Marine micro-plastic detection method based on microfluidic technology
The marine microplastic detection method using microfluidic technology solves the challenges of capture, screening, and identification in marine microplastic detection, achieving efficient and low-energy microplastic analysis and processing, and providing a highly reliable identification model supported by multi-dimensional feature data.
Patent Information
- Application Number
- CN202511634053.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-10
- Publication Date
- 2026-01-23
AI Technical Summary
Existing technologies are insufficient for efficiently and accurately sampling, identifying, and characterizing the chemical properties of marine microplastics. In particular, the application of microfluidic technology in complex marine environments is not yet mature, which poses challenges to the analysis and processing of microplastics.
A marine microplastic detection method based on microfluidics technology is adopted, including microchannel capture, dielectrophoretic sieving, and dynamic identification. By optimizing the microchannel structure, dielectrophoretic parameters, and multiple identification models, efficient capture, sieving, and identification of microplastics can be achieved.
It significantly improves the detection efficiency of marine microplastics, reduces energy consumption, enhances identification accuracy and integrated level, and provides multi-dimensional feature data to support a highly reliable dynamic identification model.
Smart Images
Figure CN121385280A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of microplastic detection, more particularly, it relates to a marine microplastic detection method based on microfluidic technology. BACKGROUND
[0002] Plastic products are widely used in our daily life and have become an indispensable part of human life. A large number of plastic products enter the ocean through direct dumping or with wastewater from treatment plants, which increasingly affects the marine ecological environment. The plastics in the ocean are deteriorated and miniaturized through photodegradation and thermal oxidative degradation, and the miniaturized plastics of various shapes with a size ranging from 1 μm to 5 mm are called "microplastics". Recently, a large number of articles have reported the accidental ingestion of microplastics by marine organisms and seabirds, and microplastics have also been detected in tap water in many places. Since microplastics have the ability to adsorb and absorb persistent organic pollutants, their damage to the marine ecosystem and public health has attracted global attention. At present, the cumulative impact of microplastic pollution on marine organisms has become a major health threat and poses a serious risk to the entire ecosystem. Efficient sampling, accurate identification and reliable chemical characterization of microplastics are crucial to understanding the impact of microplastics on the environment and organisms. However, the complexity caused by factors such as size, shape, degradation stage, aggregation and related biofilms makes the analysis and treatment of microplastics still face great challenges.
[0003] At present, the method for detecting microplastic particles from environmental or biological samples generally includes sample extraction and purification, digestion, quantification and identification processes. In the sample extraction and purification process, various sample separation and filtration methods are used to separate microplastics from the initial sample; different chemicals are used in the digestion process, aiming to remove all organic and inorganic matter, and the chemical concentration and treatment time need to be accurately controlled to avoid degrading microplastics; density separation and filtration aim to further separate microplastics from other influencing substances by floating microplastics; the quantification and identification method of microplastic particles is the most challenging, and the most commonly used visual identification method of microplastics has a high error rate (more than 20%), and the type of plastic cannot be identified by visual method (many plastics are similar in appearance to quartz, clay, algae or other substances in the sample).
[0004] Microfluidic technology is commonly used for micrometer or nanometer scale fluid handling and has been widely applied in analytical chemistry, biology, medicine and environment, etc. Since the size of microplastic particles is within the microfluidic range, inspired by the application of manipulating cells or nanoparticles using microfluidic devices, microfluidic methods can be used to handle and analyze microplastic particles, providing a new idea for the detection of microplastics. At present, the micro-particle capture, screening and identification processes that have attracted more attention include:
[0005] (1) Microfluidic capture of micro-particles
[0006] Microfluidics has the advantage of scale in capturing and adsorbing microplastics. Kim et al. developed a simulation approach based on the Lagrangian method to design fluid dynamic cell traps in microfluidic devices for efficient capture of microscale particles. Lai and Huang studied the influence of micro-pore geometry and flow particle size on particle capture in microchannels through experiments and numerical means, and they found that triangular micro-pores with larger top angles and smaller particle sizes have higher particle capture efficiency. In addition, the fluid dynamic behavior of nanoparticles flowing in microfluidic devices has also been concerned. Chong et al. studied the motion of inertial particles in viscous flow induced by an oscillating cylinder through theoretical and numerical methods. They found that inertial particles flowing near the trap inside the flow unit spiraled towards the center of the flow unit, and the particle capture rate increased with increasing particle size and decreasing particle density. Xu et al. used finite element simulation to study the fluid dynamic capture behavior of microspheres in a microfluidic particle trap array device. Haddadi et al. used the lattice Boltzmann method to numerically simulate the flow of particle-laden fluid through a cylinder. They proved that when the Reynolds number is less than 30 and the solid volume fraction is 0.04, 0.06 and 0.08, particle exchange occurs between the fluid wake and the free stream. The above research results show that microfluidic devices can be used as a tool to capture microscale particles in liquid, and studying the local interaction between particles and the flow around the capture trap is crucial for achieving efficient particle capture. However, there is still a lack of research on the capture mechanism of micro-disturbance particles of different structures, and the capture mechanism of micro-disturbance complex array of microplastics is still a research gap. Therefore, further research is needed on the capture mechanism of micro-disturbance microplastics.
[0007] (2) Microfluidic screening of microparticles
[0008] Currently, microfluidic dielectrophoresis is recognized as one of the most effective means of particle size-based particle separation. With the increase of the action diameter of dielectrophoresis force on particles, mixed particles of different sizes can be separated and moved to different microchannels under the action of dielectrophoresis force of different intensity. The size of the particle and the intensity of the electric field determine the transverse dielectrophoresis force acting on the particle, in which the larger radius of the particle deflects more than the smaller particle. When the particles pass through the microchannel, they are separated by size to different lateral positions. To separate particles of a specific diameter, only the voltage output needs to be adjusted by the external electrode. Pesch et al. demonstrated the influence of the geometry and material of the insulating pillars on the efficiency of the dielectrophoresis separation system. Weirauch et al. used the effect of direct current dielectrophoresis in a microchannel to separate 2.4 μm polystyrene particles with a purity of 100%, 4.5 μm particles with a purity of 92%, and gold-coated particles with a purity of more than 80%. To achieve the separation of particles of multiple sizes, Srivastava et al. upgraded the rectangular trap microfluidic chip by adjusting the conductivity of the suspension, and completed the separation of 3.18 μm, 6.20 μm and 10 μm fluorescent polystyrene particles. In addition, Zhao et al. used pressure-driven flow to achieve the separation of 1 μm and 3 μm polystyrene microparticles with a size difference of 2 μm in a nanohole-based direct current dielectrophoresis microfluidic device.
[0009] Different particles can exhibit different but unique dielectric characteristics at different alternating current frequencies, and these unique characteristics can be used for targeted particle separation on an alternating current dielectrophoresis microfluidic platform. When the dielectric frequency is between the critical frequencies of two different particles, one particle will experience a positive dielectrophoresis effect and move to the maximum of the electric field, while the other particle will be repelled by the negative dielectrophoresis force away from the area with a larger electric field strength. Zhang et al. demonstrated adjustable particle separation in a mixed dielectrophoresis-inertial microfluidic chip. By adjusting the applied voltage on the staggered microelectrodes at the bottom of the microchannel, particles experience dielectrophoresis and move to different positions in the microchannel. The purity separation efficiency for 5 μm and 13 μm particles is almost 96% or more. In addition, Sun et al. used the surface-induced dielectrophoresis and alternating current electrothermal flow effect of bipolar microelectrodes to achieve continuous capture, switching and sorting of particles in a microsystem. The experiment used the particle density adjustment of the bipolar control device to achieve the separation of 5 μm polystyrene particles and 4 μm silica particles, and the particle size adjustment of the device to achieve the separation of 2 μm and 5 μm polystyrene particles, with a separation efficiency of more than 93%. However, the above studies did not conduct in-depth research on the influence of complex factors such as seawater composition, shape, surface properties and composition of marine microplastics on the separation effect of microfluidic dielectrophoresis. Therefore, the dielectrophoresis separation mechanism of marine microplastics still needs further research.
[0010] (3) Visual identification of microplastics
[0011] Visual characterization is widely used in the field of microplastic identification. According to the size range of microplastic particles, they are classified as: <50 μm, 50-100 μm, 100-200 μm, 200-500 μm, 500-1000 μm and >1000 μm. Generally speaking, microplastic particles with larger size (>500 μm) can be identified by optical microscopy or naked eye, because there are differences in color, geometry and light transmission between plastic and non-plastic particles, and the image of microplastic particles can be obtained by optical microscopy to analyze its structural profile and quantity. However, due to the diffraction limit of 200 nm, the resolution of conventional optical microscopy will be limited, at which point microplastics can be identified by scanning electron microscopy. In order to obtain higher microplastic identification sensitivity and accuracy, visual inspection and spectroscopic techniques are usually combined to identify and characterize microplastics. Fluorescence microscopy is widely used for the characterization of microplastic particles. This method is often used for the identification of microplastic particles in marine sediments. The surface of marine microplastic particles adsorbs fluorescent dye and emits fluorescence, which is identified and counted by fluorescence image analysis. However, it has been difficult to integrate the above method with microfluidic technology to establish a marine microplastic microfluidic characterization platform.
[0012] In summary, the monitoring and analysis of marine microplastics have a profound significance for marine ecology and human health, and microfluidic technology has certain advantages for the detection of marine microplastics. In order to realize the popularization and application of microfluidic technology in the field of marine microplastic detection, the processes of particle capture, screening and identification in microfluidic technology need to be further studied, and a marine microplastic microfluidic detection platform needs to be built to realize the integrated integration of marine microplastic capture, screening and identification. SUMMARY
[0013] The purpose of the present application is to provide a marine microplastic detection method based on microfluidic technology, which applies microfluidic technology to the detection of marine microplastics, utilizes its scale effect, and realizes the screening and identification of marine microplastics.
[0014] The above technical purpose of the present application is realized by the following technical scheme: a marine microplastic detection method based on microfluidic technology, the detection method comprising the following steps:
[0015] S1. Capture of marine microplastics in a microchannel;
[0016] S2. Dielectrophoresis screening of marine microplastics;
[0017] S3. Dynamic identification of marine microplastics.
[0018] The present application is further provided that: the S1 specifically comprises the following steps:
[0019] a. Study the composition, shape, surface properties, microchannel structure, cross-sectional shape, area, and single-column or arrayed micro-disturbance structure with different shapes and surface properties of microplastic particles; according to the experimental observation results, introduce correction coefficients, Reynolds numbers and Stokes numbers to describe the influence of different micro-disturbance structures on the microplastic capture flow, and establish a microplastic capture regulation mechanism;
[0020] b. Establish a numerical model of fluid containing microplastics with different shapes and sizes flowing around different micro-column structures in a micro-channel, use numerical model analysis means to obtain the flow-solid coupling velocity field and pressure field in the micro-channel which is difficult to observe in experiments, further expand the research on the influence of solid particles on micro-scale fluid flow, and compare and analyze the numerical results with the experiments to perfect the numerical model.
[0021] The application further provides that the S2 specifically comprises the following steps:
[0022] a. Capture marine microplastics based on the marine microplastic regulation mechanism in S1, study the influence of marine fluid physical properties, microplastic composition, shape, size and quantity and other related parameters on the dielectrophoresis separation process, and obtain the influence mechanism of microplastic parameters on the dielectrophoresis separation effect;
[0023] b. By changing the electrode column spacing, column size and cross-sectional geometry, the key parameters of the non-uniform electric field are studied, and the influence of dielectrophoresis parameters on the separation effect of marine microplastics is studied; by reducing the number of columns in the micro-channel with insulating columns, the applied voltage required for the dielectrophoresis manipulation of marine microplastics is reduced, the critical point of low-power separation of micro-nano particles is studied, and the separation efficiency of the dielectrophoresis method is improved.
[0024] The application further provides that the S3 specifically comprises the following steps:
[0025] a. First, the marine microplastics with a size of 500-5000 mu m obtained by separation in S2 are observed by optical microscope and spectrum determination, and the shape, size and chemical composition are determined; the marine microplastics with a size of 50-500 mu m obtained by separation in S2 are dyed by dynamic fluorescence, and the dyed microplastics are directly observed and characterized by fluorescence; the marine microplastics with a size less than 50 mu m obtained by separation in S2 are directly determined by Fourier transform infrared spectrum; according to the above experimental results, the dynamic identification mechanism is determined by analysis;
[0026] b. According to the above results, support vector machine, random forest, convolutional neural network and residual neural network model are verified respectively to evaluate their performance in identifying microplastics, and a reliable model for dynamic identification of microplastics is obtained by optimization.
[0027] In summary, the present application has the following beneficial effects: the detection of marine microplastics is realized by using microfluidic technology. Quantitative experimental research is conducted on the microfluidic flow mechanism in the process of capturing, screening and identifying marine microplastics, the dielectrophoresis screening mechanism of microparticles and the accuracy of different identification models, and the internal mechanism is explained by numerical calculation. Specifically, in the capture stage, the dynamic behavior of microplastics with different particle sizes and shapes in a specific flow field is analyzed in depth by optimizing the microchannel structure and fluid parameters; in the screening stage, the relationship between the key parameters of the non-uniform electric field (such as field strength gradient and frequency) and the insulating column configuration is focused on, and through systematic experiments and coupled field numerical simulation, the differential manipulation mechanism of dielectrophoresis force on microplastics of different sizes under low voltage driving is quantitatively revealed, which significantly improves the screening efficiency and reduces the energy consumption; in the identification stage, based on the multi-dimensional feature data such as shape, size and chemical composition of multi-scale microplastics (500-5000 μm optical observation, 50-500 μm dynamic fluorescence staining characterization, <50 μm Fourier infrared spectrum determination), combined with the parallel training, cross-validation and performance comparison of models such as support vector machine, random forest, convolutional neural network and residual neural network, a solid foundation is laid for building a high-reliability dynamic identification model. BRIEF DESCRIPTION OF DRAWINGS
[0028] Figure 1 Various shapes in the capture column or capture well captured in the embodiment of the present application. DETAILED DESCRIPTION
[0029] The following will be described in detail in combination with the drawings Figure 1 The present application will be further described in detail.
[0030] Embodiment: A marine microplastic detection method based on microfluidic technology, based on existing experimental conditions, an experimental platform including a micro-feeding system, a microfluidic integrated detection chip, a high-speed (fluorescent) microscopic photography and imaging system is built. The micro-feeding and control system is composed of a Langer constant flow pump; the microchannel system needs to be designed and processed according to the flow conditions, and microfluidic chips of various materials and structures are designed and processed; the high-speed (fluorescent) microscopic photography and imaging system is composed of an optical microscope equipped with a high-speed / fluorescent lens camera, which is used to capture the time sequence images of microplastic capture and dielectrophoresis screening in the microchannel.
[0031] (1) Microplastic microfluidic capture experiment observation using experimental platform: First, use micro-feeding system to digest the collected seawater, then use high-speed microscopic photography technology to observe and record the capture of microplastics with different shape composition and surface properties in microscale channels with different structures, cross-sectional shapes and areas by single-column or array-type micro-disturbance structures with different shapes and surface properties. Compare and analyze the experimental results to obtain the best capture structure. According to the experimental results, introduce correction coefficient, Reynolds number and Stokes number to describe the influence of different micro-disturbance structures on microplastic capture flow, and establish the microplastic capture regulation mechanism.
[0032] (2) Numerical method is used to fit the numerical model of seawater containing microplastics with different shapes and sizes flowing around different micro-column structures in microchannels. The numerical model is used to obtain the flow-solid coupling velocity field and pressure field in the microchannel which is difficult to observe in experiments, and further expand the influence of solid particles on microscale fluid flow. Compare and analyze the numerical results with the experiments, correct the model parameters, improve the numerical model, and deepen the flow mechanism.
[0033] (3) Dielectrophoresis screening experiment of marine microplastics using microfluidic integrated chip system: Study the influence of seawater physical properties, microplastic composition, shape, size and quantity on the dielectrophoresis screening process, and obtain the influence mechanism of microplastic parameters on dielectrophoresis screening effect; Change the electrode column spacing, column size and cross-sectional geometry to manipulate the key parameters of non-uniform electric field, and study the influence of dielectrophoresis parameters on marine microplastic screening effect; Reduce the number of electrode columns in the microchannel and reduce the dielectrophoresis manipulation voltage, and study the microplastic
[0034] (4) Marine microplastic identification experiment using microfluidic integrated chip system: First, observe and determine the shape, size and chemical composition of marine microplastics with a size of 500-5000 μm by optical microscopy and spectroscopy; Then, use the microfluidic feeding system to dynamically fluorescently dye marine microplastics with a size of 50-500 μm, and directly observe and characterize the dyed microplastics; Finally, collect marine microplastics with a size less than 50 μm and perform Fourier transform infrared spectroscopy. Analyze the above experimental results to determine the dynamic identification mechanism.
[0035] (5) According to the results in the above (4), the programming and verification of support vector machine, random forest, convolutional neural network and residual neural network model of the image recognition system are carried out respectively, the accuracy of the above models in microplastic identification is evaluated, and the reliable model of microplastic dynamic identification is optimized and established. This specific embodiment is only an explanation of the present application, and is not a limitation of the present application. Those skilled in the art can make modifications to this embodiment without creative contribution after reading the specification, but as long as it is within the scope of the claims of the present application, it is protected by the patent law.
Claims
1. A method for detecting marine microplastics based on microfluidic technology, characterized by: The detection method comprises the following steps: S1. Capture of marine microplastics in the microchannel; S2. Dielectrophoresis screening of marine microplastics; S3. Dynamic identification of marine microplastics.
2. The marine microplastic detection method based on microfluidic technology according to claim 1, characterized in that: S1 specifically comprises the following steps: a. Study the composition, shape, surface characteristics of microplastics, the structure, cross-sectional shape and area of the microchannel, and the capture of microplastic particles by single-column or arrayed micro-disturbance structures with different shapes and surface characteristics; according to the experimental observation results, introduce correction coefficient, Reynolds number and Stokes number to describe the influence of different micro-disturbance structures on microplastic capture flow, establish the microplastic capture regulation mechanism; b. Establish a numerical model of fluid containing microplastics with different shapes and sizes flowing around different micro-column structures in the microchannel, use numerical model analysis means to obtain the flow-solid coupling velocity field and pressure field in the microchannel which is difficult to observe in experiments, further expand the study of the influence of solid particles on micro-scale fluid flow, and compare and analyze the numerical results with experiments to perfect the numerical model.
3. The marine microplastic detection method based on microfluidic technology according to claim 1, characterized in that: S2 specifically comprises the following steps: a. Capture marine microplastics based on the marine microplastic regulation mechanism in S1, study the influence of marine fluid physical properties, microplastic composition, shape, size and quantity and other related parameters on the dielectrophoresis screening process, and obtain the influence mechanism of microplastic parameters on dielectrophoresis screening effect; b. By changing the key parameters of non-uniform electric field generated by changing the electrode column spacing, column size and cross-sectional geometry, study the influence of dielectrophoresis parameters on the screening effect of marine microplastics; by reducing the number of columns in the microchannel with insulating columns, reduce the applied voltage required for dielectrophoresis manipulation of marine microplastics, study the critical point of low-power screening of micro-nano particles, and improve the screening efficiency of dielectrophoresis method.
4. The marine microplastic detection method based on microfluidic technology according to claim 1, characterized in that: S3 specifically comprises the following steps: a. First, optical microscopy observation and spectral measurement are performed on the marine microplastics with a size of 500-5000 μm obtained by screening in S2 to determine their shape, size and chemical composition; dynamic fluorescence staining is performed on the marine microplastics with a size of 50-500 μm obtained by screening in S2 by microfluidic technology, and the stained microplastics are directly observed and characterized by fluorescence; Fourier transform infrared spectroscopy is directly performed on the marine microplastics with a size less than 50 μm obtained by screening in S2; according to the above experimental results, the dynamic identification mechanism is determined; b. According to the above results, support vector machine, random forest, convolutional neural network and residual neural network models are verified to evaluate their performance in identifying microplastics, and a reliable model for dynamic identification of microplastics is obtained.