Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/10—Investigating individual particles
  • G01N15/14—Optical investigation techniques, e.g. flow cytometry
  • G01N15/1429—Signal processing
  • G01N15/1433—Signal processing using image recognition
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/10—Investigating individual particles
  • G01N15/14—Optical investigation techniques, e.g. flow cytometry
  • G01N15/1429—Signal processing
• • H—ELECTRICITY
  • H01—ELECTRIC ELEMENTS
  • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
  • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
  • H01J37/02—Details
  • H01J37/22—Optical or photographic arrangements associated with the tube
  • H01J37/222—Image processing arrangements associated with the tube
• • H—ELECTRICITY
  • H01—ELECTRIC ELEMENTS
  • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
  • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
  • H01J37/26—Electron or ion microscopes; Electron or ion diffraction tubes
  • H01J37/28—Electron or ion microscopes; Electron or ion diffraction tubes with scanning beams
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/10—Investigating individual particles
  • G01N2015/1006—Investigating individual particles for cytology
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/10—Investigating individual particles
  • G01N15/14—Optical investigation techniques, e.g. flow cytometry
  • G01N2015/1493—Particle size
• • H—ELECTRICITY
  • H01—ELECTRIC ELEMENTS
  • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
  • H01J2237/00—Discharge tubes exposing object to beam, e.g. for analysis treatment, etching, imaging
  • H01J2237/245—Detection characterised by the variable being measured
  • H01J2237/24571—Measurements of non-electric or non-magnetic variables
• • H—ELECTRICITY
  • H01—ELECTRIC ELEMENTS
  • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
  • H01J2237/00—Discharge tubes exposing object to beam, e.g. for analysis treatment, etching, imaging
  • H01J2237/26—Electron or ion microscopes
  • H01J2237/28—Scanning microscopes
  • H01J2237/2801—Details

Definitions

• the present invention relates to a method for the dimensional and morphological characterization of particles of a divided solid or powder.
• the knowledge of the size and shape of the particles of the powder is undoubtedly an important parameter in the characterization of a powder.
• the size and shape of the particles affect the behavior of the powder, such as its flow, segregation, flowability, slicing, volatility and solubility.
• the particle size of the powder very often enters into industrial and commercial criteria put forward as the ability to filtration, capping, assimilation for a drug, air pollution, pelleting, etc.
• Characterization of the structure of the powders is very important to understand and control their physical or chemical interactions with any other solid or fluid phase with which they interact.
• a powder is formed of solid particles having a more complex shape and different sizes. For more complex shapes, the number of sizes to know to determine the size increases.
• the most widespread divided solid particle size measurements in the case of powders whose particles are of medium size (between about 1 and 2000 micrometers) are generally made by laser diffraction, impedance variation or image analysis.
• the particle size measurement made by the laser diffractometers is based on the light scattering (diffraction, reflection and refraction) of monochromatic radiation from a laser through a suspension of particles.
• the particle size measurement performed by image analysis is performed on static particles.
• Image analysis methods are generally based on the use of an optical microscope.
• the software used is Oxford Instrument Inca feature software or UPMKymmene Oyj / VTT Technical Research Center of Finland software Poikkiprogram.
• the image analysis allows to determine the aspect ratio of the diameter or elongation factor and a form factor SF of the particles (for a three-dimensional evaluation):
• the aspect ratio is defined by the ratio of the minimum width of Feret to the maximum length of Feret.
• the maximum length and the minimum width of Feret are the distances between two tangents parallel to opposite sides of the particle.
• the maximum length Lmax and the minimum Imin width of Feret of a particle 1 are shown in FIG.
• the aspect ratio makes it possible to characterize the shape anisotropy of the particle, ie its elongation. It is defined as the ratio of the maximum length Lmax and the minimum width Imin of Feret. It reflects only the elongation of the particle and its symmetry but does not allow to distinguish between a spherical or cubic particle.
• the shape factor SF does not allow it to distinguish between a substantially spherical particle and a substantially cubic particle.
• the subject of the present invention is precisely a method for characterizing particles of a solid divided by image analysis, which automatically makes it possible to know more precisely and more reliably than in the prior art the actual shape of the particles and their size.
• Another object of the invention is to propose a particle characterization method which is suitable for all types of particles, whereas certain laser diffraction techniques are not particularly suitable for particles which can not be set in motion by magnetic stirring.
• Yet another object of the invention is to provide a particle characterization method which allows easy access from the image to the average of the equivalent diameters of the particles and to the particle size dispersion around the average value.
• the present invention relates to a method for characterizing particles of a divided solid comprising the following steps:
• this type of geometric figure being called a geometric model
• the characteristic size being the square root of the sum of its length squared, its width squared and its height squared, its length, width and height being obtained from geometric model, the minimum width of Feret and the maximum length of Feret;
• the sample Prior to the imaging step, the sample is placed on a conductive pad before being placed in the scanning electron microscope, the sample being a dry sample or a wet sample.
• the determination of the geometric model can take into account the shape of the particle given by the image.
• the captured image is a grayscale image and the processing includes, before the measurement, a step of detecting the particles in the image by thresholding the intensity of their gray level.
• the image processing provides for the rejection of confined particles from the detected particles in order to keep only separate particles which are exploitable particles.
• the scanning electron microscope is coupled with image analysis software to perform the processing.
• the treatment may further include:
• the equivalent diameter is an equivalent diameter of area.
• the modeling of the size distribution of the volume characteristic equivalent diameters comprises a step of calculating a cumulative increasing function from the percentage of particles by volume in each particle size class, a step of calculating an expectation by applying a distribution law, a step of modeling the distribution law with minimization of the residuals of all the values of the expectation by the least squares method.
• the distribution law can be a normal distribution law or normal log.
• the modeling is carried out using statistical processing software.
• FIG. 1 illustrates the maximum length and the minimum width of Feret for a particle as well as its equivalent diameter
• Figures 2A-21 are images of each of the samples under a scanning electron microscope
• Figure 3 is a schematic three-dimensional view of a hexagonal-based prismatic particle such as that of Sample G;
• Figure 4 illustrates the distribution of the volume form factor of sample G
• FIGS. 5A1, 5B1, 5C1, 5D1, 5E1, 5F1, 5G1, 5H1, 511 illustrate the percentage of particles in volume as a function of the characteristic equivalent diameter obtained for samples A to I respectively by the process of the invention and optionally a or two laser diffraction techniques;
• FIGS. 5A2, 5B2, 5C2, 5D2, 5E2, 5F2, 5G2, 5H2, 512 illustrate the normalized cumulative function of the percentage of each measured characteristic equivalent diameter obtained for samples A to I respectively by the method of the invention and optionally a or two laser diffraction techniques.
• Diameter 139 ⁇ 2, 6 micrometers
• the copper metal powder of the company Sigma Aldrich of chemical purity higher than 99.8%, the particle size characteristics announced by the manufacturer are included for the sample D between 200 and 600 micrometers and for the sample I 50 microns in the form of dendrites.
• the particle shape of these samples is more complex than that of the beads.
• sample G uranium-neodymium mixed oxalate powder
• sample H neodymium oxalate powder
• the particles of these powders are synthetic particles whose morphology depends on the molecular and structural arrangement of the atoms constituting them and is independent of the mechanical manufacturing process. These samples have the shape of sticks.
• the particles of the sample G are of the hexagonal prismatic type.
• the particles of the sample H are parallelepipedic type.
• Samples D, E, F are powder samples of known dimensions and announced by the manufacturer. Samples of these powders are deposited on a pad of conductive material before being placed under a scanning electron microscope.
• the preparation of the samples was done according to two techniques and the choice of one or the other of the techniques depends on the samples.
• the first technique is a dry technique, a thin particulate mono-deposition is performed on a glass slide and then transferred to an electrically conductive pad, for example carbon.
• the second technique is a wet technique, using a solution dilution of the powder, a deagglomeration of ultrasonic particles and a deposit on the electrically conductive pad, for example aluminum.
• Samples A, B, C, D, E, F and I were prepared according to the first technique and samples G and H were prepared according to the second technique.
• an image or several images are taken by the scanning electron microscope, an image may correspond to one or more measurement fields. These images are high resolution images.
• the magnification of the microscope depends on the size of the particles.
• the scanning electron microscope allows a magnification variation of 1 to 1,000,000, this variation being greater than that of an optical microscope.
• the use of a high-resolution microscope is recommended for the production of images of particles of nanometric and micrometric sizes.
• This scanning electron microscope is, for example, a Cari Zeiss Supra 55 high-resolution field-effect scanning electron microscope.
• Each image is captured by a detector and processed by image processing software coupled to the scanning electron microscope. It may be the INCA Feature software developed by Oxford Instrument for forensic science but it is not limiting. This software allows the automation of a large number of sample analysis fields on the plot and offers a suitable metric of measurements. It is assumed in the example described that the pad has two contiguous fields of analysis.
• FIGS. 2A-21 show an image taken by the electron microscope of the various samples ranging from A to I with a very large magnification so that only a few particles appear.
• This software includes a specific module for the detection of shapes by image analysis taken by the scanning electron microscope.
• the captured image is a grayscale image.
• the particles of the observed sample are detected by a grayscale intensity threshold processing of the image. Several threshold levels can be used to improve the efficiency of detection.
• the number of particles counted is 4643, the measurements were made on 420 observation zones with images carried out with a magnification of 225.
• sample B the number of particles counted is 1467, the measurements were made on 30 observation zones with images carried out with a magnification of 25.
• sample C the number of particles counted was 1169, the measurements were made on 487 observation zones with images carried out with a magnification of 25.
• the number of particles counted is 195, the images were made with a magnification of 25.
• sample E the number of particles counted is 4052, the measurements were made with a magnification of 300.
• the number of particles counted is 1818, the measurements were made with a magnification of 300.
• sample G the number of particles counted was 901, the measurements were made on 4,400 observation zones with images made at a magnification of 40,000.
• sample H the number of particles counted was 936, the measurements were made on 150 observation zones with images made at a magnification of 5000.
• sample I the number of particles counted is 2216, the measurements were made on 88 observation zones with images carried out with a magnification of 25.
• An image corresponds to an observation zone.
• geometrical model is meant the type of geometrical figure which corresponds to the particle: it may be a solid, for example, of sphere-type, parallelepipedal type, hexagonal prism, etc.
• This geometry information corresponds to the shape of the particle given by the image. On the image, we see if the particle is elongated such a needle, round as in Figures 2, polygonal etc.
• the geometric model can be applied to particles of constant geometry such as particles of samples A, B, C, D which are spherical, particles of the sample G which are hexagonal prisms, particles of the sample H which are parallelepipeds.
• an area projected in the plane of the image for the particle considered from the determined geometrical model and the minimum width Imin of Féret is then calculated.
• This projected area is conventional in the field of particle characterization.
• the area S is that of the base which is hexa onal given by the following formula:
• the particle of the sample G its projected area S is 0.964659396 square micrometer.
• the characteristic size L of the particle considered is thus calculated from the Feret dimensions and the geometrical model of the particles of the sample considered. For prismatic particles with a haxagonal base, this characteristic size L is:
• the rider b is given by:
• Figure 3 shows such a particle in the form of regular right hexagonal prism.
• the characteristic size L is 6, 39555713 micrometers.
• the next step is the calculation of the volume form factor ⁇ of the particles of the sample in question.
• This volume form factor is given by:
• the volume form factor makes it possible to better characterize the particles of the sample morphologically than the shape factor SF determined in the above-mentioned thesis.
• volume form factor of the particles of the G sample is of great interest, particularly in the case of kinetic (nucleation, growth or agglomeration) studies and the development of the modeling of oxalic co-precipitation processes. uranium and neodymium.
• the determination of the volume form factor by the method of the invention makes it possible to provide greater precision for the characterization of a very large number of particles measured in the sample.
• the automatic use of this volume form factor provides a robust, statistically significant, complete solution for modeling the formation of precipitates.
• the measured particles of the sample are divided into particle size classes according to an equivalent diameter to be calculated.
• the equivalent diameter employed is the equivalent diameter of area ECD (for equivalent circle diameter in English), it is the diameter of a circle having the same area S as that of the particle. This equivalent diameter is expressed by:
• the equivalent ECD diameter of all the measured particles of the image is calculated and these equivalent diameters are distributed into several particle size classes.
• Each granulometric class is bounded by two equivalent diameters ECD1 and ECD2.
• the center Ce is then calculated for each size class.
• the center of the granulometric class represents the diameter of a mean sphere illustrating the particle size class, it is the characteristic equivalent diameter per class center. This center is given by the formula:
• the total number of particles measured in the image and the number M of particles in each particle size class are counted.
• the PV percentage by volume of the particles in each particle size class is then obtained. This percentage is expressed by:
• An expectation ⁇ is calculated by applying a law of distribution of the inverse normal law to the values of the cumulative increasing function calculated previously.
• it may be the normal log law instead of the normal law.
• the normal law is modeled by minimizing the residuals of all the values of the expectation by the least squares method. We would do the same with the normal log law.
• the average characteristic particle diameter of the particles and the standard deviation of the characteristic equivalent diameter are calculated.
• DMI a (0) + a (l ⁇ With a (0) the average value of the characteristic equivalent diameter of standard deviation oa (0) and a (l) the width of the distribution with a standard deviation oa (l), where ⁇ is the expectation.
• the powders are suspended in a diluent, for example a mixture of deionized water and ethanol by magnetic stirring.
• the first particle size analyzer is particularly suitable for particle sizes from 0.04 microns to 2000 microns and the second is particularly suitable for particles from 0.1 micron to 2000 microns.
• n ° 2 gives the results of a hypothesis test, such as the t-test or Student's test carried out on the comparison of the average of the characteristic equivalent diameters obtained by the techniques LDM, LDC, IA with those of NIST.
• a hypothesis test is a process of evaluating a statistical hypothesis based on a dataset (sample). This test allows the comparison of the values of the average resulting from two techniques. The values are significantly different if t is greater than 2.
• FIGS. 5A1, 5A2, 5B1, 5B2, 5C1, 5C2 illustrate the particle size distribution data of the samples A, B, C obtained by the image analysis method of the invention and by the two laser diffraction techniques. LDC and LDM. More particularly, FIGS. 5A1, 5B1, 5C1 illustrate the percentage of particles in volume as a function of the characteristic equivalent diameter and FIGS. 5A2, 5B2, 5C2 illustrate the normalized cumulative function as a function of the characteristic equivalent diameter. The normative cumulative function thus makes it possible to calculate a probability density of the characteristic diameters and the calculation of the characteristic average diameter.
• Table n ° 3 summarizes the results concerning the means of the characteristic equivalent diameters and the standard deviations for the particles of the sample D, obtained by the LDM laser diffraction technique and by the image analysis method IA. object of the invention.
• FIGS. 5D1 and 5D2 illustrate the particle size distribution data of the sample D obtained by the image analysis method IA which is the subject of the invention and by the technique of LDM laser diffraction.
• Table n ° 4 groups together the results concerning the averages of the characteristic equivalent diameters and the standard deviations of the sample E.
• the two laser particle size distribution techniques LDM and LDC were used.
• FIGS. 5E1 and 5E2 illustrate the particle size distribution data of the sample E obtained by the image analysis method IA which is the subject of the invention and by both techniques. diffraction laser LDC and LDM.
• FIGS. 5F1 and 5F2 illustrate the particle size distribution data of the sample F obtained by the image analysis method IA of the invention and by the two LDC and LDM laser diffraction techniques.
• Table 4 also includes the results concerning the means of the characteristic equivalent diameters and the standard deviations of the sample F.
• the last samples G, H and I are samples of powders whose particles have complex shapes.
• the measurements on the sample G were made by the technique IA according to the invention, by the laser diffraction technique LDC but not by the laser diffraction technique LDM.
• FIGS. 5G1 and 5G2 illustrate the particle size distribution data of the G sample particles obtained by the image analysis method IA according to the invention and by the LDC laser diffraction technique.
• the distribution obtained by the LDC technique is bimodal, which could be due to the presence of agglomerates. There was no sorting step.
• Table no. 5 also contains the results concerning the means of characteristic equivalent diameters and the standard deviations of sample G.
• Table n ° 5 also contains the results concerning the means of characteristic equivalent diameters and the standard deviations of sample G.
• Table no. 5 also contains the results concerning the means of the characteristic equivalent diameters and the standard deviations of the H sample.
• FIGS. 5H1 and 5H2 illustrate the particle size distribution data of the sample H obtained solely by the image analysis method IA which is the subject of the invention.
• FIGS. 511 and 512 illustrate the particle size distribution data of the sample I obtained solely by the image analysis method IA which is the subject of the invention.
• the interest of measurements of particle size and morphology by the image analysis method object of the invention is great because it is suitable for many morphologies of particles, spherical, elongated, rough, and for many materials even those that are not suitable for LDC or LDM laser diffraction due to their roughness or chemical nature.
• Another advantage of the present invention is to allow particle size measurement of solid particles of sizes extending over a wide range, for example between 0.1 micrometer and 1000 micrometers.
• the measurement of the volume form factor and the particle size analysis can be done simultaneously from the same image.
• Particle size analysis with average diameters and standard deviation is suitable for small particles of the order of one-tenth of a micron.
• the determination of the volume form factor is a measurement inaccessible by the laser diffraction technique.
• the particle characterization method according to the invention is equally suitable for particles of simple shape as for particles of complex shape, on agglomerates and on the crystallites constituting these agglomerates.

Landscapes

• Chemical & Material Sciences (AREA)
• Analytical Chemistry (AREA)
• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Health & Medical Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Biochemistry (AREA)
• General Health & Medical Sciences (AREA)
• General Physics & Mathematics (AREA)
• Immunology (AREA)
• Pathology (AREA)
• Signal Processing (AREA)
• Dispersion Chemistry (AREA)
• Computer Vision & Pattern Recognition (AREA)
• Analysing Materials By The Use Of Radiation (AREA)

Applications Claiming Priority (2)

Publications (1)

Family

ID=47714288

Family Applications (1)

Country Status (7)

Families Citing this family (14)

Family Cites Families (6)

• 2012
  • 2012-11-20 FR FR1261016A patent/FR2998370A1/fr not_active Withdrawn
• 2013
  • 2013-11-19 US US14/443,571 patent/US20150300941A1/en not_active Abandoned
  • 2013-11-19 WO PCT/EP2013/074189 patent/WO2014079849A1/fr active Application Filing
  • 2013-11-19 KR KR1020157015324A patent/KR20150086297A/ko not_active Application Discontinuation
  • 2013-11-19 EP EP13802262.9A patent/EP2923194A1/fr not_active Withdrawn
  • 2013-11-19 JP JP2015542303A patent/JP2016502661A/ja not_active Withdrawn
  • 2013-11-19 CN CN201380060710.7A patent/CN104797923A/zh active Pending

Non-Patent Citations (2)

Also Published As

Similar Documents

Legal Events