Automated manufacturing method of nano-magnesium-based hydrogen storage material

Abstract

This application relates to the technical field of metal material spectral analysis, and specifically to an automated manufacturing method for nano-magnesium-based hydrogen storage materials. The method comprises: mixing metal oxides and nano-graphene sheets to prepare mixed solutions A and B, dripping mixed solution A into mixed solution B and stirring, acquiring spectral data during the stirring process, determining a flocculent evaluation coefficient based on the degree of difference in reflection intensity corresponding to pixels in the hyperspectral gel data and the contour information of potential defect areas, and adjusting the stirring temperature; determining the bubble confidence level of the potential defect area based on the change in the reflection intensity of the pixels, and controlling the stirring time to obtain a carbon gel; grinding the carbon gel to obtain a composite catalyst, ball-milling magnesium powder and the composite catalyst, synthesizing a powdered magnesium-based hydrogen storage material via a hydrogenation combustion method, and further ball-milling to obtain a nano-magnesium-based hydrogen storage material. This application can improve the preparation quality of hydrogen storage materials.

Description

Technical Field

[0001] The present application relates to the technical field of material spectral analysis, and in particular to an automated manufacturing method for nano-magnesium-based hydrogen storage materials. Background Art

[0002] Hydrogen storage materials, which are materials capable of storing and releasing hydrogen, have important applications in energy storage, hydrogen-powered vehicles, and industrial gas processing. The production process for metal powders generally involves selecting raw materials, smelting and crushing them, and then ball milling and screening to obtain the desired refined metal powder. The preparation of hydrogen storage materials primarily utilizes the nanoconfinement method to prepare carbon gels containing metal catalysts. Nano-MgH2 is then uniformly loaded into the three-dimensional grid structure of the carbon gel, improving the thermodynamic properties of the nano-Mg for hydrogen absorption and desorption.

[0003] However, during the preparation of the gel composite catalyst, the gel time needs to be strictly controlled according to the reaction temperature and acidity. During the gel process, hydrolysis and polycondensation reactions occur simultaneously. If the gel time is short and the hydrolysis rate is too fast, a white flocculent precipitate will be produced, causing the gel preparation to fail, or the pores in the prepared wet gel will be small, and the water will not be discharged during the subsequent drying. If the gel time is long, the hydrolysis reaction will be inhibited, the polycondensation reaction will be promoted, the gel time will be extended, and the pores of the wet gel will be larger, reducing the contact area with nano-MgH2, affecting the hydrogen storage capacity of the nano-magnesium base. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides an automated manufacturing method for nano-magnesium-based hydrogen storage materials to solve the existing problems.

[0005] The automated manufacturing method of a nano-magnesium-based hydrogen storage material of the present application adopts the following technical solution:

[0006] One embodiment of the present application provides an automated manufacturing method for nano-magnesium-based hydrogen storage materials, the method comprising the following steps:

[0007] The metal oxide and nanographene sheets are mixed and treated to obtain functionalized graphene; the functionalized graphene and tetrabutyl titanate are added to isopropyl alcohol and magnetically stirred for 1 to 3 hours to obtain a mixed solution A;

[0008] Scandium nitrate monohydrate is added to isopropyl alcohol and the acid is adjusted. The mixture is stirred and mixed to obtain a mixed solution B, which is then placed in a constant temperature bath at 10°C to 20°C. Mixed solution A is dripped into mixed solution B at a rate of 1 to 5 drops per second and stirred. The gel state is analyzed during the stirring process to control the stirring time. The specific process is as follows:

[0009] Obtain hyperspectral gel data at each sampling moment during the stirring process. Based on the difference in reflection intensity of pixels corresponding to each potential defect area in the hyperspectral gel data and the contour information of each potential defect area, determine the flocculent evaluation coefficient of each potential defect area to adjust the temperature of the stirring reaction process.

[0010] The bubble confidence of each potential defect area is determined based on the change in the reflection intensity of the pixels in each potential defect area, the real bubble area is extracted, and the stirring time is controlled according to the number of real bubble areas at each sampling moment to obtain carbon gel;

[0011] The carbon gel is ground to obtain a composite catalyst, magnesium powder and the composite catalyst are ball-milled, and then a powdered magnesium-based hydrogen storage material is synthesized by a hydrogenation combustion method, and the nano-magnesium-based hydrogen storage material is obtained by ball-milling again.

[0012] Furthermore, the process of obtaining the functionalized graphene is as follows:

[0013] The nanographene sheet is placed in a metal oxide, refluxed at 150°C~200°C for 5h~7h, cooled to room temperature, washed with deionized water until neutral, and dried at 70°C~90°C to obtain functionalized graphene.

[0014] Furthermore, the floc evaluation coefficient of each potential defect area is determined as follows:

[0015] Each potential defect region is each connected domain in the pseudo-color image corresponding to the hyperspectral gel data;

[0016] Constructing the flocculent weight of each potential defect area based on the shape characteristics of each potential defect area;

[0017] Determine a difference result of each pixel in each potential defect area based on a difference between reflection intensities of each pixel in each potential defect area;

[0018] Determining a difference disorder coefficient of each potential defect region based on the degree of symmetry of the difference results of all pixels in each potential defect region, wherein the difference disorder coefficient is negatively correlated with the degree of symmetry;

[0019] The floc evaluation coefficient of each potential defect area is determined by the floc weight and the difference disorder coefficient of each potential defect area, wherein the floc evaluation coefficient is a forward fusion of the floc weight and the difference disorder coefficient.

[0020] Furthermore, the flocculent weight of each potential defect area is constructed as follows:

[0021] The flocculence weight of each potential defect region is determined based on the boundary shape aspect ratio and the circularity of each potential defect region, wherein the flocculence weight is positively correlated with the boundary shape aspect ratio and inversely correlated with the circularity.

[0022] Furthermore, the method for determining the difference results of each pixel in each potential defect area is: obtaining the neighboring pixels of each pixel, forming a pixel sequence of each pixel with the reflection intensity of each pixel at different wavelengths, and calculating the difference between each pixel and the pixel sequence of its neighboring pixels, which is recorded as the difference result of each pixel.

[0023] Furthermore, the temperature of the stirring reaction process is adjusted by:

[0024] For each potential defect area at each sampling moment, the flocculent evaluation coefficient is analyzed, and the proportion of potential defect areas with a flocculent value greater than a preset flocculent threshold value among all potential defect areas at each sampling moment is analyzed;

[0025] When the proportion is greater than the preset ratio, the temperature of the stirring reaction process is lowered by a preset value.

[0026] Furthermore, the method for determining the bubble confidence of each potential defect area is as follows:

[0027] Fitting the pixel sequence of each pixel in each potential defect area to construct a pixel curve for each pixel in each potential defect area;

[0028] The bubble confidence of each potential defect area is obtained based on the curve smoothness of each pixel in each potential defect area, wherein the bubble confidence of each potential defect area is positively correlated with the curve smoothness of each pixel therein.

[0029] Furthermore, the process of controlling the stirring time in combination with the number of real bubble regions at each sampling moment is as follows:

[0030] The appearance rate of the real bubble area corresponding to each sampling moment is counted. When the appearance rate is less than a preset percentage, the carbon gel quality at the corresponding sampling moment is qualified. When the appearance rate at multiple consecutive sampling moments is less than the preset percentage, stirring is stopped.

[0031] Furthermore, the method for obtaining the composite catalyst is:

[0032] The carbon gel is placed in an oven and dried for 12 h to 24 h, ground into powder, calcined at 600° C. to 650° C. in an air atmosphere for 3 h to 6 h, and then cooled to room temperature.

[0033] Furthermore, after ball milling the magnesium powder and the composite catalyst, a powdered magnesium-based hydrogen storage material is synthesized by a hydrogenation combustion method, and then ball milled again to obtain a nano-magnesium-based hydrogen storage material, specifically:

[0034] The magnesium powder and the composite catalyst are ball-milled for 6 to 12 hours at a ball-milling speed of 400 to 600 rpm. During the hydrogenation combustion synthesis process, the temperature is raised to 550 to 600°C in a 3MPa hydrogen atmosphere, kept warm for 1.5 to 3 hours, then cooled to 300 to 350°C and kept warm again for 4 to 6 hours, and cooled to room temperature to obtain a powdered magnesium-based hydrogen storage material. The material is then ball-milled for 12 to 24 hours in a 0.1MPa hydrogen atmosphere at a ball-milling speed of 400 to 600 rpm.

[0035] This application has at least the following beneficial effects:

[0036] This application analyzes the hyperspectral data of the blended solution in the glass container, analyzes the flocculent characteristics, air vortex characteristics, bubble area characteristics and interference area characteristics in the gel process, and performs micro-control on the gel process. Finally, the bubble confidence at each sampling moment is used to reflect the proportion of bubbles to determine the termination time of the gel process. In the prior art, by controlling the material ratio, batch production of nano-magnesium / graphene-loaded scandium trioxide and titanium dioxide hydrogen storage materials can be achieved. However, in the process of preparing carbon gel composite catalysts, improper reaction control is prone to cause carbon gel preparation failure or uneven carbon gel pores, resulting in the inability to load more magnesium-based materials and a low upper limit of hydrogen storage. This application analyzes the flocculent characteristics and bubble characteristics that are prone to appear in the gel process, which can control the gel time, improve the load capacity of the prepared nano-magnesium-based materials, and improve the thermodynamic properties and hydrogen storage capacity of the materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0038] Figure 1 A flowchart of the steps of an automated manufacturing method for a nano-magnesium-based hydrogen storage material provided in this application;

[0039] Figure 2 Schematic diagram of the process for determining the floc evaluation coefficient for each potential defect area;

[0040] Figure 3 This is a flow chart of temperature regulation during the stirring reaction process;

[0041] Figure 4 Flowchart for bubble confidence analysis of each potential defect area;

[0042] Figure 5 This is the flow chart of stirring time control in the carbon gel formation process. DETAILED DESCRIPTION

[0043] To further illustrate the technical means and effects employed by this application to achieve the intended invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the automated manufacturing method for a nano-magnesium-based hydrogen storage material proposed in this application, including its specific implementation, structure, features, and effects. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0044] Unless otherwise defined, terms such as "comprises," "comprising," or any other variants thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the article or device comprising the element. In addition, the term "and\or" as used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains.

[0045] The specific scheme of the automated manufacturing method of nano-magnesium-based hydrogen storage material provided by the present application is described in detail below with reference to the accompanying drawings.

[0046] An embodiment of the present application provides an automated manufacturing method for a nano-magnesium-based hydrogen storage material. Specifically, the following automated manufacturing method for a nano-magnesium-based hydrogen storage material is provided. Figure 1 The present application mainly provides a nano-magnesium-based hydrogen storage material with a carbon gel-loaded trace metal composite catalyst, and the manufacturing method includes the following steps:

[0047] Catalyst preparation:

[0048] a) placing nanographene sheets in a 65% scandium trioxide (S2O3) HNO3 solution, refluxing at 150°C for 7 hours, cooling to room temperature, and then washing with deionized water until neutral. The nanographene sheets are then dried at 70°C to obtain functionalized graphene, wherein the purity of the nanographene sheets is required to be greater than 99.5%. Acid washing is performed to remove impurities on the surface of the nanographene and to generate some active groups on the surface, which are conducive to oxide adsorption.

[0049] In another embodiment of the present application, in process a), the reflux temperature is 200° C., the reflux time is 5 h, and the drying temperature is 90° C.;

[0050] In other embodiments of the present application, the reflux temperature in process a) is 170°C, the reflux time is 6 hours, and the drying temperature is 80°C.

[0051] b) adding 0.4 g of functionalized graphene and 1.2768 g of tetrabutyl titanate to 10 mL of isopropanol, mixing by ultrasonic acceleration, and magnetic stirring for 1 hour to obtain a mixed solution A; adding 1.08 g of scandium nitrate monohydrate to 10 mL of isopropanol, followed by 8 mL of pure water, adjusting the acidity by adding 69% by mass concentrated nitric acid, and stirring to obtain a mixed solution B;

[0052] In another embodiment of the present application, the magnetic stirring time in process b) is 2 hours;

[0053] In other embodiments of the present application, the magnetic stirring time in process b) is 3 hours.

[0054] c) Mixed solution B is placed in a glass container in a constant temperature bath at 10°C and magnetically stirred. Mixed solution A is slowly added to mixed solution B at a rate of 1 drop / second until a carbon gel is formed.

[0055] In another embodiment of the present application, the temperature of the thermostatic bath in c) is 15° C., and the dripping rate of the mixed solution A is 3 drops / second;

[0056] In other embodiments of the present application, the temperature of the thermostatic bath in c) is 20° C., and the dripping rate of the mixed solution A is 5 drops / second.

[0057] During the stirring process, the stirring time is controlled to be 1h~5h. In order to ensure the quality of the carbon gel, the stirring termination of the carbon gel formation process is controlled. The specific process is as follows:

[0058] Step 1: Use hyperspectral acquisition equipment to obtain gel data during the gelation process.

[0059] To control the stirring time of the carbon gel, this application requires real-time acquisition of gel spectral data during the gelation process. This application places a hyperspectral acquisition device in a constant temperature bath, aligning the hyperspectral camera's position with the glass container containing mixed solution B. This allows for continuous acquisition of gel data during the gelation process. In this embodiment, the hyperspectral camera's sampling frequency is set to 10 seconds.

[0060] At this point, the spectral data collection during the gelation process is completed.

[0061] Step 2: Obtain the flocculent evaluation coefficient using the morphological characteristics of floccules and air vortices in the blend solution and the spectral pixel differences.

[0062] Ideally, a blend solution is formed by mixing solutions A and B, and the carbon gel formed under magnetic stirring in a thermostatic bath exhibits a uniform texture, free of bubbles and precipitates. However, in the actual gelation process, improper control can easily cause the hydrolysis reaction in the blend solution to be too rapid, resulting in the formation of a white flocculent precipitate. Furthermore, as magnetic stirring proceeds, the blend solution on the surface of the glass container easily entrains some air into the solution, causing bubbles to form in the gel, affecting the size of the carbon gel's microscopic pores and reducing the loading capacity of the nano-magnesium base.

[0063] When flocs form in a glass container, they often originate in the middle of the container and, as stirring progresses, develop a ribbon-like distribution, gradually descending and settling to the bottom. However, since the blended solution exhibits liquid characteristics when mixed solution A is added dropwise, air vortices are easily formed in the center of the container during magnetic stirring. Both air vortices and flocs can cause fluctuations in the reflection intensity of the gel data, but air vortices gradually disappear as gelation proceeds, so the air vortex area can interfere with the floc area.

[0064] To monitor the gel state during the gelation process, the gel data at each sampling moment was synthesized using ENVI software to generate a pseudo-color image of the gel data. Edge detection and connected domain analysis were then performed on the pseudo-color image to identify potential defect regions at the current sampling moment. Each connected domain was considered a potential defect region. Consequently, multiple potential defect regions were identified for each sampling moment. The relative positional relationship between pixels in the pseudo-color image and the hyperspectral gel data allowed the potential defect regions in the hyperspectral gel data to be determined. Based on the pixel characteristics of these potential defect regions, flocs and air vortices were distinguished.

[0065] When a single potential defect area corresponds to flocs, the overall shape of the area should show a filamentous and ribbon-like distribution, and due to the different overall thickness and material content of the flocs, the reflection intensity of the pixels in the floc area is quite different; if a single potential defect area corresponds to an air vortex, since it is caused by magnetic rotation, the air vortex is often in the middle of the glass container and is circular in shape.

[0066] Based on the morphological and pixel characteristics of flocs and air vortices, a floc evaluation coefficient is constructed to evaluate the floc situation in the gel hyperspectral data at the current sampling moment. The reflection intensity of each pixel at different wavelengths is combined into a pixel sequence for each pixel. The floc evaluation coefficient construction process is as follows:

[0067] Based on the morphological characteristics of flocs and air vortices, the boundary shape features are constructed according to the relative positions of the boundary pixels in each potential defect area. The floc weight of each potential defect area is obtained by using the boundary shape of each potential defect area, wherein the floc weight is positively correlated with the aspect ratio of the boundary shape and inversely correlated with the roundness.

[0068] In this embodiment, the flocculence weight of each pixel is the product of the aspect ratio of the boundary shape and a preset scaling factor greater than 1, and the scaling factor is 5.

[0069] It should be understood that if the potential defect area presents a filamentous and band-like distribution at the current sampling moment, the larger the aspect ratio of the boundary shape corresponding to the potential defect area and the smaller the roundness, the greater the flocculent weight obtained, indicating that the potential defect area is more likely to be a flocculent area.

[0070] Furthermore, in this embodiment, each pixel in the potential defect area is divided into 8 neighborhoods, the neighborhood pixels of each pixel are obtained, and the difference between the pixel sequence of each pixel and its neighborhood pixels is calculated, which is recorded as the difference result of each pixel. The difference measurement described in this embodiment adopts the DTW distance between sequences. The implementer can also use other methods of measuring the difference between sequences, and this application does not impose any special restrictions.

[0071] If the potential defect area is flocs, the varying thickness and content of the flocs within the area results in a more chaotic variation of the pixel differences within the area, resulting in a larger variation disorder coefficient. Conversely, if the potential defect area is an air vortex, since air vortices are often thicker in the middle and thinner on the sides, the variation of the pixel sequence will show a symmetrical pattern with larger differences in the middle and smaller differences on the sides, resulting in a smaller variation disorder coefficient. Therefore, based on the difference results of each pixel within the potential defect area, the variation disorder coefficient of the potential defect area is analyzed.

[0072] The difference disorder coefficient of each potential defect area is negatively correlated with the degree of symmetry of the difference results of all pixels in each potential defect area. The negative correlation means that the change trends between the variables are opposite, that is, the higher the degree of symmetry, the smaller the difference disorder coefficient.

[0073] Preferably, in this embodiment, the skewness and variance of the difference results of all pixels in each potential defect area are calculated, and the difference disorder coefficient of each potential defect area is the product of the skewness and variance of the difference results of all pixels in each potential defect area.

[0074] A floc evaluation coefficient of each potential defect region is determined based on the floc weight and the difference disorder coefficient of each potential defect region, wherein the floc evaluation coefficient is a forward fusion of the floc weight and the difference disorder coefficient.

[0075] It should be noted that the positive fusion means that the changing trends between the variables are the same, and the specific relationship can be addition, multiplication, square, etc. This application does not impose any special restrictions on this.

[0076] Preferably, in this embodiment, the forward fusion is an additive relationship, and the floc evaluation coefficient is the product of the floc weight and the difference disorder coefficient.

[0077] In actual application, as another embodiment, the forward fusion is a multiplication relationship, and the floc evaluation coefficient is the sum of the floc weight and the difference disorder coefficient.

[0078] It should be understood that if the boundary shape of the current potential defect area is ribbon-like or filamentous, the larger the floc weight value obtained, and the greater the difference fluctuation between the pixels in the area, the larger the value of the difference disorder coefficient obtained, which makes the floc evaluation coefficient larger, indicating that the current potential defect area is more likely to be a floc area.

[0079] For a detailed flow chart of determining the floc evaluation coefficient for each potential defect area, please refer to Figure 2 .

[0080] For each sampling moment, taking the current sampling moment as an example, all potential defect areas at that moment are traversed and the flocculent evaluation coefficients are normalized. Furthermore, a flocculent threshold is set, and the percentage of potential defect areas at the current sampling moment that exceed the flocculent threshold is calculated. When this percentage exceeds a preset ratio, indicating the presence of flocculents in the glass container, it indicates that the hydrolysis reaction in the blend solution at that sampling moment was rapid. To inhibit the hydrolysis reaction and improve gel quality, the constant temperature should be appropriately lowered by a preset value. The preset value for the temperature reduction can be set by the implementer based on the actual application scenario.

[0081] Preferably, in this embodiment, the flocculent threshold is set to 0.9, and when the proportion is greater than 5%, the temperature is lowered by 2°C.

[0082] In actual application scenarios, implementers can also set it themselves. As another implementation method, when the proportion is greater than 10%, the temperature is lowered by 5°C.

[0083] For details, please refer to the temperature regulation flow chart during the stirring reaction. Figure 3 .

[0084] Furthermore, as the gel forms, the blended solution will gradually become colloid-like. At this time, the surface blended solution will entrain air into the gel, forming bubbles in the gel. Due to the presence of bubbles, the microscopic pores of the wet gel are easily enlarged, which is not conducive to the gel's loading of nano-magnesium groups. The potential defect area at this time corresponds to the bubble area and interference area in the hyperspectral gel data. It is necessary to eliminate the interference of local noise on bubble detection to improve the accuracy of gel analysis during carbon gel formation and ensure the accuracy of stirring time control.

[0085] Considering that the bubble region is filled with air, the reflection intensity varies across wavelengths due to scattering and reflection. However, since adjacent wavelengths in hyperspectral data are relatively short, the pixel curve in the bubble region is relatively smooth. In the interference region, however, the random nature of noise may randomly affect each wavelength, resulting in a more volatile pixel curve.

[0086] Based on the characteristic differences between the bubble area and the interference area, the bubble confidence of each potential defect area is analyzed. The specific calculation process is as follows:

[0087] Based on the pixel sequence of each pixel, the pixel curve of each pixel is obtained by curve fitting, and the smoothness of the pixel curve is calculated for each pixel in the single potential defect area. The smoothness of the curve can be analyzed by existing technology, and this application does not make any special restrictions on this.

[0088] In this embodiment, the smoothness of the curve can be analyzed by the slope of the pixel curve, and the inverse of the slope of the curve is used as the smoothness of the curve.

[0089] In actual application, the implementer can also analyze the smoothness of the curve through the rate of change of the curve, and use the inverse of the rate of change of the curve as the smoothness of the curve.

[0090] It should be understood that if the current area is an interference area, the pixels inside the area are affected by noise and change more dramatically, making the pixel curve more tortuous, and the value of the smooth curve is smaller; on the contrary, if the current area is a bubble area, since it is only affected by internal air scattering and refraction, the reflection intensity of the pixel sequence changes less, the pixel curve is smoother, and the value of the smooth curve is larger.

[0091] The bubble confidence of each potential defect area is obtained based on the curve smoothness of each pixel in each potential defect area, wherein the bubble confidence of each potential defect area is positively correlated with the curve smoothness of each pixel therein.

[0092] It should be noted that the positive correlation means that the changing trends between the variables are the same. The larger the dependent variable is, the larger the independent variable is, and the smaller the dependent variable is, the smaller the independent variable is. Correspondingly, the specific relationship is determined according to the actual application scenario.

[0093] In this embodiment, the bubble confidence of the potential defect area can be analyzed by the mean and variance of the curve smoothness of all pixels in the potential defect area, and the ratio of the mean to the variance of the curve smoothness of all pixels in each potential defect area is used as the bubble confidence of each potential defect area.

[0094] It should be understood that for the bubble region, since the pixels in the region are relatively smooth overall, the curve of each pixel is smoother, the larger the mean, the smaller the variance, and the higher the bubble confidence. However, each pixel in the interference region is affected by noise to varying degrees, so the curve of each pixel is less smooth, the mean is smaller, the variance is larger, and the bubble confidence is lower.

[0095] For details, please refer to the bubble confidence analysis flow chart for each potential defect area. Figure 4 .

[0096] Step 3: Use the bubble threshold according to the bubble confidence to determine the gel termination time.

[0097] The bubble confidence can be used to measure the possibility that a single potential defect area is a bubble at the current sampling moment. The bubble confidence of all potential defect areas at the current sampling moment is used as the input of the Otsu method, and the algorithm outputs a bubble threshold. Among them, the Otsu method is also the maximum inter-class variance method. In this embodiment, it is used to perform threshold segmentation on the bubble confidence of all potential areas at the current sampling moment, and the segmentation threshold obtained after threshold segmentation is used as the bubble threshold. It should be noted that the specific process of threshold segmentation using the Otsu method is an existing technology and will not be described in detail in this embodiment. The potential defect area greater than the bubble threshold is marked as a real bubble area, and the potential defect area less than or equal to the bubble threshold is marked as an interference area. The occurrence rate of the real bubble area at each sampling moment is thus counted, and the stirring time is controlled based on the occurrence rate corresponding to each sampling moment.

[0098] In this embodiment, the occurrence rate of true bubble regions at each sampling moment is the ratio of the total number of all true bubble region pixels at each sampling moment to the total number of all pixels in the hyperspectral gel data. In other embodiments, implementers can analyze the occurrence rate of true bubble regions at each sampling moment by comparing the number of true bubble regions to the number of potential defect regions, although this application does not impose any specific limitations. If the occurrence rate is less than 3%, it indicates that the gel in the glass container corresponding to the current sampling moment has a low bubble content and the carbon gel quality meets the requirements. Furthermore, to avoid randomness at a single sampling moment, if the bubble occurrence rate meets the requirements for multiple consecutive sampling moments (six consecutive times in this embodiment), constant temperature stirring can be stopped to obtain the carbon gel.

[0099] For details, please refer to the stirring time control flow chart of the carbon gel formation process. Figure 5 .

[0100] d) The obtained carbon gel was placed in an oven and dried at 55°C for 24 hours, and then ground into a powder. The dried powder was then calcined at 600°C for 6 hours in an air atmosphere and allowed to cool naturally to room temperature, thereby obtaining a composite catalyst.

[0101] As another embodiment of the present application, in d), the drying time is 17 hours, the calcination temperature is 620° C., and the calcination time is 3 hours;

[0102] As another embodiment of the present application, in d), the drying time is 12 h, the calcination temperature is 650° C., and the calcination time is 4.5 h.

[0103] Loaded magnesium: In this example, 9.5g magnesium powder and 0.5g The prepared composite catalyst was pretreated by ball milling. It should be noted that the ball milling process was carried out under argon atmosphere, the ball milling time was set to 6 hours, and the ball milling speed was 600 rpm, thereby obtaining magnesium / composite catalyst powder. The purity of the magnesium powder is required to be above 99%, and the particle size is 40 the following;

[0104] As another embodiment of the present application, in step In the experiment, the ball milling time was 8 h and the ball milling speed was 500 rpm;

[0105] As another embodiment of the present application, in step The ball milling time was 12 h and the ball milling speed was 400 rpm.

[0106] Preparation of powdered hydrogen storage material: In this embodiment, The magnesium / composite catalyst powder was prepared by hydrogenation combustion method. During the synthesis process, the magnesium / composite catalyst powder was heated to 550 ° C in a 3 MPa hydrogen atmosphere, kept at this temperature for 3 hours, then cooled to 320 ° C and kept at this temperature for another 6 hours, and finally cooled to room temperature, thereby obtaining a powdered magnesium-based hydrogen storage material.

[0107] As another embodiment of the present application, in step In the process, the temperature is raised to 570℃, the holding time is 2h, the temperature is lowered to 300℃, and the holding time is again 5h;

[0108] As another embodiment of the present application, in step In the experiment, the temperature was raised to 600℃, the holding time was 1.5h, the temperature was lowered to 350℃, and the holding time was again 4h.

[0109] Preparation of nano hydrogen storage material: In this example, 2 g The prepared powdered magnesium-based hydrogen storage material is placed in a ball mill, preferably, and ball milled for 18 hours under a 0.1 MPa hydrogen atmosphere at a speed of 400 rpm. Thus, a nano-magnesium-based hydrogen storage material can be obtained;

[0110] As another embodiment of the present application, in step In the process, the powdered magnesium-based hydrogen storage material is placed in a ball milling jar, the ball milling time is 182, and the ball milling speed is 500 rpm;

[0111] As another embodiment of the present application, in step The ball milling time was 24 h and the ball milling speed was 600 rpm.

[0112] Thus, according to the above-mentioned embodiments and methods of the present application, the automated manufacturing of a nano-magnesium-based hydrogen storage material can be realized, the formation process of the carbon gel can be controlled during the preparation process, the stirring time of the carbon gel formation process can be controlled, the quality of the carbon gel can be ensured, and the preparation quality of the nano-magnesium-based hydrogen storage material can be improved.

[0113] It is understood that references to "one embodiment" or "some embodiments" in the present specification mean that one or more embodiments of the present application include a particular feature, structure, or characteristic described in conjunction with that embodiment. Thus, if "in one embodiment," "in some embodiments," "in other embodiments," or "in other embodiments" appear in different places in this specification, they do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0114] It should be noted that the above-mentioned sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above description is of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-tasking and parallel processing are also possible or may be advantageous. At the same time, the size of the sequence number of each step in the embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments in this specification.

[0115] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. An automated manufacturing method for nano-magnesium-based hydrogen storage materials, characterized in that: The method comprises the following steps: The metal oxide and nanographene sheets are mixed and treated to obtain functionalized graphene; the functionalized graphene and tetrabutyl titanate are added to isopropyl alcohol and magnetically stirred for 1 to 3 hours to obtain a mixed solution A; Scandium nitrate monohydrate is added to isopropyl alcohol and the acid is adjusted. The mixture is stirred and mixed to obtain a mixed solution B, which is then placed in a constant temperature bath at 10°C to 20°C. Mixed solution A is dripped into mixed solution B at a rate of 1 to 5 drops per second and stirred. The gel state is analyzed during the stirring process to control the stirring time. The specific process is as follows: Obtain hyperspectral gel data at each sampling moment during the stirring process. Based on the difference in reflection intensity of pixels corresponding to each potential defect area in the hyperspectral gel data and the contour information of each potential defect area, determine the flocculent evaluation coefficient of each potential defect area to adjust the temperature of the stirring reaction process. The bubble confidence of each potential defect area is determined based on the change in the reflection intensity of the pixels in each potential defect area, the real bubble area is extracted, and the stirring time is controlled according to the number of real bubble areas at each sampling moment to obtain carbon gel; The carbon gel is ground to obtain a composite catalyst, magnesium powder and the composite catalyst are ball-milled, and then a powdered magnesium-based hydrogen storage material is synthesized by a hydrogenation combustion method, and the powdered magnesium-based hydrogen storage material is ball-milled again to obtain a nano-magnesium-based hydrogen storage material; The method for determining the floc evaluation coefficient of each potential defect area is as follows: Each potential defect region is each connected domain in the pseudo-color image corresponding to the hyperspectral gel data; Constructing the flocculent weight of each potential defect area based on the shape characteristics of each potential defect area; Determine a difference result of each pixel in each potential defect area based on a difference between reflection intensities of each pixel in each potential defect area; Determining a difference disorder coefficient of each potential defect region based on the degree of symmetry of the difference results of all pixels in each potential defect region, wherein the difference disorder coefficient is negatively correlated with the degree of symmetry; Determine the floc evaluation coefficient of each potential defect area through the floc weight and difference disorder coefficient of each potential defect area, wherein the floc evaluation coefficient is the forward fusion of the floc weight and the difference disorder coefficient; The flocculence weight of each potential defect region is constructed by determining the flocculence weight of each potential defect region based on the aspect ratio and circularity of the boundary shape of each potential defect region, wherein the flocculence weight is positively correlated with the aspect ratio of the boundary shape and inversely correlated with the circularity. The difference result of each pixel in each potential defect region is determined by obtaining the neighboring pixels of each pixel, forming a pixel sequence of each pixel by combining the reflection intensity of each pixel at different wavelengths, and calculating the difference between each pixel and the pixel sequence of its neighboring pixels, which is recorded as the difference result of each pixel. The temperature of the stirring reaction process is adjusted by analyzing the flocculent evaluation coefficient of each potential defect area at each sampling time, and the proportion of potential defect areas with a flocculent value greater than a preset flocculent threshold among all potential defect areas at each sampling time; when the proportion is greater than a preset proportion, the temperature of the stirring reaction process is lowered by a preset value; The bubble confidence level of each potential defect area is determined by fitting the pixel sequence of each pixel in each potential defect area to construct a pixel curve for each pixel in each potential defect area; and the bubble confidence level of each potential defect area is obtained based on the smoothness of the curve of each pixel in each potential defect area, wherein the bubble confidence level of each potential defect area is positively correlated with the smoothness of the curve of each pixel therein. The process of controlling the stirring time based on the number of real bubble areas at each sampling moment is as follows: the appearance rate of the real bubble area corresponding to each sampling moment is counted. When the appearance rate is less than a preset percentage, the carbon gel quality at the corresponding sampling moment is qualified. When the appearance rate at multiple consecutive sampling moments is less than the preset percentage, the stirring is stopped.

2. The automated manufacturing method of a nano-magnesium-based hydrogen storage material according to claim 1, characterized in that: The process of obtaining functionalized graphene is as follows: The nanographene sheet is placed in a metal oxide, refluxed at 150°C~200°C for 5h~7h, cooled to room temperature, washed with deionized water until neutral, and dried at 70°C~90°C to obtain functionalized graphene.

3. The automated manufacturing method of a nano-magnesium-based hydrogen storage material according to claim 1, characterized in that: The method for obtaining the composite catalyst is: The carbon gel is placed in an oven and dried for 12 h to 24 h, ground into powder, calcined at 600° C. to 650° C. in an air atmosphere for 3 h to 6 h, and then cooled to room temperature.

4. The automated manufacturing method of a nano-magnesium-based hydrogen storage material according to claim 1, characterized in that: After ball milling magnesium powder and composite catalyst, powdered magnesium-based hydrogen storage material is synthesized by hydrogenation combustion method, and then ball milled again to obtain nano magnesium-based hydrogen storage material, specifically: The ball milling time of magnesium powder and composite catalyst is 6h~12h, and the ball milling speed is 400~600rpm; during the hydrogenation combustion synthesis process, the temperature is raised to 550℃~600℃ under 3MPa hydrogen atmosphere, kept warm for 1.5h~3h, then cooled to 300℃~350℃ and kept warm again for 4h~6h, and cooled to room temperature to obtain powdered magnesium-based hydrogen storage material, which is then ball milled under 0.1MPa hydrogen atmosphere for 12h~24h, and the ball milling speed is 400~600rpm.

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