Laser-induced graphene in-situ multi-element controllable doping method

Abstract

The invention relates to a laser-induced graphene in-situ multi-element controllable doping method which comprises the following steps: preparing a flexible substrate containing a carbon polymer, depositing a plurality of layers of micro-nano doping materials on the surface of the flexible substrate, and then carrying out laser processing according to a preset laser scanning path to obtain an in-situ doped graphene film; the method comprises the following steps: acquiring in-situ doping process parameter data sets of different batches of graphene films, establishing a mapping relationship between in-situ doping process parameters and electrochemical performance indexes, further constructing an initial prediction model by using a machine learning algorithm, and training the prediction model through a cross validation method; and inputting the target electrochemical performance indexes into the trained prediction model, outputting in-situ doping process parameters meeting the electrochemical performance requirements, and then dynamically adjusting the in-situ doping process to prepare the in-situ multi-element controllable doped graphene film. The flexible supercapacitor has the effect of improving the electric storage capacity of the flexible supercapacitor taking the multi-material doped graphene as the electrode.

Description

Technical Field

[0001] The present invention relates to the technical field of capacitors, and particularly to a method for in-situ multi-element controllable doping of laser-induced graphene. Background Art

[0002] Graphene, as a typical electrode material for energy storage devices, has been intensively studied in many application fields due to its excellent electrical, mechanical, and optical properties. Especially in the fields of high-performance capacitors, wearable flexible sensors, and electrocatalytic applications, graphene has shown great application potential. In the field of high-performance capacitors, in the face of the increasing demand for energy conversion and storage, it is particularly crucial to improve the energy storage performance of graphene electrodes.

[0003] Research has shown that by introducing heteroatom doping and nanoparticle modification in graphene, the capacitance characteristics of graphene electrodes can be significantly enhanced. This discovery has important scientific value for enhancing the electrical storage performance of supercapacitors based on graphene electrodes. For example, nitrogen-doped graphene can significantly improve the specific capacitance and cycle stability of supercapacitors. The polyaniline nanowires formed on the surface of graphene using in-situ polymerization technology are more tightly combined with graphene, which helps to exert the pseudocapacitance effect, thereby greatly increasing the specific capacitance of graphene supercapacitors and further promoting the application of graphene in the field of supercapacitors.

[0004] Although significant progress has been made in the research on the preparation process of graphene and its derivative materials, this field still faces many challenges, such as the complexity of the preparation process, high processing costs, long time consumption, and environmental pollution. In addition, current research on improving the energy storage performance of graphene through doping mainly focuses on non-metal element doping or single-element doping, while the research on doping with transition metal elements, metal oxides, and two-dimensional materials and the modification of new nanomaterial particles is relatively less. When doping graphene thin film materials, it is usually limited to a single element, and there is a lack of effective research methods for controllable doping of multiple elements, which needs to be improved. Summary of the Invention

[0005] The problem to be solved by the present invention is to provide a method for in-situ multi-element controllable doping of laser-induced graphene to achieve the purpose of regulating and improving the electrical storage capacity of flexible supercapacitors with graphene thin film doped with multi-element materials as electrodes.

[0006] The above invention object of the present invention is achieved by the following technical solutions: A method for in-situ multi-element controllable doping of laser-induced graphene, comprising the following steps: S1. Prepare a flexible substrate of carbon-containing polymer. After depositing several layers of doping materials on the surface of the flexible substrate, perform laser processing according to a preset laser scanning path to provide local high-temperature and high-pressure conditions through carbon dioxide laser, complete the processes of decomposition, carbonization, and carbon atom recombination of the carbon-containing polymer to form graphene, and complete the in-situ doping of the doping materials in the graphene to obtain a doped graphene film; S2. Collect the in-situ doping process parameter datasets of different batches of doped graphene films, establish the mapping relationship between the in-situ doping process parameters and the electrochemical performance indicators, then use a machine learning algorithm to construct an initial prediction model, and train the prediction model through a cross-validation method; S3. Input the target electrochemical performance indicator into the trained prediction model, output the in-situ doping process parameters that meet the electrochemical performance requirements, and then dynamically adjust the in-situ doping process in S1 to obtain a graphene film with in-situ multi-element controllable doping.

[0007] Further, in S1, the carbon-containing polymer is a polyimide film or a microporous polyethersulfone film.

[0008] Further, in S1, the doping material is one or a combination of several of transition metal materials (such as silver, copper, titanium, tellurium, etc. without limitation), transition metal disulfide materials, black phosphorus materials, MXene two-dimensional materials, and perovskite quantum dot materials.

[0009] Further, in S1, control the deposition thickness of the doping material to be 50 - 150 nm, and the deposition method is physical vapor deposition (such as thermal evaporation, magnetron sputtering without limitation).

[0010] Further, in S1, place the deposited flexible substrate on a laser processing platform, construct a 2D processing model of laser-induced graphene, the 2D processing structure model is a filled rectangle of 20 mm × 20 mm, and the filling density is 5000 - 15000 Dpi, and then determine the laser scanning path.

[0011] Further, in S1, use a carbon dioxide laser with a central wavelength of 10.6 mm, a frequency of 5 KHz, and a power of 50 W for laser processing, and control the laser power to be 7.5 - 17.5 W, and the laser scanning speed to be 200 - 400 mm / s.

[0012] Further, the specific implementation of S3 is as follows: Input the target electrochemical performance index and the type of doping material into the trained prediction model. The prediction model first determines whether the doping material used can achieve the target electrochemical performance. If it can be achieved, the prediction model will output the corresponding in-situ doping process parameters. Otherwise, the prediction model will reselect the type of doping material, and then dynamically adjust the in-situ doping process of S1 to obtain a graphene film with in-situ multi-element controllable doping.

[0013] In summary, the beneficial technical effects of the present invention are as follows: 1. The present invention uses a polyimide film or a microporous polyethersulfone material as a pre-treated sample, and prepares a multi-element doped material film layer on the pre-treated sample by physical vapor deposition technology. While converting the polyimide or polyethersulfone material in the pre-treated sample into graphene by laser induction, doping atoms and nanoparticles in the multi-element doped layer, such as transition metal elements, metal oxides, two-dimensional materials, and novel nanomaterials, are introduced into the graphene, creating laser-induced graphene (MD-LIG) with multi-element effective heteroatom doping and nanoparticle modification, which improves the electrochemical performance and electrochemical activity of the film. 2. The present invention constructs a database of in-situ doping processes for graphene films and a machine learning prediction model, adjusts the parameters to adapt to the training data, and simultaneously uses the cross-validation method to train the initial prediction model, thereby improving the prediction accuracy and generalization ability of the prediction model. The finally obtained prediction model can be used to guide the dynamic adjustment of the in-situ doping process of S1, realizing the precision and efficiency of graphene in-situ multi-element doping design, and greatly shortening the cycle of material research and development and process optimization. 3. The MD-LIG prepared by the present invention has excellent electrochemical performance and can be used as an electrode material for flexible supercapacitors, and is expected to be applied in fields such as high-performance capacitors, wearable flexible sensors, and electrocatalysis, having important practical application value. Description of the Drawings

[0014] Figure 1 is a flowchart of S1 provided in Embodiment 2 of the present invention.

[0015] Figure 2 is the electron microscope characterization and EDS element mapping diagram of the doped graphene film in Embodiment 13 of the present invention.

[0016] Figure 3 is a flowchart of the preparation process of the flexible supercapacitor in Embodiment 13 of the present invention.

[0017] Figure 4 is the cyclic voltammetry curve, specific capacitance curve, and galvanostatic charge-discharge curve diagram of the flexible supercapacitor in Embodiment 13 of the present invention.

[0018] Figure 5It is the cyclic voltammetry curve and constant current charge-discharge curve diagram of the copper-doped graphene flexible supercapacitor prepared based on the process parameters of the prediction model in Embodiment 14 of the present invention. Detailed implementation manners

[0019] In order to make the technical means, creative features, achieved purposes and functions of the present invention clearer and easier to understand, the present invention will be further described below in conjunction with the accompanying drawings and specific implementation manners.

[0020] Embodiment 1: A method for in-situ multi-element controllable doping of laser-induced graphene disclosed by the present invention includes the following steps: S1. Prepare a flexible substrate containing a carbon polymer. After depositing several layers of doping materials on the surface of the flexible substrate, perform laser processing according to a preset laser scanning path to provide local high-temperature and high-pressure conditions through a carbon dioxide laser, complete the processes of decomposition, carbonization, and carbon atom recombination of the carbon polymer to form graphene, and complete the in-situ doping of the doping materials in the graphene to obtain a doped graphene film; S2. Collect the in-situ doping process parameter data sets of different batches of doped graphene films, establish the mapping relationship between the in-situ doping process parameters and the electrochemical performance indicators, then use a machine learning algorithm to construct an initial prediction model, and train the prediction model through a cross-validation method; S3. Input the target electrochemical performance indicators into the trained prediction model, output the in-situ doping process parameters that meet the electrochemical performance requirements, and then dynamically adjust the in-situ doping process of S1 to obtain an in-situ multi-element controllable doped graphene film.

[0021] Embodiment 2: Refer to Figure 1 , a method for in-situ multi-element controllable doping of laser-induced graphene disclosed by the present invention. The difference from Embodiment 1 is that the specific implementation manner of S1 is as follows: S11. Prepare a polyimide film as the flexible substrate, and clean the used flexible substrate in an alcohol bath using ultrasonic cleaning technology; S12. Use a physical vapor deposition device to deposit doping materials with a thickness of about 50 - 150 nm on the already cleaned flexible substrate. In this embodiment, transition metal materials, such as silver, are preferably used; S13. Use AutoCAD software to construct a 2D processing model of laser-induced graphene. The 2D processing structure model is a filled rectangle of 20 mm × 20 mm, with a filling density of 10000 Dpi, save it as a DXF file, import it into the laser control software, generate a scanning path file, and then determine the laser scanning path; S14. Place the deposited flexible substrate on the three-dimensional moving platform of the laser processing platform, focus the laser focus on the surface of the doping material, and use a carbon dioxide laser with a central wavelength of 10.6 mm, a frequency of 5 KHz, and a power of 50 W for laser processing. Set the laser power to 7.5 W and the laser scanning speed to 200 mm / s. Provide local high-temperature and high-pressure conditions through the carbon dioxide laser to complete the process of decomposing, carbonizing, and reorganizing carbon atoms of polyimide to form graphene, and complete the in-situ doping of the doping material in graphene to obtain a doped graphene film.

[0022] Examples 3 - 12: A method for in-situ multi-element controllable doping of laser-induced graphene disclosed by the present invention is different from Example 2 in that the in-situ doping process parameters are shown in Table 1 below.

[0023] Table 1 Laser power / W Scanning speed / mm / s Scanning density / Dpi Doping material Deposit layer thickness / nm Example 2 7.5 200 10000 Ag 50 Example 3 12.5 200 10000 Ag 50 Example 4 17.5 200 10000 Ag 50 Example 5 12.5 300 10000 Ag 50 Example 6 12.5 400 10000 Ag 50 Example 7 12.5 200 5000 Ag 50 Example 8 12.5 200 15000 Ag 50 Example 9 12.5 200 10000 Cu 50 Example 10 12.5 200 10000 Ti 50 Example 11 12.5 200 10000 Cu 100 Example 12 12.5 200 10000 Ti 150 Example 13: A method for in-situ multi-element controllable doping of laser-induced graphene disclosed by the present invention is different from Examples 2 - 12 in that the specific implementation manner of S2 is as follows: S21. Take the doped graphene film obtained in Examples 2 - 12 as a sample, and use test methods such as scanning electron microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy to characterize it, analyze its microscopic morphology and the influence of the doped transition metal components, so as to obtain the morphological characteristic data of the doped graphene film, and the results are as Figure 2 shown; S22. Refer to Figure 3 , when using the above sample as an electrode to prepare a flexible supercapacitor, use laser etching to selectively etch the prepared multi-doped graphene material to form an interdigital electrode structure. Among them, the scanning speed, power, and repetition frequency of the laser used are 200 mm / s, 9 W, and 20 kHz respectively. Etch the multi-doped graphene material into an interdigitated electrode pattern, with the length of each finger being 5 mm, the width being 1 mm, and the adjacent spacing being 0.5 mm; Add 2.00 g of polyvinyl alcohol to a beaker containing 20.00 mL of distilled water, and stir it with a magnetic stirrer at 85 °C for 2 h until it is completely dissolved. Then dissolve 2.00 g of potassium hydroxide in 10.00 mL of distilled water, pour the polyvinyl alcohol solution into the potassium hydroxide solution, stir evenly and let it stand until the solution becomes clear and the bubbles are removed to obtain the gel electrolyte of the flexible capacitor; Drop the above gel electrolyte between the interdigitated electrode patterns, stick copper foil tape at the end of the interdigitated electrode, and encapsulate it with polypropylene to obtain a flexible supercapacitor; Use an electrochemical workstation to test the electrochemical performance of the prepared supercapacitor to obtain its cyclic voltammetry curve and constant current charge-discharge curve, and the test results are as Figure 4 shown; S23. Collect the in-situ doping process parameters and electrochemical performance indicators of doped graphene films in different batches. The in-situ doping process parameters include the type of doping material, deposition thickness, laser power, laser scanning speed, laser scanning density, and the morphological characteristics of the doped graphene film. The electrochemical performance indicators include the cyclic voltammetry curve and galvanostatic charge-discharge curve of the flexible supercapacitor prepared from the doped graphene film. Sort out the collected data, perform format conversion and noise processing. Select the MySQL database management system, design the table structure and import the collected data to construct a dataset of in-situ doping process parameters, and establish a mapping relationship between the in-situ doping process parameters of the graphene film and the electrochemical performance. S24. Use the random forest supervised learning algorithm to construct an initial prediction model, and train the initial prediction model by feeding the in-situ doping experimental data of doped graphene films in different batches, so that it can predict the electrochemical performance of the flexible supercapacitor prepared from the doped graphene film. S25. Split the in-situ doping process parameter dataset into a training set and a validation set by the random split cross-validation method. Reduce the overfitting risk by splitting the dataset multiple times and repeating training and evaluation. Adjust the parameters according to the prediction model evaluation results to improve the accuracy and generalization ability of the prediction model.

[0024] Example 14: A method for in-situ multi-element controllable doping of laser-induced graphene disclosed in the present invention. The difference from Example 1 is that the specific implementation of S3 is as follows: Input the target electrochemical performance indicator and the type of doping material into the trained prediction model. The prediction model first judges whether the adopted doping material can achieve the target electrochemical performance. If it can be achieved, the prediction model will output the corresponding in-situ doping process parameters. Otherwise, the prediction model will re-select the type of doping material, and then dynamically adjust the in-situ doping process of S1 to obtain the in-situ multi-element controllable doped graphene film.

[0025] In practical applications, the flexible supercapacitor needs to have a high specific capacitance to meet its usage requirements. Therefore, the specific capacitance of the flexible supercapacitor higher than 1 mF / cm 2 and the used doping material being copper are imported into the prediction model designed in S3. After model analysis and judgment, the output result is that when copper is used as the doping material, a flexible supercapacitor with a specific capacitance higher than 1 mF / cm 2 can be obtained. At the same time, the prediction system outputs the optimal parameters of the graphene in-situ doping process as the doping material being copper, the deposition layer thickness being 50 nm, the laser power being 12.5 W, the laser scanning speed being 200 mm / s, and the laser scanning density being 10000 Dpi. After obtaining the in-situ doping process parameters, graphene in-situ doping is carried out.

[0026] Correspondingly, as described in Example 2, a polyimide film was prepared as a flexible substrate, and the flexible substrate used was cleaned in an alcohol bath by ultrasonic cleaning technology; A silver coating with a thickness of about 50 nm was deposited on the cleaned flexible substrate using a physical vapor deposition apparatus; Set the process parameters of graphene in-situ doping, use AutoCAD software to construct a 2D processing model of laser-induced graphene. The 2D processing structure model is a filled rectangle of 20 mm × 20 mm, and the filling density is 10000 Dpi. Save it as a DXF file, import it into the laser control software, generate a scan path file, and then determine the laser scan path; Place the flexible substrate with the deposited silver coating on the three-dimensional moving platform of the laser processing platform, focus the laser focus on the surface of the doping material, and use a carbon dioxide laser with a central wavelength of 10.6 mm, a frequency of 5 KHz, and a power of 50 W for laser processing. Set the laser power to 12.5 W and the laser scan speed to 200 mm / s to obtain a copper-doped graphene film.

[0027] Correspondingly, the obtained copper-doped graphene film was used to prepare a flexible supercapacitor as described in Example 13, and a performance test was carried out using an electrochemical workstation to obtain the cyclic voltammetry curve and the galvanostatic charge-discharge curve of the flexible supercapacitor. The test results are as Figure 5 shown. It can be calculated that the specific capacitance of the copper-doped graphene supercapacitor is 1.1 mF / cm 2 , meeting the requirements proposed above.

[0028] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the purpose and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A laser-induced graphene in-situ multi-element controllable doping method, characterized in that: The following steps are involved: S1. Prepare a flexible substrate containing a carbon polymer, deposit several layers of doping materials on the surface of the flexible substrate, and then perform laser processing according to a preset laser scanning path, so as to provide local high temperature and high pressure conditions through a carbon dioxide laser to complete the process of decomposition, carbonization, and carbon atom recombination of the carbon-containing polymer to form graphene, and complete in-situ doping of the doping materials in the graphene to obtain a doped graphene film; S2. Collect in-situ doping process parameter data sets of different batches of doped graphene films, establish a mapping relationship between in-situ doping process parameters and electrochemical performance indicators, and then use machine learning algorithms to build an initial prediction model, and train the prediction model through a cross-validation method; S3, inputting the target electrochemical performance index into the trained prediction model, outputting the in-situ doping process parameters that meet the electrochemical performance requirements, and then dynamically adjusting the in-situ doping process of S1 to obtain an in-situ multi-element controllably doped graphene film.

2. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In S1, the carbon-containing polymer is a polyimide film or a microporous polyethersulfone film.

3. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In S1, the doping material is one or a combination of transition metal materials, transition metal disulfide materials, black phosphorus materials, MXene two-dimensional materials and perovskite quantum dot materials.

4. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In the step S1, the deposition thickness of the doping material is controlled to be 50-150 nm, and the deposition method is physical vapor deposition.

5. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In the S1, the deposited flexible substrate is placed on a laser processing platform to construct a 2D processing model of laser-induced graphene. The 2D processing structure model is a filled rectangle of 20 mm×20 mm with a filling density of 5000-15000 Dpi, thereby determining the laser scanning path.

6. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In S1, a carbon dioxide laser with a central wavelength of 10.6 mm, a frequency of 5 KHz, and a power of 50 W is used for laser processing, and the laser power is controlled to be 7.5-17.5 W, and the laser scanning speed is 200-400 mm / s.

7. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In S2, the in-situ doping process parameters include the type of doping material, deposition thickness, laser power, laser scanning speed, laser scanning density and doped graphene film morphology characteristics.

8. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: In S2, the electrochemical performance indicators include the cyclic voltammetry curve and the constant current charge-discharge curve of the flexible supercapacitor made of the doped graphene film.

9. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: The specific implementation of S2 is: S21. Collect in-situ doping process parameters and electrochemical performance indicators of different batches of doped graphene films, perform data combing, format conversion, and noise processing on the collected data, select a database management system, design a table structure, and import the collected data to construct an in-situ doping process parameter data set, and establish a mapping relationship between the in-situ doping process parameters of the graphene film and the electrochemical performance; S22. constructing an initial prediction model using a supervised learning algorithm or an unsupervised learning algorithm, and training the initial prediction model by feeding in-situ doping experimental data of different batches of doped graphene films, so that the initial prediction model can predict the electrochemical performance of a flexible supercapacitor made of doped graphene films; S23. The in-situ doping process parameter data set is split into a training set and a validation set by a cross-validation method. The risk of overfitting is reduced by splitting the data set multiple times and repeating the training and evaluation. The parameters are adjusted according to the prediction model evaluation structure to improve the accuracy and generalization ability of the prediction model.

10. The laser-induced graphene in-situ multi-element controllable doping method according to claim 1, characterized in that: The specific implementation method of S3 is: input the target electrochemical performance index and the type of doping material into the trained prediction model, the prediction model first determines whether the adopted doping material can achieve the target electrochemical performance, if it can be achieved, the prediction model will output the corresponding in-situ doping process parameters, otherwise, the prediction model will reselect the type of doping material, and then dynamically adjust the in-situ doping process of S1 to obtain an in-situ multi-element controllably doped graphene film.

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