A microfluidic chip based on the particle size distribution of muddy silt sediments and its preparation method and application

Abstract

The present invention discloses a microfluidic chip based on the particle size distribution of muddy silt sediments, and its preparation method and application. The method comprises the following steps: 1) determining the size of the pore model of the muddy silt sediment; 2) obtaining the particle size distribution curve and the basic information of the two-dimensional pore model of the porosity of the measured muddy silt sediment; 3) encrypting the particle size distribution curve based on the interpolation function, and obtaining the minimum and maximum values ​​of the particle size in the corresponding horizontal axis interval; 4) applying a normal distribution to the particle size in the horizontal axis interval to obtain the expected value and standard deviation; 5) generating particles according to the expected value and standard deviation of the normal distribution function and randomly placing the particles in the pore model area of ​​the muddy silt sediment to obtain a geometric model of heterogeneous particle distribution; 6) looping steps 3)-5) to establish the pore model of the muddy silt sediment; 7) etching the model in step 6) on a substrate to obtain a microfluidic chip. The present invention is applied to the field of porous media.

Description

Technical Field

[0001] The present 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] Geometric modeling of porous sedimentary media is a key technical challenge in fields such as oil and gas exploration, groundwater flow research, environmental science, and materials science. Modeling aims to accurately describe the complex geometry of porous media, including particle size and distribution, as well as the connectivity between pores, providing the foundation for subsequent experiments or simulations. With advances in computing power and imaging technology, the methods and accuracy of geometric modeling for porous media have significantly improved.

[0003] Artificially prepared sediment porous media is a technique used to simulate the structure and function of natural sediments in a laboratory setting. For natural sediment samples that are difficult or costly to obtain, artificial preparation provides a cost-effective alternative. However, currently, artificially prepared porous media are often too regular to reflect the particle size distribution and pore structure characteristics of real sediments.

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

[0005] Computer simulation and random generation algorithms play a crucial role in constructing geometric models of porous media. By simulating the movement and accumulation of sediments, porous structures similar to those found in natural environments 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 not only generate new models but also optimize existing models, improving their accuracy and reliability in practical applications.

[0006] Furthermore, microfluidics has demonstrated tremendous potential in recent years for simulating and studying porous media. By precisely controlling fluid movement within microfluidic chips, researchers can simulate various deposition processes and pore structure formation mechanisms. Furthermore, synthetic methods, such as employing 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-type sediments, comprising the following steps:

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

[0011] 2) Obtain the particle size distribution curve and two-dimensional pore model basic information of the measured muddy silt sediment through laser particle size analysis, where the particle size distribution curve has particle size as the x-axis and volume fraction 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 Δy, the vertical axis interval starting from the volume percentage of 1, and obtaining the minimum and maximum values ​​of the particle sizes in the corresponding horizontal axis intervals, which are recorded as 1-Δy and 1, respectively;

[0013] 4) applying a normal distribution to the particle sizes within the horizontal axis interval, and obtaining an expected value and a standard deviation of the normal distribution function of the particle sizes within the horizontal axis interval based on the minimum and maximum values ​​of the horizontal axis interval, wherein the expected value is the median of the maximum and minimum values ​​of the horizontal axis interval, and the standard deviation is the difference between the maximum and median values ​​of the horizontal axis interval;

[0014] 5) generating particles according to the expected value and standard deviation of the normal distribution function and randomly placing the particles in the pore model region of the muddy silt sand sediment, with the particles not overlapping each other, until the particle volume proportion Δy is satisfied, thereby obtaining a geometric model of particle heterogeneous distribution in the vertical axis interval;

[0015] 6) Repeat steps 3) to 5) and place particles in the next horizontal interval of the Δy vertical axis (1-a·Δy, 1-(a-1)·Δy), repeat until the end, and establish a pore model of muddy silt sand sediments, where a is the number of cycles;

[0016] 7) According to the pore model of muddy silt sediment, the placed particles are muddy silt and the unplaced part is a pore channel. Laser etching is performed on the substrate material to obtain a microfluidic chip based on the particle size distribution of muddy silt sediment.

[0017] In the above method, the length of the silty sand sediment pore model is recorded as L, the width is recorded as W, and the area is recorded as A, where 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 within the horizontal axis interval (μ-σ, μ+σ) is 0 to 68.26%; the probability density within the horizontal axis interval (μ-2σ, μ+2σ) is 0 to 95.44%; and the probability density within 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 fraction of the particles is calculated according to Formula IV:

[0027] Formula IV Δy=A×(1-φ)

[0028] In Equation IV, A is the area of ​​the two-dimensional pore model of the sediment, and φ is the porosity of the muddy silt-type 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 includes the following steps: a) cleaning the substrate: using a solvent to clean the substrate surface to remove oil and dust;

[0031] b) Laser etching: importing the designed silty sand sediment pore model into the control software of the laser processing equipment, and using the laser to scan and etch the substrate along a preset path to remove the non-particle part of 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 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 materials on which a microfluidic structure is precisely etched; the laser is selected from an ultraviolet laser or a femtosecond laser; and the appropriate type of laser is selected according to the material properties and processing requirements.

[0036] In the above method, the solvent includes isopropyl alcohol;

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

[0038] In the present invention, a pre-treatment step is further included between steps a) and b), in which the substrate is pre-treated, 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 sediments prepared by the above method.

[0040] The present invention further provides applications 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 found in nature. This approach, by accurately simulating real-world particle size distributions, can produce models that more closely resemble the characteristics of natural sediments, 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 struggle to precisely control internal geometric structures, especially at the microscopic scale. Combined with microfluidic chip etching technology, this approach can precisely construct complex internal channels and pore structures at the micro- and nanoscale, better simulating the porous media properties 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, we can achieve highly repeatable and adjustable models, allowing 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 compared with naturally collected samples, the workload of preliminary preparation and post-processing is reduced, 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 sediments in the South China Sea;

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

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

[0056] Figure 4 It is a complete pore model of muddy silt 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, causing it to evaporate or remove the material through a photochemical reaction, thereby achieving etching of fine structures.

[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 sediments, comprising the following steps:

[0061] 1) First, you need to determine the input parameters, including the particle size distribution curve, porosity, vertical axis interval Δy, and the length and width of the geometric model. Let the sediment model size be L×W, the model area be A, the normal distribution parameter μ representing the mathematical expectation of the average particle size, and σ representing the standard deviation of 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 the 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 D of the particle size range 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 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 with 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] Example 1

[0074] This example analyzes the particle size distribution curve of muddy silt sediments in the South China Sea and extracts the particle size distribution curve of the core particles into the Figure 1 The flow chart for preparing the pore model of 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 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 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 ratio 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 ratio. The minimum value of the particle size in the horizontal axis interval of the particle size distribution curve in each vertical axis interval is 62.9 μm and the maximum value is 104.6 μm;

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

[0080] 5. Generate particles based on 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 reaches (1-0.4)×20%. The geometric model of the particle heterogeneous distribution in the vertical axis interval is obtained, as shown in the figure: Figure 3 As shown;

[0081] Depend on Figure 3 It can be seen that three particles are added in the first particle addition 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%) of particle placement, and repeat until the end to establish the muddy silt sand sediment pore model, where a is the number of cycles, 5 times, 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 is consistent with the particle size distribution of muddy silt particles.

[0084] 7. Microfluidic chip etching based on the generated geometric model involves a series of delicate preparation steps aimed at accurately etching the microfluidic structure on the silicon wafer.

[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

[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 residues generated during the processing.

[0096] Inspection and evaluation: Use an optical microscope or scanning electron microscope (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, evacuate the glass chip to a high vacuum, heat it (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-type sediments, characterized in that: The steps include: 1) Determine the pore size of the muddy silt sediment according to the required microfluidic chip size; 2) Obtain the particle size distribution curve and two-dimensional pore model basic information of the measured muddy silt sediment through laser particle size analysis, where the particle size distribution curve has particle size as the x-axis and volume fraction 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 Δy, the vertical axis interval starting from the volume percentage of 1, and obtaining the minimum and maximum values ​​of the particle sizes in the corresponding horizontal axis intervals, which are recorded as 1-Δy and 1, respectively; 4) applying a normal distribution to the particle sizes within the horizontal axis interval, and obtaining an expected value and a standard deviation of the normal distribution function of the particle sizes within the horizontal axis interval based on the minimum and maximum values ​​of the horizontal axis interval, wherein the expected value is the median of the maximum and minimum values ​​of the horizontal axis interval, and the standard deviation is the difference between the maximum and median values ​​of the horizontal axis interval; 5) generating particles according to the expected value and standard deviation of the normal distribution function and randomly placing the particles in the pore model region of the muddy silt sand sediment, with the particles not overlapping each other, until the particle volume proportion Δy is satisfied, thereby obtaining a geometric model of particle heterogeneous distribution in the vertical axis interval; 6) Repeat steps 3) to 5) and place particles in the next horizontal interval of the Δy vertical axis (1-a·Δy, 1-(a-1)·Δy), repeat until the end, and establish a pore model of muddy silt sand sediments, where a is the number of cycles; 7) According to the pore model of muddy silt sediment, the placed particles are muddy silt and the unplaced part is a pore channel. Laser etching is performed on the substrate material to obtain a microfluidic chip based on the particle size distribution of muddy silt sediment.

2. The method according to claim 1, characterized in that The dimensions of the pore model of the muddy silt sand sediment are recorded as L for length, W for width, and A for area, where 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 within the horizontal axis interval (μ-σ, μ+σ) is 0 to 68.26%; the probability density within the horizontal axis interval (μ-2σ, μ+2σ) is 0 to 95.44%; and the probability density within 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 II D max = μ + σ; Formula III D 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 fraction of the particles is calculated according to formula IV: Formula IV Δy=A×(1-φ) In Equation IV, A is the area of ​​the two-dimensional pore model of the sediment, and φ is the porosity of the muddy silt-type 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 includes the following steps: a) cleaning the substrate: using a solvent to clean the substrate surface to remove oil and dust; b) Laser etching: importing the designed silty sand sediment pore model into the control software of the laser processing equipment, and using the laser to scan and etch the substrate along a preset path to remove the non-particle part of 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 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 isopropyl alcohol; In the conditions of the laser etching method: step e) further comprises a packaging step: encapsulating 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. Use of the microfluidic chip according to claim 8 in the field involving 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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