Control method and device for secondary chemical strengthening of cover plate glass and program product

Abstract

The invention provides a control method and device for secondary chemical strengthening of cover plate glass and a program product. The method comprises the following steps: determining process parameters of secondary strengthening according to a sodium ion coupling diffusion equation; and performing primary chemical strengthening and secondary chemical strengthening on the cover plate glass according to the process parameters. According to the control method for secondary chemical strengthening of the cover plate glass provided by the invention, the problem that the surface potassium ion concentration after secondary strengthening cannot be accurately predicted and controlled at present is fundamentally solved by introducing a sodium-potassium ion coupling diffusion equation. And moreover, traditional experience trial and error are replaced by accurate calculation based on a physical model, and the relative error between the predicted concentration of the model and a measured value is reduced, so that accurate prediction and regulation of the concentration are realized, and the yield of the cover plate glass is remarkably improved.

Description

Technical Field

[0001] This application relates to the field of glass chemical strengthening technology, and more specifically, to a control method, apparatus, and procedure for secondary chemical strengthening of cover glass. Background Technology

[0002] With the widespread use of smartphones, tablets, and other mobile devices, the requirements for the strength, scratch resistance, and thinness of cover glass are increasing. High-alumina glass, due to its excellent mechanical properties and chemical stability, has become the mainstream cover glass material. Its strengthening effect mainly relies on ion exchange technology, which involves exchanging small-radius sodium ions (Na⁺) on the glass surface with large-radius potassium ions (K⁺) in molten salt to form a compressive stress layer on the glass surface, thereby improving the glass strength.

[0003] To further optimize the strengthening effect, the industry widely adopts a secondary chemical strengthening process: the first step uses low-concentration potassium nitrate molten salt for ion exchange to initially form a compressive stress layer; the second step uses high-concentration potassium nitrate molten salt to deepen the exchange, increasing the surface potassium ion concentration and the depth of the compressive stress layer. However, existing secondary strengthening technologies have key drawbacks: because the potassium ion diffusion process is affected by multiple factors such as temperature, time, and molten salt concentration, it is impossible to accurately predict and control the surface potassium ion concentration after secondary strengthening. This results in large fluctuations in the strength of glass products, poor batch consistency, and a tendency for over-strengthening leading to glass warping and breakage.

[0004] In other words, current control schemes for secondary strengthening of cover glass make it difficult to accurately predict and regulate concentration. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, and program product for controlling the secondary chemical strengthening of cover glass, so as to achieve accurate prediction and control of concentration during the secondary strengthening process of cover glass.

[0006] In a first aspect, embodiments of this application provide a method for controlling secondary chemical strengthening of cover glass, comprising: determining the process parameters for secondary strengthening based on a sodium ion coupled diffusion equation; wherein, the sodium ion coupled diffusion equation is: ; In the formula, This is the partial derivative with respect to the sodium ion concentration. The partial derivative is the diffusion depth. Here, D is the partial derivative with respect to diffusion time, T is the chemical intensification temperature, and D is the partial derivative with respect to diffusion time. NN (T) is the main diffusion coefficient of sodium ions; k1 is the activity correction coefficient obtained by experimental fitting; the cover glass is subjected to the first chemical strengthening and the second chemical strengthening according to the process parameters.

[0007] The aforementioned method for controlling the secondary chemical strengthening of cover glass fundamentally solves the problem of the inability to accurately predict and control the surface potassium ion concentration after secondary strengthening by introducing a sodium-potassium ion coupled diffusion equation. Furthermore, by replacing traditional trial-and-error with precise calculations based on a physical model, the relative error between the model-predicted concentration and the measured value is reduced, thereby achieving accurate concentration prediction and control, and significantly improving the yield of cover glass.

[0008] In conjunction with the first aspect, optionally, determining the process parameters for secondary enhancement based on the sodium ion coupling diffusion equation includes: substituting the process parameters into the potassium ion concentration calculation formula for verification; wherein, the potassium ion concentration calculation formula is: ; In the formula, W is the potassium ion concentration, C0 is the initial potassium ion concentration on the surface of the cover glass, k2 is the surface ion exchange coefficient, and ωNa2O ,0 ωNa₂O represents the initial sodium ion concentration of sodium oxide in the cover glass. ,0 The sodium ion concentration of sodium oxide in the cover glass at the end of the first chemical strengthening; the process parameters include: T1, the temperature during the first chemical strengthening; T2, the temperature during the second chemical strengthening; t1, the time of the first chemical strengthening; t2, the time of the second chemical strengthening; S1, the mass percentage of potassium solution in the salt bath used in the first chemical strengthening; and S2, the mass percentage of potassium solution in the salt bath used in the second chemical strengthening.

[0009] The aforementioned method for controlling the secondary chemical strengthening of cover glass, verified using a potassium ion concentration calculation formula and used in conjunction with a sodium ion coupled diffusion equation, further improves the precision of control during cover glass production. This increases the speed of process parameter verification, thereby improving production efficiency and further enhancing control accuracy.

[0010] In conjunction with the first aspect, optionally, where 4.2 ≤ W ≤ 18.8.

[0011] The above-mentioned control method for secondary chemical strengthening of cover glass, by limiting the effective range of W value, further ensures the strength and toughness of the obtained cover glass, solves the problems of large strength fluctuations and over-strengthening caused by uncontrolled concentration, thereby further improving the prediction accuracy and control accuracy of concentration, and ultimately further improving the yield of cover glass.

[0012] In conjunction with the first aspect, optionally, the main diffusion coefficient of the sodium ions is: ; In the formula, D0 is the frequency factor, and E aR is the diffusion activation energy, R is the gas constant, and T is the chemical strengthening temperature.

[0013] The aforementioned method for controlling the secondary chemical strengthening of cover glass overcomes the shortcomings of not incorporating the temperature difference in the two-step strengthening process by introducing the Arrhenius equation to describe the temperature dependence of the diffusion coefficient. This allows the model to more accurately reflect the effect of temperature changes on the ion diffusion rate, thereby improving the model's applicability and reliability in complex industrial environments. Ultimately, it further improves the accuracy of concentration prediction and control.

[0014] In conjunction with the first aspect, optionally, determining the secondary strengthening process parameters based on the sodium ion coupled diffusion equation includes: determining the process parameters based on stress parameters and a parameter equivalent conversion model; wherein, the method for constructing the equivalent conversion model includes: generating multiple test process parameters; inputting the test process parameters into the sodium ion coupled diffusion equation to obtain output test concentration parameters; conducting a chemical strengthening experiment using the test process parameters and measuring the test stress parameters of the cover glass obtained from the experiment; and inputting the test process parameters and test stress parameters into an initial parameter equivalent conversion model to obtain the parameter equivalent conversion model; wherein, the initial parameter equivalent conversion model is: ; In the formula, σ (x) For the test process parameters at depth x, C k(x) Let be the measured concentration parameter of potassium ions at depth x, and β(x) be the mapping function.

[0015] The above-mentioned control method for secondary chemical strengthening of cover glass, by constructing an equivalent conversion model, enables the prediction of mechanical properties based on ion concentration, and achieves rapid and non-destructive prediction of key mechanical properties of the strengthened cover glass.

[0016] In conjunction with the first aspect, optionally, the step of conducting a chemical strengthening experiment with the test process parameters and measuring the test stress parameters of the cover glass obtained from the experiment includes: measuring multiple sets of initial test stress parameters of multiple sets of cover glass under the same set of process parameters in a chemical strengthening experiment; and using the average value of the multiple sets of initial test stress parameters as the test stress parameter.

[0017] The above-mentioned control method for secondary chemical strengthening of cover glass reduces the random error of a single experiment by taking the average value of multiple measurements, improves the accuracy of the constructed equivalent transformation model, ensures the reliability of the "concentration-stress" mapping relationship, thereby further improving the prediction accuracy and control accuracy of concentration, and ultimately further improving the yield of cover glass.

[0018] In conjunction with the first aspect, optionally, determining the process parameters based on stress parameters and a parameter equivalent transformation model includes: randomly generating several sets of candidate process parameters; inputting the several sets of candidate process parameters into the parameter equivalent transformation model respectively to obtain several sets of stress parameters; obtaining the user's target stress parameters; and determining the candidate process parameters corresponding to the stress parameters that satisfy the target stress parameters as the process parameters.

[0019] The aforementioned control method for secondary chemical strengthening of cover glass enables users to directly input their desired mechanical performance indicators and automatically and quickly deduce the optimal process parameters, thereby improving the production efficiency of cover glass.

[0020] In conjunction with the first aspect, optionally, the random generation of several sets of candidate process parameters includes: selecting several candidate process parameters covering a feasible region at specific intervals within the feasible domain; inputting the several sets of candidate process parameters into the parameter equivalent transformation model to obtain several sets of stress parameters includes: inputting the several candidate process parameters into the parameter equivalent transformation model to obtain several sets of stress parameters, and constructing a mapping database with the several process parameters and the corresponding several stress parameters; determining the candidate process parameter corresponding to the stress parameter that satisfies the target stress parameter as the process parameter includes: querying the corresponding process parameter in the mapping database according to the target stress parameter.

[0021] The aforementioned control method for secondary chemical strengthening of cover glass improves the reverse response speed by pre-constructing a relatively detailed mapping database, thereby further enhancing the production efficiency of cover glass.

[0022] Secondly, embodiments of this application provide a control device for secondary chemical strengthening of cover glass, comprising: a determining module, used to determine the process parameters for secondary strengthening based on a sodium ion coupling diffusion equation; wherein the sodium ion coupling diffusion equation is: ; In the formula, This is the partial derivative with respect to the sodium ion concentration. The partial derivative is the diffusion depth. D is the partial derivative with diffusion time. NN (T) is the main diffusion coefficient of sodium ions; k1 is the activity correction coefficient obtained by experimental fitting; the strengthening module is used to perform the first chemical strengthening and the second chemical strengthening of the cover glass according to the process parameters.

[0023] The control device for secondary chemical strengthening of cover glass described above has the same beneficial effects as the control method for secondary chemical strengthening of cover glass provided by the first aspect or any optional embodiment of the first aspect, and will not be elaborated here.

[0024] Thirdly, embodiments of this application provide a program product, including a computer program / instructions, which, when executed by a processor, implements the control method for secondary chemical strengthening of cover glass as described above.

[0025] The above-described process product has the same beneficial effects as the control method for secondary chemical strengthening of cover glass provided by the first aspect or any optional embodiment of the first aspect, which will not be elaborated here. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart illustrating the control method for secondary chemical strengthening of cover glass provided in an embodiment of this application; Figure 2 A flowchart illustrating the method for constructing an equivalent transformation model in the control method for secondary chemical strengthening of cover glass provided in this application embodiment; Figure 3 A detailed flowchart of step S230 in the control method for secondary chemical strengthening of cover glass provided in the embodiments of this application; Figure 4 A detailed flowchart of step S122 in the control method for secondary chemical strengthening of cover glass provided in the embodiments of this application; Figure 5 A functional block diagram of the control device for secondary chemical strengthening of cover glass provided in the embodiments of this application. Detailed Implementation

[0028] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this application.

[0030] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0031] Currently, although models related to the evolution of ion concentration have been proposed, they do not fully consider the promoting effect of components such as lithium (Li⁺) in high-alumina glass on the diffusion coefficient, nor do they take into account the temperature difference of the two-step strengthening and the influence of the early strengthening state on subsequent diffusion. Furthermore, they do not introduce the coupling diffusion effect of sodium and potassium ions, resulting in low model prediction accuracy and a relative error that is usually greater than 8%. As a result, they cannot accurately reflect the cooperative migration law of sodium and potassium ions during ion exchange, and thus cannot meet the precise control requirements of industrial production.

[0032] In view of this, this application provides a method, apparatus, and procedure for controlling secondary chemical strengthening of cover glass to solve the above-mentioned technical problems. Specifically, please refer to the embodiments and accompanying drawings provided in this application.

[0033] Please refer to Figure 1 , Figure 1 This is a flowchart of a control method for secondary chemical strengthening of cover glass provided in an embodiment of this application. The control method for secondary chemical strengthening of cover glass provided in an embodiment of this application includes: Step S120: Determine the process parameters for secondary enhancement based on the sodium ion coupled diffusion equation. The sodium ion coupled diffusion equation is: ; In step S120 above, This is the partial derivative with respect to the sodium ion concentration. The partial derivative is the diffusion depth. Here, denoted by , is the partial derivative with respect to diffusion time, and T is the chemical intensification temperature. denoted as , where is the main diffusion coefficient for sodium ions. k1 is the activity correction coefficient obtained through experimental fitting.

[0034] The specific process of establishing the sodium ion coupled diffusion equation is as follows: During the glass chemical strengthening process, sodium ions mainly migrate along the glass thickness direction (one-dimensional) without radial diffusion interference. Therefore, it conforms to the applicable scenario of Fick's second law "one-dimensional, steady-state / unsteady-state diffusion". Therefore, Fick's second law is selected as the core theoretical basis for sodium ion diffusion.

[0035] The original expression of Fick's second law is: ; In the formula, This refers to the ion concentration. For diffusion depth, For diffusion time, The diffusion coefficient is related to location and concentration.

[0036] Experimental verification revealed that in Li₂O-containing high-alumina glass, the sodium ion diffusion coefficient is only related to temperature (the correlation error with location and concentration is <0.5%, which is negligible). Therefore, the diffusion coefficient can be simplified as a single-variable function of temperature. Meanwhile, by specifying the variable as "sodium ion concentration," the basic diffusion equation for sodium ions is obtained: ; In the formula, Let be the sodium ion concentration at depth x at time t. Where is the sodium ion diffusion coefficient, and T is the chemical strengthening temperature; In the two-step chemical strengthening process, the migration of sodium ions (Na⁺, radius 95 pm) and the migration of potassium ions (K⁺, radius 138 pm) occur simultaneously, resulting in a mutually reinforcing coupling effect: when K⁺ migrates in, it disrupts the local glass network structure and reduces the channel resistance for Na⁺ migration. Therefore, a "Na⁺-K⁺ cross-diffusion term" needs to be added to the sodium ion basic equation to quantify this promoting effect.

[0037] in The main diffusion coefficient characterizing sodium ions. Characterizing the promoting effect of K⁺ on Na⁺ diffusion, Let be the potassium ion concentration at depth x at time t; based on the diffusion characteristics of similar high-alumina glasses, it is assumed that the cross-diffusion coefficient and the main diffusion coefficient have a fixed proportional relationship, i.e. , where k2 is the sodium ion coupling ratio coefficient to be calibrated.

[0038] The following implementation examples are now established: The high-alumina cover glass sheet is selected, and its chemical composition, expressed as a mass fraction, is: SiO2: 61.2%, Al2O3: 19.2%, Na2O: 6.8%, K2O: 1.8%, ZrO2: 2.0%, MgO: 3.8%, Li2O: 5.2%.

[0039] SiO2: 62.1%, Al2O3: 19.8%, Na2O: 7.8%, K2O: 1.0%, ZrO2: 1.8%, MgO: 3.4%, Li2O: 4.1%.

[0040] SiO2: 61.8%, Al2O3: 19.3%, Na2O: 6.2%, K2O: 1.4%, ZrO2: 1.6%, MgO: 3.2%, Li2O: 6.5%.

[0041] Determining the first chemical strengthening time: Based on the first chemical strengthening time and performance parameters, the optimal strengthening temperature is 410℃, and the ion exchange time is 120 min; the mass percentage of potassium nitrate and sodium nitrate during the first chemical strengthening ion exchange is 50:50. Based on the second chemical strengthening time and performance parameters, the optimal strengthening temperature is 420℃ and the ion exchange time is 100min; the mass percentage of potassium nitrate and sodium nitrate during the second chemical strengthening ion exchange is 98:2.

[0042] The potassium ion concentrations after the first and second chemical strengthening processes, as well as the potassium ion diffusion coefficient during the second chemical strengthening, were determined using a Shimadzu X-ray fluorescence spectrometer (model MXF-2400) from Japan. The specific results are shown in Table 1 below. Table 1

[0043] The deduction process is based on a specific high-alumina cover glass system containing 5.2% Li2O (chemical composition: SiO2 61.2%, Al2O3 19.2%, Na2O 6.8%, K2O 1.8%, ZrO2 2.0%, MgO 3.8%, Li2O 5.2%), combined with two-step chemical strengthening process parameters (step one: 410℃, 120min, molten salt KNO3:NaNO3=50:50; step two: 420℃, 100min, molten salt KNO3:NaNO3=98:2, data source as shown in Table 2) and measured ion concentration data (measured ion concentration data table after strengthening).

[0044] Table 2

[0045] According to Table 2, during the two-step enhancement process, K⁺ (radius 138 pm) migrates into and Na⁺ (radius 95 pm) migrates into the ion concentrations after enhancement. (Based on the measured ion concentration data after enhancement) After one-step enhancement: surface K⁺ concentration = 9.0 mol / m³ (migration in = 9.0 - 1.02 = 7.98 mol / m³), surface Na⁺ concentration = 3.03 mol / m³ (migration out = 5.48 - 3.03 = 2.45 mol / m³). After two-step enhancement: surface K⁺ concentration = 15.0 mol / m³ (re-migration amount = 15.0 - 9.0 = 6.0 mol / m³), surface Na⁺ concentration = 2.11 mol / m³ (re-migration amount = 3.03 - 2.11 = 0.92 mol / m³).

[0046] It is evident that Na⁺ migration out and K⁺ migration in have a synergistic promoting effect—K⁺ migration in disrupts the glass network structure, reducing the resistance to Na⁺ migration out; the network gaps vacated by Na⁺ migration facilitate K⁺ migration in. Therefore, a cross-diffusion term needs to be added to the basic equations to characterize this coupling effect. Based on multi-component diffusion theory (a simplification of the Stefan-Maxwell equations), a preliminary equation for sodium ion coupled diffusion is constructed: The measured concentration data from the two-step enhancement were selected as the calibration benchmark. The core calibration parameters are as follows, with the process parameters corresponding to Table 2.

[0047] Fitting objective: To minimize the relative error between the "equation-based simulated concentration" and the "measured concentration" (target error < 1%).

[0048] Fitting process: 1. Substitute the basic equations, the simplified coupled diffusion equations, and the process parameters (T, t, molten salt ratio) into the numerical simulation software; 2. Iteratively optimize the value of k2 (initial range 0.1~0.6), and calculate the simulated concentration corresponding to different k2 values; 3. Calculate the relative error between the simulated concentration and the measured concentration.

[0049] 4. When k2=0.4, the error reaches its minimum: the error of Na⁺ concentration in one-step enhancement is 0.66% and the error of K⁺ concentration is 0.22%; the error of Na⁺ concentration in two-step enhancement is 0.95% and the error of K⁺ concentration is 0.13%, both of which meet the accuracy requirements.

[0050] Calibration result: k2=0.4, therefore the final expression for the cross-diffusion coefficient is: ; The coupling scaling factor k2 was calibrated using the least squares method for fitting. Fitting objective: To ensure that the relative error between the simulated concentration and the measured concentration is less than 1%. The steps are as follows: Calculate the Na⁺ principal diffusion coefficient at the one-step intensification temperature (Arrhenius equation): formula:

[0051] Substitute parameter: D N0 =8.5×10-8m2 / s (Na⁺ diffusion frequency factor); E a=75000 J / mol (Na⁺ diffusion activation energy); R = 8.314 J / (mol / K) (gas constant); One-step strengthening temperature: T = 410℃ = 683.15K The calculation yielded: ; Iteratively optimize k2, which is to substitute the one-step strengthening time: One-step enhancement time: t=120min=7200s, iterating with different k2 values ​​until the error between the simulated concentration and the measured value (3.03mol / m³) is <1%. When k2 = 0.4, the surface Na⁺ concentration after one simulation step is 3.01 mol / m³, with a relative error of: Error = =0.66%, which meets the accuracy requirement, therefore k2=0.4, cross-diffusion coefficient: .

[0052] Step S140: Perform the first and second chemical strengthening on the cover glass according to the process parameters.

[0053] In step S140 above, referring to Tables 1 and 2, exemplarily, the first and second chemical strengthening operations need to be carried out in a precisely controlled molten salt bath. The first chemical strengthening is preferably carried out under the conditions of molten salt (KNO3:NaNO3 mass ratio of 50%:50%), temperature of 405~415℃, and time of 100~130min, aiming to initially form a compressive stress layer. The second chemical strengthening is carried out under the conditions of molten salt (KNO3:NaNO3 mass ratio of 98%:2%), temperature of 410~420℃, and time of 100~120min, aiming to deepen ion exchange. In specific implementation, the parameters of Examples 1-6 in Table 2 can be referred to. For example, the first step (410℃, 120min) and the second step (420℃, 100min) process used in Example 1 ultimately resulted in the glass achieving an excellent surface compressive stress of 1111MPa and a compressive stress layer depth of 105μm.

[0054] In the above implementation process, by introducing the sodium-potassium ion coupled diffusion equation, the problem of the inability to accurately predict and control the surface potassium ion concentration after secondary strengthening is fundamentally solved. Furthermore, by replacing traditional trial and error with precise calculations based on a physical model, the relative error between the model-predicted concentration and the measured value is reduced, thereby achieving accurate prediction and control of the concentration and significantly improving the yield of cover glass.

[0055] In some alternative implementations, step S120 includes: Step S121: Substitute the process parameters into the potassium ion concentration calculation formula for verification. The potassium ion concentration calculation formula is as follows: ; In step S121 above, W is the potassium ion concentration, C0 is the initial potassium ion concentration on the cover glass surface, k2 is the surface ion exchange coefficient, and ωNa2O ,0 ωNa₂O represents the initial sodium ion concentration of sodium oxide in the cover glass. ,0 This represents the sodium ion concentration of sodium oxide in the cover glass at the end of the first chemical strengthening. Process parameters include: T1, the temperature during the first chemical strengthening; T2, the temperature during the second chemical strengthening; t1, the time of the first chemical strengthening; t2, the time of the second chemical strengthening; S1, the mass percentage of potassium solution in the salt bath used for the first chemical strengthening; and S2, the mass percentage of potassium solution in the salt bath used for the second chemical strengthening.

[0056] Experimental verification was conducted based on the optimal time range to confirm the actual strengthening process parameters. The initial potassium ion concentration of the glass substrate and the potassium ion concentration after the first strengthening step were measured by X-ray fluorescence spectrometry. Combined with the molten salt composition and temperature parameters, the surface potassium ion concentration W after the second ion exchange satisfies the above potassium ion concentration calculation formula.

[0057] Verify the parameters according to Table 2: Example 1:

[0058] Example 2:

[0059] Example 3:

[0060] Experimental verification was conducted based on the optimal time range to confirm the actual strengthening process parameters. Specifically, the first step of chemical strengthening was carried out at a temperature of 405–415℃ for 100–130 min, with a sodium nitrate to potassium nitrate mass ratio of 50%:50 in the molten salt. The second step of chemical strengthening was carried out at a temperature of 410–420℃ for 100–120 min, with a sodium nitrate to potassium nitrate mass ratio of 2%:98% in the molten salt.

[0061] Table 2 mainly illustrates the compressive stress value, compressive stress depth, compressive stress curve, Vickers hardness, and sandpaper drop height obtained by different chemical strengthening methods under the condition of a certain glass composition. Examples 1-6 are verified based on simulation results; Examples 7-9 are the first strengthening temperature and time, which are not within the preferred range of this application; Examples 10-13 are the second strengthening temperature and time, which are not within the preferred range of this application; Tables 14-19 are the first and second chemical strengthening temperatures and times, which are not within the preferred range of this application.

[0062] Chemical composition of the glass sample: SiO2 61.2%, Al2O3 19.2%, Na2O 6.8%, K2O 1.8%, ZrO2 2.0%, MgO 3.8%, Li2O 5.2%.

[0063] In the first step of chemical fortification, the mass ratio of sodium nitrate to potassium nitrate in the molten salt is 50%:50; in the second step, the mass ratio of sodium nitrate to potassium nitrate in the molten salt is 2%:98%.

[0064] Taking Example 1 as an example: C0 = 1.02 mol / m3, which is the value of the original film measured by X-ray fluorescence spectrometry; ωNa2O ,0 =5.48mol / m3, ωNa2O ,1 =3.03 mol / m³, obtained through chemical analysis; k2 = 5.643 × 10−6, obtained through fitting multiple sets of data; process parameters T1 = 410, T2 = 420, t1 = 120, t2 = 100, S1 = 50, S2 = 98. Substituting into the formula, W≈14.98 mol / m³ is calculated. This value falls within the preferred range of 4.2~18.8, and the error between this value and the measured potassium ion concentration of 15.0 mol / m³ in Example 1 in Table 1 is 0.13%, which is highly consistent, thus verifying the rationality of the process parameters. In specific implementation, if the calculated W value exceeds the range, the process parameters need to be adjusted.

[0065] In the aforementioned implementation process, the accuracy of control over cover glass production was further improved by using the potassium ion concentration calculation formula for verification and in conjunction with the sodium ion coupled diffusion equation. This increased the speed of process parameter verification, thereby improving production efficiency and further enhancing control precision.

[0066] In some alternative implementations, 4.2 ≤ W ≤ 18.8.

[0067] The range of W values ​​can be determined based on correlation analysis of measured data from multiple embodiments in Tables 1 and 2: As shown in Table 2, when the calculated or measured W value falls within this range, corresponding to Examples 1-6, the W value is distributed from 13.66 to 16.71. It can be seen that with CS≥1088 MPa, DOL≥105 μm, and drop height≥135 cm, the glass products all exhibit excellent performance.

[0068] In contrast, when the process parameters deviate from the preferred range, resulting in abnormal W values, the product performance significantly declines. For example, in Example 7, the first step of strengthening is insufficient, W≈9.89, CS is only 989MPa, and the drop height is 100cm; in Example 9, the first step of strengthening is excessive, although the W value is not directly listed, the performance deteriorates, CS is 920MPa, and Vickers hardness is only 539.

[0069] Therefore, controlling the W value within the range of 4.2 to 18.8 is crucial to ensuring high strength and durability of the product. This range provides a clear quantitative indicator for process optimization at the chemical concentration level.

[0070] In the above implementation process, by limiting the effective range of the W value, the strength and toughness of the obtained cover glass are further ensured, and problems such as large strength fluctuations and over-strength caused by uncontrolled concentration are solved. This further improves the prediction accuracy and control accuracy of concentration, and ultimately further improves the yield of cover glass.

[0071] In some alternative implementations, the main diffusion coefficient of sodium ions is: ; In the formula, D0 is the frequency factor, and E a R is the diffusion activation energy, R is the gas constant, and T is the chemical strengthening temperature.

[0072] The principal diffusion coefficient of the sodium ion is derived from the Arrhenius equation mentioned earlier, where D0 = 8.5 × 10−8 m2 / s, E a = 75000 J / mol, R= 8.314 J / (mol·K).

[0073] In the above implementation process, the Arrhenius equation was introduced to describe the temperature dependence of the diffusion coefficient, overcoming the deficiency of not incorporating the temperature difference for two-step enhancement. This allows the model to more accurately reflect the effect of temperature changes on the ion diffusion rate, thereby improving the model's applicability and reliability in complex industrial environments. Ultimately, this further improves the accuracy of concentration prediction and control.

[0074] In some alternative implementations, step S120 includes: Step S122: Determine the process parameters based on the stress parameters and the parameter equivalent transformation model.

[0075] In step S122 above, for example, within the process feasible region, such as T1: 400-430℃, t1: 80-150min; T2: 400-430℃, t2: 80-150min, parameter points are selected at relatively large intervals, such as temperature interval of 10℃ and time interval of 20min, to generate a parameter grid covering the entire region.

[0076] Each set of stress parameters (T1, t1, T2, t2) in the mesh is sequentially input into the parameter equivalent transformation model. That is, the ion concentration distribution is first calculated by the sodium ion coupled diffusion equation, and then the stress distribution is obtained by the parameter equivalent transformation model.

[0077] Extract key performance indicators, such as surface compressive stress (CS) and compressive stress layer depth (DOL), and plot the performance spectra of CS and DOL.

[0078] Based on customer requirements, such as CS > 1100 MPa and DOL > 100 μm, the parameter regions that meet the requirements are directly identified on the performance spectrum. Then, the parameter intervals within this region can be further narrowed down for a second, more refined scan, ultimately determining one or two sets of process parameters that meet the performance requirements and have a lower cost.

[0079] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the method for constructing an equivalent transformation model in the control method for secondary chemical strengthening of cover glass provided in this application embodiment. The method for constructing the equivalent transformation model includes: Step S210: Generate multiple test process parameters.

[0080] In step S210 above, the preferred process window and its surrounding region determined from the high-precision sodium-potassium ion coupled diffusion model, for example, the parameters of Examples 1-6, are used to systematically select N groups (e.g., N=30) of representative process parameter combinations (T). 1i ,t 1i ,T 2i ,t 2i ).

[0081] Step S220: Input the test process parameters into the sodium ion coupled diffusion equation to obtain the output test concentration parameters.

[0082] In step S220 above, for each set of process parameters i, a high-precision diffusion model of the high-precision sodium-potassium ion coupled diffusion model is called to perform numerical solution, and the corresponding potassium ion concentration depth distribution curve C is obtained. Ki(x) Then output the set of concentration data: {C K1(x) C K2(x) , ..., C KN(x)}

[0083] Step S230: Conduct a chemical strengthening experiment using the test process parameters, and measure the test stress parameters of the cover glass obtained from the experiment.

[0084] In step S230 above, following the preceding N sets of process parameters, and under essentially consistent glass composition and molten salt conditions, a chemical strengthening experiment was conducted to prepare N sets of glass samples. The stress depth distribution curve σ of each sample cross-section was measured using a surface stress meter. i(x) Then output the set of actual test stress parameters: {σ 1(x) ,σ 2(x) ,...,σ N(x)}

[0085] Step S240: Input the test process parameters and test stress parameters into the initial parameter equivalent transformation model to obtain the parameter equivalent transformation model.

[0086] In step S240 above, the equivalent transformation model for the initial parameters is: ; In the formula, σ (x) Let C be the test process parameters at depth x. k(x) Let be the measured concentration parameter of potassium ions at depth x, and β(x) be the mapping function.

[0087] In the above implementation process, by constructing an equivalent conversion model, the mechanical properties can be predicted based on ion concentration, thus enabling rapid and non-destructive prediction of key mechanical properties of the cover glass after strengthening.

[0088] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating step S230 in the control method for secondary chemical strengthening of cover glass provided in this application embodiment. In some optional embodiments, step S230 includes: Step S231: Under the same set of process parameters, measure multiple sets of initial test stress parameters for multiple sets of cover glass.

[0089] Step S232: Use the average value of multiple sets of initial test stress parameters as the test stress parameters.

[0090] In steps S231 to S232 above, due to slight fluctuations in experimental and model calculations, for each depth point x... j You will get N β i(x_j) For each set of data process parameter i, the value is calculated according to the following formula at discrete depth points. Calculate the initial value of the mapping function: ; Therefore, the mapping function is obtained as β(x) = (1 / N) • Σ [β j(x) ].

[0091] In the above implementation process, by taking the average of multiple measurements, the random error of a single experiment is reduced, the accuracy of the constructed equivalent transformation model is improved, and the reliability of the "concentration-stress" mapping relationship is ensured. This further improves the prediction accuracy and control accuracy of concentration, and ultimately further improves the yield of cover glass.

[0092] Please refer to Figure 4 , Figure 4 This is a flowchart illustrating step S122 in the control method for secondary chemical strengthening of cover glass provided in this application embodiment. In some optional embodiments, step S122 includes: Step S1221: Randomly generate several sets of candidate process parameters.

[0093] In step S1221 above, within the feasible range of process parameters (e.g., T1: [400, 430]℃, t1: [80, 150]min, T2: [400, 430]℃, t2: [80, 150]min), a pseudo-random number generator, such as the Mersenne Twister algorithm, is used to uniformly generate a large number of process parameter combinations, such as 10,000 sets.

[0094] Step S1222: Input several sets of candidate process parameters into the parameter equivalent transformation model to obtain several sets of stress parameters.

[0095] In step S1222 above, parallel computing or vectorized programming techniques can be used to process a large number of candidate parameters in batches. For example, the parameters can be combined and organized into a matrix form and input into the model all at once. For each set of parameters (T1, t1, T2, t2), the prediction process is as follows: 1) Substituting into the sodium ion coupled diffusion equation, the potassium ion concentration distribution C is obtained by numerical solution. K(x) ; 2) Call the calibrated mapping function database β(x), and use the formula σ (x) =β(x)·C K(x Calculate the stress distribution; 3) Extract key performance indicators from the stress distribution curve, such as surface compressive stress (CS) and compressive stress layer depth (DOL).

[0096] Step S1223: Obtain the user's target stress parameters.

[0097] In step S1223 above, the user inputs specific performance indicators, such as CS_target=1150MPa, DOL_target=110μm. A tolerance of ±5MPa is allowed.

[0098] Target range: User-input performance range, for example: CS_target≥1100MPa, DOL_target≥105μm.

[0099] Step S1224: Determine the candidate process parameters corresponding to the stress parameters that satisfy the target stress parameters as process parameters.

[0100] In step S1224 above, all candidate process parameters and their predicted performance are traversed, and all parameter combinations that meet the objectives set in step S1223 above are directly selected and output to the user as a set of feasible solutions.

[0101] Preferably, based on simple screening, for example, among all feasible solutions, the solutions are further sorted according to secondary objectives such as the shortest total reinforcement time or the lowest cost, and the optimal solution or the top-ranked preferred solutions are recommended to the user.

[0102] In the above implementation process, users can directly input their desired mechanical performance indicators, and the optimal process parameters can be automatically and quickly derived, thereby improving the production efficiency of cover glass.

[0103] In some optional implementations, step S1221 includes: Step S12211: Select several candidate process parameters covering the feasible region at specific intervals within the feasible region.

[0104] In step S12211 above, the temperature parameters (T1, T2) can be spaced between 2°C and 5°C; the time parameters (t1, t2) can be spaced between 5 minutes and 10 minutes. For example, within the preferred range (T1: 405-415°C, t1: 100-130 min; T2: 410-420°C, t2: 100-120 min), a grid containing hundreds of process parameter combinations is generated by dividing the area with a temperature interval of 2°C and a time interval of 5 minutes. The grid points need to cover the upper and lower boundaries of the feasible region and be uniformly distributed within it.

[0105] Accordingly, step S1222 includes: Step S12221: Input several candidate process parameters into the parameter equivalent transformation model to obtain several sets of stress parameters, and construct a mapping database with several candidate process parameters and corresponding stress parameters.

[0106] In step S12221 above, the mapping database can be a table, with each row recording a unique combination of process parameters and its predicted performance.

[0107] Accordingly, step S1224 includes: Step S12241: Query the corresponding process parameters in the mapping database based on the target stress parameters.

[0108] In step S12241 above, for example, when the user's target is the point value CS=1150 MPa, a query similar to "SELECT * FROM process_database WHERE CS_pred BETWEEN 1145 AND 1155 AND DOL_pred BETWEEN 109 AND 111" is executed.

[0109] When the user's target is a range CS ≥ 1150 MPa, query all records that meet the condition. Secondary optimization objectives can be introduced, such as sorting by total time to return the most energy-efficient recipe. Execute a query similar to "SELECT * FROM process_database WHERE CS_pred >= 1150 AND DOL_pred >= 110 ORDER BY (t1 + t2) ASC".

[0110] In the above implementation process, by pre-constructing a relatively detailed mapping database, the reverse response speed is improved, thereby further enhancing the production efficiency of cover glass.

[0111] In summary, as shown in Table 2, when the simulated secondary strengthening conditions of Examples 1-6 are met, the strengthened products exhibit excellent chemical strengthening properties and good drop resistance. Specifically, Example 6 has a surface compressive stress of 1201 MPa, a DOL depth of 124 μm, a Vickers hardness of 686 MPa, and a drop height of 145 cm, demonstrating excellent scratch and bending resistance. Examples 7-9 represent the first strengthening temperature and time, which are outside the preferred range of this application. Examples 10-13 represent the second strengthening temperature and time, which are also outside the preferred range of this application. Tables 14-19 show the first and second chemical strengthening temperatures and times, which are outside the preferred range of this application. The product's strengthening effect and properties such as bending resistance, drop resistance, and crack resistance are greatly reduced. Although the surface compressive stress of Example 18 is 1200 MPa and the depth of DOL is 110 μm, its Vickers hardness is only 642 MPa and the drop height is 105 cm. Although high temperature and long-term exposure can increase the surface compressive stress and DOL, the long-term high-temperature ion exchange leads to a decrease in the density of its surface, which ultimately affects its Vickers hardness and drop performance.

[0112] By employing the control method for secondary chemical strengthening of cover glass provided in the embodiments of this application, the relevant properties of the cover glass have been significantly improved. Therefore, it is evident that, given a fixed content of each component in the glass composition, the control method for secondary chemical strengthening of cover glass provided in the embodiments of this application will produce unexpected technical effects in terms of surface compressive stress value, stress layer depth, glass integrity rate after drop, and fracture resistance of the glass product.

[0113] Please refer to Figure 5 , Figure 5 This is a functional block diagram of the control device for secondary chemical strengthening of cover glass provided in an embodiment of this application. Based on the same concept, this application provides a control device 500 for secondary chemical strengthening of cover glass, comprising: Module 510 is used to determine the process parameters for secondary enhancement based on the sodium ion coupled diffusion equation; wherein, the sodium ion coupled diffusion equation is: ; In the formula, This is the partial derivative with respect to the sodium ion concentration. The partial derivative is the diffusion depth. D is the partial derivative with diffusion time. NN (T) is the main diffusion coefficient of sodium ions; k1 is the activity correction coefficient obtained by experimental fitting.

[0114] The strengthening module 520 is used to perform the first and second chemical strengthening of the cover glass according to the process parameters.

[0115] As an optional implementation, in the process of determining the process parameters for secondary enhancement based on the sodium ion coupling diffusion equation, the determining module 510 is specifically used to: substitute the process parameters into the potassium ion concentration calculation formula for verification; wherein, the potassium ion concentration calculation formula is: ; In the formula, W is the potassium ion concentration, C0 is the initial potassium ion concentration on the cover glass surface, k2 is the surface ion exchange coefficient, and ωNa2O ,0 ωNa₂O represents the initial sodium ion concentration of sodium oxide in the cover glass. ,0 The sodium ion concentration of sodium oxide in the cover glass at the end of the first chemical strengthening; the process parameters include: T1, the temperature during the first chemical strengthening; T2, the temperature during the second chemical strengthening; t1, the time of the first chemical strengthening; t2, the time of the second chemical strengthening; S1, the mass percentage of potassium solution in the salt bath used in the first chemical strengthening; and S2, the mass percentage of potassium solution in the salt bath used in the second chemical strengthening.

[0116] As an alternative implementation, 4.2 ≤ W ≤ 18.8.

[0117] As an optional implementation, the main diffusion coefficient of sodium ions is: ; In the formula, D0 is the frequency factor, and E a R is the diffusion activation energy, R is the gas constant, and T is the chemical strengthening temperature.

[0118] As an optional implementation, in the process of determining the secondary strengthening process parameters according to the sodium ion coupled diffusion equation, the determining module 510 is specifically used for: determining the process parameters based on the stress parameters and the parameter equivalent conversion model; wherein, the method for constructing the equivalent conversion model includes: generating multiple test process parameters; inputting the test process parameters into the sodium ion coupled diffusion equation to obtain the output test concentration parameters; conducting a chemical strengthening experiment using the test process parameters and measuring the test stress parameters of the cover glass obtained from the experiment; and inputting the test process parameters and the test stress parameters into the initial parameter equivalent conversion model to obtain the parameter equivalent conversion model; wherein, the initial parameter equivalent conversion model is: ; In the formula, σ (x) Let C be the test process parameters at depth x. k(x) Let be the measured concentration parameter of potassium ions at depth x, and β(x) be the mapping function.

[0119] As an optional implementation, during the chemical strengthening experiment with test process parameters and the measurement of the test stress parameters of the cover glass obtained from the experiment, the determination module 510 is more specifically used to: measure multiple initial test stress parameters of multiple cover glasses under the same set of process parameters in the chemical strengthening experiment; and use the average value of the multiple initial test stress parameters as the test stress parameter.

[0120] As an optional implementation, in the process of determining process parameters based on stress parameters and parameter equivalent transformation models, the determining module 510 is more specifically used to: randomly generate several sets of process parameters; input several sets of candidate process parameters into the parameter equivalent transformation model respectively to obtain several sets of stress parameters; obtain the user's target stress parameters; and determine the candidate process parameters corresponding to the stress parameters that satisfy the target stress parameters as process parameters.

[0121] As an optional implementation, the determination module 510 is more specifically used to: select several process parameters covering the feasible region at specific intervals within the feasible region after randomly generating several sets of process parameters.

[0122] Accordingly, in the process of inputting several sets of candidate process parameters into the parameter equivalent transformation model to obtain several sets of stress parameters, the determination module 510 is more specifically used to: input several process parameters into the parameter equivalent transformation model to obtain several sets of stress parameters, and construct a mapping database with several process parameters and corresponding stress parameters.

[0123] Accordingly, in the process of determining the candidate process parameters corresponding to the stress parameters that satisfy the target stress parameters as process parameters, the determining module 510 is more specifically used to: query the corresponding process parameters in the mapping database according to the target stress parameters.

[0124] It should be understood that this device corresponds to the above-described control method embodiment for secondary chemical strengthening of cover glass, and is capable of performing the various steps involved in the above method embodiment. The specific functions of this device can be found in the description above, and detailed descriptions are omitted here to avoid repetition. The device includes at least one software functional module that can be stored in memory or embedded in the device's operating system (OS) in the form of software or firmware.

[0125] Based on the same concept, embodiments of this application provide a computer program product. This computer program product includes a computer program or instructions. When the computer program or instructions are executed by a processor, they can implement the methods described in any embodiment of this application.

[0126] The computer program product may be embodied on one or more computer-readable media. The computer-readable media may be, but is not limited to, volatile memory (such as random access memory RAM), non-volatile memory (such as read-only memory ROM, programmable read-only memory PROM, erasable programmable read-only memory EPROM, electrically erasable programmable read-only memory EEPROM, flash memory), magnetic storage devices (such as hard disk drives, magnetic tapes), optical storage devices (such as optical disc CD-ROM, digital versatile optical disc DVD), or any suitable combination of the above.

[0127] Specifically, the computer program or instructions may be stored in the computer-readable medium. When the computer-readable medium containing the computer program or instructions is loaded into an electronic device with processing capabilities (such as the aforementioned...), Figure 1 When the electronic device 100 shown is used (or any computing device including a processor and memory), the processor of the electronic device is capable of reading and executing the computer program or instructions. The processor's execution of the instructions causes the electronic device to perform the method steps described in the embodiments of this application.

[0128] Those skilled in the art will understand that the computer program product can exist in various forms, including but not limited to: Standalone packaged software: Software packages that are stored on physical media (such as optical discs, USB flash drives, and memory cards) and sold or distributed independently.

[0129] Pre-installed software: Firmware or part of the system / application software that has been pre-programmed or installed in the device's memory (such as ROM, Flash) at the factory.

[0130] Network distribution: Software installation packages, update packages, or applications downloaded or streamed from servers, app stores (such as Apple App Store, Google Play), software repositories, etc. via the Internet, mobile networks, etc.

[0131] Embedded software: As part of the control system of specialized equipment (such as medical imaging equipment, industrial testing equipment), it is stored in the internal memory of the device.

[0132] Cloud Service / SaaS: Deployed in a cloud computing environment, users remotely access and invoke the program's functions through client software, web browsers, or application programming interfaces (APIs) (i.e., the "Software as a Service" model). In this case, the program's execution occurs on a cloud server, but the instructions themselves and the core logic for implementing their functions still fall under the category of the computer program product.

[0133] License key / activation code: A digital key separate from the main program but used to unlock or activate the program to enable the functions of the method, and is considered part of or an accessory to the product.

[0134] Regardless of the specific form in which the computer program product is provided or distributed, as long as the computer program or instructions contained therein can implement the methods described in the embodiments of this application when executed by a processor, they fall within the protection scope of the computer program product described in this embodiment.

[0135] The computer program product in this embodiment can be used to cause an electronic device with processing capabilities to perform the steps in the various methods provided in the embodiments of this application.

[0136] The controller can be a microprocessor (MCU), a digital signal processor (DSP), or a programmable logic device (FPGA).

[0137] It should be understood that the disclosed apparatus and methods can also be implemented in other ways, given the several embodiments provided in this application. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0138] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0139] The above description is only an optional implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application.

Claims

1. A method of controlling secondary chemical strengthening of a cover glass, characterized by, The method comprises the following steps: The process parameters for the secondary strengthening are determined according to a sodium ion coupling diffusion equation; wherein the sodium ion coupling diffusion equation is: ； wherein is the partial derivative of the sodium ion concentration, is the partial derivative of the diffusion depth, is the partial derivative of the diffusion time, T is the chemical strengthening temperature, is the main diffusion coefficient of the sodium ions; k1 is an activity correction coefficient obtained by experimental fitting; The cover plate glass is subjected to the first and second chemical strengthening according to the process parameters.

2. The method of claim 1, wherein, The process parameters for the secondary strengthening are determined according to a sodium ion coupling diffusion equation; wherein the sodium ion coupling diffusion equation is: The process parameters are substituted into a potassium ion concentration calculation formula for verification; wherein the potassium ion concentration calculation formula is: ； In the formula, W is the potassium ion concentration, C0 is the initial potassium ion concentration of the surface of the cover glass, k2 is the surface ion exchange coefficient, ωNa2O ,0 is the initial sodium ion concentration of sodium oxide in the cover glass, ωNa2O ,0 is the sodium ion concentration of sodium oxide in the cover glass at the end of the first chemical strengthening; and the process parameters include: T1, the temperature during the first chemical strengthening; T2, the temperature during the second chemical strengthening; t1, the time of the first chemical strengthening; t2, the time of the second chemical strengthening; S1, the mass ratio of the potassium solution in the salt bath used in the first chemical strengthening; and S2, the mass ratio of the potassium solution in the salt bath used in the second chemical strengthening.

3. The method of claim 2, wherein, wherein, 4.2≤W≤18.8。 4. The method of claim 1, wherein, wherein, The main diffusion coefficient of the sodium ion is: ； where D0is a frequency factor, E a is the diffusion activation energy, R is the gas constant, and T is the chemical strengthening temperature.

5. The method of claim 1, wherein, The process parameters for the secondary strengthening are determined according to a sodium ion coupling diffusion equation; wherein the sodium ion coupling diffusion equation is: The process parameters are determined according to a stress parameter and a parameter equivalent conversion model; wherein the method for constructing the equivalent conversion model comprises: A plurality of test process parameters are generated; The test process parameters are input into the sodium ion coupling diffusion equation to obtain output test concentration parameters; Chemical strengthening experiments are performed using the test process parameters, and test stress parameters of cover plate glasses obtained in the experiments are measured; and The test process parameters and the test stress parameters are input into an initial parameter equivalent conversion model to obtain the parameter equivalent conversion model; wherein the initial parameter equivalent conversion model is: ； where σ (x) is the test process parameter at depth x, C k(x) is the test concentration parameter of potassium ions at depth x, and β(x) is a mapping function.

6. The method of claim 5, wherein, The chemical strengthening experiments are performed using the test process parameters, and the test stress parameters of the cover plate glasses obtained in the experiments are measured; and A plurality of initial test stress parameters of a plurality of cover plate glasses are measured under the chemical strengthening experiments of the same set of process parameters; and An average value of the plurality of initial test stress parameters is taken as the test stress parameter.

7. The method of claim 5, wherein, The process parameters are determined according to a stress parameter and a parameter equivalent conversion model; wherein the method for constructing the equivalent conversion model comprises: A plurality of candidate process parameters are randomly generated; The plurality of candidate process parameters are input into the parameter equivalent conversion model to obtain a plurality of stress parameters; A target stress parameter of a user is obtained; and The candidate process parameter corresponding to the stress parameter satisfying the target stress parameter is determined as the process parameter.

8. The method of claim 7, wherein, The plurality of candidate process parameters are randomly generated by selecting a plurality of candidate process parameters covering the feasible region at a specific interval in the feasible region; The plurality of candidate process parameters are input into the parameter equivalent conversion model to obtain a plurality of stress parameters, and a mapping database is constructed using the plurality of candidate process parameters and the corresponding plurality of stress parameters; The candidate process parameter corresponding to the stress parameter satisfying the target stress parameter is determined as the process parameter. The corresponding process parameter is queried in the mapping database according to the target stress parameter.

9. A control device for secondary chemical strengthening of a cover glass, characterized by, The method comprises the following steps: The process parameters for the secondary strengthening are determined according to a sodium ion coupling diffusion equation; wherein the sodium ion coupling diffusion equation is: ； wherein is the partial derivative of the sodium ion concentration, is the partial derivative of the diffusion depth, is the partial derivative of the diffusion time, is the main diffusion coefficient of the sodium ions; k1is an activity correction factor obtained by experimental fitting; The cover plate glass is subjected to the first and second chemical strengthening according to the process parameters.

10. A program product, characterized by The computer program / instructions are executed by a processor to implement the method according to any one of claims 1 to 8.

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