Methods, apparatus, equipment, and media for determining the interfacial bonding energy of laser-sintered thin films.

Abstract

This application discloses a method, apparatus, device, and medium for determining the interfacial bonding energy of laser-sintered thin films. In this scheme, thin film samples are prepared in advance using different laser parameters. A power-law function prediction model is generated based on the interfacial bonding energy and temperature-energy ratio of each thin film sample. When evaluating the interfacial bonding energy of the thin film sintered based on the new laser parameters, it is only necessary to simulate the temperature-energy ratio using the laser parameters to be evaluated, and then input the temperature-energy ratio into the power-law function prediction model to obtain the interfacial bonding energy of the thin film under the new laser parameters. It is evident that, due to the strong power-law correlation between the temperature-energy ratio and the interfacial bonding energy, this application eliminates the need for multiple tests when determining the interfacial bonding energy. It only requires determining the temperature-energy ratio under the new laser parameters through simulation, which can quickly and accurately predict the interfacial bonding energy, thereby finding the optimal laser parameters, significantly shortening the development cycle and reducing costs.

Description

Technical Field

[0001] This application relates to the field of interfacial bonding energy determination technology, and in particular to a method, apparatus, equipment and medium for determining the interfacial bonding energy of laser-sintered thin films. Background Technology

[0002] Currently, in the manufacture of flexible electronic devices or sensors, inkjet printing technology is typically used to print functional ink (ITO (Indium Tin Oxide)) onto a ceramic substrate, which is then solidified using a laser sintering process to form a conductive thin film. In this process, the strength of the adhesion between the film and the substrate is crucial to the reliability of the product, and the adhesion energy is a key parameter for ensuring this adhesion. If the laser parameters are not set correctly, the film can easily detach during use.

[0003] In existing methods, evaluating interfacial bonding energy primarily relies on scratch testing. This method has significant drawbacks:

[0004] 1. High cost and low efficiency: It is a destructive test that requires the preparation of a large number of real samples with different process parameters, and then testing them one by one with a scratch needle (to determine the critical load). Then, the interface binding energy is calculated, and the whole process is time-consuming and labor-intensive.

[0005] 2. Lack of predictive ability: Scratch testing can only detect the performance of already prepared samples. For a completely new set of laser parameters, since the effects cannot be known in advance, engineers can only rely on trial and error based on their experience, resulting in a very blind and inefficient process optimization.

[0006] Therefore, how to efficiently and accurately calculate the interface binding energy based on different laser parameters is a problem that needs to be solved by those skilled in the art. Summary of the Invention

[0007] This application provides a method, apparatus, device, and medium for determining the interfacial bonding energy of laser-sintered thin films, enabling efficient and accurate calculation of the interfacial bonding energy based on different laser parameters.

[0008] In a first aspect, this application provides a method for determining the interfacial bonding energy of laser-sintered thin films. The method includes: acquiring laser parameters to be evaluated; establishing a finite element model of the thin film and a substrate; performing simulation on the finite element model using a heat source model and the laser parameters to obtain simulation data; wherein the simulation data is data on temperature changes over time along the simulated laser sintering path; calculating the temperature-energy ratio based on the simulation data; the temperature-energy ratio representing the relative relationship between instantaneous thermal shock and total heat input; inputting the temperature-energy ratio into a power-law function prediction model; and predicting the interfacial bonding energy of the thin film under the laser parameters using the power-law function prediction model; wherein the generation process of the power-law function prediction model is as follows: preparing various thin film samples using different experimental laser parameters; and fitting and generating a power-law function prediction model based on the interfacial bonding energy of each thin film sample and the temperature-energy ratio of each thin film sample.

[0009] Optionally, the process of determining the interfacial bonding energy of each thin film sample includes: performing a micron scratch test on each thin film sample to determine the critical load of each thin film sample and the scratch width when the substrate is exposed; performing a nanoindentation test on each thin film sample to determine the elastic modulus of each thin film sample; and determining the interfacial bonding energy of each thin film sample based on the thickness, critical load, elastic modulus, scratch width, and interfacial bonding energy calculation rules.

[0010] Optionally, the interface binding energy calculation rule is as follows:

[0011] ;

[0012] in, Indicates interface bonding energy, Indicates the critical load. Indicates the thickness of the thin film sample. Indicates the elastic modulus. Indicates the width of the scratch.

[0013] Optionally, the process of determining the temperature-energy ratio of each thin film sample includes: establishing an experimental finite element model of each thin film sample and the substrate; performing simulation on the corresponding experimental finite element model using a heat source model and experimental laser parameters corresponding to each thin film sample to obtain experimental simulation data; wherein the experimental simulation data is the data on temperature change over time along the simulated laser sintering path; and determining the temperature-energy ratio of each thin film sample using temperature-energy ratio calculation rules and the experimental simulation data of each thin film sample.

[0014] Optionally, the temperature-energy ratio calculation rule is as follows:

[0015] ;

[0016] in, The temperature-energy ratio, For temperature, For time.

[0017] Optionally, the heat source model is a double ellipsoidal heat source model. The double ellipsoidal heat source model simulates the energy distribution and heat flux density of the moving laser beam inside the finite element model using laser parameters, and obtains simulation data of temperature change over time on the sintering path during transient thermal analysis.

[0018] Optionally, a power-law function prediction model is generated by fitting the interfacial binding energy and temperature-energy ratio of each thin film sample. This includes: using the interfacial binding energy of each thin film sample as Y-axis data and the temperature-energy ratio of each thin film sample as X-axis data to generate coordinate data for each data point; and performing nonlinear fitting of the coordinate data of each data point using a power-law function to obtain the power-law function prediction model.

[0019] Secondly, this application provides an apparatus for determining the interfacial bonding energy of laser-sintered thin films, the apparatus comprising:

[0020] The first acquisition module is used to acquire the laser parameters to be evaluated;

[0021] The second acquisition module is used to establish a finite element model of the thin film and the substrate, and to perform simulation on the finite element model using a heat source model and the laser parameters to obtain simulation data; wherein, the simulation data is the data of temperature change over time along the simulated laser sintering path;

[0022] The calculation module is used to calculate the temperature-energy ratio based on the simulation data; the temperature-energy ratio is used to represent the relative relationship between instantaneous thermal shock and total heat input.

[0023] The prediction module is used to input the temperature-energy ratio into the power function prediction model, and predict the interfacial bonding energy of the thin film under the laser parameters through the power function prediction model; wherein, the generation process of the power function prediction model is as follows: each thin film sample is prepared by different experimental laser parameters, and the power function prediction model is generated by fitting the interfacial bonding energy of each thin film sample and the temperature-energy ratio of each thin film sample.

[0024] Thirdly, this application provides an electronic device, including: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the interface binding energy determination method described above.

[0025] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the interface bonding capability determination method described above.

[0026] Compared with the prior art, the technical solution provided in this application has the following advantages: This application discloses a method, apparatus, device, and medium for determining the interfacial bonding energy of laser-sintered thin films. In this solution, thin film samples are prepared in advance using different laser parameters. A power-law function prediction model is generated based on the interfacial bonding energy and temperature-energy ratio of each thin film sample. When evaluating the interfacial bonding energy of the thin film sintered based on the new laser parameters, it is only necessary to use the laser parameters to be evaluated and the heat source model to perform simulation on the corresponding finite element model to obtain the temperature-energy ratio. Then, the temperature-energy ratio is input into the power-law function prediction model to obtain the interfacial bonding energy of the thin film under the new laser parameters. It can be seen that there is a very strong power-law function correlation between the temperature-energy ratio and the interfacial bonding energy in this application. Therefore, when determining the interfacial bonding energy, this application does not need to perform multiple tests. It only needs to determine the temperature-energy ratio under the new laser parameters through simulation to quickly and accurately predict the interfacial bonding energy, thereby finding the optimal laser parameters, greatly shortening the research and development cycle and reducing costs. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0030] Figure 1 A schematic flowchart of a method for determining the interfacial bonding energy of a laser-sintered thin film provided in an embodiment of this application;

[0031] Figure 2 A schematic diagram illustrating the power-law correlation between TER and interface binding energy, provided in an embodiment of this application;

[0032] Figure 3A schematic diagram of a device for determining the interfacial bonding energy of a laser-sintered thin film provided in an embodiment of this application;

[0033] Figure 4 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0034] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0035] The following disclosure provides numerous different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of the invention. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0036] In existing methods, the evaluation of interfacial bonding energy mainly relies on scratch experiments. This method requires the preparation of a large number of real samples with different process parameters, and then the critical load is measured one by one with a scratch needle before the interfacial bonding energy is calculated. The whole process is time-consuming and labor-intensive. When dealing with new laser parameters, since the effect cannot be known in advance, engineers can only rely on their experience to try and make mistakes, which makes the process optimization process very blind and inefficient.

[0037] Analysis revealed that the root cause of the aforementioned problems lies in the fact that laser sintering is an extremely rapid and complex transient thermal process. Currently, the industry lacks a clear physical model or key indicator that can accurately and quantitatively link the laser process parameters (input), transient thermal history (process), and final interfacial bonding energy (output).

[0038] Therefore, this application provides a method, apparatus, device, and medium for determining the interfacial bonding energy of laser-sintered thin films. This application defines the temperature-energy ratio (TER) for the first time. The TER can extract key features from complex transient thermal histories and has been proven to be a core parameter controlling the interfacial bonding energy. This application achieves a leap from physical trial-and-error to simulation prediction. It utilizes TER as a bridge to transform the expensive, time-consuming, and inefficient scratch experiment optimization process into a low-cost, high-efficiency computer simulation prediction process. The prediction accuracy is high, and the physical meaning is clear. Furthermore, a very strong power-law correlation is observed between TER and the interfacial bonding energy, proving the accuracy of the model and the effectiveness of the TER index.

[0039] This approach first uses finite element method (Abaqus) simulation to model the sintering process under different laser parameters and calculates the corresponding temperature-energy ratio from the simulation results. Simultaneously, through a small number of scratch experiments, the actual interfacial bonding energy of thin film samples prepared with different laser parameters is measured. The temperature-energy ratio (X-axis) and interfacial bonding energy (Y-axis) are then fitted to form a power-law function prediction model. Once this model is established, the temperature-energy ratio becomes the bridge connecting laser parameters and interfacial bonding energy. When evaluating a new set of laser parameters, no further experiments are needed; only a single computer simulation is required to calculate the temperature-energy ratio. This value is then substituted into the power-law function prediction model to immediately predict the final interfacial bonding energy. Therefore, this application, through computer simulation, can efficiently and accurately predict the interfacial bonding energy generated by different combinations of laser parameters. This method allows for the rapid identification of optimal process parameters via software prediction using electronic devices, eliminating the need for repeated fabrication of expensive thin film samples and destructive testing, thereby significantly shortening the development cycle and reducing costs.

[0040] See Figure 1 This is a schematic flowchart of a method for determining the interfacial bonding energy of a laser-sintered thin film according to an embodiment of this application. The method for determining the interfacial bonding energy includes:

[0041] S101. Obtain the laser parameters to be evaluated.

[0042] In this application, the laser parameters to be evaluated refer to a completely new set of laser parameters, including power, scanning speed, etc., which are not specifically limited here. Since the interfacial bonding energy of the thin film generated by laser sintering varies under different laser parameters, this application innovatively proposes a physical index to accurately and quickly determine the interfacial bonding energy of the thin film generated under different laser parameters: the Temperature Energy Ratio (TER). The Temperature Energy Ratio is used to quantitatively describe the relative relationship between the severity of thermal shock and the total heat input during laser sintering; furthermore, based on different laser parameters, the Temperature Energy Ratio and the interfacial bonding energy have a corresponding relationship during laser sintering. This application generates a power-law function prediction model based on this correspondence.

[0043] Therefore, after obtaining the laser parameters to be evaluated, this application can quickly and accurately obtain the interfacial binding energy corresponding to the laser parameters by calculating the temperature-energy ratio corresponding to the laser parameters and inputting it into the power function prediction model.

[0044] S102. Establish a finite element model of the thin film and the substrate, and perform simulation on the finite element model using the heat source model and the laser parameters to obtain simulation data; wherein, the simulation data is the data of temperature change over time on the simulated laser sintering path.

[0045] In this application, a finite element model of the thin film and substrate is first established. The substrate is the underlying material supporting the thin film. This finite element model is a geometric and thermodynamic model of the thin film-substrate built using software such as Abaqus (a finite element-based engineering simulation software). This finite element model can be understood as a digital representation of the physical entity of the thin film-substrate in a computer. The heat source model is a mathematical expression describing how laser energy is injected into the finite element model. Through the heat source model, the energy distribution and heat flux density of the moving laser beam inside the material can be simulated. After determining the laser parameters to be evaluated, this application can perform simulation on the finite element model using the heat source model and laser parameters. Here, simulation refers to calculating the temperature data of the target detection position at various times along the laser sintering path of the finite element model using the constructed finite element model and heat source model. This application refers to this as simulation data. The laser sintering path refers to the pre-set laser head movement trajectory.

[0046] In another embodiment of this application, the heat source model is a double ellipsoidal heat source model. The double ellipsoidal heat source model simulates the energy distribution and heat flux density of the moving laser beam inside the finite element model using laser parameters, and obtains simulation data of temperature change over time on the sintering path during transient thermal analysis.

[0047] Specifically, this application employs a double-ellipsoidal heat source model. This model is a mathematical model used to simulate heat distribution during hot processing processes such as welding and laser machining. It assumes that the heat source forms a double-ellipsoidal (i.e., composed of two ellipsoids) heat distribution region on the workpiece surface. By adjusting the geometric parameters of the ellipsoids (such as the semi-major axis and semi-minor axis) and the heat source intensity, the morphology of the molten pool and the evolution of the temperature field during its movement can be accurately reproduced. This application uses the double-ellipsoidal heat source model for Abaqus simulation, which more closely resembles the actual physical process of laser sintering than traditional point heat sources or Gaussian heat sources, ensuring the accuracy of the simulation data. This is the foundation for accurate TER calculations.

[0048] Therefore, in the simulation, this application can perform a transient thermal analysis on the laser parameters to be evaluated based on the finite element model and the double ellipsoidal heat source model to obtain simulation data of temperature change over time along the sintering path. In this application, the simulation data is represented as... ,in Indicates temperature. Indicates time.

[0049] S103. Calculate the temperature-energy ratio based on the simulation data; the temperature-energy ratio is used to represent the relative relationship between instantaneous thermal shock and total heat input.

[0050] In this embodiment, the temperature-energy ratio is specifically calculated using temperature-energy ratio calculation rules and simulation data. These temperature-energy ratio calculation rules are derived from simulation data. By performing integral calculations, the temperature-energy ratio (TER) corresponding to the laser parameters is obtained.

[0051] In another embodiment of this application, the rule for calculating the temperature-energy ratio is as follows:

[0052] ;

[0053] in, The temperature-energy ratio, For temperature, For time.

[0054] As can be seen from the above temperature-energy ratio calculation rules, the numerator of the formula represents the cumulative rate of temperature change (thermal shock) throughout the process; the denominator represents the total heat energy absorbed by the material. Therefore, TER characterizes the relative relationship between instantaneous thermal shock and total heat input.

[0055] S104. Input the temperature-energy ratio into the power function prediction model, and predict the interfacial bonding energy of the thin film under the laser parameters using the power function prediction model. The generation process of the power function prediction model is as follows: prepare each thin film sample with different experimental laser parameters, and generate the power function prediction model by fitting the interfacial bonding energy of each thin film sample and the temperature-energy ratio of each thin film sample.

[0056] In this application, a power function prediction model needs to be pre-determined. To determine this model, thin film samples are first prepared using different experimental laser parameters. Then, the power function prediction model is generated by fitting the interfacial binding energy of each thin film sample and the temperature-energy ratio corresponding to each experimental laser parameter. Therefore, this power function prediction model reflects the correspondence between the temperature-energy ratio determined by the laser parameters and the interfacial binding energy under different laser parameters. Thus, after determining the temperature-energy ratio of the laser parameters to be evaluated, this ratio can be input into the power function prediction model, which then predicts the interfacial binding energy of the thin film under the new laser parameters.

[0057] In summary, the temperature-energy ratio and interfacial binding energy in this application exhibit a strong power-law correlation. Therefore, when determining the interfacial binding energy, this application does not require multiple tests; it only needs to determine the temperature-energy ratio under new laser parameters through simulation to quickly and accurately predict the interfacial binding energy, thereby finding the optimal laser parameters, greatly shortening the R&D cycle and reducing costs. Furthermore, this application uses a double-ellipsoidal heat source model for simulation, which can improve the accuracy of simulation data and thus improve the accuracy of temperature-energy ratio calculation.

[0058] In another embodiment of this application, the process of determining the interfacial bonding energy of each thin film sample includes: performing a micron-level scratch test on each thin film sample to determine the critical load of each thin film sample and the scratch width when the substrate is exposed; performing a nano-indentation test on each thin film sample to determine the elastic modulus of each thin film sample; and determining the interfacial bonding energy of each thin film sample based on its thickness, critical load, elastic modulus, scratch width, and the interfacial bonding energy calculation rules. The interfacial bonding energy calculation rules are as follows:

[0059] ;

[0060] in, Indicates interface bonding energy, Indicates the critical load. Indicates the thickness of the thin film sample. Indicates the elastic modulus. Indicates the width of the scratch.

[0061] In this embodiment, when determining the power-law function prediction model during the calibration stage, it is necessary to prepare various thin film samples using different experimental laser parameters. Then, the interfacial binding energy and temperature-energy ratio of each thin film sample are calculated to fit and generate the power-law function prediction model. These thin film samples refer to a series of thin film samples with different experimental laser parameters prepared on a substrate using inkjet printing and laser sintering processes. These different experimental laser parameters include multiple sets of laser parameters with different powers and scanning speeds. Then, the actual interfacial binding energy of each thin film sample is measured through a small number of scratch tests.

[0062] To determine the actual interfacial bonding energy of each thin film sample, micron-scratching and nanoindentation experiments are required. Micron-scratching records the critical load at which interfacial failure (film peeling) occurs and the scratch width at which the substrate is exposed. Nanoindentation records the elastic modulus of each sample; in this application, this elastic modulus can specifically be Young's modulus. The formula for calculating interfacial bonding energy follows the aforementioned interfacial bonding energy calculation rules, which allow for the calculation of the interfacial bonding energy of each thin film sample.

[0063] In another embodiment of this application, the process of determining the temperature-energy ratio of each thin film sample includes: establishing an experimental finite element model of each thin film sample and the substrate; performing simulation on the corresponding experimental finite element model using a heat source model and experimental laser parameters corresponding to each thin film sample to obtain experimental simulation data; wherein the experimental simulation data is the data of temperature change over time on the simulated laser sintering path; and determining the temperature-energy ratio of each thin film sample using temperature-energy ratio calculation rules and the experimental simulation data of each thin film sample.

[0064] In this application, the process of determining the temperature-energy ratio of each thin film sample is the same as that of determining the temperature-energy ratio corresponding to the laser parameters to be evaluated in the above embodiments. That is, using software such as Abaqus, a finite element model of each thin film sample-substrate is established, and a double ellipsoidal heat source model is used to accurately simulate the energy distribution and heat flux density of the moving laser beam inside the material. Then, transient thermal analysis is run based on different experimental laser parameters of each thin film sample to obtain simulation data of temperature change over time on the sintering path. This simulation data includes simulation data corresponding to each experimental laser parameter. After obtaining the simulation data of each experimental laser parameter, the TER value corresponding to each experimental laser parameter can be obtained by integral calculation of the simulation data corresponding to each experimental laser parameter according to the above temperature-energy ratio calculation rules.

[0065] In another embodiment of this application, a power-law function prediction model is generated by fitting the interfacial binding energy of each thin film sample and the temperature-energy ratio of each thin film sample. This includes: using the interfacial binding energy of each thin film sample as Y-axis data and the temperature-energy ratio of each thin film sample as X-axis data to generate coordinate data for each data point; and performing nonlinear fitting of the coordinate data of each data point using a power-law function to obtain the power-law function prediction model.

[0066] In this application, after obtaining the temperature-energy ratio and interfacial binding energy of each experimental laser parameter through the above process, it is necessary to establish a fitting model based on the above two data. In this embodiment, the interfacial binding energy of each thin film sample prepared by each experimental laser parameter can be used as the Y-axis, and the temperature-energy ratio obtained by simulation of each experimental laser parameter can be used as the X-axis to establish coordinate data pairs for each data point. Then, a power-exponential function is used to perform nonlinear fitting on the coordinate data of these data points.

[0067] The exponential function can be: a, b, and c are the fitting parameters.

[0068] See Figure 2 This is a schematic diagram illustrating the exponential function correlation between TER and interface binding energy, provided in an embodiment of this application. Figure 2 In the graph, the Y-axis represents the Adhesion Energy, and the X-axis represents the Temperature-Energy Ratio (TER). The points in the graph represent data points generated using the Adhesion Energy and TER, and the curves represent curves generated by fitting a power-law function. This curve, or the corresponding power-law function, constitutes the prediction model for the Adhesion Energy. In the application phase, the power-law function prediction model can be used to quickly predict the Adhesion Energy. Specifically, when evaluating a new set of laser process parameters, only the corresponding finite element model needs to be established, simulation data obtained, and the TER value corresponding to the new laser process parameters calculated. Then, this TER value is substituted into the power-law function prediction model (fitting the curve), and the model's output value is the predicted Adhesion Energy under the new process parameters.

[0069] In summary, this application has at least the following innovative features compared with the prior art:

[0070] This application proposes a new key physical indicator: the temperature-energy ratio (TER) is defined for the first time. This indicator can extract key features from complex transient thermal history and has been proven to be the core parameter for controlling interfacial binding energy. Thus, the interfacial binding energy corresponding to new laser parameters can be predicted quickly and accurately through the temperature-energy ratio.

[0071] This application achieves a leap from physical trial and error to simulation prediction: using TER as a bridge, this scheme transforms the expensive, time-consuming, and inefficient scratch experiment optimization process into a low-cost, high-efficiency computer simulation prediction process.

[0072] High prediction accuracy and clear physical meaning: such as Figure 2 As shown, there is a strong power-law correlation between TER and interface binding energy, which proves the accuracy of the prediction model and the effectiveness of the TER index.

[0073] Accurate simulation model: Abaqus simulation was performed using a double ellipsoidal heat source model, which is closer to the actual physical process of laser sintering than traditional point heat sources or Gaussian heat sources, ensuring the accuracy of the simulation data, which is the basis for the accuracy of TER calculations.

[0074] The interface binding energy determination device provided in the embodiments of this application is described below. The interface binding energy determination device described below and the interface binding energy determination method described above can be referred to in correspondence.

[0075] See Figure 3 , Figure 3 This application provides a schematic diagram of a device for determining the interfacial bonding energy of laser-sintered thin films, which specifically includes:

[0076] The first acquisition module 11 is used to acquire the laser parameters to be evaluated;

[0077] The second acquisition module 12 is used to establish a finite element model of the thin film and the substrate, and to perform simulation on the finite element model using a heat source model and the laser parameters to obtain simulation data; wherein, the simulation data is the data of temperature change over time on the simulated laser sintering path;

[0078] The calculation module 13 is used to calculate the temperature-energy ratio based on the simulation data; the temperature-energy ratio is used to represent the relative relationship between instantaneous thermal shock and total heat input;

[0079] The prediction module 14 is used to input the temperature-energy ratio into the power function prediction model and predict the interfacial bonding energy of the thin film under the laser parameters through the power function prediction model; wherein, the generation process of the power function prediction model is as follows: each thin film sample is prepared by different experimental laser parameters, and the power function prediction model is generated by fitting the interfacial bonding energy of each thin film sample and the temperature-energy ratio of each thin film sample.

[0080] As an optional embodiment, the device further includes: a first determining module; the first determining module is specifically used to: perform micron scratch experiments on each thin film sample to determine the critical load of each thin film sample and the scratch width when the substrate is exposed; perform nanoindentation experiments on each thin film sample to determine the elastic modulus of each thin film sample; and determine the interfacial bonding energy of each thin film sample based on the thickness, critical load, elastic modulus, scratch width, and interfacial bonding energy calculation rules of each thin film sample.

[0081] The rules for calculating the interface binding energy are as follows:

[0082] ;

[0083] in, Indicates interface bonding energy, Indicates the critical load. Indicates the thickness of the thin film sample. Indicates the elastic modulus. Indicates the width of the scratch.

[0084] As an optional embodiment, the device further includes: a second determining module; the second determining module is specifically used for: establishing experimental finite element models of each thin film sample and the substrate; performing simulations on the corresponding experimental finite element models using a heat source model and experimental laser parameters corresponding to each thin film sample to obtain experimental simulation data; wherein the experimental simulation data is data on temperature changes over time along the simulated laser sintering path; and determining the temperature-energy ratio of each thin film sample using temperature-energy ratio calculation rules and the experimental simulation data of each thin film sample. The temperature-energy ratio calculation rules are as follows:

[0085] ;

[0086] in, The temperature-energy ratio, For temperature, For time.

[0087] As an optional embodiment, the heat source model is a double ellipsoidal heat source model. The double ellipsoidal heat source model simulates the energy distribution and heat flux density of the moving laser beam inside the finite element model using laser parameters, and obtains simulation data of the temperature change over time on the sintering path during transient thermal analysis.

[0088] As an optional embodiment, the device further includes a prediction model generation module; the prediction model generation module is specifically used to: use the interfacial bonding energy of each thin film sample as Y-axis data, use the temperature-energy ratio of each thin film sample as X-axis data, and generate coordinate data for each data point; and perform nonlinear fitting on the coordinate data of each data point using a power function to obtain a power function prediction model.

[0089] Figure 4 A structural diagram of an electronic device provided in an embodiment of the present invention is shown in the figure. It includes: a memory 20 for storing a computer program; and a processor 21 for executing the computer program to implement the steps of the interface bonding capability determination method as described in the above embodiment.

[0090] The electronic devices provided in this embodiment may include, but are not limited to, smartphones, tablets, laptops, or desktop computers.

[0091] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as the Central Processing Unit (CPU), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an Artificial Intelligence (AI) processor, which handles computational operations related to machine learning.

[0092] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 20 is used to store at least the following computer program 201, which, after being loaded and executed by the processor 21, is capable of implementing the relevant steps of the interface bonding performance determination method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, and the storage method may be temporary storage or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc.

[0093] In some embodiments, the electronic device may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0094] Those skilled in the art will understand that Figure 4 The structures shown do not constitute a limitation on electronic devices and may include more or fewer components than those shown.

[0095] In another exemplary embodiment, a computer storage medium is also provided, wherein the program instructions, when executed by a processor, implement the steps of the data deduplication method described in any of the above method embodiments.

[0096] It is understood that if the interface combination method described in the above embodiments is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the current technology, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, magnetic disk, or optical disk, and other media capable of storing program code.

[0097] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here.

[0098] The various embodiments described in this specification are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” used herein may also mean the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a specific order described or illustrated, unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0099] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the permission and consent of the object, the permission and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the permission and consent of the object.

[0100] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for determining the interfacial bonding energy of laser-sintered thin films, characterized in that, The method for determining the interfacial bonding energy includes: Obtain the laser parameters to be evaluated; A finite element model of the thin film and substrate is established, and simulation is performed on the finite element model using a heat source model and the laser parameters to obtain simulation data; wherein, the simulation data is the temperature change over time along the simulated laser sintering path; the heat source model is a double ellipsoidal heat source model; The temperature-energy ratio is calculated based on the simulation data; the temperature-energy ratio represents the relative relationship between instantaneous thermal shock and total heat input; wherein, the temperature-energy ratio is calculated using the temperature-energy ratio calculation rules and simulation data, and the temperature-energy ratio calculation rules are as follows: ; The temperature-energy ratio, For temperature, For time; The temperature-energy ratio is input into the power function prediction model, and the interfacial bonding energy of the thin film under the laser parameters is predicted by the power function prediction model. The generation process of the power function prediction model is as follows: each thin film sample is prepared by different experimental laser parameters, and the power function prediction model is generated by fitting the interfacial binding energy of each thin film sample and the temperature-energy ratio of each thin film sample.

2. The method for determining interfacial bonding energy according to claim 1, characterized in that, The process of determining the interfacial bonding energy of each thin film sample includes: Micron-level scratch tests were performed on each thin film sample to determine the critical load of each thin film sample and the scratch width when the substrate was exposed. Nanoindentation experiments were performed on each thin film sample to determine the elastic modulus of each thin film sample. The interfacial bonding energy of each thin film sample is determined based on its thickness, critical load, elastic modulus, scratch width, and the interfacial bonding energy calculation rules.

3. The method for determining interfacial bonding energy according to claim 2, characterized in that, The rules for calculating interface binding energy are as follows: ； in, Indicates interface bonding energy, Indicates the critical load. Indicates the thickness of the thin film sample. Indicates the elastic modulus. Indicates the width of the scratch.

4. The method for determining interfacial bonding energy according to claim 1, characterized in that, The process of determining the temperature-energy ratio of each thin film sample includes: Establish experimental finite element models of each thin film sample and substrate; By using a heat source model and experimental laser parameters corresponding to each thin film sample, simulations are performed on the corresponding experimental finite element model to obtain experimental simulation data; wherein, the experimental simulation data is the data on temperature change over time along the simulated laser sintering path; The temperature-energy ratio of each thin film sample was determined by using the temperature-energy ratio calculation rules and experimental simulation data of each sample.

5. The method for determining interfacial bonding energy according to claim 4, characterized in that, The double ellipsoidal heat source model simulates the energy distribution and heat flux density of a moving laser beam within the finite element model using laser parameters, and obtains simulation data of temperature changes over time along the sintering path during transient thermal analysis.

6. The method for determining interfacial bonding energy according to any one of claims 1 to 5, characterized in that, Based on the interfacial binding energy of each thin film sample and the temperature-energy ratio of each thin film sample, a power-law function prediction model is generated, including: The interfacial bonding energy of each thin film sample is used as the Y-axis data, and the temperature-energy ratio of each thin film sample is used as the X-axis data to generate the coordinate data of each data point. A power function prediction model is obtained by nonlinearly fitting the coordinate data of each data point to the power function.

7. A device for determining the interfacial bonding energy of laser-sintered thin films, characterized in that, The interfacial bonding energy determining device includes: The first acquisition module is used to acquire the laser parameters to be evaluated; The second acquisition module is used to establish a finite element model of the thin film and the substrate, and to perform simulation on the finite element model using a heat source model and the laser parameters to obtain simulation data; wherein, the simulation data is the temperature change over time along the simulated laser sintering path; the heat source model is a double ellipsoidal heat source model; The calculation module is used to calculate the temperature-energy ratio based on the simulation data; the temperature-energy ratio represents the relative relationship between instantaneous thermal shock and total heat input; wherein, the temperature-energy ratio is calculated using temperature-energy ratio calculation rules and simulation data, and the temperature-energy ratio calculation rules are as follows: ; The temperature-energy ratio, For temperature, For time; The prediction module is used to input the temperature-energy ratio into the power function prediction model, and predict the interfacial bonding energy of the thin film under the laser parameters through the power function prediction model; wherein, the generation process of the power function prediction model is as follows: each thin film sample is prepared by different experimental laser parameters, and the power function prediction model is generated by fitting the interfacial bonding energy of each thin film sample and the temperature-energy ratio of each thin film sample.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the interface bonding energy determination method as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the interface bonding energy determination method as described in any one of claims 1 to 6.

Images