Rapid measurement device and measurement method for number concentration of micro-plastic based on on-chip imaging

Abstract

Disclosed in the present invention are a rapid measurement device and measurement method for the number concentration of a micro-plastic based on on-chip imaging. According to the present invention, a commercial digital image sensor chip having a small pixel size and a high pixel number is used to construct a micro-plastic measurement device, a micro-plastic sample can be directly loaded to a photosensitive surface of the image sensor chip, and the shadow image of the micro-plastic projected onto the chip can be rapidly obtained. On this basis, the number of micro-plastics in the image is counted by means of a manual analysis method or a machine learning method, and the number concentration of the micro-plastics is calculated on the basis of the volume of the micro-plastic sample, thereby overcoming the bottleneck problem of existing micro-plastic analysis methods being difficult in directly and rapidly collecting wide-field-of-view and high-resolution images of samples. The micro-plastic measurement device of the present invention is portable, the method is simple and easy to popularize, a new technical support is provided for on-site monitoring of environmental micro-plastic pollution, and the present invention can also be applied to rapid measurement of the number concentration of micron particles other than micro-plastics.

Description

A rapid detection device and method for microplastic number concentration based on on-chip imaging Technical Field

[0001] The present invention relates to a device and method for rapid detection of microplastic number concentration based on on-chip imaging, belonging to the technical field of new environmental pollutant control. Background Art

[0002] Microplastics are an emerging pollutant of international concern and a target for control by the Chinese government in its "Action Plan for the Control of Emerging Pollutants." A crucial prerequisite for the precise prevention and control of microplastic pollution is timely access to reliable data on its status. However, rapid analysis of microplastic number concentrations after separation from environmental media remains a key methodological challenge.

[0003] Usually, in order to visually check whether microplastics are present in the treated samples and to analyze their quantity and size, the samples must first be filtered on the surface of the filter membrane and then observed and analyzed under a traditional optical microscope. Since traditional (lensed) optical microscopes cannot have both wide field of view and high-resolution imaging, it is difficult to manually obtain an image of the entire filter membrane and count all the particles retained by the filter membrane at high magnification. Although automated optical microscopes can capture images of the entire filter membrane with the help of electric translation stages, autofocus, and image stitching technology, this process takes a long time (tens of minutes), and the pixel size and number of the image sensor it is configured with are limited. Observers can only identify and measure particles >30μm from the image of the entire filter membrane, missing small-sized microplastics. Therefore, optical microscopy with lenses is time-consuming and has low accuracy for microplastic detection. There is an urgent need to establish new methods to improve the imaging, counting efficiency, and reliability of microplastic samples.

[0004] Lensless holographic imaging is considered to have application prospects in microplastic detection. However, the sensor of this technology obtains the coherent diffraction pattern of the sample, which requires a reconstruction algorithm to restore the phase information of the sample. It is also impossible to directly and quickly obtain an optical image of the microplastic sample. Therefore, it is urgent to establish a method that can use lensless optical imaging technology for microplastic number concentration detection.

[0005] Summary of the Invention

[0006] Purpose of the invention: The first purpose of the present invention is to provide a device for rapid detection of microplastic number concentration based on on-chip imaging; the second purpose of the present invention is to provide a method for rapid detection of microplastic number concentration using the detection device.

[0007] Technical solution: The present invention describes a device for rapid detection of microplastic number concentration based on on-chip imaging, which includes a light source, an image sensor chip, a control system and an image processing component. The control system is connected to the light source, the image sensor chip and the image processing component respectively, wherein the light source is vertically arranged above the image sensor chip, the control system is connected to the image processing component through a data transmission line, and a sample loading area is provided on the upper surface of the image sensor chip, and the microplastic sample to be tested is placed in the sample loading area.

[0008] Furthermore, the light source is monochromatic or polychromatic light.

[0009] Furthermore, the wavelength of the light source is 300-700 nm.

[0010] Furthermore, the vertical distance from the light source to the image sensor chip is 5 to 10 cm.

[0011] Furthermore, the photosensitive area of ​​the image sensor chip is 10 to 20 mm long and 10 to 20 mm wide, the pixel size is 0.5 to 1 μm, and the number of pixels is 100 to 1.6 billion.

[0012] Furthermore, the vertical distance between the microplastic sample to be tested and the image sensor chip is 5 to 10 μm.

[0013] Furthermore, the sample loading area is a square area surrounded by the solidified glue, the sample loading area is 10-20 mm long and 10-20 mm wide, the volume of the sample loading area is 100-400 μL, and the height of the sample loading area is 0.5-1.5 mm.

[0014] Furthermore, the projection of the microplastic sample to be tested in the sample area of ​​the image sensor chip under the vertical illumination of the light source is directly recorded by the image sensor chip and converted into an electrical signal. The control system drives and controls the operation of the light source and the image sensor chip, receives the output signal from the image sensor chip, and then sends it to the image processing component through the data transmission line to display the shadow image of the microplastic.

[0015] The method for rapidly detecting the number concentration of microplastics using the detection device of the present invention comprises the following steps:

[0016] (1) Under clean environmental conditions, place the microplastic sample to be tested on the sample loading area on the surface of the image sensor chip and let it stand;

[0017] (2) Turn on the light source and collect the shadow image of the deposited microplastics in the sample area on the image sensor chip;

[0018] (3) Analyze the microplastic sample images obtained by manual analysis or machine learning methods, count and calculate the number concentration of microplastics;

[0019] (4) Anhydrous ethanol is added to the upper sample area to wipe off the microplastics deposited on the surface of the upper sample area of ​​the image sensor chip, and the cleanliness is checked by collecting shadow images for the detection of the next batch of microplastic samples.

[0020] Furthermore, in step (1), the microplastic sample is a suspension.

[0021] Furthermore, in step (1), the standing time is more than 90 seconds.

[0022] Furthermore, in step (1), the clean environment condition is a clean room or a clean bench with a cleanliness level of Class 100 (ISO 5) (the number of particles ≥1 μm is 832 / m 3 )above.

[0023] Furthermore, the mass concentration of the microplastic suspension is less than 100 mg / L, and the volume of the microplastic suspension added to the sample loading area is 100 to 400 μL.

[0024] Furthermore, in step (2), the light source is a light emitting diode.

[0025] Furthermore, in step (2), the time for acquiring the image is more than 90 seconds.

[0026] Furthermore, in step (3), the manual analysis method is to import the image into image processing software, manually mark and count the microplastics.

[0027] Furthermore, in step (3), the machine learning method automatically identifies and counts microplastics in images by constructing and training a mathematical model, wherein the mathematical model is a target key point detection algorithm based on an existing model that has been trained and tested, and the size of microplastics that can be marked or identified is 3 to 6 μm.

[0028] Furthermore, in step (3), the number concentration of the microplastic sample is calculated according to the following formula:

[0029] The number concentration of microplastics = the number of microplastics in the microplastic sample (pieces) / the volume of the microplastic sample (L).

[0030] Furthermore, in step (4), the microplastics deposited on the surface of the sample area of ​​the image sensor chip are wiped off by absorbing the waste liquid with a disposable dust-free clean cotton swab, and then gently wiping the image sensor chip with a dry disposable dust-free clean cotton swab head.

[0031] Furthermore, in step (4), the cleanliness is that the number of particles is less than 10 / cm 2 .

[0032] The present invention uses lensless shadow imaging, a "what you see is what you get" imaging method. Shadows cast by microplastic samples in the sample area of ​​an image sensor chip are recorded by the sensor and directly form an image. The imaging field of view and resolution depend on the number and size of pixels on the image sensor chip, as well as the distance from the sample to the image sensor chip. This application uses an image sensor chip with a small pixel size and a high pixel count to achieve rapid detection of microplastic concentrations based on lensless shadow imaging technology.

[0033] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0034] (1) The method of the present invention is applicable to pure microplastics or samples extracted from environmental media, and can quickly determine their number concentration. The operation process is simple and easy to promote, meeting the major needs of the country in the control of new pollutants.

[0035] (2) The method of the present invention significantly shortens the time cost of imaging microplastic samples, has the characteristics of low carbon and energy saving, and responds to the national policy of energy conservation and low carbon.

[0036] (3) The method of the present invention is also applicable to the imaging and counting of micron particles other than microplastics. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a structural diagram of the device for rapid detection of microplastic number concentration based on on-chip imaging of the present invention.

[0038] In the figure: 1. Light source; 2. Image sensor chip; 3. Control system; 4. Data transmission line; 5. Image processing component.

[0039] Figure 2 is a flow chart of the steps of the method for rapid detection of microplastic number concentration of the present invention.

[0040] Figure 3 is a lens-free shadow microscopic full-field image of the polyethylene microplastics obtained in Example 2.

[0041] FIG4 is a partial enlarged view of the S1 region in FIG3 .

[0042] FIG5 is a partial enlarged view of the S2 region in FIG4 .

[0043] Figure 6 is a lensed optical micrograph of the polyethylene microplastics obtained in Example 2. Figure 7 is a comparison of diameter statistics of lensless shadow microscopy and lensed optical microscopy of the polyethylene microplastics in Example 2.

[0044] FIG8 is a graph showing the effect of standing time on the number concentration of melamine microfibers in Example 3.

[0045] FIG9 is a graph showing the effect of standing time on the length distribution of melamine microfibers in Example 3. DETAILED DESCRIPTION

[0046] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0047] Example 1

[0048] As shown in Figure 1, the on-chip imaging-based rapid detection device for microplastic number concentration of the present invention includes a control system 3, which is respectively connected to the light source 1, image sensor chip 2 and image processing component 5. Among them, the light source 1 is arranged vertically above the image sensor chip 2, and the control system 3 is connected to the image processing component 5 via a data transmission line 4. The surface of the image sensor chip 2 is provided with a sample loading area, and the microplastic sample to be tested is placed in the sample loading area. The projection of the microplastic sample to be tested in the sample loading area of ​​the image sensor chip 2 under the vertical illumination of the light source 1 is directly recorded by the image sensor chip 2 and converted into an electrical signal. The control system 3 drives and controls the operation of the light source 1 and the image sensor chip 2, receives the output signal from the image sensor chip 2, and then sends it to the image processing component 5 via the gigabit data transmission line 4 to display the shadow image of the microplastic.

[0049] Example 2

[0050] The detection device of Example 1 was used to detect the number concentration of microplastics. The rapid detection method steps are shown in Figure 2. Polyethylene microspheres (with a diameter of about 10 to 20 μm) were selected as representatives of microplastics. 1 mg of polyethylene microspheres were weighed and transferred to a glass bottle. 10 mL of 80% ethanol solution was added and mixed to prepare a 100 mg / L dispersion. 100 μL of the dispersion was transferred using a micro-glass pipette and quickly loaded into the sample area on the surface of the image sensor chip 2. The light source 1 was turned on and the shadow image was collected after standing for 90 seconds. The results are shown in Figures 3-5.

[0051] At the same time, 100 μL of the dispersion was filtered onto an aluminum oxide filter membrane, and a reflected light image of the filter membrane surface was collected at 40 times magnification using a reflected light microscope with a lens in the prior art. The result is shown in FIG6 .

[0052] By comparing Figures 3-6, it can be seen that compared with lens-based optical microscopy, lensless shadow microscopy can obtain high-resolution images of individual microplastics in a larger field of view.

[0053] The number and diameter of microspheres in the collected shadow and reflected light images were manually measured using image processing software (Adobe Photoshop and ImageJ). The results are shown in Figure 7. Figure 7 compares the diameter statistics of the polyethylene microplastics obtained by lensless shadow microscopy and lensed optical microscopy in Example 2. As can be seen in Figure 7, there is no significant difference in the diameter of the microspheres obtained by lensless shadow microscopy and lensed optical microscopy, demonstrating the accuracy of the lensless shadow microscopy method of the present invention and its ability to accurately determine the number concentration of polyethylene microspheres.

[0054] The polyethylene microsphere sample was measured three times, and the counting results were 605, 586 and 600.

[0055] The number concentration of polyethylene microspheres was calculated according to the following formula:

[0056] Number concentration of polyethylene microspheres = number of polyethylene microspheres in the dispersion (pieces) / volume of the dispersion (L)

[0057] According to the above formula, the number concentration of polyethylene microspheres is 6.05×10 6 / L, 5.86×10 6 pcs / L and 6.00×10 6 The relative standard deviation between the three parallel samples was 1.6%, indicating that the method of the present invention has high detection accuracy for the number concentration of spherical microplastics.

[0058] Example 3

[0059] The experimental process is the same as that of Example 2. Melamine microfibers are selected as representatives of microplastics (the length of melamine microfibers is about 1-200 μm). 1 mg of melamine microfibers is weighed and transferred to a glass bottle. 10 mL of 80% ethanol solution is added and mixed to prepare a 100 mg / L dispersion. The dispersion is then diluted to 24 mg / L. 100 μL of the dispersion is transferred using a micro glass pipette and quickly loaded onto the sample area on the surface of the image sensor chip 2. Shadow images are collected after standing for 1.5 min, 3.0 min, and 10 min, respectively. The microfibers in the image are manually counted using image processing software, and the number of microfibers is divided by the sample volume (100 μL) to obtain the number concentration of the microfibers. The results are shown in FIG8 , and the length of the microfibers is measured, as shown in FIG9 .

[0060] Figure 8 shows the effect of standing time on the number concentration of melamine microfibers in Example 3. As can be seen from Figure 8, the effect of standing time on the number concentration of melamine microfibers is not significant. Figure 9 shows the effect of standing time on the length distribution of melamine microfibers in Example 3. As can be seen from Figure 9, the effect of standing time on the length distribution of melamine microfibers is not significant. This shows that the method of the present invention can ensure the accuracy of sample image acquisition by standing for 90 seconds. This shows that the method of the present invention greatly reduces the detection time compared to the tens of minutes required by existing automated optical microscopes, and can achieve rapid detection of microplastic number concentration.

Claims

1. A rapid detection device for microplastic number concentration based on on-chip imaging, characterized in that: The device for rapid detection of microplastic number concentration based on on-chip imaging comprises a light source (1), an image sensor chip (2), a control system (3) and an image processing component (5), wherein the control system (3) is connected to the light source (1), the image sensor chip (2) and the image processing component (5), respectively, wherein the light source (1) is vertically arranged above the image sensor chip (2), the control system (3) is connected to the image processing component (5) via a data transmission line (4), and a sample loading area is provided on the upper surface of the image sensor chip (2), and a microplastic sample to be detected is placed in the sample loading area.

2. The device for rapid detection of microplastic number concentration based on on-chip imaging according to claim 1, characterized in that: The light source (1) is monochromatic or polychromatic light, the wavelength of the light source (1) is 300 to 700 nm, and the vertical distance from the light source (1) to the image sensor chip (2) is 5 to 10 cm.

3. The device for rapid detection of microplastic number concentration based on on-chip imaging according to claim 1, characterized in that: The photosensitive area of ​​the image sensor chip (2) is 10 to 20 mm long and 10 to 20 mm wide, the pixel size is 0.5 to 1 μm, the number of pixels is 100 million to 1.6 billion, and the vertical distance between the microplastic sample to be tested and the image sensor chip (2) is 5 to 10 μm.

4. The device for rapid detection of microplastic number concentration based on on-chip imaging according to claim 1, characterized in that: The sample loading area is a square area surrounded by the curing glue, the sample loading area is 10-20 mm long and 10-20 mm wide, the volume of the sample loading area is 100-400 μL, and the height of the sample loading area is 0.5-1.5 mm.

5. The method for rapidly detecting the number concentration of microplastics using the detection device according to any one of claims 1 to 4, characterized in that: The following steps are involved: (1) Under clean environmental conditions, placing a microplastic sample to be tested on a sample loading area on the surface of an image sensor chip (2) and leaving it to stand; (2) turning on the light source (1) and collecting a shadow image of the deposited microplastics in the sample loading area of ​​the image sensor chip (2); (3) Analyze the microplastic sample images obtained by manual analysis or machine learning methods, count and calculate the number concentration of microplastics; (4) Anhydrous ethanol is dripped onto the upper sample area to wipe off the microplastics deposited on the surface of the upper sample area of ​​the image sensor chip (2), and the cleanliness is checked by collecting shadow images for the detection of the next batch of microplastic samples.

6. The detection method according to claim 5, characterized in that: In step (1), the microplastic sample is a suspension, the standing time is more than 90 seconds, and the clean environment conditions are a clean room or a clean bench with a cleanliness level of more than Class 100.

7. The detection method according to claim 6, characterized in that: The mass concentration of the microplastic suspension is less than 100 mg / L, and the volume of the microplastic suspension added to the sample loading area is 100 to 400 μL.

8. The detection method according to claim 5, characterized in that: In step (2), the light source (1) uses light-emitting diode lighting, and the image acquisition time is more than 90 seconds.

9. The detection method according to claim 5, characterized in that: In step (3), the manual analysis method is to import the image into the image processing software, manually mark and count the microplastics; the machine learning method is to automatically identify and count the microplastics in the image by constructing and training a mathematical model, wherein the mathematical model is a target key point detection algorithm based on an existing model that has been trained and tested, and the size of the microplastics that can be marked or identified is 3 to 6 μm.

10. The detection method according to claim 5, characterized in that: In step (4), the microplastics deposited on the surface of the sample area of ​​the image sensor chip (2) are wiped off by absorbing the waste liquid with a disposable dust-free clean cotton swab, and then gently wiping the image sensor chip (2) with a dry disposable dust-free clean cotton swab. The cleanliness is that the number of particles is <10 / cm 2 .

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