1. A method for determining the value of a wide-distribution solid particle size standard substance applied to a dry dispersion system of a laser diffraction particle size analyzer is characterized in that,

the value fixing method comprises the following steps of:

step 1): selecting an initial sample: the selected initial sample is glass bead particles, the sphericity of the particles is more than 95%, the expected characteristic particle size D50 range is 1-20 microns, and the ratio of the expected characteristic particle size D90 to the expected characteristic particle size D10 range is 1.5-10;

step 2): preparation of particle samples: dispersing the initial sample to prepare a particle sample in a single-particle independent and uniformly dispersed state;

step 3): and (3) estimating: obtaining estimated particle size distribution data of the particle sample prepared in step 2);

the estimated particle size distribution data is obtained by artificial assumption or experimental means;

the estimated particle size distribution data comprises an estimated characteristic particle size D50, an estimated particle size distribution range and a corresponding particle size standard deviation;

step 4): simulating and calculating to obtain a representative minimum particle statistical quantity value required by a fixed value;

the simulation calculation comprises the following steps:

step a): performing Gaussian fitting on the estimated particle size distribution data to obtain a corresponding volume distribution curve;

step b): setting the total volume of the particle sample prepared in the step 2) as V, and dividing the volume distribution curve into n equal subintervals; in each subinterval i (i is 1 … n), the particle size values in the interval are repeatedly and randomly generated until the sum of the volumes corresponding to the particle size values in the interval reaches the theoretical volume V occupied by the particle size interval_iIn this case, the number of particle size values in each subinterval is N_i；

Step c): combining the particle size values of each subinterval to form N simulation sampling pools, randomly taking L particle size values from the simulation sampling pools, and performing statistical analysis on the L particle size values to obtain corresponding simulation statistical characteristic particle sizes D50;

step d): comparing the simulated statistical characteristic particle diameter D50 obtained in the step c) with the estimated characteristic particle diameter D50, and calculating an error; when the fluctuation range of the error value is +/-0.3-0.4%, the corresponding minimum L value is the minimum particle statistical number value;

step 5) scanning imaging, statistics and analysis:

scanning and imaging the particle sample prepared in the step 2) by using a scanning electron microscope;

measuring the diameters of the scanned and imaged particles one by adopting an internal standard method, and performing statistical analysis according to the minimum particle statistic value obtained in the step 4) to obtain actual particle size distribution and particle characteristic particle size D50 of the particles and measurement uncertainty corresponding to the particle characteristic particle size D50.

2. The method of claim 1, wherein:

the preparation of the particle sample of the step 2) comprises the operations of rotating, cross-dividing and high-pressure dispersion;

the operation of the rotary cross division is as follows: carrying out rotary cross division on the initial sample selected in the step 1) by adopting a dry powder disperser to obtain a divided sample with the mass of 0.01-0.05 g;

the high-pressure dispersion operation comprises the following steps: and placing the sub-sample in a sample groove arranged at the upper part of the closed space, dispersing the particles of the sub-sample into a plurality of round holes uniformly distributed around the sample groove in a high-pressure spraying manner, and freely settling the particles on a sample table below from the round holes to obtain the particle sample in a single-particle independent and uniformly dispersed state.

3. The method of claim 2, wherein:

and (2) carrying out rotary cross division on the initial product selected in the step 1) to gradually divide the initial product into 10 g/bottle, after the uniformity among bottles is checked, controlling the relative uncertainty contributed by the non-uniformity among bottles of the particle characteristic particle size D50 value among each bottle, randomly selecting 1 bottle, and continuously carrying out rotary cross division to 0.01 g-0.05 g.

4. The method of claim 2, wherein:

the ratio of the diameter of the sample groove, the diameter of a plane formed by the round holes to the diameter of a plane on which the particle samples are distributed on the sample table is 1: 2: 6-1: 3: 9;

the ratio of the plane diameter of the particle sample distribution on the sample table to the height of the closed space is 1: 1-1: 2.

5. the method of claim 4, wherein:

the diameter range of the round hole is 1-5 mm.

6. The method of claim 5, wherein:

in the step 1), selecting the expected characteristic particle size D50 range of the sample to be 8-12 microns;

in the step 3), the diameter of the round hole is 2-4 mm; the diameter of the sample groove is 0.8-1.2 cm; the number of the round holes is 11-13;

the injection pressure of the high-pressure injection is 3-5 bar;

the vertical height from the circular hole to the sample table is 11-13 cm; the plane diameter range of the particle sample distribution on the sample table is 7-9 cm;

in the step 5), the magnification of the scanning electron microscope is 5000 times, and the imaging resolution is 1534 × 1024.

7. The valuing method of any one of claims 1-6, wherein:

the estimated particle size distribution data is obtained through an experimental means; the experimental means is to adopt a laser diffraction method particle size analyzer to carry out rough measurement to obtain the estimated particle size distribution data, or adopt a scanning electron microscope to randomly obtain particle images, and carry out image processing to obtain the estimated particle size distribution data.

8. The valuing method of any one of claims 1-6, wherein:

in the step 5), when the estimated characteristic particle diameter D50 is 1-5 micrometers, the magnification of the scanning electron microscope is set to 20000 times, and the imaging resolution is set to 1536 × 1024;

when the estimated characteristic particle diameter D50 is 5-20 micrometers, the magnification of the scanning electron microscope is set to 5000 times, and the imaging resolution is set to 1534 × 1024.

Background

The requirement for measuring the particle size is widely applied to the fields of energy, chemical industry, food, pharmacy and the like. Particle size measuring instruments, such as particle sizers, have become important tools for characterizing the particle size and distribution of micron-sized nanoparticles. And the accuracy of the measuring instrument requires the calibration and verification of the particle size standard substance. The particle size standard substance is an effective carrier for particle size measurement and also largely determines the accuracy and reliability of the particle size measurement.

The laser diffraction method for particle size analysis is developed and applied more maturely from the beginning of the creation over decades, and has become the mainstream of particle size analysis in the 21 st century without replacement. The market share of the laser diffraction particle size analyzer in China is up to 60-70% at present; the advantages are mainly as follows: sophisticated measurement principles; the measurement range is wide, about 20 nanometers to 2000 micrometers, and the particle size ranges of nanometer, submicron and micrometer are covered; the measurement speed is high, the test time is irrelevant to the particle size distribution of a sample, and the typical test process is generally less than one minute; each test is carried out, the sample is scanned for many times, and the repeatability of the test result is good; the sample introduction modes are various and can be suitable for various types of samples.

The requirement of laser diffraction particle size analysis on the particle size standard substance is high. The ISO 13320:2009 "particle size analysis-laser diffraction method" also requires a standard substance for instrument performance verification: "Standard substance particles should be spherical, have suitable density and optical properties, and be suitable for laser diffraction techniques, particle size distribution D₉₀And D₁₀Should be 1.5 to 10. "

In general, the particle size measuring instrument is mainly calibrated by using a standard particle sample with narrow distribution, and the particle size distribution is concentrated and can be approximately regarded as a particle sample with single particle size. For narrow-distribution or monodisperse particles, the particle size analysis result of the laser diffraction method shows that the particle size of the particles has a certain distribution range, and the measurement result of the laser diffraction method has a certain error in the analysis of the particle size distribution, i.e., the narrow-distribution or monodisperse particles are not suitable for the particle size analysis of the laser diffraction method, which is different from the prior knowledge. However, with the improvement of the particle size measurement standard, the current particle size standard substances, especially the standard substances suitable for the particle size analysis by the laser diffraction method, are gradually shifted to the wide-distribution particle size standard substances.

The national quality supervision administration published JJF1211-2008 laser particle analyzer calibration specifications in 2008, and specified specifications are made on particle sizes of standard substances for instrument calibration and uncertainty of standard values of the standard substances, and the specifications are shown in Table 1 below.

TABLE 1

D50Magnitude range	Uncertainty of standard substance
		1μm<D50<5μm	5％，k＝2
5μm<D50<20μm	3％，k＝2
		20μm<D50<100μm	2.5％，k＝2
D50>100μm	2.5％，k＝2

For 20 μm<D₅₀<100 μm, and D₅₀>The uncertainty of the standard substance is relatively easy to control at a low level for the 100 μm particles.

But less than 20 μm, e.g. 1 μm<D₅₀<5 μm and 5 μm<D₅₀<20 μm, the relative uncertainty of the standard is more difficult to control; in particular, the relative uncertainty of the widely distributed solid particle size standards currently used in dry dispersions for laser diffraction particle size analysis is typically above 5.7%, exceeding the 3% and 5% values required in table 1.

Therefore, those skilled in the art would like to be able to improve the existing method for determining the value of the standard substance of the broad-distribution solid particle size, control the relative uncertainty of the standard substance, and develop a standard substance of the broad-distribution solid particle size which is suitable for dry dispersion of laser diffraction particle size analysis and meets the above-mentioned national regulation requirements.

Disclosure of Invention

In order to solve the above technical problems, the present invention provides, in one aspect, a method for valuing a standard substance of a wide-distribution solid particle size for a dry dispersion system applied to a laser diffraction particle size analyzer, wherein,

the value fixing method comprises the following steps of:

step 1): selecting an initial sample: the selected initial sample is glass bead particles, the sphericity of the particles is more than 95%, the expected characteristic particle size D50 range is 1-20 microns, and the ratio of the expected characteristic particle size D90 to the expected characteristic particle size D10 range is 1.5-10;

step 2): preparation of particle samples: dispersing the initial sample to prepare a particle sample in a single-particle independent and uniformly dispersed state;

step 3): and (3) estimating: obtaining estimated particle size distribution data of the particle sample prepared in step 2);

the estimated particle size distribution data is obtained by artificial assumption or experimental means;

the estimated particle size distribution data includes an estimated characteristic particle size D50, an estimated particle size distribution range and its corresponding particle size standard deviation;

step 4): simulating and calculating to obtain a representative minimum particle statistical quantity value required by a fixed value;

the simulation calculation comprises the following steps:

step a): performing Gaussian fitting on the estimated particle size distribution data to obtain a corresponding volume distribution curve;

step b): setting the total volume of the particle sample prepared in the step 2) as V, and dividing the volume distribution curve into n equal subintervals; in each subinterval i (i is 1 … n), the particle size values in the interval are repeatedly and randomly generated until the sum of the volumes corresponding to the particle size values in the interval reaches the theoretical volume V occupied by the particle size interval_iIn this case, the number of particle size values in each subinterval is N_i；

Step c): combining the particle size values of each subinterval to form N simulation sampling pools, randomly taking L particle size values from the simulation sampling pools, and performing statistical analysis on the L particle size values to obtain corresponding simulation statistical characteristic particle sizes D50;

step d): comparing the simulated statistical characteristic particle diameter D50 obtained in the step c) with the estimated characteristic particle diameter D50, and calculating an error; when the fluctuation range of the error value is +/-0.3-0.4%, the corresponding minimum L value is the minimum particle statistical number value;

step 5) scanning imaging, statistics and analysis:

scanning and imaging the particle sample prepared in the step 2) by using a scanning electron microscope;

measuring the diameters of the scanned and imaged particles one by adopting an internal standard method, and performing statistical analysis according to the minimum particle statistic value obtained in the step 4) to obtain actual particle size distribution and particle characteristic particle size D50 of the particles and measurement uncertainty corresponding to the particle characteristic particle size D50.

Preferably, the preparation of the particle sample of the step 2) comprises an operation of rotating cross division and an operation of high-pressure dispersion;

the operation of the rotary cross division is as follows: carrying out rotary cross division on the initial sample selected in the step 1) by adopting a dry powder disperser to obtain a divided sample with the mass of 0.01-0.05 g;

the high-pressure dispersion operation comprises the following steps: and placing the sub-sample in a sample groove arranged at the upper part of the closed space, dispersing the particles of the sub-sample into a plurality of round holes uniformly distributed around the sample groove in a high-pressure spraying manner, and freely settling the particles on a sample table below from the round holes to obtain the particle sample in a single-particle independent and uniformly dispersed state.

Preferably, the initial product selected in the step 1) is reduced to 10 g/bottle step by adopting rotary cross reduction, after the uniformity test among bottles, the relative uncertainty contributed by the non-uniformity among bottles of the particle characteristic particle size D50 value among each bottle is controlled, 1 bottle is randomly selected, and the rotary cross reduction is continued to be carried out to 0.01 g-0.05 g.

Preferably, the ratio of the diameter of the sample groove, the diameter of the plane formed by the plurality of circular holes and the diameter of the plane on which the particle sample is distributed on the sample stage is 1: 2: 6-1: 3: 9;

the ratio of the plane diameter of the particle sample distribution on the sample table to the height of the closed space is 1: 1-1: 2.

preferably, the diameter range of the round hole is 1-5 mm.

Preferably, in the step 1), the expected characteristic particle size D50 of the sample is selected to be in a range of 8-12 microns;

in the step 3), the diameter of the round hole is 2-4 mm; the diameter of the sample groove is 0.8-1.2 cm; the number of the round holes is 11-13;

the injection pressure of the high-pressure injection is 3-5 bar;

the vertical height from the circular hole to the sample table is 11-13 cm; the plane diameter range of the particle sample distribution on the sample table is 7-9 cm;

in the step 5), the magnification of the scanning electron microscope is 5000 times, and the imaging resolution is 1534 × 1024.

Preferably, the estimated particle size distribution data is obtained by experimental means; the experimental means is to adopt a laser diffraction method particle size analyzer to carry out rough measurement to obtain the estimated particle size distribution data, or adopt a scanning electron microscope to randomly obtain particle images and carry out image processing to obtain the estimated particle size distribution data.

Preferably, in the step 5), when the estimated characteristic particle diameter D50 is 1 to 5 micrometers, the magnification of the scanning electron microscope is set to 20000 times, and the imaging resolution is set to 1536 × 1024;

when the estimated characteristic particle diameter D50 is 5-20 micrometers, the magnification of the scanning electron microscope is set to 5000 times, and the imaging resolution is set to 1534 × 1024.

The invention provides a method for valuing a wide-distribution solid particle size standard substance applied to a dry dispersion system of a laser diffraction particle size analyzer, which particularly aims at the dry dispersion system of the laser diffraction particle size analyzer and carries out particle size valuing on the wide-distribution solid particle size standard substance with the particle size of 1-20 mu m; by adopting the value fixing method, on one hand, a representative and effective standard substance can be obtained when the statistical quantity of the particles is low, and the workload of statistical analysis is greatly reduced, and on the other hand, the relative uncertainty generated in the value fixing process can be controlled at a low level so as to meet the national standard requirement.

Drawings

FIG. 1 is a partial example of a scanning electron micrograph of the particles obtained in example 1;

FIG. 2 is a volume distribution curve in step a) of the simulation calculation of example 1 of the present invention;

FIG. 3 is a graph showing the relationship between different sampling numbers L and the generated relative error in the simulation calculation according to embodiment 1 of the present invention;

FIG. 4 is a volume distribution curve in step a) of simulation calculation in example 2 of the present invention;

FIG. 5 is a graph showing the relationship between different sampling numbers L and the generated relative error in the simulation calculation of embodiment 2 of the present invention.

Detailed Description

The present invention will be described in detail below with reference to specific embodiments shown in the drawings. These embodiments are not intended to limit the present invention, and structural, methodological, or functional changes made by those of ordinary skill in the art in light of these embodiments are intended to be within the scope of the present invention.

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.

Example 1

The method for valuing a broad distribution solid particle size standard substance of example 1, the method comprising the steps of, in order:

step 1): selecting an initial sample: the initial sample selected was a product of glass bead particles (a product of "high refractive index glass beads (nD ═ 1.93)" available from retroreflection materials ltd, shenfu, jiang), the initial sample weight was 3kg, the sphericity of the particles was greater than 95%, and the expected characteristic particle diameter D50 was about 10 μm.

In one embodiment of the present application, the ratio of the expected characteristic particle diameter D90 to D10 of the initial sample after rough measurement is 1.5-10; in this example, the ratio of the expected characteristic particle size of the initial sample, roughly measured, D90 to D10 was about 2.3.

Step 2): preparation of particle samples: dispersing the initial sample to prepare a particle sample in a single-particle independent and uniformly dispersed state;

in a specific embodiment of the present application, the preparation of the particle sample of step 2) comprises an operation of spinning to fork reduction and an operation of high pressure dispersion;

the operation of the rotary cross division is as follows: carrying out rotary cross division on the initial sample selected in the step 1) by adopting a dry powder disperser to obtain a divided sample with the mass of 0.01-0.05 g;

the high-pressure dispersion operation comprises the following steps: and placing the sub-sample in a sample groove arranged at the upper part of the closed space, dispersing the particles of the sub-sample into a plurality of round holes uniformly distributed around the sample groove in a high-pressure spraying manner, and freely settling the particles on a sample table below from the round holes to obtain the particle sample which is independent of single particles and in a uniformly dispersed state.

In one embodiment of the present application, the initial product selected in step 1) is reduced to 10 g/bottle by stages by using rotary cross reduction, the relative uncertainty contributed by the non-uniformity between bottles of the particle characteristic particle size D50 value between each bottle is controlled, 1 bottle is randomly selected, and the rotary cross reduction is continued to be 0.01 g-0.05 g.

Specifically, in the present example, the relative uncertainty contributed by the bottle-to-bottle nonuniformity of the particle characteristic particle diameter D50 value between each bottle was controlled to be ± 0.5% or less.

Specifically, in this example, the mass of the divided sample obtained after the rotational cross-division was about 0.02 g.

In this embodiment, in the operation of high-pressure dispersion, the sample tank is communicated with a high-pressure gas source (generally using He gas), and particles of the divided sample are uniformly dispersed to the surrounding circular holes by high-pressure injection.

In a specific embodiment of the present application, a ratio of a diameter of the sample groove, a diameter of a plane formed by the plurality of circular holes, and a diameter of a plane on which the particle sample is distributed on the sample stage is 1: 2: 6-1: 3: 9; the ratio of the plane diameter of the particle sample distribution on the sample table to the height of the closed space is 1: 1-1: 2.

in a more preferred embodiment of the present application, the diameter of the circular hole ranges from 1 to 5 mm.

In the embodiment, the mass of the divided sample on the sample groove is 0.02g, the diameter of the sample groove is about 1cm, the distance from the center of the sample groove to the center of the circular hole is about 1.3cm, and the pressure of high-pressure injection is about 4 bar; the diameter of the circular hole is about 3 mm; the distance between the centers of the adjacent circular holes is about 2.3 times of the diameter of the circular hole; the number of the round holes is 12; the vertical height from the circular hole to the sample table is 12 cm; after high-pressure spraying, the particles of the divided sample are uniformly dispersed to the round holes at the periphery, freely fall from the round holes and settle to a sample table, and finally the plane diameter range of the plane diameter of the particle sample distribution on the sample table is about 8 cm.

On the basis of knowing the above parameter characteristics, the skilled person can adjust the high-pressure injection pressure according to the mass and volume of the sample, the distribution size of the sample grooves, and the distance between the center of the sample grooves and the center of the circular hole, so as to ensure that the particles falling on the sample table are in a single-particle independent and uniformly dispersed state.

Step 3): and (3) estimating: obtaining estimated particle size distribution data of the particle sample prepared in step 2);

the estimated particle size distribution data is obtained by artificial assumption or experimental means;

the estimated particle size distribution data includes an estimated characteristic particle size D50, an estimated particle size distribution range, and its corresponding particle size standard deviation.

In a particular embodiment of the present application, the estimated particle size distribution data is obtained experimentally; the experimental means is to adopt a laser diffraction method particle size analyzer to carry out rough measurement to obtain the estimated particle size distribution data, or adopt a scanning electron microscope to randomly obtain particle images, and carry out image processing to obtain the estimated particle size distribution data.

Specifically, in this embodiment, a scanning electron microscope is used to randomly obtain particle images, and the estimated particle size distribution data is obtained by performing image processing.

Step 4): simulating and calculating to obtain a representative minimum particle statistical quantity value required by a fixed value;

the simulation calculation comprises the following steps:

step a): performing Gaussian fitting on the estimated particle size distribution data to obtain a corresponding volume distribution curve;

step b): setting the total volume of the particle sample prepared in the step 2) as V, and dividing the volume distribution curve into n equal subintervals; in each subinterval i (i is 1 … n), the particle size values in the interval are repeatedly and randomly generated until the sum of the volumes corresponding to the particle size values in the interval reaches the theoretical volume V occupied by the particle size interval_iIn this case, the number of particle size values in each subinterval is N_i；

Step c): combining the particle size values of each subinterval to form N simulation sampling pools, randomly taking L particle size values from the simulation sampling pools, and performing statistical analysis on the L particle size values to obtain corresponding simulation statistical characteristic particle sizes D50;

step d): comparing the simulated statistical characteristic particle diameter D50 obtained in the step c) with the estimated characteristic particle diameter D50, and calculating an error; and when the fluctuation range of the error value is +/-0.3-0.4%, the corresponding minimum L value is the representative minimum particle statistical quantity value required by the fixed value.

In this embodiment, Matlab software is used for simulation calculation, and the specific calculation process is as follows:

step a): estimated characteristic particle size D50-10.2917 microns, D10-7.2067 microns and D90-12.8546 microns, standard deviation 2.0, corresponding volume distribution curves were obtained, see fig. 2;

step b): the total volume of the particle group of the selected sample was set to V (in this example, the total volume V was 4.6 × 10)⁸Cubic microns) into equal n sub-regions (specifically in this embodiment, n is chosen to be 1000); in each subinterval i (i is 1 … n), the particle size values in the interval are repeatedly and randomly generated by software until the sum of the volumes corresponding to the particle size values in the interval reaches the theoretical volume V occupied by the particle size interval_iIn this case, the number of particle size values in each subinterval is N_i；

Step c): combining the particle size values of each subinterval to form N simulation sampling pools; in the present embodiment, a simulated sampling pool with N being 100 ten thousand is obtained according to the volume distribution curve;

randomly taking L particle size values, and performing statistical analysis on the L particle size values to obtain corresponding simulated statistical characteristic particle size D50;

step d): comparing the simulated statistical characteristic particle diameter D50 obtained in the step c) with the estimated characteristic particle diameter D50, and calculating an error; and when the fluctuation range of the error value is +/-0.3-0.4%, the corresponding minimum L value is the representative minimum particle statistical quantity value required by the fixed value.

Changing the value of L, for example, 1 thousand, 2 thousand, 3 thousand.

Referring to fig. 3, the relative error resulting from different sample numbers L is shown; as can be seen from the figure, in the embodiment, the minimum L value corresponding to the error value within a fluctuation range of about ± 0.3 to 0.4% is about 2 ten thousand, which is a representative statistical quantity value of the particles required for the value determination in step 5).

Step 5) scanning imaging, statistics and analysis:

scanning and imaging the particle sample prepared in the step 2) by using a scanning electron microscope.

Measuring the diameters of the scanned and imaged particles one by adopting an internal standard method, and performing statistical analysis according to the minimum particle statistic value obtained in the step 4) to obtain actual particle size distribution and particle characteristic particle size D50 of the particles and measurement uncertainty corresponding to the particle characteristic particle size D50.

For a wide distribution solid particle size standard, the relative uncertainty of its fixed value mainly comes from several aspects, [1] grid length relative uncertainty for scanning electron microscope calibration; [2] when shooting the particles, scanning the magnification of an electron microscope; [3] when the particles are shot, the imaging resolution of a scanning electron microscope is scanned; [4] digital image pixel threshold setting when particles are measured; [5] the width of the particle distribution; [6] participating in counting the number of particles; [7] non-uniformity among the dispensed bottles; [8] instability on long-term storage.

Regarding items [1], [7] and [8], there is no relation to the method of determining a value of the present application, and a default value for contribution to relative uncertainty is set according to the routine knowledge of those skilled in the art. In particular in this example, the initial sample was selected to have a particle size D50 of 10 microns, which is expected to control the overall uncertainty in the fixed value to a level below 2%; thereby setting the relative uncertainty contributed by the inter-bottle non-uniformity of the dispensing of item [7] to 0.5%, and the relative uncertainty contributed by the instability of the long-term storage of item [8] to 0.5%. As for item [1], in this embodiment, the scanning electron microscope is calibrated with checkerboard pixels, and the selected checkerboard length contributes to a relative uncertainty range of 0.5% or less.

The inventor of the application finds that through a large number of experimental researches, the wide-distribution solid particle size standard substance applied to a dry dispersion system of a laser diffraction particle size analyzer, particularly the wide-distribution solid particle size standard substance with the particle size smaller than 20 micrometers, the process of simulation calculation is very critical, the minimum particle statistical quantity value with representativeness required by fixed value is obtained through simulation calculation, the standard substance with representativeness and effectiveness can be obtained when the particle statistical quantity is lower, the workload of statistical analysis is greatly reduced, and more importantly, the relative uncertainty generated in the fixed value process can be controlled at a lower level.

In addition, parameter control of the magnification and imaging resolution of the scanning electron microscope is important.

In one embodiment of the present application, the relative uncertainty in particle size measurements due to the magnification and imaging resolution of the scanning electron microscope is shown in table 2 when the expected particle size is 10 microns.

TABLE 2

In one embodiment of the present application, when the estimated characteristic particle diameter D50 is 1-5 μm, the magnification of a scanning electron microscope is 20000 times, and the imaging resolution is 1536 × 1024.

In another embodiment of the present application, when the estimated characteristic particle diameter D50 is 5 to 20 μm, the scanning electron microscope has a magnification of 5000 times and an imaging resolution of 1534 × 1024.

Specifically, in this example, the expected characteristic particle diameter D50 of the particle sample was around 10 μm, the magnification of the scanning electron microscope was 5000 times, and the imaging resolution was 1534 × 1024.

Referring to fig. 1, there is shown (partially) an example of a scanning electron micrograph of the particles obtained in example 1.

Specifically, in this embodiment, the diameter of the scanned and imaged particles is measured one by using an internal standard method, and statistical analysis is performed according to the minimum statistical number value (2 ten thousand) of particles obtained in step 4), so as to obtain the actual characteristic particle diameter D50 of the particles, which is 10.3 micrometers.

For the rating method of example 1 of the present application, the inventors calculated the relative uncertainty and see table 3 below for the results.

TABLE 3

And (4) supplementary notes: the calculation formula of the synthetic relative uncertainty is as follows:

the formula for the extended relative uncertainty is: u shape₉₅＝2*u_crel(x)(k＝2)

As can be seen from the above Table 3, the broad distribution solid particle size standard substance having a particle size of less than 20 μm obtained by the quantitative method of example 1 has a relative uncertainty of expansion equal to 2.0% in the above items [1] to [8 ].

By adopting the fixed value method of the embodiment 1, the relative uncertainty generated by the items [2] to [6] can be effectively estimated and greatly reduced, and the total relative uncertainty is conveniently controlled at a lower level so as to meet the national standard requirements.

Example 2

The method for valuing a broad distribution solid particle size standard substance of example 2, the method comprising the steps of, in order:

step 1): selecting an initial sample: 10g of a 1 kg product of glass bead granules (a product of "high refractive index glass beads (nD ═ 1.93)" available from shenfu, jiang, west) as a starting sample of example 2, the particles had a sphericity of more than 95%, an expected characteristic particle diameter D50 of about 3 μm, and a ratio of the expected characteristic particle diameter D90 to the expected characteristic particle diameter D10 of about 1.6, were randomly selected.

Step 2): preparation of particle samples: dispersing the initial sample selected in the step 1) to prepare and obtain a particle sample in a single-particle independent and uniformly dispersed state;

in this example, the preparation of the pellet sample of step 2) includes an operation of rotary cross-division and an operation of high-pressure dispersion;

wherein, the operation of rotating the cross division is as follows: carrying out rotary cross division on the initial sample selected in the step 1) by adopting a dry powder disperser; specifically, the method comprises the steps of reducing the grain size to 10 g/bottle in a step-by-step manner by adopting rotary cross division, controlling the relative uncertainty (for example, the relative uncertainty is less than or equal to +/-0.5%) contributed by the inter-bottle nonuniformity of the grain characteristic grain size D50 value among each bottle, randomly selecting 1 bottle, and continuing to rotate the cross division to 0.01 g.

Wherein, the high-pressure dispersion operation comprises the following steps: and placing the sub-sample in a sample groove arranged at the upper part of the closed space, dispersing the particles of the sub-sample into a plurality of round holes uniformly distributed around the sample groove in a high-pressure spraying manner, and freely settling the particles on a sample table below from the round holes to obtain the particle sample which is independent of single particles and is in a uniformly dispersed state.

In this embodiment, in the operation of high-pressure dispersion, the sample tank is communicated with a high-pressure gas source (generally using He gas), and particles of the divided sample are uniformly dispersed to the surrounding circular holes by high-pressure injection.

The sample groove is communicated with a high-pressure gas source (generally adopting He gas), and particles of the divided sample are uniformly dispersed to the peripheral round holes in a high-pressure spraying mode.

In the embodiment, the mass of the sub-sample on the sample groove is 0.01g, the diameter of the sample groove is about 0.7cm, the distance from the center of the sample groove to the center of the circular hole is about 2cm, and the pressure of the high-pressure jet is about 3 bar; the diameter of the circular hole is about 2 mm; the distance between the centers of the adjacent circular holes is about 2 times of the diameter of the circular hole; the vertical height from the circular hole to the sample table is 10 cm; after high-pressure spraying, the particles of the divided sample are uniformly dispersed to the round holes at the periphery, freely fall from the round holes and settle to a sample table, and finally the plane diameter range of the particle distribution on the sample table is about 7 cm.

Step 3): and (3) estimating: obtaining estimated particle size distribution data of the particle sample prepared in step 2);

the estimated particle size distribution data is obtained by artificial assumption or experimental means;

the estimated particle size distribution data includes an estimated characteristic particle size D50, an estimated particle size distribution range, and its corresponding particle size standard deviation.

Specifically, in this embodiment, the estimated particle size distribution data is obtained by rough measurement using a laser diffraction particle size analyzer.

Step 4): simulating and calculating to obtain a representative minimum particle statistical quantity value required by a fixed value;

in this embodiment, Matlab software is used for simulation calculation, and the specific calculation process is as follows:

step a): estimated characteristic particle size D50-2.9976 microns, D10-2.3510 microns and D90-3.6330 microns, standard deviation 0.5, corresponding volume distribution curves were obtained, see fig. 4;

step b): the total volume of the particle group of the selected sample was set to V (in this example, the total volume V was 4.6 × 10)⁷Cubic microns) into equal n sub-regions (specifically in this embodiment, n is chosen to be 1000); in each subinterval i (i is 1 … n), the particle size values in the interval are repeatedly and randomly generated by software until the sum of the volumes corresponding to the particle size values in the interval reaches the theoretical volume V occupied by the particle size interval_iIn this case, the number of particle size values in each subinterval is N_i；

Step c): combining the particle size values of each subinterval to form N simulation sampling pools; in the present embodiment, a simulated sampling pool with N being 100 ten thousand is obtained according to the volume distribution curve;

randomly taking L particle size values, and performing statistical analysis on the L particle size values to obtain corresponding simulated statistical characteristic particle size D50;

step d): comparing the simulated statistical characteristic particle diameter D50 obtained in the step c) with the estimated characteristic particle diameter D50, and calculating an error; and when the fluctuation range of the error value is +/-0.3-0.4%, the corresponding minimum L value is the particle statistical number value.

Changing the value of L, for example, 1 thousand, 2 thousand, 3 thousand.

Referring to fig. 5, the relative error resulting from different sample numbers L is shown; as can be seen from the figure, in the embodiment, the minimum L value corresponding to the error value within a fluctuation range of about ± 0.3 to 0.4% is about 4 ten thousand, which is a representative statistical quantity value of the particles required for the value determination in step 5).

Step 5) scanning imaging, statistics and analysis:

scanning and imaging the particle sample prepared in the step 2) by using a scanning electron microscope.

Specifically, in the embodiment, the scanning electron microscope is calibrated by using grid grating pixels, and the relative uncertainty range of the grid grating length is less than 0.5%;

specifically, in this example, the expected characteristic particle diameter D50 of the particles on the sample stage is about 3 μm, the magnification of the scanning electron microscope is 20000 times, and the imaging resolution is 1534 × 1024.

In one embodiment of the present application, the relative uncertainty in particle size measurements due to the magnification and imaging resolution of the scanning electron microscope is shown in table 4 for a particle size of 3 microns.

TABLE 4

Magnification factor	Resolution setting	3 μm particle measurement uncertainty%
			20000X	1536*1024	0.447

Specifically, in this embodiment, the diameter of the scanned and imaged particles is measured one by using an internal standard method, and statistical analysis is performed according to the minimum statistical number value (4 ten thousand) of the particles obtained in step 4), so as to obtain the actual characteristic particle diameter D50 of the particles, which is 3.1 micrometers.

For the rating method of example 2 of the present application, the inventors calculated the relative uncertainty and see table 5 below.

TABLE 5

And (4) supplementary notes: the calculation formula of the synthetic relative uncertainty is as follows:

the formula for the extended relative uncertainty is: u shape₉₅＝2*u_crel(x)(k＝2)

As can be seen from the above Table 5, the broad distribution solid particle size standard substance having a particle size of less than 5 μm obtained by the quantitative method of example 2 produced a relative uncertainty of expansion of less than 2.0% in the above items [1] to [8 ].

By adopting the fixed value method of the embodiment 2, the relative uncertainty generated by the items [2] to [6] can be effectively estimated and greatly reduced, and the total relative uncertainty is conveniently controlled at a lower level so as to meet the national standard requirements.

In summary, the inventor of the present application has improved the method for determining the value of the small-particle-size (particle size less than 20 microns) wide-distribution solid particle size standard substance applied to the dry dispersion system of the laser diffraction particle size analyzer, and on one hand, the minimum particle statistics value required for determining the value is obtained through simulation calculation, which can greatly reduce the workload of statistical analysis, and more importantly, can control the relative uncertainty generated in the whole value determining process to a lower level.

It should be understood that although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description of the embodiments is for clarity reasons only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can also be combined appropriately to form other embodiments understood by those skilled in the art.

The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.