CN110895237A - Micro-fluidic automatic separation and intelligent component identification system - Google Patents
Micro-fluidic automatic separation and intelligent component identification system Download PDFInfo
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Abstract
The invention discloses a micro-fluidic automatic separation and intelligent component identification system. The system comprises a liquid drop chip, a sample loading and storing unit, a particle image detection unit, a particle component identification unit and an automatic stage shifting device; a particle image detection unit and a plurality of particle component identification units are sequentially arranged above the loading and storage unit; the objective table automatic shifting device comprises an objective table and a chip displacement track, wherein a droplet chip is carried on the objective table, the objective table is arranged on the chip displacement track, and the chip displacement track is respectively connected with the sample loading and storing unit, the particle image detection unit and the particle component identification unit; the system can realize continuous automatic counting, particle size distribution and image recognition, sorting and collection of particles in a trace solution, and intelligent multifunctional analysis and identification of components.
Description
Technical Field
The invention belongs to the technical field of particle analysis, and particularly relates to a micro-fluidic automatic separation and intelligent component identification system.
Background
The requirements for particle control in liquid products are gradually increasing in the fields of medical health, environmental protection and the like, such as blood sample analysis, food and pharmaceutical development and production quality control, pure water treatment and the like. Particle detection is also a critical component in quality control of product. The particle size distribution, morphological characteristics and structural composition of the particles are known and mastered, and a direct and powerful thought and solution is provided for product process development and process optimization, product quality control and product problem investigation and research in various related fields.
Particle size analyzers based on image analysis have been widely reported. From US patent No. US 7064826B 2, a digital optical particle size detection method is known, which uses reduced magnification to perform pixel point difference analysis on the obtained particle image pixel array, thereby obtaining the detection results of particle size distribution and morphology. From US 9360410B2 it is known to provide a particle detector which covers a wide particle size range. Wherein the lower and middle size ranges are detected based on dark image areas of the particles and the larger size range of the particles is detected based on brighter image areas of the particles. The particle detector includes a sample flow cell, a dark field light source, a light field light source, an imaging system, a process system, and a pump system. A liquid sample is driven by a peristaltic pump to flow through a sample flow cell, and particles in the liquid are captured by a microscope and camera system.
Particle detection has many fields that require the volume of a detection sample to be reduced as much as possible due to the wide application fields. The sample processing system manufactured by the micro-fluidic chip technology can realize the target of micro and high-flux detection of the liquid sample. From CN 104846400B, an electrolytic device based on the principle of electrowetting on a dielectric layer is known, which obtains droplets containing electrolytic products with different polarities at specific concentrations by controlling the electrolytic process and the droplet splitting process. It is known from CN 104994955B that a droplet manipulation system manipulates droplets by providing voltage pulses to individual electrodes in an electrode array to achieve electrowetting.
The current particle detector can only analyze the particle size distribution and the morphology of particles in liquid, but cannot provide structural composition information of the particles more deeply. For morphological analysis of particles, it is still in the preliminary application stage of images. The image information of the particles obtained by the analysis of the instrument cannot be used for accurately judging the attributes of the particles, namely, the endogenous property and the heterologous property. This limitation makes particle image analysis often useful only as an aid and reference for particle analysis. If one wants to know the true structure and origin of a particle, only particle image analysis is used in conjunction with other particle component identification methods. However, current methods of particle fraction identification rely purely on manual filtration separation of particles in a liquid, which is quite time and labor consuming. A qualified researcher can only complete the separation and component identification of particles in a liquid sample within 4 hours. Based on the large volume requirement of manual operation of the sample, the destructiveness to the sample, the inevitable risk of environmental pollution in the sample detection process, and the high technical difficulty of individual identification and detection and data analysis, the identification of the particle components cannot be widely popularized and used in the industry.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a microfluidic automatic sorting and component intelligent identification system. The system has high automation degree, and can realize continuous automatic counting, image and granularity identification, sorting and collection and multifunctional intelligent component analysis and identification of particles in a trace solution by utilizing a liquid drop chip manufactured by a microfluidic technology and an optical detector for particle image detection and particle component identification.
The invention automatically separates the liquid containing particles into liquid drops under the traction of the electrowetting technology, the liquid drops reach a visible detection window through a digital liquid drop microfluidic flow path of a liquid drop chip, the liquid drops are detected by an optical detector arranged outside the position right above the detection window, and the automatic intelligent identification of the particle components is realized based on the detected particle images and spectral information. The technical scheme of the invention is specifically introduced as follows.
A micro-fluidic automatic sorting and component intelligent identification system comprises a liquid drop chip, a sample loading and storing unit, a particle image detection unit, a particle component identification unit and an objective table automatic shifting device; the sample loading and storage unit includes temperature control
Instruments and waste bottles; the objective table automatic shifting device comprises an objective table and a chip displacement track, wherein a droplet chip is carried on the objective table, the objective table is arranged on the chip displacement track, and the chip displacement track is respectively connected with the sample loading and storing unit, the particle image detection unit and the particle component identification unit; the liquid drop chip comprises a bottom plate, an electrode microarray layer, an upper hydrophobic polymer layer, a lower hydrophobic polymer layer and an electrode selector, wherein at least one electrode selector is adhered below the bottom plate, the electrode microarray layer is arranged above the bottom plate, and the lower hydrophobic polymer layer and the upper hydrophobic polymer layer are arranged above the electrode microarray layer; a sample liquid storage area, a digital liquid drop microfluidic flow path, a detection window and a liquid drop storage area are arranged between the upper hydrophobic polymer layer and the lower hydrophobic polymer layer; the sample liquid storage area is at least composed of a sample liquid storage chamber; the digital liquid drop micro-fluidic flow path comprises a main flow path and branch flow paths, wherein the main flow path is connected with a liquid flow outlet at the bottom of each sample liquid storage chamber, the main flow path is connected with an inlet of a detection window, an outlet of the detection window is connected with each liquid drop storage chamber through the branch flow paths, the distribution of the micro-fluidic flow path corresponds to the distribution of an electrode microarray in an electrode microarray layer, and the main flow path mainly realizes the separation of liquid drops; the liquid drop storage area comprises a plurality of liquid drop storage small chambers, the outlet of the detection window is divergently connected to each liquid drop storage small chamber through a branch flow path, and electrode microarrays are distributed in the main flow path at the inlet and the branch flow path at the outlet of the detection window; the particle image detection unit comprises a first detector, and the first detector is an image capturer; the particle component identification unit comprises a second detector, and the second detector is selected from any one or more of an ultraviolet spectrometer, an infrared spectrometer, a Raman spectrometer, a fluorescence spectrometer, a microwave spectrometer, an electron spin spectrometer or a nuclear magnetic resonance spectrometer.
The invention also comprises a micro battery, and the micro battery is connected with the electrode selector.
In the present invention, the image capturer is an electron microscope or an optical microscope.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention utilizes the digital electrowetting droplet microfluidic technology to process liquid particle samples, can greatly reduce the sample volume consumption, and realizes the automatic separation of particles in liquid and the nondestructive analysis of the samples, namely the collection and reutilization of sample particles.
2. The invention combines the micro-fluidic technology and the particle image detection technology, can realize the preliminary automatic separation of particles, and can remove common bubbles and silicone oil in the preliminary separation if the common bubbles and silicone oil in the pharmaceutical process are removed.
3. The invention also adopts a particle component identification technology, and can efficiently finish the component identification of suspected particles on the basis of primary particle sorting.
4. The invention adopts the automatic shifting device of the objective table, and can realize the full-automatic integrated operation of particle separation and identification.
5. The system of the invention utilizes a liquid drop chip of the digital microfluidic technology and an integrated multifunctional optical detector to realize the continuous and automatic counting, the particle size distribution and the image recognition, the sorting and the collection of the protein particles, the cells and other particles in the trace solution and the multifunctional intelligent analysis and identification of the particle components. The system can be applied to any field of process development and quality control related to particles as main components or impurities. For example, the system can be applied to quality control in the production process of liquid medicine, especially for deviation investigation and root cause analysis of particle impurities. The system can be used for knowing and confirming the reason for introducing or causing the formation of the particles by utilizing a large amount of high-value information generated by the system, and improving the production process of the liquid medicine preparation in a targeted manner, thereby finally realizing the effective control of the particles in the production process. In addition, the system can also be applied to the fields of formulation and process development, microencapsulation process development, cell clone screening and cell culture process optimization, identification of environmental bacteria microorganisms, chromatographic column filler filling process detection and quality control, food and beverage formulation process development and quality control, equipment cleaning process confirmation, diamond micronization grinding process development and optimization, sewage treatment and pure water process development, blood sample analysis and the like.
Drawings
Fig. 1 is a schematic diagram of the structure of the system of the present invention.
FIG. 2 is a schematic diagram of a droplet chip structure and droplet detection.
FIG. 3 is a schematic diagram of displacement control of droplets on a droplet chip.
Reference numerals: 1-a waste liquid bottle, 2-a chip displacement track, 3-a waste liquid pipeline, 4-a temperature controller, 5-a droplet chip, 6-a detection window, 7-a data processing center, 8-a loading and storage unit, 9-a light source, 10-an optical device, 11-a first detector, 12-a particle image detection unit, 13-a second detector, 14, 16-a particle component identification unit, 15-an nth detector, 17-a bottom plate, 18-an electrode selector, 19-an electrode microarray layer, 20-a lower hydrophobic polymer layer, 21-a droplet microfluidic flow path layer, 22-an upper hydrophobic polymer layer, 23-a droplet to be detected, 24-a polymer film, 25-a sample storage chamber and 26-a sample storage area, 27-droplet reservoir, 28-digital droplet microfluidic flow path, 29-droplet storage chamber, 30-waste droplet.
Detailed Description
The technical scheme of the invention is explained in detail in the following by combining the drawings and the embodiment.
As shown in figures 1-3, a microfluidic automatic sorting and component intelligent identification system comprises a sample loading and storage device
And a data processing center 7. A particle image detection unit 12 and a particle component identification unit 14 are sequentially arranged above the sample loading and storing unit 8 in an overlapping manner; the objective table automatic shifting device comprises an objective table and a chip displacement track 2, wherein a liquid drop chip 5 is carried on the objective table, and the objective table automatic shifting device is connected with the liquid drop chip 5, a sample loading and storing unit 8, a particle image detection unit 12 and a particle component identification unit 14. The automatic shifting device of the object stage can realize bidirectional transportation. The sample loading and storage unit 8 contains a temperature controller 4 and a waste liquid bottle 1. When the samples in the droplet chips 5 need to be incubated at a heating or cooling state, the automatic stage shifting device transfers the droplet chips 5 to the unit. In order to ensure the analysis of the temperature sensitive biological product, the temperature range of the sample can be controlled to be 2-80 ℃. After the temperature treatment is finished, the droplet chip 5 is transferred to the particle image detection unit 12 and the particle component identification units 14 and 16 in sequence through the stage automatic shifting device for detection. The particle size range of the particle which can be processed by the system is wide, and the particle size can be between 0.1 and 1000 mu m.
The droplet chip 5 is a sample processing core element of the integrated system of the invention; the droplet chip 5 is manufactured by sequentially laying an upper electrode microarray layer 19, an upper hydrophobic polymer layer 22 and a lower hydrophobic polymer layer 20 on a bottom plate 17; a droplet microfluidic flow path layer 21 is arranged between the upper hydrophobic polymer layer 22 and the lower hydrophobic polymer layer 20, at least one electrode selector 18 is adhered below the bottom plate 17 of the droplet chip 5, and the electrode selector 18 can apply pulse voltage to the electrode microarray layer 19 so as to drive droplets in the droplet microfluidic flow path layer 21 to be separated and moved in an electrowetting mode. The droplet chip 5 may be formed by integrally casting a polymer to form a film, or by separately casting upper and lower films with a polymer and adhering the films. The droplet chip 5 can handle a wide range of sample volumes, preferably 1 μ L to 1 mL.
The microfluidic channel layer 21 in the droplet chip 5 is divided into several regions including a sample storage region 26, a digital microfluidic channel 28, a detection window 6 and a droplet storage region 27.
The sample reservoir region 26 is composed of at least one or more (preferably 10) independent 1mL sample reservoirs 25, into which at least one or more of the same or different biological samples can be placed, respectively. The sample reservoir 26 is a reservoir well without an upper cover made of a polymer film (the well seal may additionally cover a cover plate, preferably a custom silicone sheet), and the well size is preferably 10mm x 10 mm.
The digital droplet microfluidic flow path 28 is a channel of the droplet chip 5, is a droplet control system based on a microfluidic electrowetting technology, and is mainly connected with the sample liquid storage chamber 25, the detection window 6 and the droplet storage region 27. The liquid droplets are separated from the sample storage chamber 25, drawn by the liquid droplet manipulation system, flow through the digital liquid droplet microfluidic flow path 28, are conveyed to the detection window 6, and are finally detected and identified by the optical detectors 11, 13 and 15 in the particle image detection unit 12 and the particle component identification unit 14 above the detection window 6 with the aid of the light source 9 and the optical device 10.
The sample liquid storage chambers 25 to the detection windows 6 are designed to be one-way flow paths, the bottom of each sample liquid storage chamber 25 is provided with a main flow path leading to the detection window 6, and the detection window 6 leads to a branch flow path; the distribution of the microfluidic flow paths at the bottom of the sample storage chamber 25 corresponds to the distribution of the electrode microarray in the electrode microarray layer 19, the chip has no special valve design, and the liquid flows by means of the pulse voltage applied to the electrodes on the electrode microarray layer 19 by the electrode selector 18 below the bottom plate 17. When liquid is charged and stored in the sample liquid reservoir 25, the liquid flow outlet at the bottom thereof is closed by a pulse voltage. When the sample is detected, the liquid outlet at the bottom is in an open state. The time length of opening of the outlet is also different based on different detection modes. In the continuous flow detection mode, the outlet may be opened for a long time until the sample reservoir 25 is depleted of liquid; in the droplet detection mode (non-continuous), the opening of the outlet can be controlled according to the size of the desired separated droplet volume. The sample reservoir 25 is relatively self-contained and does not risk cross-contamination. The sample reservoir 25 may contain a cleaning solution in addition to the sample to be tested. The cleaning solution can be used for cleaning the microfluidic flow path and the visual detection window 6 when different samples are switched. The cleaning solution may include, but is not limited to, pure water, water for formulation, an aqueous solution containing a surfactant (tween 20 or 80), and the like.
The detection window 6 is a visual window, and the window preferably has a diameter of 1mm in order to realize the micro-detection of the sample. An electrode microarray is not provided below the detection window 6. However, the micro-fluidic flow paths at the inlet and the outlet of the detection window 6 are distributed with electrode micro-arrays to realize the movement of liquid drops. With the aid of the light source 9 (directly below the chip) and the optics 10 (directly above the detection window), the particles in the droplets are detected by the multifunctional optical detectors 11, 13 and 15 in the particle image detection unit 12 and the particle component identification unit 14, which are arranged directly above and outside the detection window 6. Based on the number and type of particles detected, the droplet can be further broken down into smaller droplet units containing only one particle, if necessary. The particle image detection unit 12 comprises a light source 9, an optical device 10 and a first detector 11, the first detector 11 is an image capturer (a microscope capable of automatically adjusting the focal length), the particle image captured by the microscope is transmitted to the data processing center 7, the system automatically records the number and the size of the particles, and analyzes and judges the suspected attributes of the particles; it can identify the silicone oil and air bubbles in the liquid drops, which are common in the production of biological agents, and transmit them to the waste liquid bottle 1 of the external sample loading and storing unit 8 through the waste liquid pipeline 3, while other liquid drops containing suspicious particles can be transmitted to the liquid drop storing chamber 29 of the liquid drop storing area 27 through the channel by the liquid drop control system, and the liquid drops will be subjected to the second round of particle component identification.
The detection window 6 is connected to the droplet storage region 27 by a branch flow path, and is of a bidirectional flow path design. The droplet reservoir 27 is preferably a 5 cm x 5 cm square array, and the droplet reservoir 27 contains a sufficient number of droplet storage cells 29 to make 12 x 24=288 2 μ L storage cells, with a volume of 2 μ L = 2mm x 1mm, which can be positioned to store a corresponding number of particles to be inspected. The individual droplet storage cells 29 are independent of one another and are preferably designed to be spaced apart by 1 mm. In the droplet storage region 27, branch paths are divergently connected to the respective droplet storage cells 29. Each drop storage cell 29 has a separate number and the system will mark and number the drop containing the suspect particle based on the cell number to be detected. The droplet storage chamber 29 accomplishes the separation of particles from the sample to be tested and provides the basis for multifunctional particle identification. The droplets containing suspicious particles temporarily stored in the droplet storage chamber 29 can flow through the digital droplet microfluidic flow path 28 and are transported to the detection window 6 in the droplet chip 5 one by one again for particle component detection; some special particles can even be transferred back to the sample liquid storage area 26 through the detection window 6 again, collected and stored in a closed container, and can be used as a particle standard or further used for other particle identification detection. The function well meets the requirements of two-wheel or multi-wheel detection of suspicious liquid particles. For detecting a trace amount of a sample, the diameter of the flow path is preferably 1 mm. The liquid chip is mainly characterized by small volume, controllable liquid drop flow rate, easy cleaning and difficult cross contamination, and a closed system ensures that the detection process is not easy to be polluted by particles in the external environment.
After the particle image detection of all samples is finished, the droplet chip 5 is automatically moved to the position of the second detector 13 and then the nth detector 15, i.e., the particle component identifying units 14 and 16. The series of units is connected to a powerful data processing centre 7. The data processing center 7 comprises a particle component library with rich types, and the intelligent data processing software can realize automatic comparison of particle optical signals collected by the detectors 13 and 15 with the component library, identify and analyze particle element composition, and further provide accurate judgment of particle attributes. The detectors in the particle component identification unit 14 include, but are not limited to, ultraviolet spectrometers, infrared spectrometers, raman spectrometers, fluorescence spectrometers, microwave spectrometers, electron spin spectrometers, nuclear magnetic resonance spectrometers, and the like. And the system automatically compares the particle element database in the system software according to the particle identification result to finally generate an identification report of the particle attribute.
Claims (3)
1. A micro-fluidic automatic separation and component intelligent identification system is characterized by comprising a liquid drop chip, a sample loading and storing unit, a particle image detection unit, a particle component identification unit and an objective table automatic shifting device; the sample loading and storing unit comprises a temperature controller and a waste liquid bottle, the automatic object stage shifting device comprises an object stage and a chip displacement track, the object stage is loaded with a droplet chip and is arranged on the chip displacement track, and the chip displacement track is respectively connected with the sample loading and storing unit, the particle image detecting unit and the particle component identifying unit; the liquid drop chip comprises a bottom plate, an electrode microarray layer, an upper hydrophobic polymer layer, a lower hydrophobic polymer layer and an electrode selector, wherein at least one electrode selector is adhered below the bottom plate, the electrode microarray layer is arranged above the bottom plate, and the lower hydrophobic polymer layer and the upper hydrophobic polymer layer are arranged above the electrode microarray layer; a sample liquid storage area, a digital liquid drop microfluidic flow path, a detection window and a liquid drop storage area are arranged between the upper hydrophobic polymer layer and the lower hydrophobic polymer layer; the sample liquid storage area is at least composed of a sample liquid storage chamber; the digital liquid drop micro-fluidic flow path comprises a main flow path and branch flow paths, wherein the main flow path is connected with a liquid flow outlet at the bottom of each sample liquid storage chamber, the main flow path is also connected with an inlet of a detection window, the outlet of the detection window is connected with each liquid drop storage chamber through the branch flow paths, the distribution of the micro-fluidic flow path corresponds to the distribution of an electrode microarray in an electrode microarray layer, and the main flow path mainly realizes the separation of liquid drops; the liquid drop storage area comprises a plurality of liquid drop storage small chambers, the outlet of the detection window is divergently connected to each liquid drop storage small chamber through a branch flow path, and electrode microarrays are distributed in the main flow path at the inlet and the branch flow path at the outlet of the detection window; the particle image detection unit comprises a first detector, and the first detector is an image capturer; the particle component identification unit comprises a second detector, and the second detector is selected from one or more of an ultraviolet spectrometer, an infrared spectrometer, a Raman spectrometer, a fluorescence spectrometer, a microwave spectrometer, an electron spin spectrometer or a nuclear magnetic resonance spectrometer.
2. The microfluidic automated sorting and intelligent identity system of components of claim 1, further comprising a micro-battery, wherein the micro-battery is connected to the electrode selector.
3. The microfluidic automated sorting and intelligent identification system of components of claim 1, wherein the image capturer is an electron microscope or an optical microscope.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111521547A (en) * | 2020-05-13 | 2020-08-11 | 洹仪科技(上海)有限公司 | Particle analyzing and sorting device and method |
| EP4040138A1 (en) * | 2021-02-03 | 2022-08-10 | Hitachi, Ltd. | Particle measuring device |
| CN117368073A (en) * | 2023-09-04 | 2024-01-09 | 中山大学·深圳 | Multi-mode liquid drop detection system and method |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101726483A (en) * | 2009-12-28 | 2010-06-09 | 茅涵斌 | Method for detecting chemicals by molecular engram, laser tweezers and microfluidic technology as well as detector thereof |
| KR20110083460A (en) * | 2010-01-14 | 2011-07-20 | 한국전자통신연구원 | Fluid analyzing device and method base on electrowetting |
| CN103191791A (en) * | 2013-03-01 | 2013-07-10 | 东南大学 | Integrated chip system for high-throughput sorting and counting detection of biological particles, and application |
| CN103822868A (en) * | 2014-03-14 | 2014-05-28 | 大连海事大学 | Device and method for detecting grain size of phytoplankton in seawater |
| CN204116189U (en) * | 2014-03-13 | 2015-01-21 | 严媚 | The imaging of intelligent optical miniflow and detection system |
| CN104849444A (en) * | 2015-05-20 | 2015-08-19 | 大连海事大学 | Cell counting device and method capable of synchronously measuring fluorescence and occlusion |
| CN105764490A (en) * | 2013-09-24 | 2016-07-13 | 加利福尼亚大学董事会 | Encapsulated sensors and sensing systems for bioassays and diagnostics and methods for making and using them |
| CN107904163A (en) * | 2017-12-12 | 2018-04-13 | 厦门大学 | A kind of full-automatic individual particle based on digital microfluidic technology/unicellular capture chip and its application |
| CN211402075U (en) * | 2019-12-17 | 2020-09-01 | 复旦大学 | Micro-fluidic automatic separation and intelligent component identification system |
-
2019
- 2019-12-17 CN CN201911298294.XA patent/CN110895237B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101726483A (en) * | 2009-12-28 | 2010-06-09 | 茅涵斌 | Method for detecting chemicals by molecular engram, laser tweezers and microfluidic technology as well as detector thereof |
| KR20110083460A (en) * | 2010-01-14 | 2011-07-20 | 한국전자통신연구원 | Fluid analyzing device and method base on electrowetting |
| CN103191791A (en) * | 2013-03-01 | 2013-07-10 | 东南大学 | Integrated chip system for high-throughput sorting and counting detection of biological particles, and application |
| CN105764490A (en) * | 2013-09-24 | 2016-07-13 | 加利福尼亚大学董事会 | Encapsulated sensors and sensing systems for bioassays and diagnostics and methods for making and using them |
| CN204116189U (en) * | 2014-03-13 | 2015-01-21 | 严媚 | The imaging of intelligent optical miniflow and detection system |
| CN103822868A (en) * | 2014-03-14 | 2014-05-28 | 大连海事大学 | Device and method for detecting grain size of phytoplankton in seawater |
| CN104849444A (en) * | 2015-05-20 | 2015-08-19 | 大连海事大学 | Cell counting device and method capable of synchronously measuring fluorescence and occlusion |
| CN107904163A (en) * | 2017-12-12 | 2018-04-13 | 厦门大学 | A kind of full-automatic individual particle based on digital microfluidic technology/unicellular capture chip and its application |
| CN211402075U (en) * | 2019-12-17 | 2020-09-01 | 复旦大学 | Micro-fluidic automatic separation and intelligent component identification system |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111521547A (en) * | 2020-05-13 | 2020-08-11 | 洹仪科技(上海)有限公司 | Particle analyzing and sorting device and method |
| EP4040138A1 (en) * | 2021-02-03 | 2022-08-10 | Hitachi, Ltd. | Particle measuring device |
| KR20220112171A (en) * | 2021-02-03 | 2022-08-10 | 가부시끼가이샤 히다치 세이사꾸쇼 | Particle measuring apparatus |
| KR102609826B1 (en) | 2021-02-03 | 2023-12-06 | 가부시끼가이샤 히다치 세이사꾸쇼 | Particle measuring apparatus |
| CN117368073A (en) * | 2023-09-04 | 2024-01-09 | 中山大学·深圳 | Multi-mode liquid drop detection system and method |
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| Publication number | Publication date |
|---|---|
| CN110895237B (en) | 2024-05-28 |
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