Method for simulating anodic oxidation of oral titanium alloy implant based on COMSOL

Abstract

The invention relates to an oral titanium alloy implant, relates to the technical field of implant abutment and implant production, and discloses a COMSOL-based method for simulating anodic oxidation of an oral titanium alloy implant, which comprises the following steps: constructing a titanium alloy and reaction tank two-dimensional model by using COMSOL, and defining material attributes of an electrode and an electrolyte; adding a current distribution interface and a deformation geometric interface, and setting current distribution and potential change boundary conditions; setting an initial potential and an oxidation voltage range of the titanium alloy; grid division is carried out, and proper grid units are selected; setting a simulation research and solver; and finally, drawing a voltage and oxide film thickness regression curve, and analyzing the influence of the voltage on film generation. According to the method, the COMSOL simulation technology is adopted, the current distribution and the potential change in the anodic oxidation process are simulated by establishing the two-dimensional structure model of the titanium alloy implant and the reaction tank, the distribution of the current and the potential in the electrolyte can be accurately controlled, and the generation process of the oxidation film is optimized.

Description

Technical Field

[0001] The present invention relates to the field of oral titanium alloy implants, implant bases and implant production technology, and specifically to a method for simulating anodizing of oral titanium alloy implants based on COMSOL. Background Art

[0002] In the field of modern dentistry, titanium alloy implants are widely used in oral implantation. Due to their excellent biocompatibility and corrosion resistance, they can integrate well with human bone tissue. However, the surface properties of titanium alloy implants are crucial to their implantation effect. Untreated titanium alloy surfaces may have microscopic defects and contaminants, which affect the bonding ability of implants with bone tissue. In order to enhance the biological activity of the titanium alloy surface, anodizing technology has emerged. By applying voltage in the electrolyte, anodizing can form a dense oxide film on the surface of titanium alloy, which not only enhances the corrosion resistance of titanium alloy, but also promotes cell adhesion and growth, further improving its biocompatibility and bone integration ability. By optimizing the anodizing process, the thickness and uniformity of the oxide film can be precisely controlled, thereby improving the performance of the implant.

[0003] In existing anodizing technologies, researchers mainly rely on experience and experimental adjustments to control the quality of the oxide film by changing the voltage, time and electrolyte concentration. Some technologies have successfully used the conductivity and temperature changes in the electrolyte solution to improve the uniformity of the film layer, or control the formation rate of the film layer by adjusting the voltage. These methods can improve the surface properties of titanium alloy implants to a certain extent. In particular, the adjustment of voltage and electrolyte can affect the thickness of the film and its corrosion resistance. However, the limitation of existing technologies is the lack of comprehensive simulation of the process of oxide film formation, and they often rely on simple theoretical models to explain the growth of the film layer, which makes it difficult to effectively guarantee the stability and repeatability of the process.

[0004] However, traditional anodizing methods have many shortcomings. First, most of these methods rely on experience and repeated experiments, and cannot accurately predict the thickness and uniformity of the oxide film, making it difficult to control the quality of the film. Although some studies have tried to use simulation technology to optimize the oxidation process, these models often ignore the complex effects of current density and potential distribution in the electrolyte, and cannot truly reflect the interaction between titanium alloys and electrolytes. In addition, the existing technology does not adequately consider physical phenomena during the simulation process and cannot accurately capture the nonlinear effects of current, temperature, and voltage changes on the generation of oxide films. These shortcomings of traditional methods often require a lot of experimental verification and debugging in actual production, which is inefficient, and the instability of the final film quality is still a difficult problem to overcome. To this end, those skilled in the art proposed a method for simulating the anodizing of oral titanium alloy implants based on COMSOL to solve the above problems. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a method for simulating the anodizing of oral titanium alloy implants based on COMSOL, which solves the problem in the existing technology that it is difficult to accurately control the thickness and uniformity of the oxide film during the anodizing process.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for simulating anodizing of oral titanium alloy implants based on COMSOL, comprising the following steps: S1. Use COMSOL software to construct a two-dimensional structural model of the titanium alloy and the reaction tank, and provide a geometric framework for subsequent simulation analysis; S2. Define the material properties of the electrodes and electrolyte to provide a physical parameter basis for the subsequent simulation of current distribution and potential changes; S3. Add a Primary Current Distribution interface and combine it with the Deformed Geometry interface to determine the current distribution and potential changes in the electrolyte solution. Set boundary conditions for the current distribution to ensure that the current and potential changes accurately reflect the physical process. S4. Clarify the parameters in the simulation process, set the initial potential of the titanium alloy and the anodic oxidation voltage range, and lay the foundation for accurate simulation of the relationship between voltage and oxide film formation during the calculation process; S5. Grid the two-dimensional structural model and select appropriate grid units to ensure calculation accuracy and reliability and stability of simulation results. S6. Set up the study in the COMSOL Multiphysics Model Builder and select the appropriate solver for the simulation to further optimize the simulation accuracy and computational efficiency. S7. Draw a regression curve between voltage and oxide film thickness, analyze the effect of voltage change on oxide film formation, and ultimately provide a theoretical basis for optimizing the anodizing process of titanium alloy implants.

[0007] In summary, this application includes at least one of the following beneficial technical effects: 1. This paper uses COMSOL simulation technology to establish a two-dimensional structural model of the titanium alloy implant and reaction tank, accurately simulating the current distribution and potential changes during the anodic oxidation process. This technical solution can precisely control the distribution of current and potential in the electrolyte, thereby optimizing the formation process of the oxide film. Compared with traditional experimental methods, this simulation greatly improves experimental efficiency and avoids a large amount of time and material consumption. 2. Through meticulous meshing and high-precision simulation settings, this invention ensures accurate calculation of current density and potential changes during the anodic oxidation process. This technical solution breaks through the limitations of previous reliance on crude models and achieves precise prediction of the thickness and uniformity of the oxide film on the titanium alloy surface. Compared with existing technologies, this refined simulation method can effectively reduce errors and better control the quality of the oxide film. 3. This paper combines the primary current distribution interface with the deformed geometry interface to simulate the current flow in the electrolyte and the growth process of the oxide film. By setting the simulation results at different voltages, a regression curve between voltage and oxide film thickness is plotted, providing a theoretical basis for optimizing the voltage conditions of anodization. Unlike traditional empirical adjustment methods, this data-driven regression curve provides more scientific and reliable process parameters, reducing the uncertainty caused by human intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 Schematic diagram of the method flow of the present invention; Figure 2 It is a two-dimensional structural model diagram of the present invention; Figure 3 A two-dimensional grid division diagram of the titanium alloy and the electrolyte of the present invention; Figure 4 This is the electrolyte potential diagram of the reaction tank at 60s under 85V voltage of the present invention; Figure 5 This is the electrolyte current density diagram of the reaction tank at 60s under 85V voltage of the present invention; Figure 6 This is a regression curve diagram of the change of the titanium alloy surface film thickness with voltage after 60s in the present invention. DETAILED DESCRIPTION

[0009] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0010] Please see the attached Figure 1 -Attached Figure 6 The embodiment of the present invention provides a method for simulating anodizing of an oral titanium alloy implant based on COMSOL, comprising the following steps: S1. Use COMSOL software to construct a two-dimensional structural model of the titanium alloy and the reaction tank, and provide a geometric framework for subsequent simulation analysis; Specifically, in this embodiment, step S1 includes using COMSOL software to construct a two-dimensional structural model of the titanium alloy implant and the reaction tank. Specifically, first, a geometric model of the reaction tank is created in the "Geometry" module of the COMSOL software. The reaction tank is usually configured as a rectangle or square, and its size is adapted to the size requirements of the reaction tank in actual applications. The design of the reaction tank should take into account the ability to effectively accommodate the electrolyte and the titanium alloy implant, and provide sufficient space for subsequent simulation calculations.

[0011] In this step, the titanium alloy implant is represented by creating a two-dimensional model that matches the actual implant. The model is rectangular and has an appropriate scale to ensure that its size matches the titanium alloy implant in actual application. In the reaction tank model, the titanium alloy implant is usually placed in the center of the tank and participates in the anodic oxidation reaction as an anode. The two ends of the reaction tank are set as cathode electrodes. In the simulation model, the cathode is usually modeled with copper material (Cu[solid]) to simulate its electrical conductivity characteristics. Titanium alloy participates in the anodic oxidation reaction as an anode material, and the current will flow from the anode to the cathode to complete the entire electrolysis process.

[0012] In the process of constructing the geometric model, in addition to the basic shapes of the reaction tank and titanium alloy implant, the electrolyte container and its contact area with the titanium alloy implant also need to be considered. The area where the electrolyte interface contacts the titanium alloy surface needs to be represented accurately to facilitate the subsequent calculation of the current distribution and potential changes in the electrolyte. Through meticulous geometric modeling, it is possible to ensure that the current and potential distribution in the electrolyte are properly simulated during the simulation process, thus providing an accurate geometric framework for the calculation of current density and voltage.

[0013] Establishing this two-dimensional structural model isn't limited to creating the geometric shape; the boundary conditions between the reaction tank and the titanium alloy implant are also crucial. In this example, the position and dimensions of the cathode and anode, as well as their contact boundaries with the electrolyte, all require explicit definition. When constructing the geometric models of the reaction tank and titanium alloy implant, the current flow direction and electric field distribution must be fully considered to ensure accurate simulation of the current-potential relationship in subsequent steps.

[0014] To further ensure the accuracy of the simulation, this embodiment uses an appropriate meshing method. The level of detail in the meshing is crucial to the accuracy of the simulation results. When meshing, the appropriate mesh type and mesh density should be selected based on the complexity of the reaction tank and the titanium alloy implant surface area to ensure the accuracy of the current distribution and potential calculation. Preferably, the "physics-controlled mesh" type can be selected to use a finer mesh in the contact area between the electrolyte and the titanium alloy to improve the simulation accuracy.

[0015] After the reaction tank geometry is built, the next step is to define the material properties and electrochemical reaction conditions. This structured modeling process lays a solid foundation for subsequent simulation calculations such as current distribution and potential changes.

[0016] S2. Define the material properties of the electrodes and electrolyte to provide a physical parameter basis for the subsequent simulation of current distribution and potential changes; Specifically, in this embodiment, step S2 involves defining the material properties of the electrodes and electrolyte to ensure that the simulation accurately reflects the current and potential distribution during the anodic oxidation process. Specifically, in this step, appropriate material properties must first be specified for the titanium alloy implant (serving as the anode) and the cathode in the reaction tank (typically made of copper). These material properties directly affect the current distribution and potential changes in the electrolyte, as well as the subsequent oxide film formation process.

[0017] As an anode material, titanium alloy's material properties should include physical properties such as electrical conductivity, specific heat capacity, and density. As a metallic material, titanium alloy possesses excellent corrosion resistance and mechanical strength, playing a key role in the anodic oxidation process. An oxide film forms on the surface of titanium alloy under the action of the electrolyte, enhancing its corrosion resistance and biocompatibility. In COMSOL simulations, the titanium alloy material should be defined as "Titanium [solid]," and its electrical conductivity and electrochemical properties when interacting with the electrolyte solution should be specified. These properties of the titanium alloy material will affect the current flow and potential distribution during the anodic reaction.

[0018] For the cathode, copper is typically chosen as the material. The copper material properties also need to be defined in the simulation model. As an electrode material, copper provides electrons in the simulation, ensuring current conduction between the cathode and anode. Copper has good conductivity, so its physical properties, such as conductivity, must be accurately specified to ensure correct current simulation. In COMSOL, the copper material should be "Cu[solid]" and its relevant conductivity and other physical properties must be specified.

[0019] In addition to the material definition of the anode and cathode, this embodiment also involves the setting of the electrolyte material. The choice of electrolyte has an important influence on the current distribution and potential change during the anodic oxidation process. In this embodiment, oxalic acid solution is preferably used as the electrolyte. Oxalic acid solution plays a conductive role in the anodic oxidation process and can generate an oxide film on the surface of the titanium alloy through electrolytic reaction. Therefore, it is necessary to set the corresponding material properties for the electrolyte in COMSOL, including conductivity, density, specific heat capacity and ion migration characteristics in the electrochemical reaction. Properties such as conductivity, specific heat capacity and viscosity of oxalic acid solution will directly affect the distribution of current in the electrolyte and its conduction efficiency.

[0020] Setting the physical properties of the electrolyte not only includes conventional conductivity but also requires consideration of the various ion species and their migration rates within the solution. To this end, COMSOL defines parameters such as the electrolyte's ion mobility, diffusion coefficient, and conductivity to ensure accurate simulation of the current and potential conduction characteristics within the electrolyte during simulation. These settings provide an accurate physical basis for subsequent calculations of current distribution and oxide film thickness.

[0021] S3. Add a Primary Current Distribution interface and combine it with the Deformed Geometry interface to determine the current distribution and potential changes in the electrolyte solution. Set boundary conditions for the current distribution to ensure that the current and potential changes accurately reflect the physical process. Specifically, in this embodiment, step S3 involves adding a primary current distribution interface to the COMSOL simulation, combined with a deformed geometry interface, to simulate the current distribution and potential changes in the electrolyte solution. The main purpose of this step is to ensure that the current distribution between the anode and cathode meets the actual requirements of the electrochemical reaction process by setting appropriate boundary conditions in the simulation and to simulate the potential changes in the electrolyte.

[0022] In this example, the Primary Current Distribution interface is used to simulate the flow of current in the electrolyte. This interface calculates the current density at various locations in the electrolyte solution based on factors such as the electric field, current density, and mass transport in the electrolyte. This interface is critical because it accurately reflects the current distribution in the electrolyte, which in turn affects the thickness and uniformity of the oxide film formed on the surface of the titanium alloy implant. Current density is an important control factor in the anodic oxidation reaction, directly determining the formation rate and characteristics of the oxide film.

[0023] In order to further accurately simulate the current distribution in the electrolyte, the material properties in this embodiment also include simulations of phenomena such as ion migration and diffusion in the electrolyte. The diffusion coefficient and conductivity of ions in the electrolyte will directly affect the distribution of current density between the anode and cathode surfaces. In COMSOL simulation, the "Nernst-Planck equation" can be used to describe the migration behavior of ions in the electrolyte. This equation takes into account the diffusion, migration and electric field of ions: Where: N i is the flux of substance i; D i is the diffusion rate; c i is the concentration of ion i; z i is the valence of ion i; m i is the ion mobility; F is the Faraday constant; φ l is the ion potential; u is the velocity vector.

[0024] When simulating current distribution, the physical equations and models used in the simulation model include various phenomena such as ion migration, electric field conduction, and diffusion. Specifically, the current density i is calculated according to the following formula: Where: i is the current density; σ l is the conductivity of the electrolyte solution; c i is the concentration of ion i; z i is the valence of ion i; m i is the ion mobility; F is the Faraday constant; φ l is the ionic potential; is the electric field gradient in the electrolyte.

[0025] This approach accurately simulates the current distribution in the electrolyte, allowing for dynamic adjustments to the current direction and intensity during simulation. The current distribution not only influences the anodic oxidation process but also determines the potential changes in the electrolyte. By calculating the relationship between current density and electric field strength, we can clearly understand the electrolyte's reaction behavior under different voltage conditions.

[0026] Furthermore, to more accurately simulate the current distribution and potential variations on the anode and cathode surfaces, this example incorporates the Deformed Geometry interface. This interface is used to simulate potential variations in the electrolyte. This is particularly true during the formation of oxide films on titanium alloy implants, where changes in the potential gradient have a direct impact on the film's thickness.

[0027] In the Deformed Geometry interface, by setting the potential field distribution of the electrolyte, it is possible to track the potential variation between the anode and cathode. This variation depends not only on the current density but also on the diffusion and migration of ions in the electrolyte. Therefore, by setting appropriate potential boundary conditions in the model, the potential distribution at different locations in the electrolyte can be simulated. The potential distribution is closely related to the current density and can influence the formation of oxide films on the titanium alloy surface.

[0028] Specifically, the current density formula and the charge source term formula ensure that the current is conserved: Where: Q l is the charge source term in the electrolyte solution; i is the current density vector.

[0029] Using this equation, the model can calculate the potential value at each point in the electrolyte and further determine the flow path of the current.

[0030] Combined with the calculated results of these current and potential distributions, simulations can accurately predict the flow of current in the electrolyte and provide theoretical support for the electrochemical characteristics of the anodic oxidation reaction. By simulating the changes in current and potential, the formation process of the oxide film under different voltage conditions, as well as the thickness and uniformity of the oxide film, can be further studied.

[0031] S4. Clarify the parameters in the simulation process, set the initial potential of the titanium alloy and the anodic oxidation voltage range, and lay the foundation for accurate simulation of the relationship between voltage and oxide film formation during the calculation process; Specifically, in this embodiment, step S4 involves explicitly setting parameters during the simulation process, including the initial potential of the titanium alloy implant and the anodic oxidation voltage range. The core of this step is to define the basic conditions for the electrochemical reaction and ensure that the simulation can simulate the current distribution and potential changes in the electrolyte, thereby predicting the formation of the oxide film.

[0032] First, the initial potential of the titanium alloy implant is set in the simulation model. As the titanium alloy acts as an anode, its surface potential changes with the passage of current during oxidation. Therefore, the initial potential of the titanium alloy is set to 0V to ensure that the model begins the simulation from an initial, current-free state. This initial potential setting simulates the transition from a static state to a dynamic reaction during actual anodic oxidation. In the simulation, this initial potential setting provides the basis for subsequent voltage changes and electrochemical reactions.

[0033] Next, the setting of the anodizing voltage range is crucial for the simulation calculation. In this embodiment, the anodizing voltage range is generally set between 5V and 85V. This voltage range helps determine the optimal anodizing conditions by simulating the current density and potential distribution in the electrolyte under different voltage conditions. In practical applications, the change in voltage will directly affect the thickness and quality of the oxide film on the surface of the titanium alloy. Therefore, by setting this voltage range, the impact of the anodizing reaction under different voltages can be fully considered.

[0034] In this embodiment, the electrochemical reaction in the electrolyte solution also needs to be clearly set in the simulation. The anode reaction is usually: Ti + 2H2O → TiO2 + 4H + +4e - ; This reaction indicates that the titanium alloy reacts with water molecules in the electrolyte, forming a titanium oxide film and releasing hydrogen ions. This reaction has a significant impact on the current conduction characteristics, especially as the oxide film gradually forms, the potential distribution changes, thus affecting the reaction rate and the quality of the oxide film.

[0035] The cathode reaction is: 4H + +4e -→2H2; This reaction occurs on the cathode surface, where hydrogen ions react with electrons to generate hydrogen gas. In simulations, this reaction is also an important basis for setting current density and potential changes. The reactions at the anode and cathode jointly determine the current distribution and potential gradient, which in turn influence the formation of the oxide film on the titanium alloy surface.

[0036] By setting these potentials and electrochemical reaction parameters in step S4, the simulation can accurately simulate the current flow and potential distribution in the electrolyte, providing the necessary physical foundation for subsequent meshing, solver configuration, and oxide film thickness calculation. The potential setting and voltage selection will directly affect the simulation results of the current distribution and oxide film formation process in subsequent steps. Therefore, in this step, reasonable parameter setting is fundamental to ensuring the accuracy and feasibility of the entire simulation process.

[0037] S5. Mesh the two-dimensional structural model and select appropriate mesh units to ensure calculation accuracy; Specifically, in this embodiment, step S5 involves meshing the two-dimensional structural model. The core goal of this step is to ensure the accurate calculation of physical quantities such as current density and potential distribution during the simulation process, and to provide high-precision numerical solutions for subsequent calculations. The accuracy of the meshing directly affects the accuracy of the simulation results, especially in the simulation of oxide film formation, ion migration, and current density distribution during the anodization process.

[0038] When performing meshing, the first thing to consider is the geometric complexity of the model and the characteristics of the physical processes involved. For the geometric models of the reaction tank and titanium alloy implant, a more detailed meshing method is preferred to ensure that every detail can be accurately reflected in the calculation of the flow of current in the electrolyte, potential changes, etc. Especially on the surface of titanium alloy implants, the changes in current density and potential are more complex, so it is necessary to perform more refined meshing in this area. Through high-precision meshing, local changes in electric field and current can be captured in the simulation, thereby improving the accuracy of the simulation results.

[0039] In this embodiment, the meshing adopts the "physical field controlled mesh" type. This mesh type can automatically adjust the density of the mesh according to the distribution of the physical field to ensure sufficiently high calculation accuracy in areas where the electric field and current density change significantly. Specifically, in the electrolyte, the electric field strength and current density are usually more concentrated in the area where the anode and the electrolyte are in contact, so a denser mesh unit is required in this area. In addition, the meshing of the anode and cathode surfaces should also be refined to accurately simulate the current density and potential changes at the electrode surface.

[0040] In order to further improve the accuracy of the simulation calculation, "ultra-fine grid" units are used in this embodiment. By selecting finer grid units, it is possible to ensure that the distribution of current and the change of potential in the electrolyte can be accurately described at the microscopic scale. The purpose of refining the grid is to capture the tiny fluctuations of current and potential in the electrolyte, especially in the process of forming an oxide film on the surface of titanium alloy implants. This fine grid division plays an important role in studying the thickness and uniformity of the oxide film and its relationship with current density.

[0041] When meshing, it is also necessary to perform appropriate mesh optimization based on the computational complexity of the simulation model. An overly fine mesh may increase the amount of computation and result in excessively long computation times. Therefore, when meshing, it is preferable to optimize the mesh size to balance computation time and accuracy. In non-critical areas of the model, the mesh unit can be appropriately reduced to reduce computational complexity, but in critical areas, such as the anode surface and the current distribution area in the electrolyte, the mesh needs to be refined.

[0042] To ensure that simulation calculations after meshing can be performed stably and efficiently, this embodiment also considers post-meshing verification. By performing calculations at different mesh densities and comparing the differences in simulation results, it is ensured that the selected meshing scheme maintains calculation accuracy while avoiding unnecessary waste of computing resources. Through this verification process, the optimal meshing scheme can be determined, providing a reliable foundation for subsequent calculations such as current distribution, potential changes, and oxide film thickness.

[0043] S6. Set up the study in the COMSOL Multiphysics Model Builder and select the appropriate solver for the simulation to further optimize the simulation accuracy and computational efficiency. Specifically, in this embodiment, step S6 involves setting up the simulation study and configuring the solver. This step is one of the key steps in the entire simulation process. Its main purpose is to ensure that the physical processes such as current distribution in the electrolyte, potential changes, and oxide film formation can be effectively solved and obtain stable and accurate simulation results. Specifically, this step includes selecting the appropriate solver type, setting simulation parameters, and performing the necessary research configuration to ensure that the various physical phenomena in the anodizing process can be effectively simulated.

[0044] First of all, in simulation research, it is crucial to choose the right solver type. Since this embodiment involves a transient electrochemical process, it is very important to choose a transient solver as the solver for the simulation study. The transient solver can track the changes in physical quantities such as current density and potential in the electrolyte in real time, especially the time evolution characteristics of current distribution and potential. The current and potential distribution in the electrolyte will change over time, so simulation calculations using a transient solver can truly reflect the dynamic evolution of the anodizing process.

[0045] When setting up a transient solver, you first need to set the solver step size. The size of the solver step size determines the accuracy of the time step in the simulation calculation. Smaller step sizes can usually provide higher calculation accuracy, but will result in longer calculation times. Therefore, it is very important to choose an appropriate step size. In this embodiment, it is preferred to adjust the step size setting so that the calculation results of each time step can accurately reflect the dynamic characteristics of the current density and potential changes, while avoiding the waste of computing resources.

[0046] In addition, the solver's simulation time setting also needs to be configured. Since anodization is an ongoing electrochemical process, the choice of simulation time is crucial. Setting an appropriate simulation time can ensure a complete simulation of the anodization process while avoiding unnecessary computational burdens caused by long simulation times. In this embodiment, the simulation time is usually set to a certain number of seconds, which is sufficient to cover the formation of the oxide film and the evolution of current density and potential during the anodization process.

[0047] In addition to the solver step size and simulation time, the voltage range also needs to be set in the simulation study. In this embodiment, the simulation study involves simulation under different conditions from low voltage to high voltage. The setting of the voltage range is usually adjusted according to the needs of the actual application. By setting different voltage conditions in the simulation, the relationship between current density, potential distribution and oxide film thickness under different voltages can be studied. Through the parameterized sweep setting, the voltage range can be scanned step by step to obtain the simulation results at each voltage, and the influence of voltage on the formation of oxide film can be further analyzed.

[0048] At the same time, during the solution process, each physical field in the simulation model (such as current distribution, potential distribution, etc.) will be solved by the solver. Each physical field involves different physical equations. For example, the simulation of current distribution needs to be solved according to the current density equation, while the potential distribution is described by the potential equation. In order to ensure the accurate solution of each physical field, the corresponding boundary conditions must be set according to the characteristics of the physical field. The current density, potential distribution and oxide film formation in the electrolyte are all closely related to the coupling between the physical fields. Therefore, the solution of each physical field in the simulation process is closely linked.

[0049] In addition, the output setting of the simulation calculation results is also an important aspect in step S6. By specifying the output variables in the solver settings, the simulation results can be output in the form of current density, potential distribution, and oxide film thickness. These output results will provide the necessary data support for subsequent analysis and regression curve drawing. In this embodiment, the simulation results are usually recorded in the form of time series data to ensure that the current density, potential change, and oxide film formation at each simulation time step can be captured in real time.

[0050] S7. Draw a regression curve between voltage and oxide film thickness, analyze the effect of voltage change on oxide film formation, and ultimately provide a theoretical basis for optimizing the anodizing process of titanium alloy implants.

[0051] Specifically, in this embodiment, step S7 involves plotting a regression curve between voltage and oxide film thickness based on the simulation results, and further analyzing the variation of oxide film thickness under different voltage conditions. The core purpose of this step is to reveal the relationship between voltage and oxide film formation by processing the simulation data, providing a theoretical basis for optimizing the anodizing process.

[0052] In this embodiment, the regression curve is drawn by extracting the relevant data of voltage and oxide film thickness from the simulation results. During the simulation process, as the voltage changes, the current density and potential distribution will change accordingly, which directly affects the growth rate and final thickness of the oxide film. Therefore, under each voltage condition, the simulation results will include the corresponding oxide film thickness data. By organizing these data points, a regression curve between voltage and oxide film thickness is drawn.

[0053] To plot the regression curve, the first step is to extract oxide film thickness data at different voltages based on the simulation results. This data is typically obtained by recording the oxide film thickness in real time during the simulation. At each simulation time step, the oxide film thickness gradually increases with changes in current and potential. Higher voltages typically increase current density, which accelerates the oxide film growth rate and ultimately results in a thicker oxide film. Therefore, there is a positive correlation between voltage and oxide film thickness.

[0054] To ensure the accuracy of the regression curve, the simulation data must be properly processed and analyzed. The regression curve is typically fitted using statistical analysis methods such as the least squares method. This process effectively reveals the quantitative relationship between voltage and oxide film thickness and helps predict oxide film formation under different voltage conditions.

[0055] Specifically, the regression curve fitting process requires statistical analysis of the oxide film thickness data at each voltage value, and regression analysis is used to derive a mathematical model between voltage and oxide film thickness. This model can provide theoretical support for subsequent oxide film thickness control and a reference for optimizing voltage settings during the anodizing process.

[0056] Furthermore, regression curve analysis can reveal the nonlinear effects of voltage changes on oxide film formation. In some cases, increasing voltage can lead to a rapid increase in oxide film thickness, but above a certain voltage, the film's growth may become more gradual. Detailed analysis of the regression curve can clarify the optimal control range between voltage and oxide film thickness, thereby optimizing the anodizing process and avoiding the adverse effects of excessive voltage.

[0057] The regression curve results can also be used to guide process optimization in actual production. For example, by adjusting the voltage range and optimizing the voltage distribution, the thickness and uniformity of the oxide film can be controlled while ensuring the quality of the oxide film. The regression curve provides a scientific basis for this process, allowing for more precise control of the oxide film formation process.

[0058] The examples of this specific embodiment are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, any equivalent changes made based on the structure, shape, and principle of this application should be included in the scope of protection of this application.

Claims

1. A method for simulating anodizing of oral titanium alloy implants based on COMSOL, characterized in that: The following steps are involved: S1. Use COMSOL software to construct a two-dimensional structural model of the titanium alloy and the reaction tank, and provide a geometric framework for subsequent simulation analysis; S2. Define the material properties of the electrodes and electrolyte to provide a physical parameter basis for the subsequent simulation of current distribution and potential changes; S3. Add a Primary Current Distribution interface and combine it with the Deformed Geometry interface to determine the current distribution and potential changes in the electrolyte solution. Set boundary conditions for the current distribution to ensure that the current and potential changes accurately reflect the physical process. S4. Clarify the parameters in the simulation process, set the initial potential of the titanium alloy and the anodic oxidation voltage range, and lay the foundation for accurate simulation of the relationship between voltage and oxide film formation during the calculation process; S5. Mesh the two-dimensional structural model and select mesh units to ensure calculation accuracy; S6. Set up your study in the COMSOL Multiphysics Model Builder and select a solver for simulation to further optimize simulation accuracy and computational efficiency. S7. Draw a regression curve between voltage and oxide film thickness, analyze the effect of voltage change on oxide film formation, and ultimately provide a theoretical basis for optimizing the anodizing process of titanium alloy implants.

2. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The two-dimensional structural model of the titanium alloy and the reaction tank includes: Use the geometry module to create a rectangular model to represent the reaction tank; Set the left and right ends of the electrolytic cell as cathodes, and choose copper as the cathode material; Create a rectangular model representing the titanium alloy implant and set it as the anode.

3. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The material properties of the electrodes and electrolyte include: Titanium alloy as anode material; Copper as cathode material; The electrolyte material is oxalic acid solution, which defines the physical property of conductivity.

4. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The Primary Current Distribution interface, combined with the Deformed Geometry interface, determines the current distribution using the following formula: Where: N i is the flux of substance i; D i is the diffusion rate; c i is the concentration of ion i; z i is the valence of ion i; m i is the ion mobility; F is the Faraday constant; φ l is the ion potential; u is the velocity vector.

5. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 4, characterized in that: The Primary Current Distribution interface further incorporates the current density formula for the electrolyte solution, where the current density i is: Where: i is the current density; σ l is the conductivity of the electrolyte solution; c i is the concentration of ion i; z i is the valence of ion i; m i is the ion mobility; F is the Faraday constant; φ l is the ionic potential; is the electric field gradient in the electrolyte.

6. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The parameters in the simulation process include: The initial potential of the titanium alloy was set to 0 V; The anodizing voltage range is 5V to 85V; The anode reaction and cathode reaction are: Cathode: 4H + +4e - →2H2; Anode: Ti+2H2O→TiO2+4H + +4e - .

7. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The method for meshing a two-dimensional structural model comprises: Select the physics-controlled mesh type; Select extremely fine mesh elements to improve simulation accuracy and ensure the stability of calculation results.

8. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The study setup in the COMSOL Multiphysics Model Builder includes: Set the transient solver, the solver step size to 1s, and the simulation time to 60s; Add a parametric sweep during the simulation process, and simulate the voltage range from 5V to 85V with a step size of 5V.

9. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 1, characterized in that: The drawing of the regression curve between the voltage and the oxide film thickness comprises: Draw a regression curve between voltage and oxide film thickness based on simulation results; The variation of oxide film thickness under different voltage conditions was analyzed by regression curve.

10. The method for simulating anodizing of oral titanium alloy implants based on COMSOL according to claim 4, characterized in that: The current distribution formula further includes: a current density formula and a charge source term formula to ensure current conservation: Where: Q l is the charge source term in the electrolyte solution; i is the current density vector.

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