CN110702705A - Method for measuring and calculating dispersion degree of loaded metal catalyst based on atomic resolution electron microscope - Google Patents
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Abstract
The invention provides a method for measuring and calculating the dispersion degree of a loaded metal catalyst based on an atomic resolution electron microscope, which specifically comprises the following steps: (1) acquiring a picture of the metal catalyst by adopting a transmission electron microscope; (2) identifying metal particles, namely sequentially performing top hat transformation, filtering a substrate by a frequency domain method, image sharpening, dynamic threshold binarization processing and target area marking processing; (3) calculating the dispersity: and (3) carrying out metal particle identification processing on all the pictures acquired in the step (1) according to the step (2) to obtain a single-point diagram and a cluster diagram corresponding to each picture, calculating the dispersion degree according to picture information provided by the single-point diagram and the cluster diagram, and fitting the dispersion degree into a function, wherein the picture information comprises the number of metal particles, the distribution position of the metal particles, the number of clusters, the cluster area and the area of the image with a substrate. The technical scheme of the invention solves the problem that the prior art lacks a method for measuring and calculating the dispersity of the catalyst technology aiming at atomic scale.
Description
Technical Field
The invention relates to the field of measuring and calculating atomic dispersity, in particular to a method for measuring and calculating the dispersity of a supported metal catalyst based on an atomic resolution electron microscope.
Background
The information of the dispersion degree such as the density, the distance, the adjacent coordination relationship and the like of metal atoms in the supported metal catalyst is of great importance to the influence of the performance of the catalyst, and is directly related to the activity, the selectivity and the stability of the catalyst. Methods for determining the degree of dispersion of metal atoms in supported catalysts have been widely discussed in academia and industry.
The method for measuring the metal atom dispersity of the supported catalyst comprises an X-ray photoelectron spectroscopy (XPS), an X-ray diffraction method (XRD), a Transmission Electron Microscopy (TEM), a chemical adsorption method and the like, and the methods have advantages and disadvantages and application ranges, wherein in recent years, as the transmission electron microscope has atom resolution capability, the method has unique advantages that the method can directly resolve the position and the number of metal atoms, and the method is gradually developed into an important means for representing the structure information of the catalyst. However, at present, a systematic measuring and calculating method is provided in the literature aiming at the statistical dispersion degree of the metal of the catalyst on the atomic scale.
Disclosure of Invention
According to the problem that the prior art lacks a method for measuring and calculating the technical dispersity of the catalyst on an atomic scale, the method for measuring and calculating the dispersity of the supported metal catalyst based on the atomic resolution electron microscope is provided. The method mainly comprises the steps of directly distinguishing the positions of metal atoms by using a Transmission Electron Microscope (TEM), counting the metal atom dispersion degree information of the catalyst based on the position information, and defining the metal dispersion degree under an atom distinguishing scale, and provides a distinguishing standard for judging the performance of the catalyst.
The technical means adopted by the invention are as follows:
a method for measuring and calculating the dispersion degree of a loaded metal catalyst based on an atomic resolution electron microscope specifically comprises the following steps:
(1) acquiring a picture of the metal catalyst by adopting a transmission electron microscope;
(2) identifying metal particles, namely sequentially performing top hat transformation, filtering a substrate by a frequency domain method, image sharpening, dynamic threshold binarization processing and target area marking processing;
(3) calculating the dispersity:
carrying out metal particle identification processing on all the pictures acquired in the step (1) according to the step (2) to obtain a single-point diagram and a cluster diagram corresponding to each picture, calculating the dispersion degree according to picture information provided by the single-point diagram and the cluster diagram, and fitting the dispersion degree into the following function:
Diversity＝f(x1,x2,x3,x4,...)
the picture information comprises the number of metal particles, the distribution position of the metal particles, the number of clusters, the cluster area and the area of the part of the image with the substrate.
Further, the step (2) specifically comprises the following steps:
(2-1) top-hat transform is a method of image morphology, defined as image minus image-on operation result, which can highlight bright areas in a darker background:
where b is a structural element in the top-hat transform operation, f is the original image,
the structural element b carries out opening operation on the image f;
(2-2) filtering low-frequency components of the substrate by adopting a high-pass frequency domain filtering method, and then performing Fourier inverse transformation;
(2-3) sharpening the Fourier transformed image by adopting a Laplace operator;
(2-4) carrying out binarization processing on the gray level histogram of the image by adopting a method for dynamically generating a threshold value, then marking a target area, wherein an iterative formula for calculating the threshold value is as follows:
hkthe number of pixels when the gray scale is k value is iterated until | Ti+1-Ti|＜Δ；
Dividing gray data by using a threshold, dividing an image into a foreground and a background pixel by pixel, obtaining an average value by using a foreground integrator and a background integrator, averaging to obtain a new threshold, repeating the process until delta is less than or equal to 0.0001, and obtaining a final segmentation result of the foreground and the background.
Further, the dispersion calculation function is:
wherein λ is1，λ2，λ3As weighting coefficients, natomIs the number of metal particles, SatomFor each area of metal particles, medgeFor triangulation of the mean value of all side lengths, stdedgeIs the standard deviation of all side lengths after triangulation,
the area of the ith cluster.
Compared with the prior art, the invention has the following advantages:
the invention provides a method for measuring and calculating the dispersion degree of a loaded metal catalyst based on an atomic resolution electron microscope, which breaks through the limitation of the representation of a micro area of the traditional electron microscope, can realize the atomic dispersion degree statistics of a mass of catalyst high resolution pictures, really realizes the one-stop solution of the evaluation from an atomic structure to a macro structure, realizes the hundred thousand-level atomic dispersion degree statistics and the millimeter-level material (catalyst) atomic structure traversal statistics with atomic precision through the mass atomic picture identification, thereby constructing a full-scale statistical method from micro (atom) to macro (ten thousand-level millimeter scale), establishing a bridge from metal atoms, clusters, nanoparticles to macro catalytic performance, and counting a large number of pictures, reliably and essentially.
In summary, the technical solution of the present invention includes a method and a system for directly resolving metal atom positions by using a Transmission Electron Microscope (TEM), counting catalyst metal atom dispersion degree information based on the position information, and defining metal dispersion degree under an atom resolution scale, so as to provide a criterion for catalyst performance judgment. Therefore, the technical scheme of the invention solves the problem that the prior art lacks a method for measuring and calculating the technical dispersity of the catalyst on an atomic scale.
Based on the reasons, the method can be widely popularized in the fields of atom dispersity measurement and calculation and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of the method for calculating the degree of dispersion according to the present invention.
Fig. 2 is a schematic view of a metal particle identification process according to the present invention.
FIG. 3 shows Pt/Al as described in example 12O3Atomic resolution STEM-HAADF images of supported metal catalysts.
Fig. 4 is a top-hat transformed image.
Fig. 5 is a spectrum diagram after fourier transform.
Fig. 6 is an image after the low-frequency component is filtered out after the inverse fourier transform.
Fig. 7 is the image sharpened in fig. 6.
Fig. 8 is a diagram illustrating histogram statistics.
FIG. 9 is a schematic diagram of a dynamic threshold generation method.
Fig. 10 is an image after the dynamic threshold value binarization processing.
Fig. 11 is an identified single point image.
Fig. 12 is an image of the identified clusters.
Fig. 13 is a segmented image with and without a base portion.
FIG. 14 is a graph showing the results after triangulation.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. Any specific values in all examples shown and discussed herein are to be construed as exemplary only and not as limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
In the description of the present invention, it is to be understood that the orientation or positional relationship indicated by the directional terms such as "front, rear, upper, lower, left, right", "lateral, vertical, horizontal" and "top, bottom", etc., are generally based on the orientation or positional relationship shown in the drawings, and are used for convenience of description and simplicity of description only, and in the absence of any contrary indication, these directional terms are not intended to indicate and imply that the device or element so referred to must have a particular orientation or be constructed and operated in a particular orientation, and therefore should not be considered as limiting the scope of the present invention: the terms "inner and outer" refer to the inner and outer relative to the profile of the respective component itself.
Spatially relative terms, such as "above … …," "above … …," "above … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial relationship to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if a device in the figures is turned over, devices described as "above" or "on" other devices or configurations would then be oriented "below" or "under" the other devices or configurations. Thus, the exemplary term "above … …" can include both an orientation of "above … …" and "below … …". The device may be otherwise variously oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, and therefore, the scope of the present invention should not be construed as being limited.
Example 1
As shown in fig. 1, the present invention provides a method for measuring and calculating the degree of dispersion of metal atoms of a supported catalyst by using electron microscope characterization, image program identification and information statistics, which specifically comprises the following steps:
(1) acquiring a picture of the metal catalyst by adopting a Transmission Electron Microscope (TEM); the selection of scanning transmission electron beam (STEM-HAADF) parameters and the parameter setting of the imaging sensor were performed before using the transmission electron microscope: the parameters of the scanning transmission electron beam comprise acceleration voltage, diaphragm size, camera constant and the like; parameters of the imaging sensor comprise signal gain, signal baseline compensation, image contrast display mode and the like;
(2) identifying metal particles, namely sequentially performing top hat transformation, filtering a substrate by a frequency domain method, image sharpening, dynamic threshold binarization processing and target area marking processing;
(3) calculating the dispersity:
carrying out metal particle identification processing on all the pictures acquired in the step (1) according to the step (2) to obtain a single-point diagram and a cluster diagram corresponding to each picture, calculating the dispersion degree according to picture information provided by the single-point diagram and the cluster diagram, and fitting the dispersion degree into the following function:
Diversity＝f(x1,x2,x3,x4,...)
the picture information comprises the number of metal particles, the distribution position of the metal particles, the number of clusters, the cluster area and the area of the part of the image with the substrate.
Further, the step (2) specifically comprises the following steps:
(2-1) top-hat transform is a method of image morphology, defined as image minus image-on operation result, which can highlight bright areas in a darker background:
where b is a structural element in the top-hat transform operation, f is the original image,
the structural element b carries out opening operation on the image f;
(2-2) filtering low-frequency components of the substrate by adopting a high-pass frequency domain filtering method, and then performing Fourier inverse transformation;
(2-3) sharpening the Fourier transformed image by adopting a Laplace operator;
(2-4) carrying out binarization processing on the gray level histogram of the image by adopting a method for dynamically generating a threshold value, then marking a target area, wherein an iterative formula for calculating the threshold value is as follows:
hkthe number of pixels when the gray scale is k value is iterated until | Ti+1-Ti|＜Δ；
Dividing gray data by using a threshold, dividing an image into a foreground and a background pixel by pixel, obtaining an average value by using a foreground integrator and a background integrator, averaging to obtain a new threshold, repeating the process until delta is less than or equal to 0.0001, and obtaining a final segmentation result of the foreground and the background.
Further, the dispersion calculation function is:
wherein λ is1，λ2，λ3As weighting coefficients, natomIs the number of metal particles, SatomFor each area of metal particles, medgeFor triangulation of the mean value of all side lengths, stdedgeIs the standard deviation of all side lengths after triangulation,the area of the ith cluster.
This example shows a Pt/A catalyst for cracking and reforming industrial petroleuml2O3The detailed steps of the proposed method are explained as an example.
The general flow of the method of the invention for calculating the degree of metal dispersion in a supported metal catalyst is schematically illustrated in FIG. 1.
Referring to fig. 2, the metal atom or particle identification flowchart includes top-hat transformation, sequentially top-hat transformation, frequency domain method substrate filtering, image sharpening, dynamic threshold binarization processing, and target region labeling processing.
The original image of the supported metal catalyst is shown in fig. 3, the metal atoms/particles are bright parts, the substrate is a gray part, and the background is a black part; in order to count the distribution of metal atoms/particles, it is necessary to identify bright color portions including single points, clusters, and particles in the image.
Fig. 4 illustrates a top-hat transformed picture.
In order to better identify metals, a base part needs to be removed, and because the fluctuation of the base part is very small, a high-pass frequency domain filtering method is adopted to filter out low-frequency components of the base, and then Fourier inversion is carried out, so that an image with the base basically removed can be obtained.
The spectrum after the fourier transform is shown in fig. 5, and after the inverse fourier transform is shown in fig. 6, it can be seen that the basis components have been removed much, but still have traces, and need to be further processed later.
In order to improve the identification accuracy of metal atoms/particles in the image, the image is sharpened by using a laplacian operator, and the sharpening result is shown in fig. 7.
As seen in fig. 7, the images are mainly classified into three categories: black background, grey substrate part, metal particles (bright spots), the next step is to identify the bright spots.
Histogram statistics were performed on a number of images, the results are shown in fig. 8, where the grey values were normalized (divided by 255). The image gray level histogram does not show two peaks or multiple peaks, only has a single peak, and the threshold is difficult to select by using the traditional method for determining the valley bottom.
The invention adopts a method of dynamically generating a threshold value to carry out binarization processing, and an iterative formula for calculating the threshold value is as follows:
hkthe number of pixels when the gray scale is k value is iterated until | Ti+1-Ti|＜Δ。
First, it can be seen from observing the histogram that the gray values of the image are mostly concentrated between [0,80], a black background and a gray load substrate are concentrated, and a binarization threshold is selected between the gray load substrate and the metal atoms, i.e. the black background is not a factor to be considered, so that the black background is removed, the remaining statistical data is used as a basis for segmentation, and the gray value range is selected as [ low, high ] ═ 60,230 according to the statistical result.
The whole idea of the dynamic threshold generation method is explained by using fig. 9, the gray data is divided by using the threshold, the image is divided into the foreground and the background pixel by pixel, the average value is obtained by using the foreground integrator and the background integrator, then the average is carried out to obtain a new threshold, the above processes are repeated until delta is less than or equal to 0.0001, and the final segmentation result of the foreground and the background is obtained, as shown in fig. 10.
The binary image is divided into a single-point map and a cluster map to obtain fig. 11 and 12, respectively, where fig. 11 includes the identified metal single atoms and fig. 12 includes the identified metal cluster portions.
Since the image may contain non-substrate portions, the non-substrate portions need to be removed, not counting the total area of the image. Fig. 13 is a divided image with and without a substrate portion, and a black appearing portion is an area without a substrate and a white portion is an area with a substrate.
After the metal atoms/particles are identified in the above procedure, an example of a calculated dispersion is given below, but not limited thereto:
in order to count the integral condition of the dispersion of the catalyst metal, all metal particles are connected into a triangular mesh by utilizing a triangulation method, a Delaunay triangulation method is adopted, the minimum angle of a triangle formed by the Delaunay triangulation is the largest in triangulation possibly formed by a dispersed point set, and the Delaunay triangulation has good properties and can represent the distribution condition of metal atoms/particles.
In the triangulation network, the distance between atoms (the side length of a triangle) and the number of vertices of the triangle (the number of metal atoms) are obtained, the area of a metal cluster and the area occupied by the metal atoms are added, and the mathematical formula of the metal dispersion degree of the catalyst is embodied as:
wherein λ is1，λ2，λ3As weighting coefficients, natomIs the number of metal particles, SatomFor each area of metal particles, medgeFor triangulation of the mean value of all side lengths, stdedgeIs the standard deviation of all side lengths after triangulation,
the area of the ith cluster.
Fig. 14 is a schematic diagram of a result after triangulation, a first term in calculation of the dispersion degree considers a proportion of the area of a single metal particle occupying the total area, the larger the proportion is, the higher the dispersion degree is, and the better the catalytic effect is, a second term is a ratio of an average distance of the particles to a standard deviation of the distances, the larger the average distance is, the smaller the standard deviation is, the higher the dispersion degree is, a third term is a proportion of all cluster areas occupying the total area, the larger the proportion is, the lower the dispersion degree is, and the lower the catalytic effect is.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. A method for measuring and calculating the dispersion degree of a loaded metal catalyst based on an atomic resolution electron microscope is characterized by comprising the following steps:
(1) acquiring a picture of the metal catalyst by adopting a transmission electron microscope;
(2) identifying metal particles, namely sequentially performing top hat transformation, filtering a substrate by a frequency domain method, image sharpening, dynamic threshold binarization processing and target area marking processing;
(3) calculating the dispersity:
carrying out metal particle identification processing on all the pictures acquired in the step (1) according to the step (2) to obtain a single-point diagram and a cluster diagram corresponding to each picture, calculating the dispersion degree according to picture information provided by the single-point diagram and the cluster diagram, and fitting the dispersion degree into the following function:
Diversity＝f(x1,x2,x3,x4,...)
the picture information comprises the number of metal particles, the distribution position of the metal particles, the number of clusters, the cluster area and the area of the part of the image with the substrate.
2. The method for measuring and calculating the dispersion degree of the supported metal catalyst based on the atomic resolution electron microscope according to claim 1, wherein the step (2) specifically comprises the following steps:
(2-1) top-hat transform is a method of image morphology, defined as image minus image-on operation result, which can highlight bright areas in a darker background:
where b is a structural element in the top-hat transform operation, f is the original image,
the structural element b carries out opening operation on the image f;
(2-2) filtering low-frequency components of the substrate by adopting a high-pass frequency domain filtering method, and then performing Fourier inverse transformation;
(2-3) sharpening the Fourier transformed image by adopting a Laplace operator;
(2-4) carrying out binarization processing on the gray level histogram of the image by adopting a method for dynamically generating a threshold value, then marking a target area, wherein an iterative formula for calculating the threshold value is as follows:
hkthe number of pixels when the gray scale is k value is iterated until | Ti+1-Ti|＜Δ；
Dividing gray data by using a threshold, dividing an image into a foreground and a background pixel by pixel, obtaining an average value by using a foreground integrator and a background integrator, averaging to obtain a new threshold, repeating the process until delta is less than or equal to 0.0001, and obtaining a final segmentation result of the foreground and the background.
3. The method for measuring and calculating the dispersion degree of the loaded metal catalyst based on the atomic resolution electron microscope as claimed in claim 1, wherein the dispersion degree calculation function is as follows:
wherein λ is1，λ2，λ3As weighting coefficients, natomIs the number of metal particles, SatomFor each area of metal particles, medgeFor triangulation of the mean value of all side lengths, stdedgeIs the standard deviation of all side lengths after triangulation,the area of the ith cluster.
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