Method, device and equipment for constructing morphology of nano-porous material and medium

Abstract

The invention relates to the technical field of microcosmic measurement, and discloses a morphology construction method, device and equipment of a nanoporous material and a medium, and the method comprises the following steps: obtaining profile data of the nanoporous material; determining a baseline of the profile data based on the profile data; based on the profile data and the base line, pore parameters are obtained, and the pore parameters comprise the pore diameter, the pore depth and the porosity; and based on the pore parameters, constructing the morphology of the nano-pore material. According to the method, the limitation of a traditional measurement method is effectively overcome, the complete three-dimensional shape of the nano-porous material can be constructed, and the method is also suitable for various nano-porous materials including but not limited to porous media such as energy storage materials, catalytic materials, biomedical materials and shale.

Description

Technical Field

[0001] The present application relates to the field of microscopic measurement technology, and in particular to a method, device, equipment and medium for constructing the morphology of nanoporous materials. Background Art

[0002] Nanopore microscopic measurement methods include imaging and quantitative measurement methods. Imaging methods include two-dimensional imaging and three-dimensional imaging. Two-dimensional imaging mainly relies on scanning electron microscopy, while three-dimensional imaging usually relies on micro / nano X-ray computed tomography and focused ion beam scanning electron microscopy. Quantitative methods include gas adsorption experiments and mercury intrusion porosimetry.

[0003] Metal or carbon particles during the sputtering process in scanning electron microscopy and focused ion beam scanning electron microscopy can block nanopores and introduce noise, while focused ion beam scanning electron microscopy inevitably produces artifacts, leading to inaccurate characterization of pore structure. Quantitative porosity determination is similarly limited by the limited pore size measurement range, and even combined application often results in significant measurement errors. Therefore, existing nanopore microscopic measurement methods have many limitations when applied to complex nanoporous materials. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method, device, equipment and medium for constructing the morphology of nanoporous materials, so as to solve the technical defects of the existing nanoporous microscopic measurement methods in the prior art, which have many limitations when applied to complex nanoporous materials.

[0005] In order to achieve the above objectives, the present application provides, in a first aspect, a method for constructing the morphology of a nanoporous material, comprising: Obtain cross-sectional data of nanoporous materials; Based on the profile data, determine the baseline of the profile data; Based on the profile data and the baseline, pore parameters are obtained, wherein the pore parameters include pore diameter, pore depth and porosity; Based on the pore parameters, the morphology of nanoporous materials is constructed.

[0006] In the embodiment of the present application, determining the baseline of the profile data based on the profile data includes: Determine the minimum sum of squares of distances between profile data and a preset baseline; Obtaining a slope of a preset baseline based on a partial derivative of the minimum sum of squared distances with respect to a preset slope of the preset baseline; Obtaining an intercept of a preset baseline based on a partial derivative of the minimum sum of squared distances with respect to a preset intercept of the preset baseline; Based on the slope and intercept, the baseline is determined.

[0007] In the embodiment of the present application, the morphology of the nanoporous material is constructed based on the pore parameters, including: Using the cross-section data, a cross-section data grid is formed; Construct a surface spatial model of nanoporous materials based on the cross-sectional data grid, pore depth, and pore diameter; Fill the area formed by the cross-section data in the surface space model to generate a continuous three-dimensional surface; Based on the continuous three-dimensional surface, the internal structural characteristics of the nanoporous material are simulated to obtain the initial morphology of the nanoporous material; The morphology of the nanoporous material is obtained by correcting the pore volume ratio of the initial morphology of the nanoporous material based on the porosity.

[0008] In the embodiment of the present application, it also includes: The nanoporous material is scanned using a sinusoidal scanning function to obtain a scanning response value; Based on the scan response value and the theoretical response value, a deviation value is obtained; Based on the deviation value, the pore distribution correction coefficient is obtained; Compensate profile data based on the porosity distribution correction factor.

[0009] In the embodiment of the present application, it also includes: Based on the profile data, the spatial distribution characteristic frequency of the pores is obtained.

[0010] In the embodiment of the present application, it also includes: Based on the profile data, pore characteristics of different scales are separated and obtained.

[0011] In the embodiment of the present application, obtaining cross-sectional data of the nanoporous material includes: The surface topography information of nanoporous materials can be obtained through atomic force microscopy; Based on the surface topography information, profile data is extracted.

[0012] A second aspect of the present application provides a device for constructing the morphology of a nanoporous material, the device comprising: An acquisition module, used for acquiring cross-sectional data of nanoporous materials; A determination module, for determining a baseline of the profile data based on the profile data; An obtaining module is used to obtain pore parameters based on the profile data and the baseline, wherein the pore parameters include pore diameter, pore depth and porosity; A building block for constructing the morphology of nanoporous materials based on pore parameters.

[0013] A third aspect of the present application provides a device for constructing the morphology of a nanoporous material, comprising: a memory configured to store instructions; The processor is configured to call instructions from the memory and implement the method for constructing the morphology of nanoporous materials according to the first aspect when executing the instructions.

[0014] A fourth aspect of the present application provides a machine-readable storage medium having stored thereon instructions for enabling a machine to execute the method for constructing the morphology of nanoporous materials according to the first aspect.

[0015] Through the above technical solution, the profile data is obtained to determine the profile baseline, and based on the profile data and the baseline, the pore parameters are obtained. Using the pore parameters, the morphology of the nanoporous material is constructed. This application effectively overcomes the limitations of traditional measurement methods. Not only can it construct the complete three-dimensional morphology of nanoporous materials, but it is also applicable to various nanoporous materials, including but not limited to energy storage materials, catalytic materials, biomedical materials, and porous media such as shale. This application has broad application prospects.

[0016] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present application but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings: Figure 1 The following schematically shows a flow chart of a method for constructing the morphology of a nanoporous material according to an embodiment of the present application; Figure 2 A schematic diagram schematically illustrates cross-sectional data according to an embodiment of the present application; Figure 3 The figure schematically shows a schematic diagram of obtaining cross-sectional data using an atomic force microscope according to an embodiment of the present application.

[0018] Description of Reference Numerals DETAILED DESCRIPTION

[0019] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0020] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of laws and regulations. In the embodiments of this application, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use such solutions.

[0021] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), such directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0022] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0023] Figure 1 The following schematically shows a flow chart of a method for constructing the morphology of a nanoporous material according to an embodiment of the present application. Figure 1 As shown, an embodiment of the present application provides a method for constructing the morphology of a nanoporous material, which may include the following steps.

[0024] Step S110: Acquire cross-sectional data of the nanoporous material; Step S120: determining a baseline of the profile data based on the profile data; Step S130: obtaining pore parameters based on the profile data and the baseline, wherein the pore parameters include pore diameter, pore depth and porosity; Step S140: constructing the morphology of the nanoporous material based on the pore parameters.

[0025] In step S110 , cross-sectional data of the nanoporous material is acquired using a scanning electron microscope, a confocal laser scanning microscope, an optical profilometer, an X-ray computed tomography scanner, or a focused ion beam scanning electron microscope.

[0026] In one embodiment, cross-sectional data can be acquired using a confocal laser scanning microscope. By scanning the nanoporous material point by point in the focal plane and using a pinhole to block light outside the focal plane, a confocal laser scanning microscope can provide high-contrast optical sections and construct the three-dimensional structure of the nanoporous material. This microscope is suitable for observing the pore distribution in transparent or translucent materials.

[0027] In another embodiment, cross-sectional data can be acquired using X-ray computed tomography (CT). CT can non-destructively acquire internal structural information of nanoporous materials. By reconstructing multi-angle X-ray projection images, a three-dimensional model of the nanoporous material's interior can be formed. This is suitable for observing the connectivity and distribution of the pore network within the nanoporous material.

[0028] In another embodiment, an optical profilometer can be used to acquire cross-sectional data. Using the principle of white light interferometry, an optical profilometer can rapidly acquire three-dimensional surface topographic data of nanoporous materials over large areas by analyzing the interference fringes of light reflected from different surface heights. Compared to atomic force microscopy, an optical profilometer offers faster measurement speeds and requires less preparation for nanoporous material testing, making it suitable for preliminary scans of irregular surfaces.

[0029] In step S120 , a baseline of the profile data is determined based on the profile data of the nanoporous material. The baseline is used as a reference standard when analyzing the profile data.

[0030] In step S130, pore parameters are determined based on the profile data and the baseline. The performance of nanoporous materials is highly dependent on the pore parameters, and the performance of nanoporous materials can be evaluated by the pore parameters.

[0031] Figure 2 Schematic diagram of cross-sectional data according to an embodiment of the present application is shown. Figure 2 As shown, the x-axis represents the horizontal direction, the y-axis represents the vertical direction, the curve represents the curve of the cross-sectional data of the nanoporous material, and the dotted line represents the baseline of the cross-sectional data of the nanoporous material.

[0032] In the embodiments of this application, reference is made to Figure 2 The pore size represents the distance between adjacent intersection points of the profile data and the baseline (the width of the pore opening). The pore bottom represents the lowest point of the profile data on the y-axis, and the pore depth represents the vertical distance from the baseline to the pore bottom. The porosity represents the ratio of the area below the profile data to the area below the baseline. The porosity calculation formula is:

[0033] Where, represents the area of ​​a single pore, Indicates the length of the measuring line, Indicates the maximum hole depth.

[0034] In step S140, the morphology of the nanoporous material is constructed using pore parameters. The morphology construction of nanoporous materials is an important research direction in the field of materials science. The pore parameters of the microstructure directly affect the adsorption, catalytic, mechanical and other properties of the nanoporous material.

[0035] The embodiments of the present application effectively overcome the limitations of traditional measurement methods, construct a complete three-dimensional morphology of nanoporous materials, and are applicable to various nanoporous materials, including but not limited to energy storage materials, catalytic materials, biomedical materials, and porous media such as shale, and have broad application prospects.

[0036] Furthermore, step S120 may include the following steps: Step S121: determining the minimum sum of squares of distances between the profile data and a preset baseline; Step S122: Obtaining the slope of the preset baseline based on the partial derivative of the minimum distance squared sum with respect to the preset slope of the preset baseline; Step S123: Obtaining the intercept of the preset baseline based on the partial derivative of the minimum distance square sum with respect to the preset intercept of the preset baseline; Step S124: Determine the baseline based on the slope and the intercept.

[0037] In step S121, the preset baseline is The least squares method is used to obtain the minimum sum of squares of the distances from the data points of the profile data to the preset baseline.

[0038]

[0039] In the above formula, represents the minimum sum of squared distances, represents the height of the i-th data point of the profile data, Indicates the slope of the preset baseline, Represents the width of the i-th data point of the profile data, Indicates the intercept of the preset baseline.

[0040] In step S122 , the partial derivative of the minimum distance square sum with respect to the preset slope of the preset baseline is set to zero to obtain the slope of the preset baseline.

[0041]

[0042]

[0043] In step S123 , the partial derivative of the minimum distance square sum with respect to the preset intercept of the preset baseline is set to zero to obtain the intercept of the preset baseline.

[0044]

[0045]

[0046] In step S124 , a baseline is determined according to the slope of the preset baseline and the intercept of the preset baseline.

[0047]

[0048] Furthermore, step S140 may include the following steps: Step S141: using the cross-sectional data to form a cross-sectional data grid; Step S142: constructing a surface space model of the nanoporous material based on the cross-sectional data grid, pore depth, and pore diameter; Step S143: filling the area formed by the cross-section data in the surface space model to generate a continuous three-dimensional surface; Step S144: simulating the internal structural characteristics of the nanoporous material based on the continuous three-dimensional surface to obtain the initial morphology of the nanoporous material; Step S145: Based on the porosity, the pore volume ratio of the initial morphology of the nanoporous material is corrected to obtain the morphology of the nanoporous material.

[0049] In step S141 , a cross-sectional data grid is formed based on the cross-sectional data in multiple parallel directions.

[0050] In step S142, the initial morphology of the nanoporous material is constructed using triangulation or a Voronoi diagram. Triangulation is the process of dividing a set of points, polygons, or geometric bodies in space into non-overlapping triangles (or higher-dimensional simplices). The Voronoi diagram divides space into several regions based on a set of given points (called mother points), so that the distance from any point in each region to the mother point of that region is less than the distance to any other mother point. The pore depth is used to set the spatial range and grid density in the Z-axis direction of the triangulation or Voronoi diagram, and the aperture is used to control the grid size of the triangulation or Voronoi diagram to ensure that the grid resolution can accurately capture the characteristics of the minimum aperture.

[0051] In step S143, an interpolation algorithm is used to fill the area formed by the cross-sectional data in the surface space model to generate a continuous three-dimensional surface. The interpolation algorithm constructs a simple function to fit the known points based on their distribution pattern, thereby predicting the values ​​of unknown points.

[0052] In step S144, based on the continuous three-dimensional surface, the internal structural characteristics of the nanoporous material are simulated using a Markov random field model to obtain the initial morphology of the nanoporous material. The formula of the Markov random field model includes:

[0053] In the above formula, represents the Markov random field model, represents the normalization constant, Indicates a nearby point The potential function of the Markov random field model is iteratively optimized so that the initial morphology of the generated nanoporous material conforms to the measured statistical characteristics.

[0054] In step S145 , the porosity is used for overall volume constraint to correct the pore volume ratio of the initial morphology of the nanoporous material to obtain the morphology of the nanoporous material.

[0055] In this application, the present embodiment uses pore parameters as constraints and transforms these constraints into a continuous three-dimensional structure through mathematical models (triangulation, Voronoi diagrams, and Markov random field models). This results in a reconstructed 3D morphology that is not only visually realistic but also statistically consistent with actual nanoporous materials. This 3D reconstruction allows for intuitive observation of the spatial distribution, connectivity, and internal structure of pores, providing a microscopic foundation for understanding the properties of nanoporous materials.

[0056] In an optional implementation, the method further includes: Based on the connectivity formula, the calculated connectivity value of the pores is obtained, where the connectivity formula includes:

[0057] Where, Indicates connectivity, represents the number of edges in the pore network, Indicates the number of nodes; A connectivity measurement value is obtained, and when the calculated connectivity value is not equal to the connectivity measurement value, parameters of the Markov field model are adjusted until the calculated connectivity value is equal to the connectivity measurement value.

[0058] In the embodiments of the present application, during the three-dimensional morphology reconstruction process, the connectivity of the pores can be used to guide the construction and optimization of the pore network, ensuring that the reconstructed three-dimensional morphology accurately reflects the connectivity state of the pores and the fluid flow path in the actual nanoporous material. The higher the connectivity, the more complex the pore network and the more diverse the fluid flow path, which is crucial for applications such as catalysis and adsorption.

[0059] In an optional embodiment, constructing the surface space model of the nanoporous material in step S142 includes the following steps: Step S142a: Separate and obtain pore features of different scales based on the profile data; Step S142b: using a fractal dimension formula to obtain the fractal dimension of the pore structure of the nanoporous material; Step S142c: Based on the pore characteristics and fractal dimensions of different scales, pore parameters with different weight coefficients are applied to the pore characteristics of different scales to construct a surface space model of the nanoporous material.

[0060] In step S142a, wavelet transform is used to perform multi-scale analysis on the profile data to separate pore characteristics of different scales. The wavelet transform formula includes:

[0061] In the above formula, represents the scale parameter, represents the translation parameter, represents the wavelet function, represents the profile data function, Represents a position coordinate variable.

[0062] In step S142b, the fractal dimension is obtained by using the fractal dimension formula, wherein the fractal dimension formula includes:

[0063] Where, represents the fractal dimension, Indicates the measurement scale or the length of the box side, The measurement scale is The minimum number of boxes required to completely cover the fractal shape. is a small positive number. Specifically, small squares to cover the fractal graphics.

[0064] In step S142c, when the fractal dimension is greater than 1.5, it indicates that the pore structure is complex, and the weight coefficients of micropores and mesopores are increased to 1.2-1.5; when the fractal dimension is greater than 1.3, it indicates that the pore structure is relatively simple, and the weight coefficients of each scale are kept at 1.0.

[0065] In the embodiment of the present application, a surface space model of a nanoporous material is constructed by weighted pore parameters to reflect the contribution of pores of different scales.

[0066] In an optional implementation, the method further includes: Step S210: Scanning the nanoporous material using a sinusoidal scanning function to obtain a scanning response value; Step S220: obtaining a deviation value based on the scan response value and the theoretical response value; Step S230: obtaining a pore distribution correction coefficient based on the deviation value; Step S240: Compensating the profile data based on the pore distribution correction coefficient.

[0067] In step S210, the sinusoidal scanning function is:

[0068] Where, represents the sine sweep function, represents the amplitude, Indicates frequency, Indicates the scanning position coordinates, Represents the phase shift. The sine sweep function is used to scan the nanoporous material to obtain the scan response value.

[0069] In steps S220 to S230, a deviation value is obtained by comparing the scanning response value and the theoretical response value, and then a pore distribution correction coefficient is obtained by the deviation value.

[0070]

[0071] Where, represents the pore distribution correction coefficient, Indicates the scan response value, represents the theoretical response value, Indicates the number of measurement points.

[0072] In step S240, the pore distribution correction coefficient Compensate the profile data.

[0073] The embodiments of the present application improve the ability to detect pore characteristics in the depth direction, especially for nanoporous materials with complex internal structures.

[0074] In an optional implementation, the method further includes: Step S310: Based on the profile data, obtain the spatial distribution characteristic frequency of the pores.

[0075] In step S310 , the characteristic frequency of the spatial distribution of the pores reflects the periodic characteristics of the pore size, spacing or arrangement.

[0076] In an optional implementation, the method further includes: Step S410: obtaining surface topography information of the nanoporous material through atomic force microscopy; Step S420: extracting profile data based on the surface topography information.

[0077] In the present embodiment, before obtaining cross-sectional data of a nanoporous material using an atomic force microscope, the nanoporous material is subjected to argon ion polishing to ensure a smooth surface. The laboratory ambient temperature fluctuation is controlled within ±0.2°C, and the relative humidity fluctuation is controlled within ±2% to prevent temperature and humidity changes from affecting the measurement results. The surface topography information of the nanoporous material is obtained using an atomic force microscope, and cross-sectional data can be extracted from this surface topography information. Figure 3 Schematic diagram of obtaining cross-sectional data using an atomic force microscope according to an embodiment of the present application. Figure 3 As shown, when obtaining cross-sectional data of nanoporous materials through atomic force microscopy, the laser beam emitted by the laser 1 is focused onto the back of the cantilever 3 through the photoelectric feedback system 2 and reflected to the photodiode detector 4. The cantilever 3 bends according to the surface morphology of the nanoporous material 5, and the reflected light beam moves accordingly, enabling the photodiode detector 4 to measure the displacement. The measured displacement is converted into height change data, thereby obtaining complete surface topography information of the nanoporous material. Based on the surface topography information, cross-sectional data is extracted along a specific path. It is worth noting that the nanoporous material 5 is fixed on the sample stage of the atomic force microscope. It is necessary to ensure that there is enough space between the nanoporous material 5 and the probe 6 of the atomic force microscope. The probe 6 is manually positioned on the surface of the nanoporous material 5 using an external camera. In this embodiment, a Tap190Al-G probe is used for tapping mode measurement, and the height between the nanoporous material 5 and the probe 6 is automatically adjusted using integrated software.

[0078] The nanoporous materials of the embodiments of the present application include, but are not limited to, nanoporous carbon materials, nanoporous silica materials, composite materials with nano-multilevel pore structures, and nanoporous glass materials.

[0079] The following embodiments of the present application are further described based on the nanoporous material being a nanoporous carbon material.

[0080] In the embodiment of the present application, an atomic force microscope is used in tapping mode to obtain a high-resolution image of the surface of a nanoporous carbon material. The scanning range is set to 2×2μm and the number of scanning points is 1024×1024, ensuring that pore structures as small as 2nm can be resolved. The watershed segmentation algorithm is applied to the acquired atomic force microscope image for preliminary pore identification, and then two vertical profile lines are extracted from the image. The profile lines include an X-axis profile line and a Y-axis profile line. The X-axis profile line is horizontal along the surface of the nanoporous carbon material (parallel to the main axis of the porous silica material), and the Y-axis profile line is vertical (perpendicular to the main axis of the nanoporous carbon material). The baseline of each profile line is determined using the least squares method. During the fitting process, an iterative method is used to exclude data points in the pore area to ensure that the baseline accurately represents the overall trend of the surface of the nanoporous carbon material. Based on the relationship between the profile data and the baseline, the pore parameters of the nanoporous carbon material are obtained, and the pore parameters are shown in Table 1.

[0081] Table 1

[0082] Low-temperature nitrogen adsorption experiments were performed on the nanoporous carbon material to obtain nitrogen adsorption-desorption isotherms and pore size distribution curves. The experiments were conducted at 77 K, with a relative pressure (P / P0) range of 0.01 to 0.99. Within this range, multiple discrete relative pressure values ​​were set as measurement points. At each measurement point, the system was held for 60 seconds to ensure that the adsorption reached equilibrium before recording data. A total of 20 measurement points were collected to construct a complete adsorption-desorption curve. The measurement results obtained by the low-temperature nitrogen adsorption method are shown in Table 2.

[0083] Table 2

[0084] High-pressure mercury intrusion experiments were performed on the nanoporous carbon materials using an AutoPore IV 9500 automated mercury porosimeter. The nanoporous carbon materials were dried at 105°C for 24 hours to remove moisture and then placed in the permeameter. The analysis consisted of two stages: a low-pressure stage (0.1-50 psia) to fill the permeameter and characterize the macropores, followed by a high-pressure stage (up to 60,000 psia) to analyze the mesopores and micropores. The measurement results obtained by the high-pressure mercury intrusion method are shown in Table 3.

[0085] Table 3

[0086] The results of the profile method and the nitrogen adsorption method were compared and analyzed, and the relative error of the first porosity was 7.09%. The results of the profile method and the mercury intrusion method were compared and analyzed, and the relative error of the second porosity was 4.93%. From the comparison results, it can be seen that the porosity measured by the profile method is close to the results of the conventional nitrogen adsorption method and mercury intrusion method, and the relative errors are less than 10%, which verifies the effectiveness and accuracy of the profile method. In addition, the profile method of this embodiment can also provide parameters such as pore depth and fractal dimension that cannot be directly obtained by the conventional nitrogen adsorption method and mercury intrusion method, providing more comprehensive information for the microstructural characterization of nanoporous carbon materials.

[0087] Cross-sectional analysis of the nanoporous carbon material reveals a rich mesoporous structure with an average pore diameter of approximately 25 nm, a maximum pore depth of approximately 11 nm, and a porosity of approximately 17%. The fractal dimension is approximately 1.74, indicating a degree of self-similarity and complexity in the pore structure. These microstructural features, consistent with the material's high specific surface area and excellent electrochemical performance, provide a microscopic foundation for understanding its application in energy storage devices such as supercapacitors.

[0088] The following examples of the present application are further described based on the nanoporous material being a nanoporous silica material, wherein the nanoporous silica material is prepared by a sol-gel method and is widely used in the fields of catalyst supports, drug sustained-release systems, and the like.

[0089] First, an atomic force microscope is used to obtain a high-resolution image of the surface of the nanoporous silica material. The scanning range is set to 5×5μm and the number of scanning points is 2048×2048 to ensure that pore structures as small as 2.5nm can be distinguished. In order to obtain a wider range of pore distribution information, in the embodiment of the present application, four different areas are selected using a uniform distribution strategy based on the pore distribution characteristics of the surface of the nanoporous silica material: located in the center area of ​​the nanoporous silica material, 2mm above, below, left and right from the center, and the scanning area of ​​each area is 2×2μm. In each area, two orthogonal profile lines are extracted using an atomic force microscope. The profile lines include an X-axis profile line and a Y-axis profile line. The X-axis profile line is horizontal along the surface of the porous silica material (parallel to the main axis of the porous silica material), and the Y-axis profile line is vertical (perpendicular to the main axis of the porous silica material). A total of eight profile data are used for analysis. Profiles were extracted from areas with the most representative pore distribution, with each profile containing 5–8 typical pores. The baseline was determined using the least squares method, and the associated pore parameters were calculated. The pore parameters of the porous silica material were obtained based on the relationship between the profile data and the baseline, as shown in Table 4.

[0090] Table 4

[0091] The measurement results obtained by low-temperature nitrogen adsorption method are shown in Table 5.

[0092] Table 5

[0093] The measurement results obtained by the high-pressure mercury intrusion method are shown in Table 6.

[0094] Table 6

[0095] The results of the profile method and the nitrogen adsorption method were compared and analyzed, and the relative error of the first porosity was 4.69%. The results of the profile method and the mercury intrusion method were compared and analyzed, and the relative error of the second porosity was 3.16%. As can be seen from the comparison results, the porosity measured by the profile method is very close to the results of the conventional nitrogen adsorption method and the mercury intrusion method, and the relative errors are all less than 5%, which further confirms the validity and accuracy of the profile method. In addition, the profile method of the present embodiment can also provide parameters such as pore depth and fractal dimension that cannot be directly obtained by the conventional nitrogen adsorption method and the mercury intrusion method, providing more comprehensive information for the microstructural characterization of porous silica materials.

[0096] Analysis of the results in Table 4 shows that the nanoporous silica material possesses a uniform mesoporous structure with an average pore diameter of approximately 7 nm, a maximum pore depth of approximately 5 nm, and a porosity of approximately 43.5%. The pore shape factor is as high as 0.84, indicating a very regular, nearly circular pore shape. The fractal dimension is only 1.40, indicating a relatively simple pore structure lacking complex fractal features. This regular, uniform pore structure enables the nanoporous silica material to exhibit excellent performance in catalytic and separation applications.

[0097] Optionally, an embodiment of the present application further provides a device for constructing the morphology of a nanoporous material, the device comprising: An acquisition module, used for acquiring cross-sectional data of nanoporous materials; A determination module, for determining a baseline of the profile data based on the profile data; An obtaining module is used to obtain pore parameters based on the profile data and the baseline, wherein the pore parameters include pore diameter, pore depth and porosity; A building block for constructing the morphology of nanoporous materials based on pore parameters.

[0098] It is understandable that the device for constructing the morphology of nanoporous materials provided in the embodiment of the present application can implement each process of the method for constructing the morphology of nanoporous materials in the above embodiment and can achieve the same technical effect. To avoid repetition, it will not be described here.

[0099] Optionally, an embodiment of the present application further provides a device for constructing the morphology of a nanoporous material, comprising: a memory configured to store instructions; The processor is configured to call instructions from the memory and implement the above-mentioned method for constructing the morphology of nanoporous materials when executing the instructions.

[0100] It is understandable that the nanoporous material morphology construction device provided in the embodiment of the present application can realize each process of the nanoporous material morphology construction method in the above embodiment and can achieve the same technical effect. To avoid repetition, it will not be described here.

[0101] Optionally, an embodiment of the present application further provides a machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the method for constructing the morphology of the nanoporous material as described above.

[0102] It is understandable that the machine-readable storage medium provided in the embodiment of the present application can implement each process of the morphology construction method of the nanoporous material in the above embodiment and can achieve the same technical effect. To avoid repetition, it will not be described here.

[0103] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0104] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0105] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0106] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0107] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0108] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0109] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0110] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0111] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for constructing the morphology of nanoporous materials, characterized in that: include: Obtain cross-sectional data of nanoporous materials; Based on the profile data, determining a baseline of the profile data; Based on the profile data and the baseline, pore parameters are obtained, wherein the pore parameters include pore diameter, pore depth and porosity; Based on the pore parameters, the morphology of the nanoporous material is constructed.

2. The method according to claim 1, characterized in that Determining the baseline of the profile data based on the profile data includes: Determining the minimum sum of squares of distances between the profile data and a preset baseline; Obtaining the slope of the preset baseline based on a partial derivative of the minimum distance squared sum with respect to the preset slope of the preset baseline; Obtaining an intercept of the preset baseline based on a partial derivative of the minimum distance square sum with respect to a preset intercept of the preset baseline; Based on the slope and the intercept, the baseline is determined.

3. The method according to claim 1, characterized in that The step of constructing the morphology of the nanoporous material based on the pore parameters includes: Using the cross-sectional data, forming a cross-sectional data grid; constructing a surface space model of the nanoporous material based on the cross-sectional data grid, the pore depth, and the pore diameter; Filling the area formed by the cross-sectional data in the surface space model to generate a continuous three-dimensional surface; Based on the continuous three-dimensional surface, simulating the internal structural characteristics of the nanoporous material to obtain the initial morphology of the nanoporous material; The pore volume ratio of the initial morphology of the nanoporous material is corrected based on the porosity to obtain the morphology of the nanoporous material.

4. The method according to claim 1, wherein Also includes: Scanning the nanoporous material using a sinusoidal scanning function to obtain a scanning response value; Obtaining a deviation value based on the scan response value and the theoretical response value; Based on the deviation value, a pore distribution correction coefficient is obtained; The profile data is compensated based on the pore distribution correction factor.

5. The method according to claim 1, characterized in that Also includes: Based on the cross-sectional data, the spatial distribution characteristic frequency of the pores is obtained.

6. The method according to claim 1, wherein Also includes: Based on the cross-sectional data, pore characteristics of different scales are separated and obtained.

7. The method according to claim 1, characterized in that The obtaining of cross-sectional data of the nanoporous material includes: Obtaining surface topography information of the nanoporous material through atomic force microscopy; The profile data is extracted based on the surface topography information.

8. A device for constructing the morphology of nanoporous materials, characterized in that: The device comprises: An acquisition module, used for acquiring cross-sectional data of nanoporous materials; a determination module, configured to determine a baseline of the profile data based on the profile data; an obtaining module, configured to obtain pore parameters based on the profile data and the baseline, wherein the pore parameters include pore diameter, pore depth and porosity; A construction module is used to construct the morphology of the nanoporous material based on the pore parameters.

9. A device for constructing the morphology of nanoporous materials, characterized in that: include: a memory configured to store instructions; A processor is configured to call the instructions from the memory and implement the method for constructing the morphology of a nanoporous material according to any one of claims 1 to 7 when executing the instructions.

10. A machine-readable storage medium, characterized in that The machine-readable storage medium stores instructions for enabling a machine to execute the method for constructing the morphology of a nanoporous material according to any one of claims 1 to 7.

Images