Micro-fluidic chip based on particle size distribution of muddy silt sediment and preparation method and application of micro-fluidic chip

Abstract

The invention discloses a micro-fluidic chip based on muddy silt sediment particle size distribution as well as a preparation method and application of the micro-fluidic chip. The method comprises the following steps: 1) determining the size of a pore model of the muddy silt type sediment; 2) obtaining the two-dimensional pore model basic information of the particle size distribution curve and the porosity of the measured muddy silt type sediment; 3) encrypting the particle size distribution curve based on an interpolation function, and obtaining the minimum value and the maximum value of the particle size of the particles in the corresponding horizontal axis interval; 4) performing normal distribution on the particle sizes in the horizontal axis interval to obtain an expected value and a standard deviation; 5) generating particles according to the expected value and the standard deviation of the normal distribution function, and randomly putting the particles in the argillaceous silt type sediment pore model region to obtain a particle heterogeneous distribution geometric model; (6) circulating the steps (3)-(5), and establishing an argillaceous silt type sediment pore model; and 7) etching the model in the step 6) on a substrate to obtain the micro-fluidic chip. The method is applied to the field of porous media.

Description

Technical Field

[0001] The invention belongs to the field of porous medium preparation, and relates to a microfluidic chip based on the particle size distribution of muddy silt sediments, and a preparation method and application thereof. Background Art

[0002] The construction of geometric models of porous media in sediments is one of the key technical challenges in many fields, including oil and gas exploration, groundwater flow research, environmental science, and materials science. The construction of the model aims to accurately describe the complex geometric structure of porous media, including particle size, distribution, and connectivity between pores, which is the basis for subsequent experiments or simulations. At present, with the improvement of computing power and the advancement of imaging technology, the methods and accuracy of constructing geometric models of porous media have developed significantly.

[0003] Artificial preparation: Artificially prepared sediment porous media is a technology that simulates the structure and function of natural sediments in a laboratory environment. For some natural sediment samples that are difficult to obtain or too expensive, artificial preparation provides an economical and effective alternative. However, at present, artificially prepared porous media are often too regular and difficult to reflect the particle size distribution and pore structure characteristics of real sediments.

[0004] Geometric model analysis: Through high-resolution X-ray computed tomography (CT), magnetic resonance imaging (MRI) and other technologies, researchers can obtain three-dimensional internal structure images of rock samples. Based on these image data, accurate geometric models of porous media can be constructed by applying image processing and reconstruction techniques. However, the model constructed by this technology is difficult to directly apply to experimental measurements of permeability, conductivity, etc., and real rock cores are difficult to obtain and costly.

[0005] Computer simulation and random generation algorithms play an important role in the construction of porous media geometry models. By simulating the movement and accumulation of sediments, porous structures similar to those in the natural environment can be generated. Random generation algorithms, such as the random sphere packing algorithm, are used to simulate the random distribution of pores in porous media. These methods can be used not only to generate new models, but also to optimize existing models and improve their accuracy and reliability in practical applications.

[0006] In addition, microfluidics has shown great potential in simulating and studying porous media in recent years. By precisely controlling the movement of fluids on microfluidic chips, researchers can simulate different deposition processes and pore structure formation mechanisms. In addition, artificial synthesis methods, such as using specific chemicals or biomaterials to construct porous media models with specific pore structures, have also become a research hotspot. Summary of the invention

[0007] The purpose of the present invention is to provide a microfluidic chip based on the particle size distribution of muddy silt sediments and a preparation method and application thereof.

[0008] To achieve the above objectives, the present invention constructs a two-dimensional geometric model of sediments based on the particle size distribution ratio and porosity in the real reservoir particle size distribution curve, prepares a random distribution geometric model by inputting specific parameters, and prepares a microfluidic etching model by laser etching.

[0009] The present invention provides a method for preparing a microfluidic chip based on the particle size distribution of muddy silt-sand sediments, comprising the following steps:

[0010] 1) Determine the pore model size of muddy silt sand sediment according to the required microfluidic chip size;

[0011] 2) Obtain the particle size distribution curve of the measured muddy silt-sand sediment and the basic information of the two-dimensional pore model of porosity through laser particle size analysis, where the particle size distribution curve takes the particle size as the x-axis and the volume percentage as the y-axis;

[0012] 3) encrypting the particle size distribution curve based on an interpolation function, and taking the volume percentage in the particle size distribution curve as the vertical axis interval with Δy as the starting point of the vertical axis interval with the volume percentage of 1, obtaining the minimum and maximum values ​​of the particle sizes in the corresponding horizontal axis interval, which are recorded as 1-Δy and 1, respectively;

[0013] 4) adopting a normal distribution for the particle size in the horizontal axis interval, and obtaining an expected value and a standard deviation in the normal distribution function of the particle size in the horizontal axis interval according to the minimum value and the maximum value of the horizontal axis interval, wherein the expected value is the median of the maximum value and the minimum value of the horizontal axis interval, and the standard deviation is the difference between the maximum value and the median value of the horizontal axis interval;

[0014] 5) Generate particles according to the expected value and standard deviation of the normal distribution function and randomly place particles in the pore model area of ​​the muddy silt sand type sediment, without overlapping each other, until the particle volume proportion Δy is satisfied, and obtain a particle heterogeneous distribution geometric model of the vertical axis interval;

[0015] 6) Repeat step 3) to step 5), carry out particle placement in the next horizontal axis interval of Δy vertical axis interval (1-a·Δy, 1-(a-1)·Δy), repeat until the end, and establish a pore model of muddy silt sand sediment, where a is the number of cycles;

[0016] 7) According to the pore model of muddy silt sand type sediment, the introduced particles are muddy silt sand, and the unintroduced part is a pore channel. A laser etching method is used to etch the substrate material to obtain a microfluidic chip based on the particle size distribution of muddy silt sand sediment.

[0017] In the above method, the length of the silty silt sediment pore model is recorded as L, the width is recorded as W, and the area is recorded as A, wherein A = L × W;

[0018] The calculation formula of the probability density function corresponding to the particle size is shown in Formula I:

[0019] Formula I

[0020] In formula I, r is the particle size, f(r) is the probability density corresponding to r, μ is the expected value of the normal distribution parameter of the average particle size, and σ is the standard deviation of the particle size distribution range.

[0021] In the above method, in formula I, the probability density in the horizontal axis interval (μ-σ, μ+σ) is 0 to 68.26%; the probability density in the horizontal axis interval (μ-2σ, μ+2σ) is 0 to 95.44%; the probability density in the horizontal axis interval (μ-3σ, μ+3σ) is 0 to 99.73%.

[0022] In the above method, the expected value of the normal distribution parameter of the average particle size and the standard deviation of the particle size distribution range are calculated according to formula II-III:

[0023] Formula II D max =μ+σ;

[0024] Formula IIID min =μ-σ;

[0025] In formula II-III, D max , D min They represent the upper and lower limits of the horizontal axis range and automatically delete the particle size range outside the range; μ is the expected value of the normal distribution parameter of the average particle size, and σ is the standard deviation of the particle size distribution range.

[0026] In the above method, in step 3), the volume percentage of the particles is calculated according to Formula IV:

[0027] Formula IV Δy=A×(1-φ)

[0028] In formula IV, A is the area of ​​the two-dimensional pore model of the sediment, and φ is the porosity of the muddy silt-sand sediment obtained by laser particle size analysis.

[0029] In the above method, the conditions of the laser etching method are as follows:

[0030] a) Step 7) further comprises the following steps: a) cleaning the substrate: using a solvent to clean the surface of the substrate to remove oil and dust;

[0031] b) Laser etching processing: importing the designed silty sand sediment pore model into the control software of the laser processing equipment, using the laser to scan and etch the substrate according to the preset path, removing the non-particle part in the pore model to form a microfluidic structure;

[0032] c) Post-processing: Use deionized water or a suitable solvent to clean the processed chip to remove the residues generated during the processing;

[0033] d) Inspection and evaluation: Use an optical microscope or scanning electron microscope to check the etching quality to ensure that the structure meets the design requirements;

[0034] e) Testing: Perform fluid injection test to verify the functionality of the microfluidic chip.

[0035] In the present invention, the substrate is selected from a silicon wafer or other suitable material on which a microfluidic structure is precisely etched; the laser is selected from an ultraviolet laser or a femtosecond laser; and an appropriate type of laser is selected according to material properties and processing requirements.

[0036] In the above method, the solvent includes isopropanol;

[0037] In the conditions of the laser etching method: step e) also includes a packaging step: packaging the microfluidic channel by bonding a transparent cover sheet.

[0038] In the present invention, a pretreatment step is also included between steps a) and b), in which the substrate is pretreated, such as coating a layer of light-absorbing material to increase the laser absorption rate.

[0039] The present invention also provides a microfluidic chip based on the particle size distribution of muddy silt sand sediments prepared by the above method.

[0040] The present invention further provides application of the above-mentioned microfluidic chip in the field involving porous media.

[0041] In the above applications, the field is selected from any one of petroleum engineering, groundwater, environmental engineering, concrete pavement, recycled aggregate permeable concrete, botany and biology.

[0042] The present invention has the following beneficial effects:

[0043] 1. Improve the accuracy and representativeness of the model

[0044] Previous models often relied on simplifying assumptions and idealized structures, such as using regular shapes to simulate irregular particles in nature. This approach can generate models that are closer to the characteristics of natural sediments by accurately simulating the real-world particle size distribution, thereby improving the accuracy of experimental data and the representativeness of related research.

[0045] 2. Overcoming limitations in material acquisition

[0046] In the fields of geology and petroleum engineering, obtaining natural sediment samples with specific physical and chemical properties can be difficult and expensive. This method can circumvent this obstacle by synthesizing sediment models in the laboratory, providing a more flexible and economical material choice for research.

[0047] 3. Achieve precise manufacturing of complex geometric structures

[0048] Traditional sediment models often have difficulty in accurately controlling the internal geometric structure, especially at the microscopic scale. Combined with microfluidic chip etching technology, this method can accurately construct complex internal channels and pore structures at the micro-nano level, better simulating the porous media characteristics of natural sediments.

[0049] 4. Enhance the repeatability and adjustability of the model

[0050] Existing physical models often have large variability, and once manufactured, their structure and properties are difficult to adjust. Through computer-controlled particle generation algorithms and laser etching technology, the model can be highly repeatable and adjustable, supporting customization for different research needs.

[0051] 5. Reduce experimental costs and time

[0052] The sediment model made by this method can be completed in a short time and reduces the workload of preliminary preparation and post-processing compared to naturally collected samples, thereby significantly reducing the experimental cost and cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is the particle size distribution curve of muddy silt-type sediments in the South China Sea;

[0054] Figure 2 It is a flow chart of the method for preparing a microfluidic chip based on the particle size distribution of muddy silt sand sediments of the present invention;

[0055] Figure 3 This is the pore model of muddy silt-sand type sediment in the first cycle;

[0056] Figure 4 It is a complete pore model of muddy silt sand sediment. DETAILED DESCRIPTION

[0057] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0058] Unless otherwise specified, the materials and reagents used in the following examples can be obtained from commercial sources.

[0059] The working principle of the present invention is that the particle size conforms to the normal distribution principle and the particle placement positions are random and do not overlap. In addition, a high-energy-density laser beam is used to locally heat the target material to evaporate it or remove the material through a photochemical reaction, thereby achieving etching of a fine structure.

[0060] like Figure 1 As shown in the flowchart, the present invention provides a method for preparing a microfluidic chip based on the particle size distribution of muddy silt sediment, comprising the following steps:

[0061] 1) First, the input parameters need to be determined, including the particle size distribution curve, porosity, vertical axis interval Δy, and the length and width of the geometric model. Assume that the sediment model size is L×W, the model area is A, the normal distribution parameter mathematical expectation μ represents the average particle size, and the standard deviation σ represents the particle size distribution range;

[0062] 2) The particle size adopts the normal distribution function, and the calculation formula of the probability density function f(r) corresponding to the particle size r is:

[0063]

[0064] Where σ represents the standard deviation of the particle size distribution range, and μ represents the expected value of the normal distribution parameter of the average particle size.

[0065] According to the normal distribution principle, the probability of particle size being in the horizontal axis range is:

[0066] The area within the horizontal axis interval (μ-σ, μ+σ) is 0 to 68.26%;

[0067] The area within the horizontal axis interval (μ-2σ, μ+2σ) is 0 to 95.44%;

[0068] The area within the horizontal axis interval (μ-3σ, μ+3σ) is 0 to 99.73%;

[0069] 3) Determine the upper and lower limits of the particle size range D corresponding to the vertical axis interval (1-a·Δy, 1-(a-1)·Δy) in each cycle max , D min ,

[0070] D max =μ+σ, D min =μ-σ

[0071] D max , D min Respectively represent the horizontal axis interval and automatically delete the upper and lower limits of the particle size range outside the interval; calculate μ and σ, and randomly place particles in the model area. The placement principle complies with step 2, and the particles do not overlap each other. Place particles until the particle volume ratio reaches A×(1-φ)×Δy

[0072] 4) Repeat step 3 to generate particles corresponding to all vertical axis intervals to generate a complete pore model of muddy silt sand sediments.

[0073] Embodiment 1,

[0074] This example analyzes the particle size distribution curve of muddy silt sand sediments in the South China Sea and extracts the particle size distribution curve of the core particles into Figure 1 The flow chart of pore model preparation for muddy silt sediment is shown in Figure 2 shown.

[0075] The detailed steps are as follows:

[0076] 1. Determine the pore model size of muddy silt sand sediment according to the size of the microfluidic chip, where the length is 1000 μm and the width is 500 μm;

[0077] 2. Obtain the basic information of the two-dimensional pore model such as the particle size distribution curve and porosity of the muddy silt sand sediment in the South my country Sea through laser particle size analysis. The x-axis of the particle size distribution curve is the particle size, the y-axis is the volume percentage, and the porosity is 0.4. Figure 1 shown.

[0078] 3. The particle size distribution curve data is encrypted based on the interpolation function, and the volume proportion in the particle size distribution curve is set as 20% as the vertical axis interval, and the vertical axis interval is set as 100% of the volume proportion as the starting point, and the minimum value of 62.9μm and the maximum value of 104.6μm of the particle size in the horizontal axis interval of the particle size distribution curve in each vertical axis interval are obtained;

[0079] 4. The particle size in each horizontal axis interval adopts normal distribution. According to the minimum and maximum values ​​of the horizontal axis interval, the expected value and standard deviation in the normal distribution function are obtained. Among them, the expected value is the median of the maximum and minimum values, which is 83.8μm, and the standard deviation is the difference between the maximum and the median, which is 20.8μm;

[0080] 5. Generate particles according to the expected value and standard deviation of the normal distribution function parameters and randomly place particles in the model area. The particles do not overlap with each other until the particle volume ratio is (1-0.4)×20%, and obtain the particle heterogeneous distribution geometric model in the vertical axis interval, as shown in Figure 3 As shown;

[0081] Depend on Figure 3 It can be seen that three particles are placed in the first particle placement cycle, and the particle volume accounts for 12% at this time.

[0082] 6. Repeat steps 3 to 5, and carry out the next Δy vertical axis interval (1-a×20%, 1-(a-1)×20%) particle placement, and repeat until the end to establish the pore model of muddy silt sand sediments, where a is the number of cycles, 5 times, and after the end, Figure 4 As shown;

[0083] Depend on Figure 4 It can be seen that at this time, the particles are placed completely, tiny clay particles are filled in the middle of large particles, the porosity is 0.4, and the particle distribution conforms to the particle size distribution of muddy silt particles.

[0084] 7. Etching microfluidic chips based on the generated geometric model involves a series of delicate preparation steps aimed at accurately etching microfluidic structures on silicon wafers.

[0085] 7.1 Optical Equipment Setup

[0086] Laser selection: Select the appropriate type of laser, such as UV laser, based on material properties and processing requirements.

[0087] Parameter adjustment: Set the laser power to 20-50W, pulse width to 75fs, scanning speed to 30mm / s, and focus size to 10um to optimize the processing effect.

[0088] 7.2 Surface treatment

[0089] Clean the substrate: Use a solvent (such as isopropyl alcohol) to clean the substrate surface for 10 minutes to remove oil and dust.

[0090] Pretreatment: If necessary, pretreat the substrate and coat it with a layer of light-absorbing material to increase the laser absorption rate.

[0091] Laser Etching Processing

[0092] Import design files: Import the designed geometric model into the control software of the laser processing equipment.

[0093] 7.3 Laser scanning etching: Use laser to scan and etch the substrate along a preset path to remove material to form a microfluidic structure.

[0094] 7.4 Post-processing

[0095] Cleaning: Use deionized water or a suitable solvent to clean the processed chip for 5 minutes to remove the residues generated during the processing.

[0096] Inspection and evaluation: Use optical microscopy or scanning electron microscopy (SEM) to check the etching quality to ensure that the structure meets the design requirements.

[0097] 7.5 Packaging and Testing

[0098] Packaging: Place the glass chip in a bonding machine and evacuate the vacuum, heat (573.0K) and apply pressure (72.0K) for bonding.

Claims

1. A method for preparing a microfluidic chip based on the particle size distribution of muddy silt-sand sediments, characterized in that: The steps include: 1) Determine the pore model size of muddy silt sand sediment according to the required microfluidic chip size; 2) Obtain the particle size distribution curve of the measured muddy silt-sand sediment and the basic information of the two-dimensional pore model of porosity through laser particle size analysis, where the particle size distribution curve takes the particle size as the x-axis and the volume percentage as the y-axis; 3) encrypting the particle size distribution curve based on an interpolation function, and taking the volume percentage in the particle size distribution curve as the vertical axis interval with Δy as the starting point of the vertical axis interval with the volume percentage of 1, obtaining the minimum and maximum values ​​of the particle sizes in the corresponding horizontal axis interval, which are recorded as 1-Δy and 1, respectively; 4) adopting a normal distribution for the particle size in the horizontal axis interval, and obtaining an expected value and a standard deviation in the normal distribution function of the particle size in the horizontal axis interval according to the minimum value and the maximum value of the horizontal axis interval, wherein the expected value is the median of the maximum value and the minimum value of the horizontal axis interval, and the standard deviation is the difference between the maximum value and the median value of the horizontal axis interval; 5) Generate particles according to the expected value and standard deviation of the normal distribution function and randomly place particles in the pore model area of ​​the muddy silt sand type sediment, without overlapping each other, until the particle volume proportion Δy is satisfied, and obtain a particle heterogeneous distribution geometric model of the vertical axis interval; 6) Repeat step 3) to step 5), carry out particle placement in the next horizontal axis interval of Δy vertical axis interval (1-a·Δy, 1-(a-1)·Δy), repeat until the end, and establish a pore model of muddy silt sand sediment, where a is the number of cycles; 7) According to the pore model of muddy silt sand type sediment, the introduced particles are muddy silt sand, and the unintroduced part is a pore channel. A laser etching method is used to etch the substrate material to obtain a microfluidic chip based on the particle size distribution of muddy silt sand sediment.

2. The method according to claim 1, characterized in that The dimensions of the pore model of the muddy silt sand sediment are L for length, W for width, and A for area, wherein A=L×W; The calculation formula of the probability density function corresponding to the particle size is shown in Formula I: Formula I In formula I, r is the particle size, f(r) is the probability density corresponding to r, μ is the expected value of the normal distribution parameter of the average particle size, and σ is the standard deviation of the particle size distribution range.

3. The method according to claim 2, characterized in that In formula I, the probability density in the horizontal axis interval (μ-σ, μ+σ) is 0 to 68.26%; the probability density in the horizontal axis interval (μ-2σ, μ+2σ) is 0 to 95.44%; the probability density in the horizontal axis interval (μ-3σ, μ+3σ) is 0 to 99.73%.

4. The method according to claim 2 or 3, characterized in that: The expected value of the normal distribution parameter of the average particle size and the standard deviation of the particle size distribution range are calculated according to Formula II-III: Formula ⅡD max = μ + σ; Formula ⅢD min = μ - σ; In formula II-III, D max , D min They represent the upper and lower limits of the horizontal axis range and automatically delete the particle size range outside the range; μ is the expected value of the normal distribution parameter of the average particle size, and σ is the standard deviation of the particle size distribution range.

5. The method according to claim 4, characterized in that In step 3), the volume percentage of the particles is calculated according to formula IV: Formula IV Δy=A×(1-φ) In formula IV, A is the area of ​​the two-dimensional pore model of the sediment, and φ is the porosity of the muddy silt-sand sediment obtained by laser particle size analysis.

6. The method according to claim 1 or 2, characterized in that: The conditions of the laser etching method are as follows: a) Step 7) further comprises the following steps: a) cleaning the substrate: using a solvent to clean the surface of the substrate to remove oil and dust; b) Laser etching processing: importing the designed silty sand sediment pore model into the control software of the laser processing equipment, using the laser to scan and etch the substrate according to the preset path, removing the non-particle part in the pore model to form a microfluidic structure; c) Post-processing: Use deionized water or a suitable solvent to clean the processed chip to remove the residues generated during the processing; d) Inspection and evaluation: Use an optical microscope or scanning electron microscope to check the etching quality to ensure that the structure meets the design requirements; e) Testing: Perform fluid injection test to verify the functionality of the microfluidic chip.

7. The method according to claim 6, characterized in that The solvent includes isopropanol; In the conditions of the laser etching method: step e) also includes a packaging step: packaging the microfluidic channel by bonding a transparent cover sheet.

8. A microfluidic chip based on the particle size distribution of muddy silt sediments prepared by the method according to any one of claims 1 to 7.

9. Application of the microfluidic chip according to claim 8 in the field of porous media.

10. The use according to claim 9, characterized in that: The field is selected from any one of petroleum engineering, groundwater, environmental engineering, concrete pavement, recycled aggregate permeable concrete, botany and biology.

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