity of the sample was measured at nine different locations at 10nm intervals within the wavelength range of 400-700nm using an X-Rite SpectroEye spectrophotometer. The calculated standard deviation of the sample reflectivity was reduced from 0.035 to 0.028 after optimization, verifying the improvement in display uniformity.

[0020] Furthermore, in this embodiment, step S6 specifically includes: Imaging the optimized microcapsule array electronic paper display screen to obtain initial image data of the display screen; imaging is performed using an optical microscope; According to the initial image data, the microcapsule array electronic paper display is folded into a plurality of preset angles to obtain microscopic images of the folded area and the plane area; The grayscale analysis of the microscopic image is performed by image processing software to obtain the grayscale distribution data of the folded area and the plane area at different folding angles; The reflectivity of the folded area and the plane area at each folding angle is measured to obtain the reflectivity curves of the folded area and the plane area in the visible light band at different folding angles; the reflectivity is measured using a spectrometer; According to the reflectivity curve data, the average reflectivity of the folded area and the flat area at each folding angle is calculated, and the display uniformity index is calculated using a preset formula, and it is determined whether the display uniformity of the optimized design meets the preset threshold; If the display uniformity index is less than the preset threshold, the display uniformity of the optimized design meets the requirements; If the display uniformity index is greater than or equal to the preset threshold, the display uniformity of the optimized design does not meet the requirements, and the microcapsule array parameters are readjusted; Specifically, an Olympus BX53M optical microscope was used with a magnification of 100 times to image the optimized microcapsule array electronic paper display. The electronic paper display was folded into angles of 45 degrees, 90 degrees, and 135 degrees, respectively, and fixed on a special fixture for measurement. Microscopic images of the folded area and the plane area at each folding angle were obtained. The grayscale analysis of the microscopic images was performed using ImageJ software to obtain grayscale distribution data of the folded area and the plane area at different folding angles. The reflectivity of the folded area and the plane area at each folding angle was measured using an OceanOpticsUSB4000 spectrometer. The wavelength range was set to 400-700nm, and the step length was 10nm. The reflectivity curves of the folded area and the plane area in the visible light band at different folding angles were obtained. According to the reflectivity curve data, the average reflectivity of the folded area and the flat area at each folding angle is calculated, and the display uniformity index is calculated using the formula "display uniformity index = standard deviation / average reflectivity*100%". The smaller the display uniformity index, the better the uniformity; The calculated display uniformity index at each folding angle is compared with a preset threshold of 5%; If the display uniformity index is less than the preset threshold, it is judged that the display uniformity of the optimized design meets the requirements; If the display uniformity index is greater than or equal to the preset threshold, the display uniformity of the optimized design does not meet the requirements, and the microcapsule array parameters are readjusted; Here is an example: The optimized microcapsule array electronic paper display was imaged using an Olympus BX53M optical microscope, with a magnification of 100 times and a resolution of 2048 x 2048 pixels. The display screen was folded into 45, 90, and 135 degree angles using an automated fixture, and five images of the folded area and five images of the flat area were captured at each angle. Image processing was performed using ImageJ software, and Gaussian blur (σ = 2) was applied for denoising, followed by binarization using the Otsu threshold method, and the mean grayscale value and standard deviation of each image were calculated; The OceanOpticsUSB4000 spectrometer was set to an integration time of 100 ms, averaging 10 measurements, and collecting a data point every 10 nm in the range of 400-700 nm; For each folding angle, 9 points are measured in the folding area and the flat area, forming a 3x3 grid covering the entire area; The area under the reflectivity curve was calculated using the trapezoidal rule to obtain the average reflectivity; The display uniformity index at each folding angle was calculated using the formula "display uniformity index = standard deviation / average reflectivity * 100%". The results showed that the display uniformity index at folding angles of 45 degrees, 90 degrees and 135 degrees was 3.8%, 4.2% and 4.5% respectively, all less than the preset threshold of 5%; The relationship between the folding angle and the display uniformity index was analyzed by linear regression, and the slope was 0.007% / degree, indicating that as the folding angle increased, the display uniformity decreased slightly, but it was still within an acceptable range; Based on these data, it is judged that the display uniformity of the optimized design meets the requirements and there is no need to return to adjust the microcapsule array parameters.

[0021] Furthermore, in this embodiment, step S7 specifically includes: Determine whether the optimized microcapsule array electronic paper display screen meets preset requirements, including display uniformity and folding performance of the microcapsule array electronic paper display screen; If both the display uniformity and the folding performance meet the preset requirements, it is determined that the optimized microcapsule array electronic paper display meets the preset requirements, and the optimization design process is ended to obtain microcapsule array parameters that meet the performance requirements; If the display uniformity and / or folding performance do not meet the preset requirements, it is determined that the optimized microcapsule array electronic paper display screen does not meet the preset requirements, and the multi-objective optimization model is reconstructed, the weight coefficient of the multi-objective optimization model is adjusted, and the optimization design of the microcapsule array is re-executed until the display uniformity and folding performance both meet the preset requirements, and the microcapsule array parameters that meet the performance requirements are obtained; Specifically, according to the display uniformity and folding performance test results of the microcapsule array electronic paper display screen, it is determined whether the display uniformity index is less than a preset 5% threshold value, and whether the folding performance index is greater than a preset 90% threshold value; If the display uniformity index or the folding performance index does not meet the preset requirements, an adaptive weight adjustment algorithm is used to build a multi-objective optimization model; According to the weight coefficient obtained by the adaptive weight adjustment algorithm, the optimization design of the microcapsule array is performed, wherein the optimization design adopts a genetic algorithm to optimize the parameters, the genetic algorithm uses real number coding, and the chromosome length is the number of microcapsule array parameters; The performance of the microcapsule array parameters optimized by genetic algorithm was evaluated to obtain the display uniformity index and folding performance index; If the display uniformity index and / or the folding performance index still do not meet the preset requirements, return to the adaptive weight adjustment algorithm to re-acquire the weight coefficient, and repeat the optimization design until the microcapsule array parameters that meet the preset requirements are obtained; Here is an example: According to the display uniformity and folding performance test results of the optimized microcapsule array electronic paper display, the display uniformity index threshold is set to 5%, and the folding performance index threshold is set to 90%. If both indicators meet the preset thresholds, the current microcapsule array parameters are recorded and the optimization process is terminated. If the display uniformity or folding performance does not meet the preset requirements, the multi-objective optimization model is rebuilt, and the adaptive weight adjustment algorithm is used to dynamically adjust the weight coefficients of display uniformity and folding performance according to the performance improvement degree of the previous iteration, and the initial weights are set to 0.5; The optimized design of the microcapsule array was re-executed using the adjusted weight coefficients. The genetic algorithm was used for parameter optimization. Real number coding was used. The chromosome length was the number of microcapsule array parameters. The fitness function was the weighted sum objective function. The population size was set to 100, the crossover probability was set to 0.8, the mutation probability was set to 0.1, and the maximum number of iterations was set to 1000. The performance of the new microcapsule array parameters obtained by optimization is evaluated, the display uniformity and folding performance indicators are calculated, compared with the preset requirements, the optimal solution of each iteration is recorded, the performance index is plotted as a function of the number of iterations, and the convergence trend is analyzed. If the requirements are still not met, return to the second step to continue adjusting the weight coefficients and repeat the optimization process until the microcapsule array parameters that meet the performance requirements are obtained or the maximum number of iterations is reached; The physical samples of the finally optimized microcapsule array parameters are produced and tested to verify their actual performance; For example, based on the test results of the optimized microcapsule array electronic paper display, the display uniformity index was 4.8% and the folding performance index was 88%, compared with the preset thresholds of 5% and 90%; Since the folding performance did not meet the standard, the adaptive weight adjustment algorithm was started, and the initial weights were set to 0.5 for display uniformity and 0.5 for folding performance; According to the performance improvement, the weights are adjusted to 0.4 for display uniformity and 0.6 for folding performance; Genetic algorithm was used to optimize the microcapsule array parameters. The chromosome was encoded as [spacing, size, deformation], and each gene was represented by 8 bits of binary. The fitness function is f = 0.4*(1-display uniformity / 5%)+0.6*(folding performance / 90%); Set the population size to 100, the crossover probability to 0.8, use single-point crossover, the mutation probability to 0.1, and use bit flip mutation; After running for 500 generations, the optimal solution is [32μm, 35μm, 15%], corresponding to a display uniformity of 4.6% and a folding performance of 91.2%; Plotting the convergence curve shows that the fitness value tends to be stable after 300 generations; The final optimized parameters were used to make samples, and the actual measurement showed a uniformity of 4.7% and a folding performance of 90.8%, which verified the effectiveness of the optimization results; The entire optimization process took about 2 hours, of which genetic algorithm calculation accounted for 85% and sample preparation and testing accounted for 15%.

[0022] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention.

[0023] For those skilled in the art, various other corresponding changes and deformations can be made according to the technical solutions and concepts described above, and all of these changes and deformations should fall within the protection scope of the claims of the present invention.

Claims

1. A folding display method based on a flexible electronic paper display, characterized in that: The following steps are involved: S1, obtaining microcapsule arrangement density data of the folding area and the flat area of ​​the electronic paper display screen, and determining the relationship between the change in the microcapsule spacing and the local reflectivity under the folding action; S2, obtaining the folding curvature distribution data and the folding times of the folding area, analyzing the deformation of the microcapsules under the target stress distribution, and obtaining the relationship between the deformation and arrangement density of the microcapsules under the folding action; S3. Establishing an evaluation model of microcapsule size distribution and display uniformity based on the standard deviation and mean value of microcapsule size distribution, and determining a uniformity threshold of microcapsule size distribution; S4. According to the influence of the change of microcapsule spacing, microcapsule deformation and microcapsule size distribution on display uniformity during folding action, a multi-objective optimization model of display uniformity and folding performance is constructed; S5. Prepare microcapsule arrays with optimized arrangement on flexible substrates and characterize the mechanical properties of the folded regions to verify the folding performance of the optimized design. S6. Characterize the display effect of the optimized microcapsule array electronic paper display in the folded state, obtain reflectivity data of the folded area and the flat area, and calculate the display uniformity index; S7. Determine whether the optimized microcapsule array electronic paper display screen meets preset requirements, and obtain microcapsule array parameters that meet the performance requirements.

2. The folding display method based on the flexible electronic paper display according to claim 1, characterized in that: The step S1 specifically includes: The microcapsule arrangement density data of the folding area and the flat area of ​​the electronic paper display are obtained, and a folding area microcapsule arrangement density model is established for the folding area. A flat area microcapsule arrangement density model is established for the flat area. By comparing the difference in microcapsule arrangement density between the folding area and the flat area, the relationship between the change in microcapsule spacing and the local reflectivity under the folding action is determined.

3. The folding display method based on the flexible electronic paper display according to claim 1, characterized in that: The step S2 specifically includes: Acquire surface contour data of the folding area, and use Gaussian curvature algorithm to calculate folding curvature distribution data and folding times of the folding area; Conduct tensile and compression tests on the microcapsules to measure the material characteristic parameters of the microcapsules; A three-dimensional finite element model of the microcapsule is established according to the folding curvature distribution data and the material characteristic parameters, and deformation data of the microcapsule under the target stress distribution is obtained by numerical simulation calculation; A multivariate nonlinear regression method is adopted to establish a relationship model among microcapsule deformation, folding times and arrangement density according to the deformation data and the folding times, and a quantitative relationship among the three is obtained.

4. The folding display method based on the flexible electronic paper display according to claim 1, characterized in that: The step S3 specifically includes: Calculate the coefficient of variation of the microcapsule size distribution according to the standard deviation and the average value of the microcapsule size distribution, wherein the coefficient of variation is a parameter for measuring the uniformity of the microcapsule size distribution; According to the coefficient of variation and average value of microcapsule size distribution and the reflectivity of the display screen, an evaluation model of microcapsule size distribution and display uniformity is established, and the uniformity threshold of microcapsule size distribution is determined by the evaluation model.

5. The folding display method based on the flexible electronic paper display screen according to claim 1, characterized in that: The step S4 specifically includes: According to the influence of the change of microcapsule spacing, microcapsule deformation and microcapsule size distribution on display uniformity under folding action, a display uniformity evaluation function and a folding performance evaluation function are established, wherein the display uniformity evaluation function adopts the inverse of the grayscale standard deviation, and the folding performance evaluation function adopts the ratio of the maximum stress to the yield strength; Combining the display uniformity evaluation function and the folding performance evaluation function as the objective function of a multi-objective optimization problem, and constructing a multi-objective optimization model of display uniformity and folding performance; Genetic algorithm was used to obtain the optimized parameter combination of microcapsule array that takes into account both display uniformity and folding performance.

6. The folding display method based on the flexible electronic paper display according to claim 1, characterized in that: The step S5 specifically includes: According to the optimized microcapsule array parameters, a microcapsule array with optimized arrangement is prepared on a flexible substrate; Controlling the size and spacing of microcapsules according to the microcapsule array word optimization parameters; The microcapsule array is characterized by using an atomic force microscope to obtain actual size and spacing data of the microcapsules; Measure the mechanical properties of the folded area and obtain the data on the changes of storage modulus and loss modulus with temperature; According to the data of the storage modulus and the loss modulus changing with temperature, a curve of the storage modulus changing with the number of folding times is plotted; measuring the reflectivity of the microcapsule array in different areas, wherein the reflectivity is used to calculate a standard deviation; The microcapsule array having a standard deviation smaller than a preset threshold is judged to exhibit improved uniformity.

7. The folding display method based on the flexible electronic paper display according to claim 1, characterized in that: The step S6 specifically includes: Imaging the optimized microcapsule array electronic paper display screen to obtain initial image data of the display screen; According to the initial image data, the microcapsule array electronic paper display screen is folded into a plurality of preset angles to obtain microscopic images of the folded area and the plane area; Performing grayscale analysis on the microscopic image by image processing software to obtain grayscale distribution data of the folded area and the plane area at different folding angles; The reflectivity of the folded area and the plane area at each folding angle is measured to obtain the reflectivity curves of the folded area and the plane area in the visible light band at different folding angles; According to the reflectivity curve data, the average reflectivity of the folded area and the flat area at each folding angle is calculated, and the display uniformity index is calculated using a preset formula, and it is determined whether the display uniformity of the optimized design meets the preset threshold; If the display uniformity index is less than a preset threshold, the display uniformity of the optimized design meets the requirement; If the display uniformity index is greater than or equal to the preset threshold, the display uniformity of the optimized design does not meet the requirements, and the microcapsule array parameters are readjusted.

8. The folding display method based on the flexible electronic paper display screen according to claim 1, characterized in that: The step S7 specifically includes: Determine whether the optimized microcapsule array electronic paper display screen meets preset requirements, including display uniformity and folding performance of the microcapsule array electronic paper display screen; If both the display uniformity and the folding performance meet the preset requirements, it is determined that the optimized microcapsule array electronic paper display screen meets the preset requirements, and the optimization design process is terminated to obtain microcapsule array parameters that meet the performance requirements; If the display uniformity and / or the folding performance do not meet the preset requirements, it is determined that the optimized microcapsule array electronic paper display screen does not meet the preset requirements, and the multi-objective optimization model is reconstructed, the weight coefficient of the multi-objective optimization model is adjusted, and the optimization design of the microcapsule array is re-executed until the display uniformity and the folding performance both meet the preset requirements, and the microcapsule array parameters that meet the performance requirements are obtained.

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