Perovskite film coating method and device, electronic equipment, computer storable medium and computer program product

Abstract

The invention relates to coating of a perovskite thin film, in particular to a coating method and device of the perovskite thin film, electronic equipment, a computer storable medium and a computer program product. The method comprises the following steps: constructing a coating model based on a mechanical coupling relationship between a target substrate and a coating device; based on the coating model, obtaining a target coating thickness and a target injection rate and a coating rate corresponding to the target coating thickness; constructing a fluid flow model of the coating fluid medium between the coating die head and the substrate and on the surface of the substrate; and calculating the fluid model based on the target coating thickness, the target injection amount corresponding to the target coating thickness, the coating rate pair and the fluid model, and determining a target coating parameter. According to the perovskite coating method using the coating simulation model, coating parameters are optimized through simulation testing, the quality and research and development efficiency of the perovskite thin film are improved, and the perovskite coating method has wide application prospects.

Description

Technical Field

[0001] The present invention relates to the coating of perovskite thin films, and particularly to a method, device, electronic device, computer-readable storage medium and computer program product for coating perovskite thin films. Background Art

[0002] There is still a gap between large-area perovskite solar cell modules and the theoretical efficiency limit. The key technical difficulty lies in the lack of a deposition method for large-area perovskite thin films with high quality and high uniformity. As a non-contact liquid film forming technology, slot coating technology has advantages such as precise controllability and high reproducibility. However, there are many adjustable parameters and complex combined regulation during the coating process, which affect the characteristics of the perovskite liquid film. Currently, there is a lack of simulation software for the perovskite coating process, resulting in high R & D and testing costs and low efficiency. Summary of the Invention

[0003] To solve the above problems, the present invention provides a method, device, electronic device, computer-readable storage medium and computer program product for coating perovskite thin films. The present invention provides the following technical solutions:

[0004] A method for coating a perovskite thin film, the method includes,

[0005] Constructing a coating model based on the mechanical coupling relationship between a target substrate and a coating device;

[0006] Based on the coating model, obtaining a target coating thickness and a target injection amount and coating rate corresponding to the target coating thickness;

[0007] Constructing a fluid flow model of a coating fluid medium between a coating die head and a substrate and on the substrate surface;

[0008] Calculating based on the target coating thickness, the target injection amount corresponding to the target coating thickness, the coating rate pair and the fluid model to determine the target coating parameters.

[0009] Further, the mechanical coupling relationship between the target substrate and the coating device includes:

[0010] Determining an initial injection amount of a coating liquid based on the geometric size of the target substrate and the set coating thickness;

[0011] Based on the geometric size of the target substrate, the coating gap difference between the coating head and the target substrate, the material of the injection liquid pipeline and the internal diameter of the pipeline, and the internal diameter of the exhaust pipe, determining the calibration amount, recovery amount of the coating liquid during the coating process, and the liquid splash amount caused by exhaust;

[0012] Constructing a coating model based on the initial injection amount of the coating liquid, the calibration amount, recovery amount of the coating liquid during the coating process, and the liquid splash amount caused by exhaust.

[0013] Further, the formula of the coating model includes:

[0014]

[0015] In the formula, δ represents the set coating thickness, V z2 represents the set injection volume, k 2 represents the length coefficient between the start of liquid discharge from the coating head and the contact of the liquid with the substrate; h 2 represents the coating gap difference between the coating head and the target substrate; W represents the width of the target substrate; L represents the length of the target substrate; k 3 represents the influence coefficient of the injection liquid pipeline in the coating device on the coating liquid; v 3 represents the withdrawal speed; t 3 represents the withdrawal time; k 4 represents the gas carrier liquid coefficient; D 4 represents the inner diameter of the exhaust pipe; v 4 represents the exhaust speed; t 4 represents the exhaust time; k 1 represents the empirical coefficient, and the variation range is 0.43 - 2.73.

[0016] Further, based on the coating model, obtaining the target coating thickness and the corresponding target injection volume and coating rate includes:

[0017] Using the relaxation method to perform iterative calculations on the coating model. During the iterative calculation process, the parameters of the coating gap difference, withdrawal speed, withdrawal time, gas carrier liquid coefficient, inner diameter of the exhaust pipe, exhaust speed, and exhaust time between the coating head and the target substrate are adjusted multiple times until the actual coating thickness obtained by the calculation, and the absolute value of the difference between the actual coating thickness and the set coating thickness is less than the first threshold;

[0018] The actual coating thickness when the absolute value of the difference between the actual coating thickness and the set coating thickness is less than the first threshold is the target coating thickness;

[0019] According to the target coating thickness, obtain the target injection volume and coating rate corresponding to the target coating thickness.

[0020] Further, the formula of the fluid flow model of the coating fluid medium between the coating die head and the substrate and on the substrate surface is:

[0021]

[0022] In the formula, is the time-averaged velocity component in the j direction, v is the kinematic viscosity, is the average pressure; represents the time-averaged velocity component in the i direction; xi , x j respectively represent spatial coordinates, where i ≠ j, i represents the coating liquid thickness direction along the length direction, width direction of the substrate or perpendicular to the substrate; j represents the coating liquid thickness direction along the length direction, width direction of the substrate or perpendicular to the substrate; represents the time-averaged pulsating velocity component in the j direction; represents the time-averaged pulsating velocity component in the i direction; is the Reynolds stress term; v t is the turbulent viscosity, k is the turbulent kinetic energy; δ ij is the Kronecker function, ρ represents the coating liquid density, ω represents the specific dissipation rate; C 3 represents the empirical coefficient.

[0023] Furthermore, based on the target coating thickness, the target injection amount corresponding to the target coating thickness, the coating rate pair and the fluid model, the target coating parameters are determined, including:

[0024] Taking the target coating thickness, the target injection amount corresponding to the target coating thickness, and the coating rate as boundary conditions, discretize the liquid film thickness, the length of the target substrate, the width of the target substrate, and the coating gap difference respectively to obtain the corresponding physical geometry lattice points;

[0025] In each layer in the height direction of the physical geometry lattice points, use the fluid model for iterative calculation until the difference between the target results of two consecutive iterations is less than the second threshold or the maximum predetermined number of iterations is reached, and the iteration terminates;

[0026] When the iteration terminates, the corresponding coating parameters are the target coating parameters.

[0027] Furthermore, the target coating parameters include the control gap height between the coating die and the substrate, the running speed in the width direction of the coating substrate, the running speed in the length direction of the coating substrate, the coating liquid concentration and the feeding speed.

[0028] The present invention also provides a coating device for perovskite thin films, and the device includes,

[0029] A first construction unit for constructing a coating model based on the mechanical coupling relationship between the target substrate and the coating device;

[0030] A first determination unit for obtaining the target coating thickness, the target injection amount corresponding to the target coating thickness, and the coating rate based on the coating model;

[0031] A second construction unit for constructing a fluid flow model of the coating fluid medium between the coating die and the substrate and on the substrate surface;

[0032] A second determination unit, configured to calculate based on a target coating thickness, a target injection amount corresponding to the target coating thickness, a coating rate pair, and a fluid model, and determine target coating parameters.

[0033] The present invention also provides an electronic device, which includes at least one processor and at least one memory, and the memory is in data connection with the processor. Among them,

[0034] the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above method.

[0035] The present invention also provides a computer-readable storage medium, characterized in that computer instructions are stored on the storage medium, and when the computer instructions are executed by a processor, the steps in the above method are specifically executed.

[0036] The present invention also provides a computer program product, including computer instructions, characterized in that when the computer instructions are executed by a processor, the steps in the above method are specifically executed.

[0037] Technical effects and advantages of the present invention:

[0038] By using simulation software to establish a coating device and a fluid model, coupling to generate a system of nonlinear equations, and iteratively solving to obtain optimal coating parameters, a large number of repeated on-site tests are avoided, the R & D efficiency is improved, and a high-quality perovskite liquid film is obtained. The perovskite coating method using a coating simulation model provided by the present invention optimizes coating parameters through simulation tests, improves the quality of perovskite thin films and the R & D efficiency, and has broad application prospects.

[0039] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures pointed out in the specification and the drawings. Description of the Drawings

[0040] Figure 1 is a flowchart of a method for coating a perovskite thin film provided by an embodiment of the present application;

[0041] Figure 2 is a schematic diagram of the coating process of a perovskite thin film provided by an embodiment of the present application;

[0042] Figure 3 is a diagram of a coating device for a perovskite thin film provided by an embodiment of the present application;

[0043] Figure 4 is a block diagram of an electronic device according to an embodiment of the present application. Detailed implementation manners

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0045] To solve the deficiencies of the prior art, the present invention discloses a method for coating a perovskite thin film, as Figure 1 shown, the method includes

[0046] Step 1: Construct a coating model based on the mechanical coupling relationship between the target substrate and the coating device;

[0047] Step 2: Based on the coating model, obtain the target coating thickness and the corresponding target injection volume and coating rate;

[0048] Step 3: Construct a fluid flow model of the coating fluid medium between the coating die head and the substrate and on the substrate surface;

[0049] Step 4: Calculate based on the target coating thickness, the corresponding target injection volume, coating rate pair and the fluid model to determine the target coating parameters.

[0050] In some specific embodiments of the present invention, in combination with Figure 2 , for Step 1, the mechanical coupling relationship between the target substrate and the coating device includes:

[0051] Step 101: Determine the coating area according to the geometric dimensions (L×W) of the target substrate; determine the initial solution demand V1 according to the coating area and the set coating thickness δ, so as to initialize the liquid injection volume Vz1, where Vz1 = k1×L×W×δ, and k1 is an experimental experience coefficient mainly affected by the viscosity of the liquid, and the variation range is 0.43 - 2.73.

[0052] Based on the geometric dimensions of the target substrate, the coating gap difference h2 between the coating head and the target substrate, the material of the injection liquid pipeline and the internal diameter of the pipeline, and the internal diameter of the exhaust pipe, determine the calibration amount, recovery amount of the coating liquid during the coating process, and the liquid splash amount caused by exhaust; specifically, the following is executed:

[0053] In the model, due to the coating gap difference h 2 between the coating head and the target substrate and the solution outflows V 2 and V 3 respectively caused by the initial calibration and tail recovery during the coating process. V2 = k 2 × h 2 × W, k 2 is the length coefficient from when the coating head starts to discharge liquid to when the liquid contacts the substrate, k 2 The variation range is 0.1 - 1, where 1 indicates that the liquid viscosity is very high and it flows out slowly. V 3 = k 3 × v 3 × t 3 , where v 3 is the set retraction speed, t 3 is the set retraction time, k 3 is the influence coefficient applicable to different solutions, with a variation range of 0.5 - 1.5, affected by the material of the injection liquid pipeline and the internal diameter D of the pipeline 3 influence, 0.5 indicates that the liquid viscosity is relatively high, and after retraction, part of the liquid does not fully enter the injection cavity, and part of the gas enters the injection cavity. The volume of liquid splashing caused by exhaust is V 4 = k 4 × π × (D 4 / 2) 2 × v 4 × t 4 , where, D 4 is the internal diameter of the exhaust pipe, v 4 is the exhaust speed, t 4 is the exhaust time, k 4 is the gas - liquid carrier coefficient, mainly affected by physical property parameters such as the relative humidity of the ambient air and the saturated vapor pressure of the liquid, with a variation range of 0 - 1, where 0 indicates that the discharged gas is completely a gas working medium and does not contain liquid.

[0054] Based on the initial injection volume of the coating liquid, the calibration amount, the recovery amount of the coating liquid during the coating process, and the liquid splashing amount caused by exhaust, a coating model is constructed. Among them,

[0055] Set the injection volume V z2 :

[0056] V z2 = k 1 × L × W × δ + k 2 × h 2 × W + k 3 × v 3 × t 3 + k 4 × π × (D 4 / 2) 2 × v 4 × t 4

[0057] Therefore, the formula representation of the coating model is:

[0058]

[0059] In the formula, δ represents the set coating thickness, V z2 represents the set injection volume, k 2 represents the length coefficient between the start of liquid discharge from the coating head and the contact of the liquid with the substrate; h 2 represents the coating gap difference between the coating head and the target substrate; W represents the width of the target substrate; L represents the length of the target substrate; k 3 represents the influence coefficient of the injection liquid pipeline in the coating device on the coating liquid; v 3 represents the back-drawing speed; t 3 represents the back-drawing time; k 4 represents the gas carrier liquid coefficient; D 4 represents the inner diameter of the exhaust pipe; v 4 represents the exhaust speed; t 4 represents the exhaust time; k 1 represents an empirical coefficient, and the variation range is 0.43 to 2.73. The coefficient k 1 ~k 4 varies and affects the setting of the operating parameters when the target film thickness is desired to be achieved.

[0060] In a specific embodiment of the present invention, in combination with Figure 2 , for step 2, based on the coating model, obtaining the target coating thickness and the target injection volume and coating rate corresponding to the target coating thickness includes:

[0061] Step 201: Use the relaxation method to perform iterative calculations on the coating model. During the iterative calculation process, adjust the parameters of the coating gap difference, back-drawing speed, back-drawing time, gas carrier liquid coefficient, inner diameter of the exhaust pipe, exhaust speed, and exhaust time between the coating head and the target substrate multiple times until the calculated liquid film thickness δ 1 (actual coating thickness), the calculated liquid film thickness δ 1 (actual coating thickness) and the absolute value of the difference between the control target thickness δ 2 (which is equivalent to the set coating thickness δ in this embodiment) is less than the first threshold; preferably, during the iterative solution of the coating model, use the relaxation method for iterative calculation and adjust the relaxation factor (the relaxation factor variation range is 0.01 to 1). If the calculation collapses (that is, numerical instability or no solution occurs during the calculation process), gradually reduce the relaxation factor (1, 0.9, 0.8... 0.1, 0.09, 0.08... 0.01) until the solvable function value is output, that is, the calculation converges and a solution that conforms to physical meaning is obtained; determine whether the absolute value of the difference between the solvable function value and the control target value is less than the preset difference. If it is less than, stop adjusting the value range and continue to solve the iteration until the optimal solution is output. Preferably, the preset difference is 1%.

[0062] Step 202: When the absolute value of the difference between the actual coating thickness and the set coating thickness is less than the first threshold, the actual coating thickness is the target coating thickness;

[0063] Step 203: According to the target coating thickness, obtain the target injection volume and coating rate corresponding to the target coating thickness.

[0064] In a specific embodiment of the present invention, constructing the fluid flow model of the coating fluid medium between the coating die head and the substrate and on the substrate surface includes the following steps:

[0065] According to the coating requirements and process conditions, select the coating model type, fluid model type, and control objectives applicable to different solution conditions (the control objectives include but are not limited to the perovskite layer film thickness (i.e., the target coating thickness), thickness uniformity, fluid flow velocity, etc.), couple to generate the corresponding non-linear equations, establish the fluid flow model of the coating fluid medium between the coating die head and the substrate and on the substrate surface, and combine Figure 2 , and the specific implementation steps are as follows:

[0066] According to the basic form of the N-S equation of an incompressible fluid, it is divided into two parts: the continuity equation and the momentum equation:

[0067] The original momentum equation of the non-linear equations:

[0068]

[0069] Among them, u is the fluid (coating liquid) velocity, p is the fluid (coating liquid) pressure, ρ is the fluid density, v is the kinematic viscosity; F is the external force, and t represents the preset coating time.

[0070] Mass equation:

[0071]

[0072] In the formula, ρ represents the fluid density; u represents the fluid velocity; t represents the preset coating time; represents the divergence operator, for an incompressible fluid:

[0073]

[0074] Simplify the N-S equation and approximately solve to capture the motion of all scales. The basis of the turbulence model is the Reynolds-averaged N-S equation, which simplifies the original N-S equation by time-averaging the instantaneous variables:

[0075]

[0076] In the formula, is the time-averaged velocity component in the j direction; v is the kinematic viscosity; is the mean pressure; represents the time-averaged velocity component in the i direction; x i and x j represent the spatial coordinates respectively, where i ≠ j, i represents the coating liquid along the length direction of the substrate, the width direction of the substrate or the coating liquid thickness direction perpendicular to the substrate; j represents the coating liquid along the length direction of the substrate, the width direction of the substrate or the coating liquid thickness direction perpendicular to the substrate; represents the time-averaged fluctuating velocity component in the j direction; represents the time-averaged fluctuating velocity component in the i direction; is the Reynolds stress term; v t is the turbulent viscosity, k is the turbulent kinetic energy, v t and k are obtained by calculating through the turbulence model; δ ij is the Kronecker function, ρ represents the fluid density, represents the standard partial derivative symbol.

[0077]

[0078] is the Reynolds stress term. A turbulence model is introduced to approximately represent the Reynolds stress. According to the Boussinesq eddy viscosity hypothesis, this Reynolds stress term is related to the mean velocity gradient:

[0079]

[0080] In the formula, ν t is the turbulent viscosity, k is the turbulent kinetic energy, δ ij is the Kronecker function, where ν t and k are obtained by calculating through the turbulence model. Here, a turbulence model is introduced, such as the k-ε turbulence model, the k-ε RNG turbulence model, the k-ω turbulence model, the SST k-ω turbulence model, to solve for the turbulent viscosity ν t and k.

[0081] Among them,

[0082] In the formula, C 3 is an experimental coefficient, usually calibrated by experiments. In different turbulence models, the value of this experimental coefficient is different.

[0083] In a specific embodiment of the present invention, the k-ε turbulence model is adopted to solve for the turbulent viscosity v t when

[0084] Turbulent kinetic energy k equation:

[0085]

[0086] In the formula, ρ represents the fluid density; k represents the turbulent kinetic energy, t represents the preset coating time, represents the time-averaged fluid velocity, P k represents the generation term, and ε represents the dissipation rate.

[0087] Dissipation rate ε equation:

[0088]

[0089] In the formula, C 0 , C 1 , C 2 , σ k , σ ε are empirical constants, usually calibrated by experiments.

[0090] Define v through the k-ε turbulence model equation t ,

[0091]

[0092] Among them, At this time, in the k-ε turbulence model:

[0093] At this time, in the standard k-ε model, C 0 , C 1 , C 2 , C 3 , σ k , σ ε are 1.0, 1.44, 1.92, 0.09, 1.0, 1.3 respectively.

[0094] In a specific embodiment of the present invention, the k-ε RNG turbulence model is adopted to solve the turbulent viscosity v t When

[0095] A correction function f is introduced into the k-ε turbulent viscosity equation, that is:

[0096] C 3 = C 3 'f

[0097]

[0098] In the formula, C 3 ' is an empirical coefficient, f is a correction function, and at the same time, a term r is introduced into the dissipation rate equation, and r is an additional term to correct the dissipation behavior of separated flow and swirling flow.

[0099] In a specific embodiment of the present invention, the k-ω turbulence model is adopted to solve the turbulent viscosity v t When

[0100] First, ω in the k-ω turbulence model is the specific dissipation rate:

[0101]

[0102] Turbulent kinetic energy k equation:

[0103]

[0104] Specific dissipation rate ω equation:

[0105]

[0106] Compared with the k-ε turbulence model, the k-ω turbulence model has a wider application range. At this time, C in the turbulent viscosity equation 0 , C 1 , C 2 , C 3 , σ k , σ ε are 0.09, 5 / 9, 0.075, 1.0, 2.0, 2.0 respectively.

[0107] In a specific embodiment of the present invention, the SST k-ω turbulence model is adopted to solve the turbulent viscosity ν t When

[0108] It can be understood as a combined application of the k-ω turbulence model and the k-ε turbulence model. Different turbulent models are used for calculation in different regions, which is more in line with the actual flow situation.

[0109] After defining the turbulent viscosity, it can be known from the simplification of the Reynolds stress term that the N-S equation is closed. In this application, the fluid flow model of the coating fluid medium between the coating die head and the substrate and on the substrate surface refers to the N-S equation and some simplified equations that need to be solved. In a specific embodiment of the present invention, the fluid flow model includes the N-S equation after Reynolds averaging, the equation after viscosity assumption, the flow energy equation, and the dissipation rate equation.

[0110] Combined with the boundary conditions (setting the injection volume V z2 , preset coating time t) and the physical model (setting the coating thickness δ, substrate length L, substrate width W, coating gap difference h 2 ), the velocity field of the incompressible fluid at different times can be calculated, and then the target coating film thickness can be deduced.

[0111] The momentum equation is the original momentum equation in the Navier - Stokes equations and cannot be solved directly. The simplified equation is the Reynolds - averaged Navier - Stokes equations, in which the Reynolds stress term is introduced. This term is combined with the turbulent viscosity and turbulent kinetic energy through the Reynolds - averaged Navier - Stokes equations, and then the solution is achieved with the help of a turbulence model. After solving, the film thickness can be obtained, and then the coating parameters can be obtained by relating the film thickness to other parameters through a coating model.

[0112] In a specific embodiment of the present invention, the formula for the fluid flow model of the coating fluid medium between the coating die and the substrate and on the substrate surface is:

[0113]

[0114] where, v t and k are obtained by selecting a turbulence model. Preferably, the turbulence model includes the k - ε turbulence model, the k - ε RNG turbulence model, the k - ω turbulence model, and the SST k - ω turbulence model.

[0115] ν t and k can also be obtained by calculating with the Bernoulli equation, which is used to describe the relationship between fluid pressure and velocity.

[0116] In a specific embodiment of the present invention, based on the target coating thickness, the target injection amount corresponding to the target coating thickness, the coating rate pair, and the fluid model, the target coating parameters are determined, including:

[0117] Taking the target coating thickness, the target injection amount corresponding to the target coating thickness, and the coating rate as boundary conditions, the liquid film thickness, the length of the target substrate, the width of the target substrate, and the coating gap difference are discretized respectively to obtain the corresponding physical geometry lattice points;

[0118] In each layer in the height direction of the physical geometry lattice points, the fluid model is used for iterative calculation until the difference between the target results of two consecutive iterations is less than the second threshold or the maximum predetermined number of iterations is reached, and the iteration terminates; during the solution process of the fluid flow model, the reference physical geometry (set coating thickness (or liquid film thickness) δ, substrate length L, substrate width W, coating gap difference h 2 ) is discretized, and the existing physical geometry is expressed by a lattice. The number of lattice points can be 10 - 1000000 (the number can be adjusted according to the computing power of the computer). According to the lattice parameters of the physical geometry, in each layer in the height direction, a non - linear equation set and a turbulence model are used, and the upwind scheme is adopted for iteration. When the difference between the target results of two consecutive iterations is less than the preset threshold (the deviation percentage of the iteration target result from the previous result ≤ 1‰) or the maximum number of iterations is reached, the iteration terminates. The numerical solutions in the vertical direction of each layer are superimposed to obtain the lattice thickness of the surface.

[0119] When the iteration terminates, the corresponding coating parameters are the target coating parameters.

[0120] In a specific embodiment of the present invention, the target coating parameters include the controlled gap height between the coating die and the substrate, the running speed in the width direction of the coating substrate, the running speed in the length direction of the coating substrate, the concentration of the coating solution, and the feeding speed. Among them, the running speed is calculated after iterative calculation of a non-linear equation system after discretization and meets the uniformity condition. The concentration of the solution is used as a pre-parameter of the coating model, that is, for a given solution, various corresponding parameters are obtained through a series of subsequent calculations. The feeding speed determines the coating time through the final iteration, and at the same time, the injection volume is determined in the first step, and the actual injection volume / time is obtained.

[0121] The present invention also provides a coating device for perovskite thin films, as Figure 3 shown, the device includes

[0122] A first construction unit for constructing a coating model based on the mechanical coupling relationship between the target substrate and the coating device;

[0123] A first determination unit for obtaining the target coating thickness and the corresponding target injection volume and coating rate based on the coating model;

[0124] A second construction unit for constructing a fluid flow model of the coating fluid medium between the coating die and the substrate and on the substrate surface;

[0125] A second determination unit for calculating based on the target coating thickness, the corresponding target injection volume, the coating rate pair, and the fluid model to determine the target coating parameters.

[0126] Regarding the device in the above embodiments, the specific manners in which each unit performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0127] Based on the above-disclosed content, correspondingly, the present invention also provides an electronic device. As Figure 4 shown, the electronic device of the embodiment of the present disclosure includes at least one processor and at least one memory that are electrically connected. The memory is electrically connected to the processor. Among them, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method steps executed by the above controller.

[0128] An embodiment of the present invention also provides a storage medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the steps in the method in the above embodiment are specifically executed.

[0129] An embodiment of the present invention also provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the steps in the method in the above embodiment are specifically followed.

[0130] The technical solution of the present invention will be further described below in conjunction with specific embodiments.

[0131] Embodiment 1:

[0132] A slit coating device model is established. The k-ε turbulence model is selected as the fluid model. The control target is that the thickness of the perovskite layer film is 200 nm, the thickness uniformity is ±3%, and the glass size is 300×400 mm. Through iterative solution, the optimal coating parameters are obtained: the control gap height between the coating die head and the substrate is 100 μm, the running speed is 0.5 m / s, the concentration of the precursor solution is 1.2 M, and the feeding speed is 20 ml / min.

[0133] 1) Target setting:

[0134] Target thickness of the perovskite layer film: 200 nm

[0135] Thickness uniformity requirement: ±3%

[0136] 2) Model establishment:

[0137] Coating device type: slit coating

[0138] Fluid model selection: k-ε turbulence model to accurately simulate the flow state of the precursor solution during the coating process

[0139] 3) Initial parameter setting:

[0140] Initial gap height between the coating die head and the substrate: 120 μm

[0141] Initial value of the running speed: 0.4 m / s

[0142] Initial concentration of the precursor solution: 1.0 M

[0143] Initial value of the feeding speed: 18 ml / min

[0144] Initial value of the air knife pressure: 0.15 MPa

[0145] 4) Iterative solution process:

[0146] Establish a mathematical model: Based on the physical principle of slot coating and combined with the k-ε turbulence model, establish a mathematical model to describe the flow of the precursor solution, coating thickness distribution, etc.

[0147] Set optimization objectives: Take the perovskite layer film thickness and thickness uniformity as optimization objectives and set specific numerical ranges.

[0148] Parameter sensitivity analysis: By changing parameters such as the gap height between the coating die and the substrate, running speed, precursor solution concentration, feeding speed, and air knife pressure, analyze their effects on the coating thickness and uniformity.

[0149] Iterative optimization: Adopt numerical optimization algorithms (such as genetic algorithms, particle swarm optimization algorithms, etc.) to iteratively optimize the above parameters until the best parameter combination that meets the requirements of the target thickness and uniformity is found.

[0150] Result verification: Verify the optimized parameter combination through simulation or experiment to ensure that the coating effect meets the expectations.

[0151] 5) Optimal coating parameters:

[0152] Controlled gap height between the coating die and the substrate: 100 μm

[0153] Running speed: 0.5 m / s

[0154] Precursor solution concentration: 1.2 M

[0155] Feeding speed: 20 ml / min

[0156] 6) Best coating effect:

[0157] Perovskite layer film thickness: 200 nm (meeting the target)

[0158] Thickness uniformity: ±2.8% (better than the requirement)

[0159] Example 2:

[0160] Establish a model of the slot coating device, select the SST-ω turbulence model as the fluid model, control the target fluid flow velocity to be 0.8 m / s, and at the same time ensure a perovskite layer film thickness of 300 nm, thickness uniformity of ±5%, and glass size of 500×600 mm. Through iterative solution, the optimal coating parameters are obtained: the controlled gap height between the coating die and the substrate is 150 μm, the running speed is 0.7 m / s, the precursor solution concentration is 1.3 M, and the feeding speed is 25 ml / min.

[0161] 1) Target setting:

[0162] Target fluid flow velocity: 0.8 m / s (considering the coating thickness at the same time)

[0163] Target thickness of perovskite layer film: 300 nm

[0164] Thickness uniformity requirement: ±5%

[0165] 2) Model establishment:

[0166] Coating device type: slot coating

[0167] Fluid model selection: SST-ω turbulence model to more accurately simulate turbulent flow at high Reynolds numbers

[0168] 3) Initial parameter setting:

[0169] Initial gap height between coating die and substrate: 160 μm

[0170] Initial value of running speed: 0.6 m / s

[0171] Initial concentration of precursor solution: 1.25 M

[0172] Initial value of feeding speed: 22 ml / min

[0173] 4) Iterative solution process (similar to Example 1):

[0174] Establish a mathematical model of slot coating considering fluid flow velocity.

[0175] Set the optimization objectives (including fluid flow velocity, coating thickness and uniformity).

[0176] Conduct parameter sensitivity analysis.

[0177] Adopt a numerical optimization algorithm for iterative optimization.

[0178] Verify the optimization results.

[0179] 5) Optimal coating parameters:

[0180] Controlled gap height between coating die and substrate: 150 μm

[0181] Running speed: 0.7 m / s

[0182] Concentration of precursor solution: 1.3 M

[0183] Feeding speed: 25 ml / min

[0184] 6) Best coating effect:

[0185] Fluid flow velocity: 0.8 m / s (meeting the target)

[0186] Thickness of perovskite layer film: 300 nm (meeting the target)

[0187] Thickness uniformity: ±4.8% (better than the requirement)

[0188] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A coating method for a perovskite thin film, characterized in that: The method comprises, Constructing a coating model based on the mechanical coupling relationship between the target substrate and the coating device; Based on the coating model, a target coating thickness and a target injection amount and a coating rate corresponding to the target coating thickness are obtained; Constructing a fluid flow model of the coating fluid medium between the coating die head and the substrate and on the surface of the substrate; The target coating parameters are determined based on the target coating thickness, the target injection volume corresponding to the target coating thickness, the coating rate and the fluid model.

2. A coating method for a perovskite thin film according to claim 1, characterized in that: The mechanical coupling relationship between the target substrate and the coating device includes: Determine the initial injection amount of the coating liquid based on the geometric size of the target substrate and the set coating thickness; Based on the geometric dimensions of the target substrate, the coating gap difference between the coating head and the target substrate, the injection liquid pipeline material and the pipeline inner diameter, and the exhaust pipe inner diameter, determine the calibration amount of the coating liquid during the coating process, the recovery amount, and the liquid splashing amount caused by the exhaust; The coating model is constructed based on the initial injection amount of the coating liquid, the calibration amount of the coating liquid during the coating process, the recovery amount, and the amount of liquid splashing caused by exhaust.

3. A coating method for a perovskite thin film according to claim 2, characterized in that: The formula of the coating model includes: Where, δ represents the set coating thickness, V z2 represents the set injection volume, k2 represents the length coefficient from the start of liquid discharge from the coating head to the liquid contacting the substrate; h2 represents the coating gap difference between the coating head and the target substrate; W represents the width of the target substrate; L represents the length of the target substrate; k3 represents the influence coefficient of the injection liquid pipeline in the coating device on the coating liquid; v3 represents the withdrawal speed; t3 represents the withdrawal time; k4 represents the gas-liquid carrier coefficient; D4 represents the inner diameter of the exhaust pipe; v4 represents the exhaust speed; t4 represents the exhaust time; k1 represents the empirical coefficient.

4. The method for coating a perovskite thin film according to claim 1, characterized in that: Based on the coating model, a target coating thickness and a target injection amount and a coating rate corresponding to the target coating thickness are obtained, including: The coating model is iteratively calculated using a relaxation method, and the parameters of the coating gap difference between the coating head and the target substrate, the retraction speed, the retraction time, the gas-liquid coefficient, the inner diameter of the exhaust pipe, the exhaust speed and the exhaust time are adjusted multiple times during the iterative calculation process until an actual coating thickness is calculated and the absolute value of the difference between the actual coating thickness and the set coating thickness is less than a first threshold value; The actual coating thickness when the absolute value of the difference between the actual coating thickness and the set coating thickness is less than the first threshold is the target coating thickness; According to the target coating thickness, the target injection amount and coating rate corresponding to the target coating thickness are obtained.

5. The method for coating a perovskite thin film according to claim 1, characterized in that: The formula of the fluid flow model of the coating fluid medium between the coating die head and the substrate and on the surface of the substrate is: In the formula, is the time-averaged velocity component in the j direction, ν is the kinematic viscosity, is the average pressure; represents the time-averaged velocity component in the i direction; x i 、x j Respectively represent spatial coordinates, wherein i≠j, i= represents the coating liquid along the length direction, width direction or the coating liquid thickness direction perpendicular to the substrate; j represents the coating liquid along the length direction, width direction or the coating liquid thickness direction perpendicular to the substrate; represents the time-averaged pulsating velocity component in the j direction; represents the time-averaged pulsating velocity component in the i direction; is the Reynolds stress term; v t is the turbulent viscosity, k is the turbulent kinetic energy; δ ij is the Kronecker function, ρ represents the coating liquid density, ω represents the specific dissipation rate; C3 represents the empirical coefficient.

6. The method for coating a perovskite thin film according to claim 1, characterized in that: Based on the target coating thickness, the target injection volume corresponding to the target coating thickness, the coating rate pair and the fluid model, the target coating parameters are determined, including: Taking the target coating thickness, the target injection volume corresponding to the target coating thickness, and the coating rate as boundary conditions, the liquid film thickness, the length of the target substrate, the width of the target substrate, and the coating gap difference are discretized to obtain the corresponding physical geometric lattice; Iterative calculation is performed using the fluid model in each layer in the height direction of the physical geometric lattice until the difference between two consecutive iteration target results is less than a second threshold or reaches a maximum predetermined number of iterations, and the iteration is terminated; When the iteration ends, the corresponding coating parameters are the target coating parameters.

7. A coating method for a perovskite thin film according to any one of claims 1 to 6, characterized in that: The target coating parameters include the controlled gap height between the coating die head and the substrate, the running speed in the width direction of the coating substrate, the running speed in the length direction of the coating substrate, the coating liquid concentration and the feeding speed.

8. A coating device for a perovskite film, characterized in that: The device comprises, A first construction unit is used to construct a coating model based on a mechanical coupling relationship between a target substrate and a coating device; A first determination unit is used to obtain a target coating thickness and a target injection amount and a coating rate corresponding to the target coating thickness based on the coating model; The second construction unit is used to construct a fluid flow model of the coating fluid medium between the coating die head and the substrate and on the surface of the substrate; The second determination unit is used to determine the target coating parameters by calculating based on the target coating thickness, the target injection volume corresponding to the target coating thickness, the coating rate and the fluid model.

9. An electronic device, comprising at least one processor and at least one memory, wherein the memory is data-connected to the processor, wherein: The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A computer storable medium, characterized in that: The storable medium stores computer instructions, and when the computer instructions are executed by the processor, the steps in the method according to any one of claims 1 to 7 are specifically performed.

11. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps in the method according to any one of claims 1 to 7 are specifically performed.

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